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Eindhoven, August 2007
Student identity number 0576606
in partial fulfilment of the requirements for the degree of
Master of Science
in Operations Management and Logistics
Supervisors:
Dr. ir. H.P.G. van Ooijen, TU/e, OPAC
Dr. ir. P.A.M. Kleingeld, TU/e, HPM
Measuring and improving productivity in a job shop
environment: the applicability of the ProMES
methodology
By
T. de Boer
Measuring and improving productivity in a job shop environment
T. de Boer 2
TUE. Department Technology Management.
Series Master Theses Operations Management and Logistics, nr.11
ARW 2007 OML / 11
Subject headings: Human performance, Production processes, productivity measurement,
productivity improvement.
Measuring and improving productivity in a job shop environment
T. de Boer 3
Preface
The final project in the Master of Science program is the Master Thesis Project. The master thesis
project is the final part of the Operations Management and Logistics (OML) master’s degree
program. The project consists of a research and design assignment to be independently carried out
by the student. First, the student has to prepare himself for this project during the periods
preliminarily to this actual Master Thesis Project. This period is called the Master Thesis
Preparation. The assignment for this preparation is to conduct a literature study about the
graduation topic and second, to write a research proposal. At the time of writing this report, the
Master Thesis Preparation is finished.
This report is the result of the graduation project conducted as a scientific research within the
Technical University of Eindhoven. The Master Thesis Project is conducted in order of the
Operations Planning Accounting and Control (OPAC) group of the department Technology
Management. The first supervisor is dr. ir. H.P.G. van Ooijen and represents the OPAC research
domain; production control in capital goods industry. The second supervisor is dr. ir. P.A.M.
Kleingeld and represents the Human Performance Management group.
I want to thank the people of Exerion Precision Technology for their cooperation and time for this
research project. It was not always easy to make appointments in-between the normal working
times, but when finally the conversations took place, they were very enthusiastic and willingly to
cooperate. Second I want to thank my thesis mentor, dr. ir. H.P.G. van Ooijen. I am very grateful
to him for the provided cooperation what led to a sufficient development and execution of the
master thesis project. I also want to thank the second supervisor dr. ir. P.A.M. Kleingeld for the
cooperation on this project.
Measuring and improving productivity in a job shop environment
T. de Boer 4
Abstract
This thesis describes a research about productivity measurement and improving in a production
process situation called a “job shop”. A job shop is a system in which various machines
manufacture various products. A typical job shop is defined by the number of jobs, the number of
machines and the many different routings in which the jobs are processed and is commonly used
to meet specific customer orders and there is great variety in the type of work done in the plant.
This research tried to apply the performance measurement system called “ProMES”, which stands
for “Productivity Measurement and Enhancement System” to a job shop situation. The main
problems which showed up at applying a ProMES system to a job shop situation at unit level are
the difficult decomposition of departmental productivity, the low controllability on productivity
and the increasing risks at sub-optimization. The purpose of this paper is to describe the results of
the literature study, discuss ideas for applying ProMES to a job shop situation, describe the
possibilities within the research company and finally to present solutions and recommendations
about how ProMES should be applied in a job shop production process.
Measuring and improving productivity in a job shop environment
T. de Boer 5
Management abstract
THE MASTER THESIS PROJECT
The project is based on the following research objective:
“The objective of the Master Thesis Project will be to analyse the applicability of ProMES into a
job shop setting; thus to study whether and in what way ProMES could help to improve
productivity in a job shop production process”.
Four research questions are stated according to the research objective. The four research
questions are formulated as following:
1. What are the characteristics of a job shop production process?
2. What are the characteristics of ProMES?
3. Can productivity be measured in a job shop situation?
4. How can ProMES be applied to a job shop situation?
Question one and two are both discussed according to a literature study and question three and
four are discussed according to both a practical analyses of the research company and analysis of
the literature research results.
A JOB SHOP PRODUCTION SYSTEM
A job shop system is a classification of discrete production systems in which various machines
manufacture various products and the manufacturing of a single product may require several
successive process steps, each on another machine. In a job shop environment machines are
ordered in groups, having the same functionality. Typical for a job shop system is that not every
manufactured product requires the same process steps on the same machines in the same order.
The production process of a single product is generally referred to as a job and a single process
step required is referred to as an operation. A typical job shop is defined by the number of jobs,
the number of machines and the many different routing in which the jobs are processed.
According to Pritchard, Jones, Roth, Stuebing and Ekeberg (1989), productivity is a combination
of both effectiveness and efficiency. Efficiency is an output to input ratio and effectiveness is the
relationship of outputs to some standards or expectations. Thus efficiency is how well the
organization uses its resources to produce its products or services. Effectiveness is how well the
organization is reaching its goals. This study will define productivity as “how well a system uses
its resources to achieve its goals” (Pritchard, 1992, p. 455).
We studied scientific literature about current ways of measuring performance in job shops. We
conclude the objective of both the measurement systems described in current scientific literature
and the ProMES approach is to improve productivity, but the ProMES approach (which is used in
this research) motivates people to change their working behaviour by themselves to improve
productivity.
THE PROMES METHODOLOGY
The concern of the ProMES (Productivity Measurement and Enhancement System) approach is
how to structure work so that people can and will want to behave in a way that will maximize
their productivity (Pritchard, 1995).
Measuring and improving productivity in a job shop environment
T. de Boer 6
The purpose for measuring productivity, according to the ProMES approach is used as a
motivational tool. “The objective is to improve productivity and the assumption is that if
individuals change their behaviour appropriately, productivity will increase” (Pritchard, 1990, pp.
10). Here it is assumed that the personnel have a great impact on productivity. They work more
efficiently because their effort is more directly related to organizational objectives and they
improve work strategies.
The department constructs the system by defining their objectives, identifying productivity
indicators for each objective, developing utility curves or contingencies for each indicator and
specifying the overall and relative value to the organization of different performance levels on
each indicator. The performance what subsequently is achieved is than fed back by means of a
feedback report. Productivity enhancement is thus tried to achieve by setting difficult, but
reachable goals and subsequently giving feedback on the performance on these goals. This will
lead to changes in motivation which on his turn will lead to increased productivity of the
employees.
The ProMES system is based on three principles from the motivation literature; goal setting,
feedback and reinforcement. The design of a ProMES system is characterized by a bottom-up
design process, a bottom-up design process means that the system is developed by the lower level
of the organization.
ProMES has been successfully implemented in different organisations, departments and setting,
but has only been implemented once in the situation of complex interdependencies between
machines and teams such as a job shop production process (Huve, 2005).
PRODUCTIVITY MEASUREMENT IN JOB SHOPS ProMES can in theory be developed and applied to different group sizes and at three levels
(Pritchard 1990). The three levels that can be determined are individual level, group level and
department level. Evaluating both job shop processes and the ProMES methodology with its
requirements, we could identify four aspects (the between-group dependencies, shifting operators,
varying orders, and the different interests of units) which are related to three main
problems/difficulties for applying ProMES to a job shop:
1. Decomposition of departmental performance - Departmental performance can hardly be
decomposed into the performance of independent units.
2. Low controllability - Groups can have a substantial, but not major influence on system
performance.
3. Risks at sub-optimization - Job shops consists of multiple compositions of groups with
different interests.
Due to the theoretically stated problems and difficulties which show up at applying ProMES to a
job shop, we do not know what the possibilities in a practical situation are. That’s why we
formulated several ideas for applying ProMES to a job shop. The ideas are set up from the point
of view of the desired situation and it is also tried to solve the problems by these ideas.
The main goal of the ProMES methodology is to improve the productivity of the employees in
order to achieve the organisational objectives. For example; manufacture more and innovative
products in a safe environment at low cost. The changes in productivity will at first be
recognizable at departmental level. When productivity changes are recognized at departmental
level, in for example; processing times, lateness and quality, we want to be able to determine
which factors at unit level influenced these changes.
Measuring and improving productivity in a job shop environment
T. de Boer 7
And the other way around, when changes are applied on unit level, we want to be able to
determine to which changes that will lead in total departmental productivity. From this point of
view, we formulated the first idea. The other three ideas are formulated to try to overcome the
problems showed up at the preceding ideas. The ideas are tested according to the situation at the
research company. The four ideas are:
1. Develop a ProMES system for the department, and measure each functional unit
individually
2. Expand idea 1 with measures on departmental level
3. Develop a ProMES system for the department, and measure a group of functional units
4. Develop a ProMES system for the department, and measure on departmental level
MAIN RESULTS OF THE PRACTICAL ANALYSIS The main results of analyzing the research company are:
1. It is possible to decompose the departmental productivity into single unit’s productivity. This
means that at the research company it is possible to develop a ProMES system at unit level
2. The chances at sub-optimization of the units are low at the research company
3. The problem of low control over the productivity of the employees due to interdependencies
is minimal
4. The problem of getting enough historical experience to make any judgments about what is
low or high output is not that difficult as found in literature
5. The problem of unreliable measures due to shifting and working with several shifts could be
solved by enlarging the measurement period to average out the fluctuations in productivity
per day or week.
The outcome of the literature research and the analysis at the research company is that the desired
situation can be created. Thus the conclusion is that the best idea is to develop the ProMES
system at departmental level and information about productivity is measured and evaluated at unit
level.
RECOMMENDATIONS
Along with the solution about the most optimal level of measurement (which is also possible in
practice) we provide recommendations about how to apply and develop a ProMES system to a
job shop, as outcome of this research. The main recommendations are as following:
1. The ProMES system has to be developed by determining common products and indicators for
each unit, contingencies will be drawn for each unit, and the feedback report contains the
overall departmental score and also shows the individual unit contribution to that score.
2. This general feedback report is then build-up out of the unit scores and represents the overall
score of the department on each product and a total departmental productivity score.
3. Remove the interdependency relationships by; proper development of indicators, by detailed
planning and scheduling processes and by the use of a central warehouse.
4. Rescale contingencies so each unit’s productivity can be summed up.
5. The responsibilities, roles and activities have exactly to be appointed and applied to one of
the functional units.
6. Develop an information system for; exchange of information, increase cooperation between
units, generating and registering productivity and decreasing time and effort to maintain the
system.
7. Decrease chances at sub-optimization between units and create a cooperative organization.
Measuring and improving productivity in a job shop environment
T. de Boer 8
8. Enlarge the measurement period to average out the uncontrollable variation in productivity.
9. Restrict the responsibility to tasks that are completely controllable (e.g. do not cover all parts
of the unit’s tasks).
THE DEVELOPED PROMES SYSTEM FOR A JOB SHOP
To explain and clarify the outcomes of the research we developed a design of a ProMES system
as it should be applied to the job shop production process of the research company. We worked
out (a part of) the presented solutions and recommendations in this design.
CONCLUSIONS By matching the theoretically developed statements with the results of the practical analysis, we
were able to determine how the ProMES system has to be developed, and how it leads to
increases in motivation and the highest gain in total productivity of the overall job shop floor,
thus representing a successful measurement and enhancement system
This research shows that the characteristics of both the job shop production process of the
research company and the ProMES methodology can be matched so productivity can be
measured and a ProMES system can properly be applied. We were able to do this because the
situation of the research company did not lead to the difficulties and problems as were assumed in
literature. Some of the theoretical stated assumptions (e.g. the complex interdependencies
between units) were not valid at the research company, so it was possible to apply ProMES at unit
level, in comparison with the study of Huve (2005). We also analyzed the research company
along with scientific literature to define recommendations. These can generally be applied to
other situations to help to increase the effectiveness and success of ProMES because these are not
dependent on this specific situation. On the other hand, the design of the system is applicable to
the research company because of the specific situation in which the study is conducted.
Even though we have designed an effective and efficient ProMES system for the research
company, and determined some important recommendations, people have to bear in mind that the
implementation of a ProMES system is also dependent on other factors which are not considered
in this research
Measuring and improving productivity in a job shop environment
T. de Boer 9
Table of content
Preface............................................................................................................................................. 3 Abstract ........................................................................................................................................... 4 Management abstract....................................................................................................................... 5 Table of content............................................................................................................................... 9 1. Introduction ........................................................................................................................... 11 2. The master thesis project ....................................................................................................... 12
2.1 Motive of the research.................................................................................................. 12 2.2 Overview of the Master thesis preparation .................................................................. 12
2.2.1 Literature research ................................................................................................... 12 2.2.2 Deliberations of the alternative PM systems ........................................................... 13 2.2.3 Conclusion ............................................................................................................... 14
2.3 Definition of the final research objective and questions .............................................. 14 2.4 Research design and approach ..................................................................................... 15 2.5 Narrow the scope of the project ................................................................................... 15
3. The job shop production system............................................................................................ 16 3.1 What is a job shop production system?........................................................................ 16 3.2 Some concepts defined................................................................................................. 16 3.3 Interdependencies within work groups ........................................................................ 18 3.4 Difficulties for measuring and evaluating productivity in job shops ........................... 19 3.5 Current methods of measuring productivity in job shops ............................................ 22
4. The ProMES methodology .................................................................................................... 23 4.1 A description of the system.......................................................................................... 23 4.2 Theory and basic principles of ProMES ...................................................................... 24
4.2.1 The NPI Theory ....................................................................................................... 24 4.2.2 The accepted control loop........................................................................................ 25
4.3 Requirements for developing and implementing ProMES .......................................... 27 4.4 The ProMES approach ................................................................................................. 27 4.5 Past experiences with ProMES .................................................................................... 28
4.5.1 ProMES in manufacturing settings .......................................................................... 28 4.5.2 ProMES in service settings...................................................................................... 29 4.5.3 Differences between previous cases and a job shop case ........................................ 29
4.6 Advantages and disadvantage of the ProMES approach.............................................. 30 4.7 Conclusion ................................................................................................................... 31
5. Productivity measurement in job shop situations .................................................................. 32 5.1 Discussion of the levels of measurement ..................................................................... 32 5.2 Factors influencing the success of ProMES................................................................. 33
5.2.1 The interdependencies between units ...................................................................... 33 5.2.2 Shifting operators between units ............................................................................. 35 5.2.3 The rapidly changing orders .................................................................................... 35 5.2.4 Different interests of the units ................................................................................. 35 5.2.5 The relational model ................................................................................................ 36
5.3 Generating ideas for developing and applying ProMES.............................................. 38 6. Description of the research company .................................................................................... 45
6.1 Short description of the company ................................................................................ 45 6.2 Overview of the production process ............................................................................ 45 6.3 The four functional units.............................................................................................. 46
6.3.1 Metal sheet cutting................................................................................................... 46
Measuring and improving productivity in a job shop environment
T. de Boer 10
6.3.2 Parts production....................................................................................................... 46 6.3.3 Kitting...................................................................................................................... 47 6.3.4 Welding ................................................................................................................... 47 6.3.5 Automatic warehouse .............................................................................................. 47
6.4 The job shop within the production department .......................................................... 47 6.5 Current way of measuring at the production department............................................. 48 6.6 The meaning of ProMES in the framework of the whole organization ....................... 49
7. Assessing the research company on the applicability of ProMES ........................................ 50 7.1 Results of the practical analysis ................................................................................... 50
7.1.1 Method..................................................................................................................... 50 7.1.2 Comparing theory with practice .............................................................................. 50
7.1.2.1 Level of measurement..................................................................................... 50 7.1.2.2 The interdependencies between units ............................................................. 51 7.1.2.3 Shifting operators between units..................................................................... 53 7.1.2.4 The rapidly changing orders ........................................................................... 53 7.1.2.5 Different interest of the units .......................................................................... 54
7.2 Evaluation of the results............................................................................................... 55 8 Matching ProMES with a job shop ....................................................................................... 57
8.1 When is ProMES applicable ........................................................................................ 57 8.2 Determining the best idea ............................................................................................ 58 8.3 Description of the system and recommendations......................................................... 58
8.3.1 Description of the system ........................................................................................ 58 8.3.2 Recommendations.................................................................................................... 59
8.3.2.1 Recommendations for reducing dependency relationships............................. 59 8.3.2.2 Recommendations to overcome the problem of low controllability ............... 60 8.3.2.3 Recommendation to reduce the chances at sub-optimization of units ............ 61
9 Developing ProMES for a job shop production process ....................................................... 62 10 Conclusions and recommendations ................................................................................... 69 11 List of references ............................................................................................................... 72
Measuring and improving productivity in a job shop environment
T. de Boer 11
1. Introduction
This report is the result of the graduation project conducted as a scientific research within the
Technical University of Eindhoven. The topic of the graduation project is about performance
measurements and improvements in a job shop production process.
Improving organizational productivity has been an issue for some time and will continue to be
important. All types of organizations need to be as productive as possible to optimally use their
precious resources, to meet their customers’ needs and to stay competitive with similar
organizations. There are two ways to improve productivity: one can change the technology or one
can change how people work. The concern of the ProMES approach is the second: how to
structure work so people can and will want to behave in a way that will maximize their
productivity (Pritchard, 1995). The ProMES method has been developed and implemented very
successful in many manufacturing and service settings (Pritchard, 1995), but has only been
implemented once in the situation of complex interdependencies between machines and teams
such as a job shop production process (Huve, 2005). This study showed that it very difficult to
implement this performance measuring and improving system in a job shop situation, because this
kind of production processes results in a highly complex order and material flow with lots of
transitions between the different workshops. A main shortcoming of the ProMES method is that it
is less applicable in situations of complex interdependencies between work teams (Pritchard,
1990). So it will be a difficult task to implement the ProMES approach in a complex production
situation as a job shop. The fact that performance measurement and enhancement for this kind of
complex production processes have only been described in literature by one study (Huve, 2005)
gave rise to a research in this specific area. The objective of this Master Thesis Project is
formulated as follows:
The objective of the Master Thesis Project will be to analyse the applicability of ProMES into a
job shop setting; thus to study whether and in what way ProMES could help to improve
productivity in a job shop production process.
The content of the report is as following. In chapter 2 we describe the motive of this research,
present an overview of the results of the literature review, (which was preliminarily conducted to
the master thesis project). The research objective and the questions and the boundaries of the
research are also described in this chapter. In chapter 3 we determine the main characteristics of a
job shop production process, discuss the problems about measuring productivity in job shops and
present some methods about how productivity is currently been measured in job shops. The
underlying theory, basic principles and the methodology of ProMES discussed in chapter 4. The
past experiences of ProMES are also discussed in this chapter. The factors which influence the
application of ProMES to a job shop and the generated ideas to deal with these factors are
determined in chapter 5. Chapter 6 is a description of the research company. Chapter 7
determines if and how the ProMES system could be applied to the production situation of the
research company by combining the results of both the literature and practical analyses. We
develop solutions and recommendations about applying ProMES to a job shop in chapter 8.
Chapter 9 provides a global design of the ProMES system applied to the productivity department
of the research company, to explain and clarify how the solutions and recommendations have to
be applied. This report ends with a conclusions and recommendations in chapter 10.
Measuring and improving productivity in a job shop environment
T. de Boer 12
2. The master thesis project
The motive of the Master thesis project is described in paragraph 2.1. The main results of the
literature research conducted in order of the master thesis preparation are described in paragraph
2.2. The objective and the research questions are determined according to the results of the master
thesis preparations and are described in paragraph 2.3. According to these research questions the
design and approach of the research are shortly described in paragraph 2.4. Paragraph 2.5
discusses the scope of this research.
2.1 Motive of the research
The initial paper used for this research is the master thesis report of Huve (2005). This report
describes the development of ProMES for a company in the Netherlands which manufactures
wooden furniture. The researcher studied the applicability of the ProMES methodology to the
complex production process of the company, characterized as a job shop and how the system has
to be developed and implemented within the production department of the company. After
studying and analysing the report of Huve (2005) we concluded that the study did not lead to the
most effective measurement and enhancement system; the system is developed at departmental
level (highest), which leads to smaller chances in productivity than when applied on a lower
level. The most important reasons to develop a system on a highest level were the complex
relationships between work groups and the limited availability of production data. This system
leads to minimum increases in people’s motivation that changes their working behaviour, and will
lead to less productivity improvement. We assume that it was the best solution possible in the
situation of that company, but it could probably be different in other situations, where ProMES
could be more effectively. The study of Huve (2005) gave interest to further research the area of
performance measurements in a job shop production process by using the ProMES methodology.
In the initial phase, we studied several performance measurement systems and classes of
production processes to determine if the ProMES methodology is best the option to be applied to
a job shop, and not another PM system. This research is conducted during the master thesis
preparation period. An overview and the results of that study are described in paragraph 2.2.
2.2 Overview of the Master thesis preparation
2.2.1 Literature research
The literature research preliminarily conducted to this research was to study different classes of
production processes and the most well known and often used performance measurement
systems. The literature study concerned one specific part of an organisation; the production
department. A production department is often a part of a large production organisation with other
departments as; sales, purchase, production development, etc. The transformation process
operated in the production department generally involves a sequence of steps called production
operations. “Each production operation is a process of changing the input into outputs while
adding value to the entity”, (Viswanadham and Narahari, 1992, p.31). This transformation
process is also called manufacturing. Manufacturing is a broad term and includes many various
types of production operations and products (Viswanadham and Narahari, 1992). The results of
the literature study showed that four general configurations can be recognized based on the
number of products and volume (Viswanadham and Narahari, 1992).
Measuring and improving productivity in a job shop environment
T. de Boer 13
Another way to define the different production categories is to distinguish between capacity
complexity and material complexity (Bertrand, Wortmann and Wijngaard, 1998). The results
showed that four types of categories can be distinguished:
- Job shops - A job shop consists of a number of functionally organized work centres and
each job requires a number of operations in different work centres at many different
routings (Silver, Pyke and Peterson, 1998).
- Batch production - “A process business which primarily schedules short production runs
of products” (Fransoo and Rutten, 1994, p.48) .
- Assembly lines - A manufacturing process in which interchangeable parts are added to a
product in a sequential manner to create a finished product (Viswanadham and Narahari,
1992).
- Continuous flow processes - “Process manufacturing involves a continuous flow of raw
materials through a series of sequential operations, where these operations transfer the
raw materials into a final product” (Viswanadham and Narahari, 1992).
The next part of the literature study concerned the often used and most successful performance
measurement systems. It turned out that many different theories, tools and frameworks are
developed, which all have different goals and working methods for measuring performance. The
performance measurement systems studied are: the Balanced scorecard, the Performance prism,
SMART, ProMES and the Business excellence model.
2.2.2 Deliberations of the alternative PM systems
The goal of the Business Score Card is providing strategic management information needs
(Kaplan and Norton, 1992). The performance prism is a comprehensive measurement framework
that addresses the key business issues (Neely, Adams and Crowe, 2001). The SMART approach
combines elements of a control system with elements of strategic planning (Cross and Lynch,
1988). The main goal of ProMES is measurement and improvement of productivity (Pritchard et
al., 1989). The business excellence index can be used to measure how well different areas of the
organisations are performing (Kanji, 1998). The result of the literature research was that ProMES
analyses performance on a lower level and directly improves productivity of the employees itself
in comparison with the other PM systems. All other PM systems are considering the visions and
strategy of the organisation, thus these systems seems to be effective at the organisational level,
and ProMES seems effective at the plant level. The PM systems, except ProMES, are all intended
to be applied on a higher level, for example for generating business strategies and increasing
business growth and competitiveness. Thus it all serves a much broader business decision support
system in comparison with the ProMES approach which serves to actually improve productivity
on the plant. In comparison with the other systems, ProMES is really a practical approach which
aims at improving productivity. Thus the advantage of ProMES is that it actually improves
productivity. This broader aim also implies that the PM systems consider several aspects of
performance measurement such as stakeholder satisfaction, management strategies, technologies,
processes, market, financial, customer, etc, thus productivity improvement is not the main goal of
these PM systems. In comparison, the main goal of ProMES is to gain improvements in
productivity. Thus applying the ProMES system is much more relevant to improve productivity
of (in this situation) a job shop department instead of applying other PM systems which considers
much more (irrelevant) aspects and only slightly productivity.
The main problems and difficulties as logistics, scheduling, strongly varying orders and demand
and complex material routings showing up at managing and controlling a job shop system are
indirectly tried to be solved or prevented by implementing a PM system.
Measuring and improving productivity in a job shop environment
T. de Boer 14
The ProMES approach is the best alternative in comparison with the others, because it motivates
people to improve their productivity which on his turn creates solutions and strategies to solve the
problems on the plant.
We conclude that the ProMES methodology is best suitable to be applied on operational level and
to improve productivity of a job shop production department, and the other PM systems are more
suitable when applied on an organizational level to improve business strategies. Thus we have
chosen to study the applicability of the ProMES methodology to a job shop situation.
2.2.3 Conclusion
The ProMES system has been successfully implemented many times, in different organisations
and production situations (Pritchard, 1990), but has only been implemented once in the situation
of complex interdependencies between machines and teams as in a job shop production process
(Huve, 2005). Job shop production processes are characterised by a very complex environment
due to the high product differentiation, different routings and low level of automation. ProMES
seems to be the best potential (in comparison with the other PM systems) to improve productivity
of a job shop production department. The situation at other companies might be different to the
situation of the study of Huve (2005). The study of Huve (2005) gave interest to further study
how a ProMES system can be matched with a job shop. So in the master thesis project we analyse
if ProMES can be applied to a job shop situation and whether it can lead to productivity
improvements in a job shop setting.
It is very interesting to conduct a study about measuring and improving productivity in a job shop
production process along with applying the ProMES methodology because:
- ProMES has been developed for work teams and also for individual jobs;
- ProMES is a bottom up approach, thus participated by employees;
- ProMES’ main goal is to improve productivity;
- ProMES has proven to be successful in practice.
Accordingly, all PM systems showed to be accepted on the floor and all people can participate
(Pritchard, 1995), but only by the use of ProMES, the employees really are involved in the whole
process of setting up and maintaining the system, which will result in high acceptance and
commitment.
2.3 Definition of the final research objective and questions
The final research objective is formulated according to the results of the preliminary literature
study. The objective of the master thesis project is as follows:
There are four research questions defined according to the research objective. These are based on
the possibilities of the student within the research domain of the University. The four major
research questions are formulated as follows:
The objective of the Master Thesis Project will be to analyse the applicability of ProMES to a
job shop setting; thus to study whether and in what way ProMES could help to improve
productivity in a job shop production process.
Measuring and improving productivity in a job shop environment
T. de Boer 15
2.4 Research design and approach
According to the four research questions, a research design and approach is set up. The research
can be divided up into four phases:
Phase 1: Literature research - studying job shops and ProMES
Phase 2: Generating ideas - solutions for measuring productivity
Phase 3: Analysing practice – assessing the research company
Phase 4: Implementation - matching ProMES and job shops
For gathering information about a job shop production process, generating ideas and testing
solutions we have contacted a manufacturing company. The management of that company is
willing to cooperate in the project. The name of the company is “Exerion Precision Technology”,
located in Ulft, the Netherlands. Exerion designs and manufactures precision metal frames and
mechanical parts for printing and medical equipment. A part of the production department
situated at the research company can be characterized as a job shop production process. The
complete description of the research design and approach can be found in appendix A.
2.5 Narrow the scope of the project
In this part we will make some assumptions and determine some basic points of view. These are
important for the study and especially for analyzing the research objective and questions. When
considering other or more aspects, the research will be influenced so the solutions and
recommendations at the end will not be appropriate for the specific research objective. But also
the research is time, knowledge and skills constrained.
The following assumptions and statements narrow the scope of this research:
- Only the option of applying the ProMES system is evaluated, so no other performance
measurements systems are discussed;
- The research only concerns a job shop production process, so no other production
configurations will be evaluated;
- We will use one company as a research company concerned for this research, so
conclusions will be drawn from only this company;
- The system will be evaluated on the applicability to the production department, so no
other departments of the company will be discussed;
- We consider if and how the ProMES system could be applied to a job shop, so the system
will not fully be developed and implemented.
1. What are the characteristics of a job shop production process?
2. What are the characteristics of ProMES?
3. Can productivity be measured in a job shop situation?
4. How can ProMES be applied to a job shop situation?
Measuring and improving productivity in a job shop environment
T. de Boer 16
3. The job shop production system
This chapter discusses different facets of job shop systems. Paragraph 3.1 describes the method of
manufacturing according to a job shop. Paragraph 3.2 defines different performance measures
like productivity and efficiency, etc. to overcome misunderstanding or misinterpreting. In
paragraph 3.3 is discussed which different dependency relationships exist between work groups,
which are very important to understand at measuring productivity in job shops. The specific
production structure of a job shop results in difficulties/problems what causes a job shop hard to
be measured and evaluated on productivity what is described in 3.4. Finally an overview of
current scientific literature about productivity and performance measures in job shops is provided
in 3.5.
3.1 What is a job shop production system?
We will shortly describe here what a job shop production system is; a more detailed description
of a job shop system is described in appendix B. A job shop system is a classification of discrete
production systems in which various machines manufacture various products and the
manufacturing of a product requires several process steps, each on another machine. A typical job
shop is defined by the number of jobs, the number of machines and the many different routing in
which the jobs are processed. Job shops are characterized by the difficulty of planning and
controlling due to the high complexity of scheduling jobs on the different machines.
Viswanadham and Narahari (1992) state that job shops are commonplace in mechanical
engineering, with low to medium volumes and with a wide range of products.
3.2 Some concepts defined
The terms “performance” and “productivity” are two very important characteristics used in this
research. These two, but also some other terms are often defined differently by many researchers.
To overcome the problems of misunderstanding and misinterpreting these terms, we will give the
exact definitions of these terms, as used in the current research.
In the literature studied, authors often talked about the term productivity (improvement) instead
of performance (improvement). Improving the productivity is referred in most of the papers
interchangeable with improving performance, or some authors even confuse both terms. There
has to be a clear distinction between both terms according to Sink, Tuttle and De Vries (1984),
because they stated that productivity represents a critical component of performance and not a
synonym for it. “Productivity needs to be viewed as one of a group of performance criteria
against which managers can assess, evaluate and base decisions regarding the organizational
systems they are managing” (Sink et al., 1984, p.265). Productivity represents a critical
component of the performance definition. Productivity can be evaluated at the work group,
function, division, plant or firm level.
Performance is typically output such as number of pieces finished, but productivity is an output
relative to inputs, or outputs relative to objectives or goals (Pritchard et al. 1989).According to
Pritchard et al. (1989) productivity is a combination of both effectiveness and efficiency.
Efficiency (also called productivity) is an output to input ratio (monthly manufacturing output
divided by number of labour hours used) and effectiveness is the relationship of outputs to some
standard or expectation (e.g. monthly output expressed as a percentage of the unit’s goal).
Measuring and improving productivity in a job shop environment
T. de Boer 17
Thus efficiency is how well the organization uses its resources to produce its products or services.
Effectiveness is how well the organization is reaching its goals. This study will define
productivity as “how well a system uses its resources to achieve its goals” (Pritchard, 1992, p.
455). This definition will be applied in this study to view productivity mostly from a behavioural
perspective.
As told above, productivity is a component of performance. According to Sink et al. (1984) the
performance of an organizational system is comprised of seven criteria; effectiveness, efficiency,
quality, productivity, quality of work life, innovation and profitability/budgetability. These terms
will be explained below.
Effectiveness - Doing the right things on time, and in the right manner, in terms of goals,
objectives, activities, goods, products, services, etc, thus it focuses on what we should be doing
and have done. ectedoutput
observedoutputessEffectiven
exp=
Efficiency - It focuses on the relationship between what we felt should have been consumed and
what was actually consumed. ectedinput
observedinputEfficiency
exp=
Quality - The products and/or services have been performed conformance to the specifications.
Productivity - It is the ratio of quantities of output to quantities of input resources; the ratio of
quantity at the desired quality level to resources actually consumed. observedinput
observedoutputoductivity =Pr
Quality of work life - This is the human beings’ affective response/reaction to working and living
in organizational systems.
Innovation - The creative process of adaptation of product, service, process, structure, etc. in
response to internal as well as external pressures demands, changes, needs, etc. it is extremely
hard to measure something that implies effective implementation of a creative new idea.
Profitability/budgetability - A measure or set of measures that assess attributes of financial
resource utilization.
Figure 3.1: The seven criteria are causally related, source: Sink et al. (1984).
Measuring and improving productivity in a job shop environment
T. de Boer 18
3.3 Interdependencies within work groups
The team members of the various functionally units in a job shop situation are interdependent on
each others task fulfilment. Team members are very dependent of the outputs of other team
members, and the way the work flows between unit members. “Work flows are the materials,
objects, or clients that are sent or transported between people within organizational units”, (Van
de Ven and Ferry, 1980, p. 166). The amount of work flow indicates the degree of task
interdependence between people in a unit. “Task interdependence is the work connectedness of
unit personnel or the extent to which people in a unit are dependent upon one another to perform
their individual jobs”, (Van de Ven and Ferry, 1980, p. 166). Tesluk, Mathieu, Zaccaro and
Marks (1997) state that interventions aimed at improving team performance are likely more
successful when they take into account the team’s specific task functions and requirements. This
is an important statement when considering the groups (functionally units) within a job shop. The
group members are working closely together and exchange information to fulfill the group’s
tasks. At assessing the performance of the unit, we have to take into account that, additional to the
performance of various individuals, the ultimate effectiveness of the team depends on well-
coordinated transitions between team members (Tesluk et al., 1997). According to the authors,
critical team levers (the most important factors or work processes that underlie a particular team’s
performance) have to be defined for the measurement and diagnoses of team performance.
Understanding the nature of the task performed by the team is critical for proper diagnoses of
problems in team performance. If the critical levers for the team performance are not identified,
measurement efforts may be targeted at the wrong level of analysis. For example, when team
members are working independently of each other, one can decide to measure performance of
each individual on their tasks and summing across individuals. Four basic work flow
arrangements can be distinguished. Below we describe these four arrangements that are used to
characterize the work of different types of team interdependencies (Tesluk et al., 1997, Van de
Ven & Ferry, 1980). The four arrangements are graphically shown in figure 3.2.
Figure 3.2: Taxonomy of team work processes. Source: Tesluk et al. (1997).
Pooled interdependence - in pooled tasks, each individual contributes incrementally to overall
task completion, and team performance and work does not flow between members of the team.
Each individual’s performance is a function of his or her efforts and does not depend directly on
the performance of others.
Measuring and improving productivity in a job shop environment
T. de Boer 19
Sequential interdependence - work moves from one member to another, and mostly in one
direction. Work flows in a consistent unidirectional through each of the members.
Reciprocal interdependence - interactions are more dynamic in nature and work flows back and
forth between team members. Team performance is a function of more complex forms of
coordination.
Intensive - team members closely work together to diagnose, solve problems and collaborate in
performing a task. The nature of the task is dynamic and complex.
When the critical levers of team performance are identified (what to measure), the particular
method of measuring has to be determined that is most appropriate for assessing team
performance (how to measure). There are various methods of measuring team performance. A
choice has to be made about the source of information (who provides the information of the
team’s performance) and the method(s) of measuring (how data on team performance are
collected) (Tesluk et al., 1997).
“An important factor in team performance assessment is that the nature of the team’s task and
particular processes or aspects of performance that are being measured should play an important
role in determining which particular method of measurement to use” (Tesluk et al., 1997, p.210).
The study describes some trends about the target of a human resource program by assessing
different kinds of teams. We describe which specific motivational human resource program to use
accordingly to the four different team characteristics. Motivational programs for pooled team
should be designed to facilitate and reward the contributions of individuals (e.g. piece rate
compensation). Motivational programs for teams operating in sequential task settings should
emphasize individuals’ contribution but also focus on the exchange sequences between members.
Motivational efforts for reciprocal teams should be directed to the team as a whole. Reward and
feedback programs should be based less on individual contribution and more on team
performance. Motivational programs for intensive designs should focus on team level processes
and outcome by providing team-level feedback and incentives (Tesluk et al., 1997).
3.4 Difficulties for measuring and evaluating productivity in job shops
The production structure within a job shop can be characterized as a functionally oriented
structure with the functional units at where the products and parts are manufactured. The
functional units characterize a layout in which machines and people handle similar operations and
are grouped together in a workshop. The functional oriented layout is required because each of
the production operations requires different operational means and skills. The different units
within the functional production organization do represent its own task. The disadvantage of this
kind of production processes is that this results in highly complex order and material flow with
lots of transitions between the different workshops. Thus a job shop system represents a highly
complex production environment with complex dependency relationships between the different
units, so the units are strongly dependent of each other if it comes to exchange of information and
products and changes of any kind. These dependencies can be seen as sequential dependency
(work on the result of previous units) and reciprocal dependency (work flows back and forth
between units). Examples of interdependencies relationships are: work on a part when another
unit is finished with that, the quality of preceding work, speed of doing work is dependent on the
speed of getting parts or material when needed, how efficiently the output is produced depends on
how production scheduling has arranged the orders (Pritchard, 1990).
Measuring and improving productivity in a job shop environment
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Due to these dependencies between units, the departmental performance can hardly be
decomposed into the performance of independent units. So the main question here is: “At which
of the three levels (individual, group or department) it is best to measure and evaluate
productivity so the most successful measurement system will be developed?” Another problem
which shows up point due to the interdependencies between the units is that the control over the
unit’s productivity decreases when units are individually being measured and evaluated. It is a
problem because each individual unit has to be able to influence their unit’s output when a
performance measurement system is applied at unit level. Thus one of the most important
decisions is the decision about the level at which the measurement system is developed. When
measured on individual or group level it will take much time and effort the develop and maintain
the measurement system because a system has to be developed for each unit or individual, but
will have more impact on productivity than when measuring on department level what will take
less time and effort to develop and maintain. Providing feedback to each individual or a small
group of people will lead to higher changes in motivation and productivity because then people
can easily recognize there individual (or unit) contribution. This is difficult to recognize when a
large group is provided with feedback about the overall productivity performed by the whole
group. Thus the less people are covered in one measurement system, the more effective it is, but
the more the development time will increase.
A main characteristic of a job shop production system is that a lot of various products are
manufactured. Because of the varying products, the processing times will also vary. The
manufacturing lead time is mainly defined by the waiting times in front of the work centres and
the processing times at the machines. Due to the strong varying routings and occupation times,
the number of orders arriving at the units strongly varies per time unit (day or week). So when is
chosen to measure the number of produced parts in a period, it will be difficult to define a
standard or desired level of production and also it will be difficult to compare the performed
productivity between periods. This is because each order has different processing times and thus a
different total lead time in comparison with other orders. For example a work group maximized
its productivity a specific day and produced three parts, and the next day it also maximized its
productivity and produced ten parts. The effectiveness was equal at both days, but the number of
parts was unequal, which is caused by the differences in jobs. What can be done is to use the
actual number of hours worked relative to the standard working hours. When one determines the
time it takes to fulfil a task, the actual time it took to fulfil that task can then compared with that
standard processing time. In this way, the productivity of both days can be compared fairly,
because for example the three parts were calculated to be processed in eight hours and also the
ten parts were calculated to be processed in eight hours. Other productivity factors, as for
example quality, amount of waste material, etc, are also influenced by the various orders. A
problem, because of the vast changing orders, is the fact that it is difficult to control the output
(productivity) of the operators, units and department over time and as told above, each individual
unit has to be able to influence their unit’s output when a performance measurement system is
applied at unit level.
The incoming orders do vary in amount, design, urgency and processing time, which result in a
very complex material flow control. It is very hard to define how the different orders will be
distributed among the machines in next periods. Machine utilization and variation of the orders
will generally lead to long waiting times for orders on the floor. A difficulty is the production
speed of a work centre is dependent of another unit. In fact, the amount of work to be done by a
unit varies a lot per period. An example is that the orders for a specific period requires much
more capacity of unit 1 and less capacity of unit 2, whereas orders in the next period can be vice
versa. Thus there are continuously changing bottlenecks in the production department.
Measuring and improving productivity in a job shop environment
T. de Boer 21
This unknown distribution and machine utilization leads to a difficult determination of
productivity standards and goals for the coming periods and the control on productivity over time.
In a job shop production environment, it is usual (when demand is high at a specific functional
unit) to shift one or more employees from a less demanding unit to a high demanding unit. We
assume that these persons are less familiar with the handlings and operations at that unit than the
“fixed” employees, so the result is that the scores on the performance indicators (e.g. speed and
quality) will not be as high as normal for that unit. The productivity and thus the scores on the
performance indicators of a specific functional unit are not representative anymore for the
actually possible achievable performance of that unit by shifting employees. The functional units
cannot fully control the output of their unit over time when persons are transferred to an
“unfamiliar” functional unit when capacity requirements are high. This has to be considered when
a performance measurement system is developed at individual or unit level.
A difficulty at measuring productivity and subsequently comparing the results with previous
productivity achievements or norms is that people do not have the full control over some factors
such as machine breakdown and lateness of delivered raw material. The measurement system
may not be valid, because it is difficult to take the factors which can not be influenced into
account.
The probability of individualistic behaviour among units increases when the individual unit
productivity is measured, because the achievements of each of the units will be compared with
each other. The goals for the units will become independent when the unit productivity is
measured. Van Vijfeijken, Kleingeld, Schmidt, Kleinbeck, Pritchard and Algera (2002) state that
goal interdependence reflects the way in which goal attainment of an individual (a unit in this
situation) is influenced by goal attainment of other. Goal interdependence can vary from (highly)
negative to (highly) positive. Neutral goal interdependence means that achieving the pre-defined
goals by one group does not influence the attainment of the same goal by the others. Contrarily to
the neutral interdependency, the case of positive goal interdependency, the attainment of one’s
goal is positively influenced by the attainment of goals by others. And in the case of negative goal
interdependency, the attainment of one’s goal is negatively influenced by the attainment of goals
by others (Van Vijfeijken et al., 2002). We assume that the goal interdependency is neutral in our
situation. Van Vijfeijken et al. (2002) state that groups performing a highly interdependent task
performed significantly worse when confronted with an individual goal compared to a group goal,
a group plus an individual goal, or no specific goal. Neutral goal interdependency leads to
individualistic behavior of the units because under a individual goal condition the group members
direct all their action and attention to the attainment of the individual goal. Individualistic
behavior can lead to sub-optimization because little energy will be used to develop cooperation
strategies (Van Vijfeijken et al., 2002) and sub-optimization can on his turn lead to competition
between units. Competition means that units try to increase productivity what can be of
disadvantage of other units
An example of sub-optimization is that a unit decides to increase the batch sizes with
subsequently less set ups what implies a decrease in total processing time. The speed of
production will increase at this specific unit, but leads to a decrease in production speed at the
succeeding unit, because now they have to wait before all parts are delivered. A second example
is the decision of a unit to slightly change the design of a part to increase the production speed,
but resulting in an increase of processing time of the succeeding unit. The production speed of
one specific unit increases, but the overall processing time will decrease.
Measuring and improving productivity in a job shop environment
T. de Boer 22
As conclusion we can state that it is difficult to measure group productivity at a valid and reliable
way in a job shop situation. The main reasons are the interdependencies within and between units,
the changing skills of the employees due to shifting, the low controllability ad the risks at sub-
optimization. The insecure and vast changing environment makes it difficult to apply a system on
each of the three possible levels.
3.5 Current methods of measuring productivity in job shops
In this part, we will give an overview of current scientific literature about the area of productivity
measurements in job shop production processes. The first conclusion we can state here is that
very little work is conducted in this area of research, because very few scientific papers about
productivity measurements in job shops could be found. The majority of the research in the area
of performance measurement in job shops has used time based performance measures to evaluate
the system (Rohleder and Scudder, 1993). The often used measures are lateness, tardiness, flow
time, percent tardy. Managers consider these kinds of performance measures because of the view
that time is money according to the authors. Recent research in scheduling and performance
measurement in job shops used the profit measure; Net Present Value (NPV) which is the present
value of net cash flows (Rohleder and Scudder, 1993).
In the study of Bertrand (1983), productivity is measured by the mean and the standard deviation
of the lateness of the jobs. The lateness of the job is defined as the delivery time minus the due
date of that job. In the study of Lee and Posner (1997) two productivity measures are used; cycle
time and makespan which are closely related. The makespan is a measure according to the time it
takes to complete all jobs. According to Viswanadham and Narahari (1992), the following
performance measures are often used: manufacturing lead time, work-in-process, throughput
time, machine utilization, capacity, flexibility, performability and quality. According to them, job
shop characteristics are; large setup times, large WIP inventory, large manufacturing lead time,
high machine utilization and high quality. Only one paper describes the use of the ProMES
approach for measuring and improving the productivity of a job shop (Huve, 2005). This paper
describes the development of ProMES for the production department of a Dutch company. The
study resulted in a system developed on a high level (departmental). It was not possible to
develop the system on group level mainly due to the complex mutual dependencies between the
working units and the limited availability of production data.
The difference between methods of measuring productivity in job shops as described by current
scientific literature and the ProMES approach is that the ProMES approach, which aims at the
human aspects, uses goals and feedback (to group and/or individuals) as a motivational tool, so
people themselves can change their working behaviour to improve productivity. We conclude the
objective of both the measurement systems described in current scientific literature and the
ProMES approach is to improve productivity, but the difference is that the ProMES approach
(which is used in this research) motivates people to change their working behaviour by
themselves to improve productivity. It is about letting people work more efficiently and
effectively to increase the productivity of a department or organization.
Measuring and improving productivity in a job shop environment
T. de Boer 23
4. The ProMES methodology
This chapter describes the underlying theory, basic principles and the methodology of ProMES.
The generally description of the ProMES system is given in 4.1. When the system is generally
described, we explain the underlying theory of the measurement system in 4.2. The requirements
for a successfully and accepted implementation of the system are described in paragraph 4.3. The
ProMES system has to be developed and implemented according to four succeeding phases which
are described in 4.4. The past experiences with implementations of the ProMES system in
different companies and departments are discussed in 4.5. In paragraph 4.6 we provide the
advantages and disadvantages of the measurement system. The chapter ends with a short
conclusion in paragraph 4.7.
4.1 A description of the system
All types of organizations need to be as productive as possible to best use their expensive
resources, to meet their customers needs and to stay competitive with similar organizations. There
are two ways to improve productivity: you can change the technology or you can change how
people work. The concern of the ProMES approach is the second: how to structure work so that
people can and will want to behave in a way that will maximize their productivity (Pritchard,
1995). “Enhancing productivity has been seen as important for our quality of life, our economy,
and our competitive position in the world marketplace”, (Pritchard, Jones, Roth, Stuebing and
Ekeber, 1988, pp. 337). ProMES has its theoretical foundations within a theory of behaviour in
organizations. The idea behind ProMES can be seen in figure 4.1.
Figure 4.1: The basic ProMES approach, source: Pritchard (1990).
ProMES is an intervention that relies on feedback to let personnel know their levels of
performance; this knowledge then serves as a tool that leads to more efficient and effective ways
of performing tasks (Pritchard, 1990). The system is developed and accepted by both employees
and management, and provides an overall index of productivity. An organizational unit constructs
the system by defining their objectives, identifying productivity indicators for each objective, and
developing utility curves or contingencies for each indicator, specifying the overall and relative
value to the organization of different performance levels on each indicator. The performance what
subsequently is achieved is than feedback by means of a feedback report. Productivity
enhancement is thus tried to be achieved by setting difficult, but reachable goals and subsequently
giving feedback on the performance on these goals. This will lead to changes in motivation which
on his turn will lead to increased productivity of the employees.
The goal of the ProMES method is to measure and improve productivity. The application of the
system begins with clear statements or organizational objectives. Productivity can be generally
defined as the degree in which a system uses its means to reach its goals (Pritchard 1992).
Organizational objectives Productivity
measurement system
Feedback system
Increased productivity Meeting organizational
objectives
Measuring and improving productivity in a job shop environment
T. de Boer 24
ProMES can be used as a measurement and enhancement system for individuals, groups and
departments as well. The system urges people to work smarter, not (necessarily) harder.
There are generally three characteristics of ProMES at which it can be distinguished from other
performance measurement systems. The first is the fact that ProMES is developed by a so called
bottom-up approach; the participation of employees in the design of the system plays a major
role. The second is that the employees are actually participating in the development of the system
to increase the acceptation and willingness to cooperate. The third characteristic is that meetings
are held by the employees and management for development of the system and agreement about
the goals.
4.2 Theory and basic principles of ProMES
The literature on performance appraisal distinguishes three basic approaches managers can use to
tell their employees to working a performance sessions: ‘tell and sell’, ‘tell and listen’ and
‘problem solving’ (Algera, Kleingeld and Van Tuijl, 2002). The ‘tell and sell’ style is a one-way
approach; the manager presents his assessment of the performance achieved and explains what he
wants to see in the future. In the ‘tell and listen’ style, the manager not only presents his opinion,
but also listens to the opinions of his employees. The ‘problem solving’ style gives employees
plenty of opportunity for active participation in developing ideas for improving performance in
the future. This approach is the most appropriate one for the ProMES sessions (Algera, et al.,
2002).
4.2.1 The NPI Theory
The conceptual foundation behind ProMES is the “theory of work behavior” developed by
Naylor, Pritchard and Ilgen in 1980, also called the NPI theory (Pritchard, Holling, Lammers and
Clark, 2002). ProMES maximizes motivation and thereby performance that comes from this NPI
theory. We will now explain this NPI theory. “Motivation in NPI is seen as a resource allocation
process where the resource is a person’s time and energy. This time and energy is allocated across
possible actions or tasks” (Pritchard et al., 2002, p.4). The NPI motivational process is shown in
figure 4.2.
Figure 4.2: The basic NPI Theory, source: Pritchard et al. (2002).
The process is a motivational sequence or chain composed of the following elements: acts,
products, evaluations, outcomes, and need satisfaction. People anticipate the amount of need
satisfaction that will occur when outcomes are received (motivation). “Acts, products,
evaluations, outcomes and need satisfaction are combined into motivational force which is
defined as the degree to which a person believes that changes in the amount of personal resources
in the form of time and energy (effort), devoted to different acts (tasks) over time, will result in a
change in anticipated need satisfaction” (Pritchard et al., 2002, p. 5). NPI views motivation as a
process, each stage of the process must function well for the outcome of the process (motivation)
to be high, thus to maximize motivation, each component of the theory must be maximized
(Pritchard et al., 2002).
Figure 4.3 adds contingencies, which indicates, for example, the amount of a product produced is
to some degree contingent on the effort devoted to the acts that generate it.
Measuring and improving productivity in a job shop environment
T. de Boer 25
Figure 4.3: The NPI Theory with contingencies added, source: Pritchard et al. (2002).
Figure 4.4 graphically shows the connection between NPI and ProMES. The ProMES objectives
and indicators (which will be discussed in paragraph 4.4) are the operationalization of the NPI
products. ProMES contingencies are the operationalization of NPI product-to-evaluation
contingencies (the person’s perceived relationship between the amount of the product and the
expected level of the evaluation as a result of this level of product). Feedback indicates how much
of each product was done, and how good that amount was.
Figure 4.4: ProMES components and NPI, source: Pritchard et al. (2002).
ProMES can produce improvements in productivity by increasing motivation, because between
the development of the system, receiving feedback and using feedback to make improvements
there are direct connection between ProMES components and the NPI motivational chain
(Pritchard et al., 2002). ProMES is designed to affect all the variables influencing the
motivational process simultaneous, what leads to large changes in productivity.
4.2.2 The accepted control loop
According to van Tuijl (1997) ProMES can be interpreted as a method for the development of
control loops for self-management, called “accepted control loops”. But ProMES does not
automatically lead to accepted control loops, this depends on the way in which the development
process is completed and the characteristics of the control loop designed.
The idea behind the accepted control loop for self management is that in essence “motivation
stems from people’s own choices”. By using the ProMES method, a group can develop a system
so the productivity of the employees can be measured. The control loop occurs when the
measured productivity is compared with the goals that are determined and is fed back to the
group. The feedback tells to what extent these concrete goals are being realized. Then, these goals
are transformed into new more difficult goals. In this way reduction of discrepancy leads to the
production of discrepancy (van Tuijl, 1997). The accepted control loop for self management is
shown in figure 4.5.
Measuring and improving productivity in a job shop environment
T. de Boer 26
Figure 4.5: The accepted control loop, source van Tuijl (1997).
The lower half is the input-transformation-output model, in which the responsibilities of a group
are presented (goods or services). The degree to which these responsibilities are realized
(feedback) is passed on to a regulatory mechanism (upper half), which compares the feedback
with the target goals. The goals are transformed into new and more difficult goals if the goals are
met or surpassed (discrepancy production). Then the process of discrepancy reduction begins,
where people put in time and effort to reach the goals. Results from the area of motivation
research state that feedback and goal setting have a strong effect on individuals and teams. Van
Tuijl (1997) states that people motivate themselves by formulating goals that lead to a situation of
imbalance (discrepancy production), and then put in time and energy which are necessary to
reach the goals (discrepancy reduction). According to van Tuijl (1997), the reactions to the
ProMES method can be; acceptance, compliance or rejection. Acceptance means that the
accepted control loop is complete. When the initial goal is satisfied, the group or individual sets a
new, more difficult goal and is striving to reach that new goal. At compliance, the control loop is
not complete; the individual or group does not make effort to reach a higher goal when the initial
goal is reached thus the group only tries to hold on to that initial goal. Rejection means that the
people do not make any use of the system and the feedback method and there is no effort towards
reaching goals.
When the ProMES method leads to an accepted control loop, it can lead to an increase of the
organizational effectiveness. The first reason for this is that employees get a better understanding
of their roles and responsibilities during development of the system. The second reason for
productivity improvement during development is that people already get informal feedback about
their performance. Productivity improvement after implementation of the system can be
explained through the use of feedback reports. The already improved productivity at this moment
can even be more increased by the use of incentives such as intrinsic and extrinsic rewards.
According to van Tuijl (1997) three conditions have to be present so employees are encouraged to
achieve the goals of the organizations: goals, feedback and endorsement. Goals have to be
functionally related to the goals of the organization. Employees want feedback because they are
interested in the degree to which these goals are achieved. They will adjust their work when the
goals are not fully achieved and may set higher goals when goals have been attained. The third
condition represents the degree in which the organization appreciates the performance. These
three conditions have to meet some requirements to be effective (van Tuijl, 1997):
- goals have to be specific, difficult, but attainable;
- feedback has to be specific;
- endorsement has to be consistently related to the goal achievement.
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4.3 Requirements for developing and implementing ProMES
Time, effort, and acceptance are required to make sure that the ProMES method will be a valid
and reliable measuring system in an organization. The chances at acceptance and at a successful
implementation and development increases when (some of) the following conditions are satisfied
(Pritchard, 1990):
- dominant attitude in the department on the necessity of improvement of performance;
- all people involved endorsing the importance of productivity improvement;
- the personnel subsystems being viewed as critical for success;
- minimum level of trust between management and the work force;
- be sure that management really wants to invest in the system, e.g. by providing resources;
- willingness to measure performance and to be measured;
- visible commitment of management;
- in case of lacking skills, provide training before and during development;
- no “not invented here” culture;
- check whether the system is compatible with other organizational control systems, e.g.
reward systems.
The conditions mentioned above concern the human aspects preliminary to the development of
the system. The criteria mentioned below are required to the ProMES system itself, to increase
the chances at a successful measuring and enhancing system (Van Tuijl, 1997):
- The system has to be able to represent one single score for the total performance of the
group or department.
- The system has to be able to show how the total score is build up from the sub-scores,
which represents the productivity of the different activities.
- The responsibilities have to be represented by the system and the system has to show
these responsibilities at a valid way.
- The system has to be flexible, what means that the system can response and adapt to the
changes in circumstances and policies of the organization.
- The system has to be accepted both by employees and by management.
4.4 The ProMES approach
The design of a ProMES system is characterized by a bottom-up design process, leading to four
elements of the system (Algera and van Tuijl, 2004). A bottom-up design process means that the
system is developed by the lower level of the organization; the employees participate in designing
the system instead of the management (top down approach). A detailed description of each of the
four elements of the system can be found in appendix C. The four elements of the system are:
1. key result area (called products): a limited number of result areas that are essential for
performance (e.g. quality, costs, safety, etc);
2. performance indicators: one or more indicators that reflect the performance in the related
key result area;
3. contingencies: utility functions that express the relation between a score at a specific
performance indicator and the value for the organization (effectiveness);
4. feedback report: a report that gives regular feedback on performance and effectiveness.
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4.5 Past experiences with ProMES
ProMES is successfully implemented in many different industries, companies and departments.
Some of these studies will be discussed in this paragraph. Over the last twenty years, a large
database of ProMES projects has been developed (Pritchard et al., 2002). Most of the data are at
the group or unit level. The sample of jobs is diverse, including photocopier repair technicians,
university professors, police officers, and circuit board manufacturers. The types of organizations
are diverse, ranging from the military to educational settings. In general, ProMES has proven to
be a very successful methodology. Pritchard (1995) describes studies about development and
implementation of the ProMES system. He distinguishes between implementation in
manufacturing settings and service settings. We first discuss some examples of the manufacturing
studies and end discussing the service settings.
4.5.1 ProMES in manufacturing settings
ProMES is implemented in an electronic computer components assembly plant for the aerospace
industry in the US. The unit in which ProMES is developed consisted out of five members and
the activities performed by that unit included inspection of end products, correcting problems,
apply coatings and final inspection. The researchers were successful in using the ProMES
approach in an organization engaged in team-based manufacturing. The exact gain in
effectiveness is not known because only anecdotal data could be used at the company.
The next company in which ProMES is implemented is “Vandra Corrugated Fibreboard”. It is a
medium sized firm that produces corrugated packaging for a large variety of customers. The
development group included a group of employees operated a die cut machine that produces
various kinds of corrugated board boxes and consisted of four people. The production process is
simple and straightforward. Two years after implementation of the system, is has resulted in an
effectiveness increase of 37% as a percentage of the maximum scores, thus the ProMES system
was successfully implemented.
Another study describes the development and implementation of ProMES in a factory for the
production of safety devices for electric control systems. The research setting was one of the
manufacturing centres of the production department and was characterized by a high degree of
automation. The group (five people) assembled circuit breakers in a flexible assembly centre,
with main activities as maintenance, (un-)loading parts, tool change and control. The conclusion
was that ProMES could successfully be developed in an advanced manufacturing system, because
the effectiveness of the experimental group doubled.
The fourth study described in the textbook (Pritchard, 1995) was about implementing ProMES in
a manufacturing department of a small corporation in an outdoor sports industry in the US. The
measurement system was implemented in the manufacturing department, where raw materials
were purchased, cut and sewed, and where inspection and packaging took place. The
effectiveness at the department improved with 15%, which was determined by dividing the actual
improvement by the maximum possible improvement.
The final study about ProMES in a manufacturing setting was about a manufacturing facility in
the US. The development group consisted of fourteen people and was working in a chemical
processing assembly line. The group blends, compacts, and granulates powdered chemicals
together. The study gave an indication that ProMES can successfully be implemented even in a
private sector organization that is already performing well, because there was a 24% gain in
overall effectiveness.
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4.5.2 ProMES in service settings
The developer of the ProMES system, Pritchard et al., 1988, developed the system with the help
of field studies at five organizational units at an Air Force base in the US. One was the
maintenance section (repairing electronic equipment) and the other four sections made up the
material storage and distribution branch. The number of people involved in the project ranged
from 29 to 35 and from 47 to 54 respectively. The outcome of the study was that ProMES appears
to be a very effective way of measuring productivity: the system is successful in aggregating
productivity measures across units, feedback has a strong effect (productivity increase of 77%) on
productivity and goal setting and incentives (total productivity increase of 79%) increased
productivity over feedback.
ProMES is implemented in a branch of a service division of a multinational computer systems
organization. The service groups are responsible for the maintenance and repair of the computer
systems where the ProMES system resulted in a 25% increase of productivity. ProMES is also
developed and implemented in a field service department of technicians servicing photocopiers at
client offices (Kleingeld, Van Tuijl and Algera, 2004). They tested which of the two methods
(participation vs. tell-and-sell) resulted in the highest increase in performance. The participation
method resulted in higher performance increases. ProMES is also implemented at a major US
university for evaluating the teaching effectiveness of professors. Receiving feedback about the
scores of the instructors from ProMES caused a productivity increase of about 86%. Other studies
described by Pritchard (1995) are about the development of ProMES at a large Dutch bank and in
units of a small oil trading company (clerical support and sales). The final study described was
about an organization of commercial painters. The activities performed by the work organization
were painting (buildings etc.), installing glass, heat insulation and handling administration.
4.5.3 Differences between previous cases and a job shop case
The manufacturing settings in which ProMES is implemented up till now can be generalized as a
straight line production process at which a group of employees work together on one product. The
studies mainly involved only one group of employees at which ProMES is developed. No big
problems showed up by developing the ProMES system in these situations. In table 4.1 we give
an overview of the main differences between the situations in which ProMES has successfully
been implemented and the situation of a job shop. We highlight the factors which make it difficult
to implement a ProMES system. As can be seen, difficulties arise at a job shop (sign X) in
comparison with the flow line and assembly line (sign O).
Factors Job shop Flow line Assembly
Scheduling X O O
Flexibility X O O
Varying routings X O O
Varying capacity X O O
Level of automation X O O
Number of work groups X O O
Table 4.1: Differences between job shops and other production configurations
We can conclude that the ProMES has been successfully implemented in different organisations
and production situations, but has only been implemented once in a situation of complex
interdependencies between machines and teams such as a job shop production process (Huve,
2005).
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4.6 Advantages and disadvantage of the ProMES approach
In most cases ProMES has been developed for groups of employees and also for individual jobs
(bank and university employees). “The main advantage of the ProMES method is that the
complexity and uncertainty of collaborative relations is made clear and a common frame of
reference is developed so that communication about what is happening is greatly simplified and
improved”, (Van Tuijl, 1997, pp. 353). The most important advantages according to Pritchard,
Lawrence, Goode and Jensen (1990) are:
1. The ability to provide a single index of productivity as well as sub-indices
2. The system is valid (complete and accurate system), because several components are
involved in a valid system
3. Flexibility, it can respond to changes in organization’s priorities
4. The ability to aggregate across units
5. Acceptance of organizational personnel
6. Positive motivational properties. ProMES measures and improves productivity by
increasing the amount and quality of the feedback, positive feedback, and enables
employees to see the results of their efforts.
7. Role clarification. By proceeding through the first three steps of the system (product,
indicators and contingencies), employees are helped to more clearly understand their
roles, which on his turn has a positive motivational effect
8. The ability to provide a considerable amount of information about the work to be done. It
guides employees by indicating which activities they should be doing and their
importance.
The major risks and disadvantages of the system will now be discussed. It is essential that the
department is working in such a way as to maximize the objectives of the broader organization.
By the use of a bottom up approach (such as ProMES) it is difficult to insure that this consistency
between the group’s products and the overall organizational objectives exists. For example if
higher management is not clear on their goals, it will be difficult for them to assess whether the
group’s products are consistent with these broader goals. Another situation is where management
itself is not comfortable with the typical ProMES bottom up approach. They may not have trust in
the lower level groups when these people have to develop the measuring system, or they may
want to implement some changes in the business strategy and want to use the top down approach
to communicate these changes. This suggests that in some situations a top-down approach can be
a valuable addition to the standard ProMES approach.
But on the other hand, a too much top down approach may limit the acceptance of the system by
the employees, so participation is an essential element of the design process. By the use of
ProMES, the employees really are involved in the whole process of setting up and maintaining
the system, which will result in high acceptance and commitment (Pritchard, 1995). Thus to
increase the acceptance of the system by the employees a bottom up approach, as used by
ProMES, is required. An alternative of both approaches is the tell-and-sell approach (Kleingeld,
et al., 2004). In this study, the tell-and-sell approach was used for the implementation of ProMES.
The tell-and-sell style can lead to acceptance because then it is told that other employees are
developing the indicators and do have the control over these indicators. The tell-and-sell approach
turned out to be slightly less successful than the participative method, because there is no
personal involvement in developing and controlling the indicators by those to whom the system is
told and sold, but it may satisfy in some specific situations.
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Another aspect which has to be taken into account is that the system will probably not survive
when the system is not compatible with other control systems (Kleingeld, et al, 2004). Another
problem is the time span needed for development of the system. It takes a lot of meetings of the
design team what will result in development duration of about 6 to 18 months, what may lead to
that design team members lose interest (Pritchard, 1995). A main characteristic of the system that
can be taken as a disadvantage is that the system of ProMES only provides outcome feedback,
and does not provide suggestions how to change task strategies, cooperation and exchange of
information to improve productivity.
4.7 Conclusion
ProMES has been successfully developed for different organisations, departments and settings, as
described in this chapter. The system is applied to different types of industries, the technologies
varied greatly and included personal service, high and low technology manufacturing in
individual, team and assembly line settings, technical repair and professional service. Also the
jobs themselves varied greatly. The conclusion is that the ProMES system is applied to situations
which differ from the job shop situation (except the study of Huve, 2005). Because the job shop is
a different production process with its specific difficulties/problems as mentioned in chapter 3,
we will determine how the ProMES system and the production process can be matched, so the
system leads to reliable measures and to effective improvements in productivity.
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5. Productivity measurement in job shop situations
In this chapter we provide ideas and solutions how to develop a ProMES system for a job shop
situation. In paragraph 5.1, we discuss the level at which ProMES could be applied. The level of
measurement is dependent on job shop specific factors which influence the success of the
ProMES system. We explain why these factors are negatively influencing the implementation and
maintenance of a ProMES system and put that into a model in paragraph 5.2. Ideas and solutions
for these stated difficulties are generated in paragraph 5.3. General, these ideas are concerning the
level (individual, group or departmental) at which it is most optimal to measure productivity and
give feedback to.
5.1 Discussion of the levels of measurement
ProMES can in theory be developed and applied to different group sizes and at three levels
(Pritchard 1990). The three levels that can be determined are:
1. Individual level
2. Group level
3. Department level
At distinguishing the levels to which the system has to be applied, two factors have to be
analyzed (Pritchard, 1990):
- The kind of work and company
- The consideration between the effect of the feedback and the ease with which the
system is developed and maintained
In general, feedback about individual performance is more effective than feedback about
performance of a group of people. Providing feedback to each individual or a small group of
people will lead to higher changes in motivation and productivity because then people can easily
recognize there individual contribution, which is difficult to recognize when a large group is fed
back at once. The difficulty here is that is takes a lot of time to generate detailed information and
data of each person individually. Thus the trade off is between the level of measurement and the
time and effort of generating feedback, to make the performance measurement system efficient.
Another problem is that it is not always possible to separate the activities and productivity of an
individual from the activities and productivity of a group. Generally in a job shop, the individuals
within a unit are commonly responsible for the same tasks and have the same activities to
perform, so it is probably not needed to separate the activities and productivity of each individual
within a unit. Also the within-group task independencies are high, so it is not preferable to
measure on individual level. Individuals are performing as an intensive team and according to
Tesluk et al. (1997), motivational programs for these kind of teams should focus on team level
processes and outcomes. A ProMES system at individual level can only be applied when each
individual employee is responsible for a specific operation or task and the within-group task
independencies are low. Generally this is not the case in a job shop situation. Because a group of
employees are responsible for a similar operation(s); common products, performance indicators,
contingencies and a feedback report can be developed. For example, all employees who are
situated at the saw unit perform about the same activities (sawing parts on the machines) and are
as a group responsible for the output of that unit.
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In general, the rule is to give feedback to the smallest possible group in which the internal
dependency relationships are stronger than the extern dependency relationships. Results of
previous studies (Pritchard, 1990) showed that it is most effective to give feedback to a group of
five to thirty people. Thus concluding, due to the intensive characteristics of the group (tasks
interdependency within the group is high) and due to the difficulties of applying ProMES to each
individual employee of each unit, we leave out this option for the remainder of the research and
we state that in a job shop situation ProMES can only be developed and applied at two different
levels:
1. A ProMES system for each functional unit (which can also be a one-person group);
2. A ProMES system for the whole production department.
When measured at group level it will take more time and effort the develop and maintain the
measurement system because a system has to be developed for each unit, but will have more
impact on productivity than when measuring on department level what will take less time and
effort to develop and maintain. It is difficult to recognize the unit contribution when a large group
is provided with feedback about the overall productivity performed by the whole group. Applying
on group level and on departmental level has both its advantages and disadvantages. It is clear
that applying on departmental level will be easiest, but is the least effective option. Up till now
we can not make a valid choice about which of the both levels is possible and the most effective
in a job shop.
To be able to make a valid choice about the most optimal level of measurement, we will discuss
the problems/difficulties which will show up at applying a ProMES system to a job shop process
in the next paragraph.
5.2 Factors influencing the success of ProMES
A main shortcoming of the ProMES method is that it is less applicable in situations with complex
interdependencies between groups. So it will be a difficult task to implement the ProMES system
in a complex production situation as a job shop at unit level. When productivity of units is
measured, it automatically leads to comparisons between these units, what leads to individualistic
behaviour and increases the risks of sub-optimization (and competition). Another aspect what
could lead to problems at implementing the system at unit level is that the operators do not have
the complete control over there productivity. Showing these examples indicated that some typical
job shop characteristics are influencing the success of the ProMES system.
5.2.1 The interdependencies between units
A job shop system represents a highly complex production environment with complex
dependency relationships between the different units, so the units are strongly dependent of each
other if it comes to exchange of information and products and changes of any kind. These
dependencies can be seen as sequential dependency (work on the result of previous units) and
reciprocal dependency (work flows back and forth between units). Examples of interdependencies
are: work on a part when another unit is finished with that, the quality of preceding work, speed
of doing work is dependent on the speed of getting parts or material when needed, how efficiently
the output is produced depends on how production scheduling has arranged the orders (Pritchard,
1990). For this kind of relationships, interventions aiming at improving performance should be
focusing on the contribution of the units and also focus on the exchange sequences between units
and on departmental performance as a whole (Tesluk et al., 1997).
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When measuring and evaluating on unit level, the individual unit contribution has to be
visualized. This is needed for obtaining detailed production data of each unit. But the problem is
that due to the dependencies between units, the departmental performance can hardly be
decomposed into the performance of independent units. The requirement of the ProMES
methodology is that the activities and tasks of the employees have to be controllable so the group
has the ability to influence the score on the indicator. Thus another problem for the development
of a ProMES system at unit level is that due to the interdependencies between units, the activities
and output of each single unit can not be fully controlled by each unit itself.
The productivity of the employees is influenced by some factors which they can not control.
These uncontrollable factors have to be ruled out or have to be taken into account by
implementing a measurement system. Factors influencing the controllability on the productivity
of the operators are for example; machine breakdowns, changes in production planning and
quality of raw material.
When a ProMES system is developed for each functional unit, all roles, activities and
responsibilities within the production department of the company must exactly be appointed and
applied to one of the functional units. Then no misunderstandings will exist about who is
responsible for which operation. This means that the units only have to work on those specific
operations at all times to be able to carefully measure their score on the performance indicators.
On this turn, it implies that other units may not (want to) work on the operations of another units
because this can have a negative influence on their productivity. This process leads to an increase
of productivity of that unit, but a decrease of the overall productivity of the department.
A practical difficulty is that is takes a lot of time and effort to develop a ProMES system for each
individual functional unit. Because then for each unit; products, performance indicators,
contingencies, the method of measuring and the relative importance for the company have to be
determined several times. With other words, each of the four development steps of the ProMES
system has to go through several times for each functional unit. But also the time required for
measuring the productivity each period at each single unit is much higher in comparison with
measuring on departmental level. This increase in development and maintenance time will
decrease the effectiveness of the application of the measurement system and will lower the trust
of the employees to the system.
The alternative is to develop a system for the whole production department with common
products, performance indicators, contingencies and one feedback report and measures take place
departmental level. According to the problems described above does it seem that a system for the
whole production department will be a better option, because among other things; the
interdependencies will not be removed, cooperation stay intact, it is less time demanding and
roles and activities do not have to be exactly appointed to a specific unit. The cooperation
between the different functional units will stay intact when a common system for the whole
production department is developed. Thus the employees will share the same feeling of strong
commitment to achieve a high as possible productivity for the whole department because
everyone is responsible for the overall result. A major disadvantage of developing and applying a
ProMES system to the whole production department is that the feedback report represents a
general feedback for all units in common. When information about the performance is fed back to
the whole department, it is difficult to recognize what the individual contribution was to the total
performance. An additional drawback of applying the system to the whole department is that
some units will perform less work when their unit productivity is not confirmed. This will lead to
a decrease in total productivity and an unfair situation because some units have to compensate for
the less performing units.
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5.2.2 Shifting operators between units
Often in job shop production processes operators are shifted between various functionally units.
Operators are shifted to a high demanding unit when the demand at “their” unit is low. The
problem is that the scores on the indicators will be influenced because changing the number of
operators and also the skills of the operators influences the outcome of that specific unit. The
achieved productivity is then not representative anymore for the possible achievable productivity
of that unit. The fact that operators are shifted between units influences the possibilities to apply
ProMES at unit level. The result of the varying unit output is that it is difficult to decompose the
departmental productivity into single unit productivity, thus it would be a problem when the
system is applied at unit level.
The output of the units will depend on the personnel working at a specific unit. This implies that
the personnel of the functional units can not fully control the output of the unit when the amount
and skills of the personnel is constantly being changed. Thus shifting operators between the
functionally units, which happens often in a job shop, decreases the ability to influence the
outputs and productivity of the functional units.
5.2.3 The rapidly changing orders
As described in chapter 4, at development phase 3 of the ProMES system, contingencies have to
be established. The contingencies show the amount of an indicator, ranging from worst feasible
level to best feasible level of productivity that could be scored on an indicator and also the
effectiveness value which represent what the achieved productivity (score on indicator) means for
the whole organization. A job shop production situation is characterized as a vast changing
production environment as described in paragraph 3.4. Thus in job shops, historical production
data is not always present due to much varying demand and nature of the orders each period,
which changes the possibilities of the units per period. And historical production data is just what
is needed to define the standards (worst and best feasible performance levels) which are required
by determining the contingencies. The unstable and unpredictable situation which is typical for a
job shop is caused by some various reasons. The first reason is that at job shops many different
products and parts (and of few amounts) are manufactured. Thus various orders and tasks have to
be processed by the functional units per period. Each order has its specific design and
requirements, which leads to different achievements in productivity over a specific period of
time. Thus it is hard to obtain historical experiences to make any judgments as to what is low or
high output due to the large variations in orders. The output varies each period, depending on the
nature and the demand of the work. This negatively influences the control the operators have on
the output of their units. The more the orders are varying, the more variations in output, what
implies decreasing control on unit’s productivity.
5.2.4 Different interests of the units
When ProMES is developed for each functional unit within the production department each
having its own (different) products, performance indicators and contingencies; the dependencies
between groups will partly be removed. Unit goals will become independently of the goals of
other unit when the productivity of the units are measured and evaluated separately from the rest.
Due this independent goal relationship; the interest of each unit will differ from the interest of
other units. Van Vijfeijken et al. (2002), state that goal interdependence reflects the way in which
goal attainment of an individual (a unit in this situation) is influenced by goal attainment of
others. In our situation, the goal interdependency is neutral (Van Vijfeijken et al., 2002).
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Neutral goal interdependency leads to individualistic behavior of the units, what on his turn can
lead to sub-optimization because little energy will be used to develop cooperation strategies (Van
Vijfeijken et al., 2002). Sub-optimization could lead to competition between units what will lead
to decreased coordination and productivity. Sub-optimization means that a functional unit on its
own does perform well, but the performance of the whole production department will likely not
increase. Units try to score high on their own products and performance indicators when ProMES
is implemented for each functional unit, but this can have negative influences on the other
functional units and the score on their indicators. It is stated by Van Vijfeijken et al. (2002) that in
this situation, the development of cooperation strategies can be stimulated by setting common
goals which create positive goal interdependence, and individual unit goals, because this
combination resulted in the highest productivity improvements. Thus by setting both goals for the
units and joint goals for the whole department, the units also try to reach these common goals
along with their own specific goals, so sub-optimization can be overcome.
Productivity achieved by one unit can have less meaning to the overall company than another
unit. Thus the contingencies have to be adjusted by concerning the relative importance of each
functional unit. A solution to this problem is a method called “scaling”, developed by Pritchard et
al. (1990). Scaling means that the contingencies developed for each unit have to be rescaled to the
relative importance of the units. The relative importance of each unit can be used when taking the
individual conditions at each unit into account. If it is possible to convert the contingencies to the
relative importance of each unit, we are able to combine the unit’s measures into a single measure
for the whole department. Factors that influence the productivity of the functional units are for
example the number of tasks the unit is performing, the nature of the work, number of machines
and operators and the production speed of machines and people.
But the scaling strategy is developed in the early phase of ProMES and the view of Pritchard has
been changed over time (Pritchard, 1995). Pritchard believes that the strategy will not optimally
work because not all the responsibilities of a department are contained into the measurement
system. An example is the responsibility to manage the coordination between different functional
units. A solution according to Pritchard (1995) might be to measure both on unit level and on
departmental level. The scaling strategy can still be used as we attended to do; the productivity
measures of each of the units can be combined and give an index of the average total productivity
of the units (thus how the units are doing as a group). But a comment we can place is that when
one optimally wants to make use of the scaling strategy, should also take the responsibilities for
the department as a whole into account.
5.2.5 The relational model
When we summarize the problems described above into a model; each of the described factors is
commonly related to three main factors. These three main factors are on their turn indirectly
influencing the success of a ProMES system for a job shop. These factors are negatively related
to the success and can be identified as:
1. Decomposition of departmental performance - Departmental performance can hardly be
decomposed into the performance of independent units.
2. Low controllability - Groups can have a substantial, but not major influence on unit
performance.
3. Risks at sub-optimization - Job shops consists of multiple compositions of groups with
different interests.
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These three factors are influenced by other related factors. We can define four factors which are
directly related to the three main factors and which are indirectly related to success; the between-
group dependencies, shifting operators, varying orders and the different interests of units. The
degree to which the success of the system decreases depends on how strong the influences of
these factors and relationships are at a specific job shop situation. The relationships between the
factors can be made clear in a model, which is presented in figure 5.1. The relationships are
represented by the arrows between the eight factors.
Figure 5.1: Relationships between factors influencing success of ProMES.
Decomposition is required when a system is applied on unit level. The interdependencies between
the functional units are negatively influencing the degree to which the departmental productivity
can be decomposed into single unit productivity. The interdependencies do also negatively
influence the control over the productivity, which is one of the most important requirements of
ProMES. Shifting operators between units negatively influences the ability to decompose
departmental productivity and the control over productivity. The many different orders that have
to be processed, which is typical for a job shop, are related to the control over productivity. Risks
at sub-optimization increase because the goals for each unit will become independent of each
other when the units are individually being measured. The three main factors are all related to the
success of the implementation of a ProMES system. The stronger these problems are, the lower
the chances at a successful implementation.
Up till now, we have described the difficulties and problems for applying ProMES which are
specific for a job shop situation. The developers of the ProMES methodology have determined
requirements for a successful development and maintainability of the ProMES system. The job
shop situation leads to these difficulties/problems because the specific characteristics and
conditions of a job shop can probably not satisfy these requirements. Application of ProMES to a
job shop can lead to problems because the situation can probably not satisfy the following
requirements (Van Tuijl, 1997):
Measuring and improving productivity in a job shop environment
T. de Boer 38
- the system is able to represent one single score for the total departmental productivity;
- the system is able to show how the total score is build up from sub-scores;
- the responsibilities have to represented by the unit and show these responsibilities at a
valid way.
The facts discussed above require us to create a situation in which the total departmental
productivity is decomposed into single unit productivity, so one is able to individually recognize
and measure the productivity of each single unit. Thus one of the most important trade-offs is the
level at which productivity is measured and at which information is feed back (unit or
departmental). Additional requirements are stated for the development of products, indicators and
contingencies which are probably difficult to satisfy by the job shop situation (Van Tuijl, 1997):
- employees have to be in control so they are able to influence their productivity;
- stable work environment and conditions for reliable determination of the contingencies.
In this paragraph we have explained why it is hard to satisfy these requirements when ProMES
have to be applied to a job shop. Due to these problems, we do not know what the possibilities of
applying ProMES to a job shop are at this moment and how strong the relationships of the model
are. In the next paragraph we formulate some ideas to solve the problems stated above. And in the
next chapters we try to find out if the causal relationships as presented in figure 5.1 are valid for
the research company.
5.3 Generating ideas for developing and applying ProMES
One of the research questions of this research was; “How to define productivity in a job shop
situation and how can it be measured?” Productivity can be defined and measured as described by
Pritchard (1990), thus we do not only determine the definition of productivity of a job shop, but
we will combine that with the determination of the level to which it is best to develop and apply
ProMES. At generating ideas for applying ProMES and measure the productivity we concentrate
on what level (unit or departmental or a combination) it is best to measure productivity instead of
defining productivity. In other words; the question; “What is productivity in a job shop?” will be
answered in combination with the determination of the level at which it is best to develop and
apply ProMES.
The objective of this idea generating phase is to come up with a solution about the level at which
it is best to development of a ProMES system. The ideas are determined according to the
possibilities within a job shop, and the trade off between the development time and time to
maintain the system and the highest possible improvement of overall productivity. We want to
create a situation where it is possible to recognize the changes (increase or decrease in
productivity) at departmental level by knowing which factors at unit level caused these changes.
The main goal of the ProMES methodology is to improve the productivity of the employees so to
achieve the organisational objectives. For example; manufacture more and innovative products in
a safe environment at low cost. The changes in productivity will at first be recognizable at
departmental level. When productivity changes are recognized at departmental level, in for
example; processing times, lateness and quality, we want to be able to determine which factors at
unit level influenced these changes, see figure 5.1. And the other way around, when changes
applied on unit level, we want to be able to determine to which changes that will lead in total
departmental productivity.
Measuring and improving productivity in a job shop environment
T. de Boer 39
Figure 5.1: Relationships between unit and departmental level
We want to visualize and measure the productivity at each unit to gain improvements in total
departmental productivity, but we do have to bear in mind what the possibilities and difficulties
for such a system are. At this moment we do know what the difficulties in theory are, but we do
not know what the possibilities in practice are. The situation described above is the most optimal
situation and is the objective of the idea generating phase, but again, we do not know what the
possibilities in practice are. That is why we generate ideas by considering the difficulties of a job
shop and possibilities of the ProMES system. We first determine the idea which creates the
situation as described above, this would then be the idea what leads to the most optimal situation.
After explaining this first idea, we will determine if there are any difficulties or disadvantages
implied, which are then tried to be solved by introducing a new idea. After analysing a job shop
system at the research company we can determine which of the ideas are possible and is the best
option for the development of the ProMES system, but this will be discussed in chapter 7 and 8.
IDEA 1 The objective is that we want to be able to know to which changes in total departmental
productivity it leads when changes are applied on unit level. Thus we have to apply ProMES to
the smallest possible group in a job shop, to determine which and/or who influenced the changes
in productivity at departmental level. An additional advantage is that a performance measurement
system is most effective when the achieved performance is fed back to a “small” group of people.
The production department characterized as a job shop can be split up into different functional
units. This is the smallest group of people that can be measured and evaluated (we already left out
the option of a system for each individual person). The first idea is to develop a ProMES system
for the department, and measures takes place at each individual functional unit, as graphically
shown in figure 5.2.
Figure 5.2: Idea 1
The same products, indicators and contingencies are determined for all the units, because then it
is possible to compare and sum up the unit scores and to obtain scores representing the overall
productivity of the department.
Department
Feedback
Measure Measure
Measure Measure
Unit
Unit Unit
Unit
Measuring and improving productivity in a job shop environment
T. de Boer 40
One general feedback report must be set up which represents the total departmental scores on the
indicators which are build up out of the scores of each single unit. This leads to decreasing
chances at sub-optimization because employees are forced to maximize the overall departmental
score. The first idea for measuring productivity and developing a ProMES system is:
Idea 1: Develop a ProMES system for the department, and measure each
functional unit individually
We will now analyse if difficulties show up at each of four development phases of ProMES. The
idea causes no problems at the first phase; key result areas (products) can be defined because
products stem from the organizational objectives and goals. Products which can be determined for
example are production speed and machine utilization. No problems will occur at development
phase 2; developing indicators. An indicator is a measure of how well the unit is generating the
product in question. Indicators for the two given products above can be for example the number
of products processed and the time the machines were on divided by the time the machines were
off. In phase 3 where low and high productivity must be determined is not dependent on the level
of measuring, so no specific problem caused by this idea. Phase 4, where the actual productivity
has to be measured and recorded in a feedback report can hardly be performed due to this idea.
Each kind of output per unit has to be made visible and measurable what will be difficult due to
the interdependencies between the units. And as told before in this chapter, measuring on unit
level involves some other disadvantages such as; scores will not represent the actually possible
achievable performance due to shifting employees, it takes much time to develop and maintain
the system, the cooperation between the units is partly removed which can lead to a decrease of
overall productivity.
IDEA 2 Due to the described problems above we now come up with an idea which takes out some of
these problems. Generally, the next idea is to measure both at unit and departmental level, thus by
setting unit goals with additionally some departmental goals. This will decrease the chances at
sub-optimization, it will increase the cooperation between the units and the relationships between
the units stay intact. The design team has to analyze which productivity aspects can not or are
hard to separate into unit’s productivity, and choose to measure these aspects at departmental
level. Products to be set up at unit level can be for example; the number of products produced,
quality and machine utilization and on departmental level for example; lateness of delivery and
total energy use. Products, indicators and contingencies have to be set up for both the units and
the production department when this idea is implemented. Goals have to be set on unit level
because this mostly motivates people to work more efficiently and information can be fed back to
each individual unit and also goals have to be set on departmental level to take away the
difficulties described above. This second idea is graphically shown in figure 5.3.
Figure 5.3: Idea 2
Measure Department
Feedback
Measure Measure
Measure Measure
Unit
Unit Unit
Unit
Measuring and improving productivity in a job shop environment
T. de Boer 41
The idea is thus to maintain the first idea and expand that idea with some measures on
departmental level. The second idea for measuring productivity and developing a ProMES system
is:
Idea 2: Expand idea 1 with measures on departmental level
Development phase 1 of the ProMES system (identifying products) will not cause any problems.
The difference now is only that on both levels (unit and department) products have to be defined.
The same counts for phase 2 and 3; no problems will show up after implementing this second
idea, it will only take more time to determine and set up the indicators and contingencies at both
levels. The difference this idea makes in comparison with idea 1 is that fewer problems will show
up at the measurement and feedback phase (phase 4). This is because now some productivity
aspects which can not be decomposed into unit’s productivity will be measured on departmental
level. So it is not required anymore to visualize and measure all the productivity aspects at each
single unit. A comment here is that it may not be possible to visualize and measure any kind of
productivity at each single unit, what implies that this idea is not an improvement over the first
idea.
When this idea is applied to the ProMES system, it will require much more development time,
because products, indicators and contingencies must be defined on both unit level and
departmental level. Also the maintenance time will increase drastically because productivity has
to be measured and fed back on both levels. It might be still the case that productivity cannot be
measured at unit level because none of the productivity aspects can be separated and ascribed to
single units. The problem of shifting employees remains so unit scores will not represent the
actually possible achievable performance.
IDEA 3
Due to the problems showing up at both ideas described above, it turns out that it would be better
to measure on a higher level. The improvement is that measuring on higher level leads to better
cooperation between the units and the interdependencies between the units will not be removed.
A disadvantage of measuring on a level which is too high is that the individual unit contribution
can not be recognized anymore what leads to fewer changes in motivation and productivity. It
might be possible to combine units which are closely cooperating and to measure and apply
feedback to as a whole group. According to Pritchard (1990) a group is formed with the criterion
that the smallest possible combination is formed in which the intern dependency relationships are
stronger than the extern dependency relationships. Thus we want to keep the measurement group
as small as possible (most effective), but the measurement level has to be increased. Thus we first
propose the idea to form a cluster of units, instead of developing a system at departmental level.
Other advantages in comparison with idea 2 are the decrease in measurement time and the most
important relationships will stay intact. Forming a cluster of functional units is only possible
when that specific set of units are very closely cooperating and having together the
responsibilities for manufacturing specific parts. Thus they are together performing tasks and
operations which results in a common measurable outcome. Often in job shops operators are
transferred between the units when demand is low on one unit and high on another, and because
the have the skills to operate other machines. The thought behind this third idea is thus that due to
closely cooperation between some units and shifting of operators, a group of units can be
combined and be taken as one group. An example is to combine a saw unit with the milling unit,
because they are tightly joint together, have a narrow cooperation, and the operators perform
activities on both units. The idea is thus to develop a ProMES system for the department, and
measure a group of functional units. The third idea is graphically shown in figure 5.4.
Measuring and improving productivity in a job shop environment
T. de Boer 42
Figure 5.4: Idea 3
The same products and indicators have to be set up for the groups, and then the group scores can
be summed up as one score representing the score of the whole department. The general feedback
report is built up out of the group scores which are summed up to the total department
productivity. The third idea for measuring productivity and developing a ProMES system is:
Idea 3: Develop a ProMES system for the department, and measure a group of
functional units
Considering the four development phase of ProMES, we can state that the first phase will not
cause any problems; products can still be defined for the units. This idea does not change
anything on the performability of development phases 2 and 3 in comparison with the previous
ideas; indicators and contingencies can be set up without influences of this third idea. Still
problems might show up at development phase 4 where the actual scores on the indicators have to
be measured and fed back to the floor. We can state that this third idea is an improvement in
comparison to idea 1 and 2 concerning the problem of recognizing and measuring the
productivity of each single unit, only if there is a situation of closely cooperating units.
A disadvantage of this idea is that the motivational efficiency decreases, because feedback is
given to a larger group of people. A drawback of this third idea is that we do not know if it is
possible to form a group of units. Other problems which emerge are the same as emerged at idea
1 and 2; scores do not represent the possible achievable performance (changing production
environment), it still takes much time to develop and maintain the system and maybe it is till not
possible to remove all the relationships between the units even though groups are formed.
IDEA 4
Due to the remaining problems of this third idea, we will enlarge the measurement level to
department level. The improvements in comparison with the previous ideas is that it is not needed
to separate the production department into smaller groups, so relationships and cooperation will
stay intact and eventually increases, development and maintenance time drastically decreases
(measure only at departmental level), sub-optimization and shifting of employees do not cause
problems any more. So the next idea provided (see figure 5.5), is to develop one measurement
system by which the overall productivity of the department is measured and fed back. The idea is
thus to develop and implement one ProMES system, with common products, indicators and one
feedback report. The fourth idea for measuring productivity and developing a ProMES system is:
Idea 4: Develop a ProMES system for the department, and measure on
departmental level
Department
Feedback
Measure Measure
Unit
Unit Unit
Unit
Measuring and improving productivity in a job shop environment
T. de Boer 43
Figure 5.5: Idea 4
When the ProMES system is applied according to this idea, no problems will occur at the four
development phases; products, indicators, contingencies can all be defined and it is easy to
measure the productivity of the whole department at the end of the final production step, and a
feedback report can be set up easily. The departmental score on each of the indicators is fed back
as a whole to the department. But even this fourth idea implies some problems when implemented
into the company; a major disadvantage of this fourth idea is that it is the least effective idea (less
motivation thus small changes in productivity) because the measurement group is probably too
large. The disadvantage is that people or units cannot recognize their individual contributions
when the scores are fed back to the whole group, because they are not enough motivated to
improve their productivity. Also, it can not be assumed that each employee and unit works as
hard and do one’s best as another to maximize his or her productivity, because he or she does not
have the intention (not enough motivated) or the possibilities to do that. The problem is thus that
the total overall productivity can not fairly be seen as the sum of productivity of all units because
units do not always (try to) maximize their productivity.
After describing the succeeding ideas it turned out to be that each idea does not overcome all the
problems. Thus maybe the first idea will still be best performable, because the other ideas do also
encounter important problems. The advantages and disadvantage we mentioned at the four
described ideas are concerning a job shop situation which is the “worst case scenario”, thus the
situation with the most difficult interdependencies, complex material flow, low control on
productivity, etc. The advantages and disadvantage of each of the provided ideas are summarized
in table 5.1.
The conclusion is that at this moment we can not make a grounded and reliable judgment about
which of the ideas is best possible. First we have to analyze the production department of the
research company before evaluating the four ideas. We will analyse the practical possibilities of a
ProMES system according to the research company in chapter 7 and the best idea is determined in
chapter 8.
Measure Department
Feedback
Unit
Unit Unit
Unit
Measuring and improving productivity in a job shop environment
T. de Boer 44
Ideas Advantages Disadvantages
Idea 1 - This is the most optimal situation. Thus
one is able to know which changes to
apply on unit level, to recognize the
desired changes in productivity on
departmental level.
- Hard to measure each unit individually
- Much development and maintenance time
- Fact of shifting employees
- Chances at sub-optimization
- Cooperation between units might be
removed
Idea 2 - The most important relationships stay
intact
- Better cooperation between units
- Decreasing chances at sub-optimization
- Still not possible to measure each unit
individually
- Much development and maintenance time
- Fact of shifting employees
Idea 3 - Better cooperation between units
- Interdependencies between units are only
partly removed
- Decreasing measurement time
- Shifting employees is no problem
- Less motivational
- Still some chances at sub-optimization
- Difficult to combine specific units
Idea 4 - No separation of units
- Cooperation and relationships stay intact
- Shifting employees is no problem
- Development and maintenance time
drastically decreases
- No sub-optimization
- Least motivational idea, thus small
changes in productivity is expected
- No fair measurement system
Table 5.1: Advantages and disadvantages of the generated ideas
Measuring and improving productivity in a job shop environment
T. de Boer 45
6. Description of the research company
The theory described in previous chapters will be tested in the practical situation of the research
company; “Exerion Precision Technology”, Ulft, the Netherlands. Also the ideas presented in
chapter 5 will be checked and tested according to the situation at that company. Paragraph 6.1
shortly describes the company. In paragraph 6.2 we give a general overview of the production
process. The production department can generally be divided up to four work centers, which are
described in 6.3. The part of the production department which can be characterized as a job shop
system is described in 6.4. The question; “Does and how does the company measure the
productivity of the production department?” is answered in paragraph 6.5. In paragraph 6.6 is
explained what the implementation of the ProMES system means for the remaining departments
of the research company.
6.1 Short description of the company
Exerion precision technology designs and manufactures metal chassis and mechanical parts for
printing and medical equipment and the demand is stable and predictable. It operates three
production facilities in Czech Republic, the Netherlands and Malaysia. The market can be
characterized as a business to business one. There are working around 250 employees in the
production facilities in the Netherlands, Czech Republic and Malaysia. The project is
concentrating on the production facility in Ulft (Netherlands). The product assortment can be
defined as low volume and high variety. The acceptance of ordering is according to a yearly
agreement at which the customers provide Exerion with a forecast of their requirements. The
actual demand is realized by means of call-offs or single orders. The major part of the demanded
volume is rather stable from week to week. Exerion jointly designs new products for its
customers.
6.2 Overview of the production process
The project will be concentrated on the “parts production department” of the company, where a
large number of parts and operations are to be managed, and where most of the metal parts are
manufactured for later assembly at the welding lines. This department can best be characterized
as a job shop. At the production department, the process can generally be divided into four steps;
metal-sheet cutting, parts production, kitting and welding. All products manufactured by the
production department do not necessarily require each of these steps, and are often processed
through varying routings. After welding, the frames may be sent to an external supplier for
surface treatment, to module building (where additional components are affixed to them) or
directly to the customer. The general production process is sketched in figure 6.1.
Figure 6.1: The general production process at Exerion
The general production process will now be described. The main raw material consists of metal
sheets which are first cut into smaller flat parts and holes are punched into these part. These parts
are then further processed (bending and/or clinching) depending on the specific customer order.
Measuring and improving productivity in a job shop environment
T. de Boer 46
After the parts are processed at the bending and/or clinching unis, the finished parts are kitted
(collection of different part in a box, called a kit) and welded together forming sub-frames. These
sub-frames are next welded together which forms the final frame. In most cases, the frames are
transported to an external company for surface treatment. The treated frames are returned to
Exerion where additional parts are assembled to the frame or sometimes a couple of frames are
assembled together to form a “module”. The frames and modules are packed and sent to the
customers.
6.3 The four functional units
6.3.1 Metal sheet cutting
The end-products stem from large metal sheets. Thus at first the metal sheets are cut into smaller
pieces and also holes and large figures are made into the metal sheets by punching and laser
machines. Some parts are now ready for welding, other parts are first to be processed at the other
functional units. Three cutting machines are placed at this unit:
• One machine which cuts the large metal sheets by “punching”. Manual labour is required
to load and unload the machine
• Two laser cutters which can run unmanned. When the tools have been placed in the
machine, the machines automatically retrieve metal sheets from the automated
warehouse, cut the parts, and the parts are send back to the warehouse
This unit is working in two shifts, with three persons per shift. The required capacity is according
to the machines running, so there is no opportunity to increase the productivity at this unit by
adding more people. Sometimes, people are transferred from this unit, when more capacity is
required at one of the other units. The laser cutters can work unmanned, so when required to work
outside the normal working days, the operators set up the machines and let them run for example
in the weekends. A part of the metal parts are automatically stored at the warehouse and the other
part is manually collected in a box or carrier.
6.3.2 Parts production
Many of the parts that are processed at the cutting unit require further processing before they are
welded into a frame at the welding unit. Two main processes take care the parts production:
clinching (where a metal nut is attached to the flat part), and bending. It is preferred to firstly
perform the clinching activity before bending, because the parts will take more storage space after
they are bend, and flat parts are easier to handle at the clinching unit, when this is not performable
the sequence is vice versa.
Clinching At this clinching unit are two large machines and some smaller machines situated. The first large
machine is an automatic machine and the second is a manual machine. The automatic machine is
to operate big flat parts, thus no bended parts can be loaded on this machine. The parts are
horizontally positioned on a bench which can move in two dimensions, so the flat parts are
positioned to be automatically clinched according to the programmed coordinates. The manual
machine is loaded with parts one by one by the operator, where he or she manually positions the
parts and executes the clinch.
Measuring and improving productivity in a job shop environment
T. de Boer 47
All parts required to be clinched after bending have to be processed by this manual machine. The
remainder of the machines and equipment are used for smaller parts which require few
operations.
Bending
Four bending benches are located at this unit. Not all parts that previously are processed at the
cutting and clinching machines can be loaded at all the benches. The parts are processed one by
one and the bending benches are loaded manually by the operators. The setup of the bending
benches is precise and requires specific handlings by the operators. Mainly, there are two
activities which have to be performed in behalf of the set up. The first activity is preparing and
placing the tooling into the bench. Time required is more dependent on the thickness of the metal
sheets than on the shape or size of the parts: when thickness remains unchanged, only little time is
needed to change the tooling. The second activity consists of controlling the correctness of the
first bended parts. If correct, the remainder of the batch can be processed.
6.3.3 Kitting
The parts are stored at the automatic warehouse after the parts are cut and/or processed at the
bending and clinching units. These parts and parts from external suppliers are collected at this
unit. The parts arriving at this unit are collected in a “kit” and are prepared to be welded. This kit
is a metal box with compartments where the parts are put in.
6.3.4 Welding
There are five different welding stations placed at this unit:
1. A manual station, used when the geometry of the product(s) are not able to be welded
automatically by a robot
2. A dedicated robot
3. A flexible welding robot for small subassembly’s
4. A flexible welding robot for bigger subassembly’s
5. A flexible welding robot for welding the subassembly’s welded at the above mentioned
stations
The parts from the kits are positioned in welding moulds. The parts are manually fixed at a metal
tray, with presses for fixation of the parts. More than one sub-assembly can be obtained from one
welding mould. The flexible robots can proceed welding without changes in tooling or other set
ups, but loading the stations requires operators.
6.3.5 Automatic warehouse
The automatic warehouse is located in the centre of the production department. Material can be
flown via five different inlets and outlets. Two are assigned to the cutting units, two to the
bending and clinching units, each for one unit, and one to the kitting unit. A single lift in the
warehouse receives and passes on carriers from the units, with the highest priority for the cutting
machines, kitting and parts production (bending and clinching unit) respectively.
6.4 The job shop within the production department
The production department at Exerion contains the following operations in random order:
warehouse, cutting, bending, clinching, kitting, other operations, welding and module building. A
specific part of the production department can be characterized as a job shop system. The job
shop system itself contains four functionally divided units; these are the bending, clinching,
kitting and “other operations” units.
Measuring and improving productivity in a job shop environment
T. de Boer 48
The material can flow in different routings through the system depending on the specific orders.
Examples of these different routings for different orders are graphically shown in figure 6.2. The
produced parts at each of the units are stored in the automated warehouse before the parts are
further processed at other functional unit(s).
Figure 6.2: Examples of various material routings due to various orders in the job shop
6.5 Current way of measuring at the production department
Examining if and how management measures the productivity of the production department and
which aspects are measured can give some insights and ideas about the possibilities of ProMES in
the job shop. Exerion only measures one productivity aspect, which is the efficiency of the
working hours. The actual working hours are compared with the norm which stands for the
working hours. We will now explain this method. The first production run of new parts and
products is observed and the time span in which these parts and products can be processed is
registered. The set up times (for loading the machine with the tooling and the parts), the design of
the product and operating speed of the machines and operators are taken into account for
determining the standard working time. The management set this required time as a standard and
enters it in a database. This pre-calculation is performed at the cutting, bending, clinching, and
welding units.
Orders for the day and the week are announced to the operators by the use of memo’s, along with
the standard for each order. The employees have to register the starting and finishing time of
processing an order. The actual time which is used to manufacture the products, is compared with
the standard of that order. The efficiency is calculated according to these two figures by dividing
the standard by the actual working time. When it turns be that the efficiency was too low at a
specific unit in a specific period; the management reports it to the responsible person(s) and they
try to figure out what the problem caused.
Measuring and improving productivity in a job shop environment
T. de Boer 49
The outcome is that the management is able to measure the amount of time spend on processing
orders at each functional unit. This positive and very important outcome of the practical analysis
is that at Exerion it is possible to visualize and measure “productivity” at each single unit, thus
they are able to decompose the departmental productivity into single unit’s productivity when the
factor “efficiency of working hours” is considered. The management also explained that it is
probably possible to set up a kind of information system which will enhance registering more
than one productivity aspect at each functional unit, such as machine utilization, quality, safety,
etc. These results show that the current situation looks like the desired situation presented at idea
1 and indicates that it is probably possible to execute idea 1.
6.6 The meaning of ProMES in the framework of the whole organization
Companies are often composed of several departments. The overall goal of implementing the
ProMES system to a job shop is to improve productivity at the production department and on his
turn to better achieve the organizational goals or objectives, so the organization benefits from the
system. ProMES cannot independently be applied to the job shop department without influences
of other departments. Other departments do influence the development of the ProMES system
because the goals defined during the development of ProMES have to be corresponding to the
goals of other departments. The goals defined during the development of the ProMES system
should stem from the organizational goals, just as at the other departments but it has to be
controlled that the goals of ProMES are corresponding to the goals of the other departments. An
example of conflicting goals between two departments is that the productivity department focuses
on manufacturing high quality products in spite of the increasing manufacturing time, so the sales
department can not fulfill its goal to deliver products within due date. Both departments have
conflicting goals, because one department is aiming at quality and the other at the due date. We
believe that ProMES cannot be applied without any influences from other departments, because
there is a risk that the activities and goals, defined in order of the ProMES system, are in conflict
with the activities and goals of the other departments. Concluding; departments cannot be seen as
self-working-units, so ProMES cannot be applied to a department without taking the influences of
the other departments into account.
This study only implies improving productivity at a job shop department but it can also be applied
to other departments. The productivity improvements gained at the job shop department will lead
to better achievements of the organizational goals, and when ProMES is implemented in the other
departments it will probably result in even more benefits for the organization. But this has to be
researched in other studies.
Measuring and improving productivity in a job shop environment
T. de Boer 50
7. Assessing the research company on the applicability of ProMES
After analysing the situation at the research company we are able to determine if the theoretically
stated assumptions are confirmed by practise and to determine which of the ideas generated in
chapter 5 will be best possible. In this chapter we will asses the research company on the
applicability of the ProMES system. The question is thus whether and how ProMES can be
applied at Exerion. The results of the practical analysis at the research company are described and
compared with theory in paragraph 7.1. In paragraph 7.2 we evaluate the results and summarize
the possibilities of applying ProMES to the job shop of Exerion.
7.1 Results of the practical analysis
7.1.1 Method
We analysed the production department of the research company and interviewed employees of
the company to get insights of production process. The analysis was built up out of two parts; we
visited the research company and analysed the production department and interviewed people
(both operators and management) a few times. By analysing the production department we
concentrated on the part which can be characterized as a job shop. Things that became clear were
among other things material flow, batch sizes, shifting personnel, material waste etc. Next we
interviewed the manufacturing manager and the supervisors/planners of the production
department. The focus during the visits was on the difficulties of applying ProMES to a job shop;
the measurement level, variation in workload, dependencies between functional units, etc. The
questions stated during an interview can be found in appendix D.
7.1.2 Comparing theory with practice
In this part we will compare the results of the analysis of the job shop at the research company
with the theoretical findings which are described in chapter 3, 4 and 5. We will focus on the
difficulties/problems for applying ProMES to a job shop situation and compare that with what we
found in practise. The question to be answered here can be determined as: “Does the practical
situation confirm or reject the theoretically found difficulties/problems for applying ProMES to a
job shop?” We will discuss the results of the practical analysis according to the three main
difficulties for applying ProMES, mentioned in chapter 5.
7.1.2.1 Level of measurement
During the interviews we asked the management about the consideration of the level of
measuring. As described before, the ProMES system can be developed at three different levels:
individual, group and department. We have already taken out the option of developing at
individual level, but in spite of that, we search for the possibilities and asked for the opinion of
the management.
We presented the option of developing a ProMES system for each individual and thus separately
measure the productivity of each person at the production department. The people made clear that
it will probable take too much time and effort to develop and maintain a measurement system for
each individual employee. Then the implementation of the system will not be efficient, because
the time it will take to develop and maintain the system will not surpass the benefits of the
system. This is confirming what we found in literature.
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The second point is that a ProMES system at individual level has only to be applied when each
individual employee is responsible for a specific activity or task, what was not the case at the
company. Thus another result of the interviews why a system for each individual is not a good
option is because the employees at the units are performing about the same activities and have the
same responsibilities. Thus the people within a group can generally be placed under one activity
(e.g. bending or clinching) because of their common activities and responsibilities. This is partly
confirming the literature because in literature it is stated that it is difficult to separate the activities
and productivity of an individual with the activities and productivity of a group. But the
additional outcome was that it is not needed to do so, because the employees within a unit are
performing about the same activities. Within the units, people are also dependent on each other so
they closely have to cooperate, exchange information and make together decisions. Thus the
people within the units are much more interrelated than with people between the units, because
they do not take too much care of other unit’s responsibilities.
The fourth reason is that management believes that people just cannot be compared, because each
employee has different capabilities and skills. For example, one’s doing its very best can result in
more/less manufactured parts at a day than the result of another one’s doing its best. The fifth
reason why employees cannot separately be measured is because at the company often operators
are shifted between the working units, thus they are not always performing the same activities.
This is necessary when demand is low at unit A and demand is high at unit B. The system cannot
take into account all these constantly changing activities of each of the operators. These latter two
disadvantages of a ProMES system for each individual employee is not stated in literature, but are
very clear and good reasons to take this option out.
7.1.2.2 The interdependencies between units
Next, questions are asked about the possibility of developing the system for each functional unit
and the possibility of separating units from each other. First we want to highlight the fact that the
company is actually registering performance measures at unit level, but these measurements are
different and not as extensive as the ProMES methodology is meant to do. Management is only
measuring the efficiency of the working hours of the operators and slightly the waste of material
at each working unit. As described earlier in this report, a job shop situation represents a high
complex production environment with complex relationships between the different units and the
employees within these units. The main dependencies which cause productivity hard to measure
are that a unit continues to work on the result of the previous units and is dependent on the
performance of that previous unit and products continually flow between the different functional
units. The results of analysing the company showed us that this was not really the case and the
dependencies are not of that nature what causes large difficulties/problems for measuring each
unit individually.
We will now explain why the complexity and dependencies were not really a problem at the
research company for measuring productivity. Actually, there were not many relationships
between the working units which could cause difficulties for visualizing and measuring the
productivity at each unit. The first reason is that the persons who are responsible for preparing
and planning the manufacturing processes are creating an optimal manufacturing process and
conditions so operators are not highly dependent on others achievements. An example is that
when parts are not ready at the right time; different orders are scheduled so the operators do not
have to wait. The second reason is that the material flow at the job shop is structured so the
employees are as low as possible dependent on other units; after an operation at each of the
working units, the products and parts are stored at the automated warehouse and are not directly
flown to other units. Thus with other words, the working units are decoupled by storing parts in-
between the process.
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The rule of the company is that only products can be stored and taken out of the warehouse when
the right products are ready, with the right amount and quality. The big advantage is that when
parts are stored in the warehouse, people can always assume that the right products are present at
the right amount and quality, which decreases the dependencies between the working units. The
third reason is that each operator has access to an information system, were each of his or her
handlings are registered. So at each time the newest information can be looked up for by each of
the employees. This enhances the exchange of information and decreases the required closely
cooperation and thus the dependencies between the working units. The three reasons described
above make clear that no complex dependencies between functional units are present at the
research company, which increases the possibility of applying the ProMES system at unit level.
Additionally, the information system used, in which several software packages are linked to each
other takes out another major problem, which is called time efficiency. It was assumed that
measuring productivity at each unit will take a lot of time. On the one hand does it take time to
set up the system, but on the other hand, a sophisticated information system in which the
production aspects are registered will decrease the required effort to maintain the system very
much. But at maintaining a ProMES system, a much more sophisticated automated measurement
system has to be developed.
We now summarize the three reasons. Proper preparing and planning at the research company
result in fewer dependencies between units. The second is that the material flow at the job shop
decreases the dependencies between the units, because the parts and products are stored only
within the right amount and the right quality at the warehouse each time. The third is that each
operator has access to a database in which each of his or her handlings are registered which
enhances (faster and better) exchange of information. When some dependencies do still cause
problems, a solution is to form the indicators such that the interdependent relationships are
removed. After analyzing the company, it can be concluded that it is possible to decompose the
departmental productivity into single unit’s productivity. The management was able to visualize
and measure the individual productivity of the units because the complex interdependencies were
reduced as much as possible, operators can easily be appointed to a specific unit, each operator at
the units is responsible for the same activities and tasks. Thus the practical analysis showed us
that the factor “task interdependencies between units” was weak and does not reduce the ability to
decompose departmental productivity into single unit’s productivity and the productivity can be
influenced by the units itself which increases the controllability over output.
Developing and maintaining one ProMES system for the whole production department is the
option which implies the minimum amount of development time and effort. This is also
confirmed after analysing the company and interviewing employees. Then only once a list of
products, indicators and contingencies have to be determined and one feedback report can be
provided to the whole department because productivity is only measured at departmental level.
According to the problems caused by the complex production environment and interdependencies
between the units, it seems that a system for the whole production department will be a good
potential. It was assumed that the complexity of the production situation as a job shop department
will cause difficulties at measuring productivity, but as told above, we can not really speak of that
high complexity at the research company. Thus, at only considering the complexity and
interdependencies between the functional units of the research company, the solution to measure
on departmental level is not explicitly necessary anymore. The people of the research company
did support the very important disadvantage of one feedback report for the whole department.
They confirmed that is would be difficult to recognize what the individual contribution of the
units was when one measurement system was set up and feedback was provided to the whole
department.
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An example is a general score of three functional units on production speed of 80% in a specific
period, but two units maximized their performance and one unit did not. The average was 80%,
but the employees can not see that one unit had actually a lower score than 80% and the other two
units scored 80% or higher. Thus the effectiveness of the ProMES system is low when the people
of the department can not recognize their individual unit contribution. The conclusion we can
draw after comparing the theoretically stated problems with the analysis of the research company
is that the problems of measuring at departmental level are for the most part confirmed by the
research company. And additionally, it turned out to be that it is not explicit necessary to set up
one system for the whole production department because departmental productivity can be
decomposed into single unit’s productivity in the situation of the research company.
7.1.2.3 Shifting operators between units
Often in job shops operators are working at different units because the workload at “his” unit is
low and at another unit high and they are acquainted with more than one activity. Shifting
operators leads to varying production achievements, because each employee has different skills
and capabilities. A second reason why the productivity differs per day is that often the company
is working with more than one shift, so the achievements are shift-dependent. The problem stated
in theory is that when the productivity at each unit is measured; the measures are not reliable and
can not be compared with the productivity in other periods because of the changing operators.
The situation of shifting operators and several shifts a day is the same at the research company.
The fact that operators are shifted between units, what leads to fluctuations in unit output,
influences the possibilities to apply ProMES at unit level. But despite the fact that not all the
employees do have the same skills, what results in varying production speed, quality, etc,
analyses of the company showed that enlarging the measurement period will average out the
fluctuations in unit productivity. Thus it will be easier to decompose the departmental
productivity and to apply ProMES on unit level at the research company by ruling out the varying
productivity. The problem of the low control at the units due the changing output can also be
overcome by enlarging the measurement period. Thus the research company confirmed the
influence shifting of operators has on both the difficult decomposition and decreasing control.
7.1.2.4 The rapidly changing orders
In a vast chancing environment of the job shop, orders, tasks and batch sizes are strongly varying
each week or month or even per day. This unstable and unpredictable situation is typical for a job
shop. Historical production data is required for the ProMES methodology, but these are not
available due to continuously changing orders and demand. Then it is hard to set any productivity
standards or norms (worst and best feasible performance levels) which are required by
determining the contingencies. Analyses of the research company confirmed the problem of vast
changing design and amount of orders which have to be processed by the operators. The orders at
the research company do vary a lot, even per day. About 3000 different parts are currently
processed by the manufacturing department at Exerion. These highly varying orders do lead to
changes in workload, production speed, quality, waste of material, etc. Not only the design of the
orders is varying, also the amount of orders does vary a lot per period. In a specific period often
the demand at unit A is much higher than at unit B, but the next period vice versa. This leads to
periods in which the units are not able to fully use their resources and to achieve their optimal
productivity. The company anticipates on the changes in design of orders and workload by first
changing the production planning or by letting the employees work in the evenings. When it
seems that the amount of work to be done is high/low for a longer period of time, the company
adapts to this by hiring and firing temporary workers.
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Analysing the company showed that the majority of the parts and products to be manufactured are
standard products. Thus besides that the analyses of the research company confirmed the problem
of highly varying orders, the amount of standard products is that high that they can use
productivity standards. Also each new product which is to be manufactured, often as a project,
will become a standard product. The company has a large database with all the productivity
norms of each of his products and continuously adds new norms for new products. Thus the
problem of getting enough historical experience to make any judgments as to what is low or high
output is not that difficult at the research company. Relatively many standard products are being
manufactured at the research company, thus the control the operators have on the unit output is
not that low as assumed.
Concluding, even though the variations in productivity in periods and between units, for this
situations we are able to determine the best and worst possible output for a unit due to many
standard products, the presence of historical data and enlargement of the measurement period.
This makes it possible to translate the productivity to an effectiveness value for the company and
a higher control on unit productivity.
7.1.2.5 Different interest of the units
When measuring each single functional unit separate, it is stated in literature that the functional
units will then first try to reach their own goals and prefer to optimize their own performance
without taking their responsibilities for the other units into account. One system for the whole
department is a solution to increase cooperation, which could be low when measuring at unit
level. The interviews at the research company showed that the risks at individualistic behaviour
of the units are low at the research company. The organisation strives to create an environment
and culture in which employees together want to achieve a high as possible productivity. The
employees do not only have to take care of their own functional unit with its tasks and
responsibilities, but also look outside the unit to strive together to solutions which results in
productivity improvement of the total department. Thus we might state that the solution of setting
overall goals for the department is not necessary because of the cooperative culture within the
organisation. But setting goals and providing feedback at unit level can still lead to individualistic
behaviour because the goal interdependency between the units are neutral (Van Vijfeijken et al.,
2002). So even within a cooperative culture units will probably act in individualistic behaviour
what can lead to sub-optimization. Thus a cooperative culture is a necessary condition, but will
only partly prevent sub-optimization. Concluding, the relationship between “different interests”
and “risks at sub-optimization” was confirmed by the research company, but is not that strong as
assumed to be.
A difficulty which resulted from the research company is that, when separately measuring the
units, it seemed impossible to compare the productivity of each unit, because each unit has its
specific importance. For example, the amount of parts produced per day by one unit can not
objectively be compared with the amount of parts produced by another unit, because less
operators and machines are placed at that unit. A solution is to rescale the contingencies, which
also came out the literature study. The employees of the company found it a good idea to rescale
the scores on the indicator dependent on the working environment and possibilities, so the scores
of the functional units can subjectively be compared and summed up as one overall score.
A result from the company which is not specified in literature is the problem of “social loafing”.
Social loafing means that people are profiting by the success which other people of the
department have achieved. This will result in a unfair situation and decreases the effectiveness of
ProMES.
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7.2 Evaluation of the results
After comparing the theoretical findings about applying ProMES to a job shop system with a
practical situation, we are now able to give an overview and conclude what the possibilities in our
situation are. With other words, we will give an overview of what is best possible by aiming at
creating the desired situation.
As we conclude in chapter 5, also in the setting of the research company it is not optimal and
even not required to measure the productivity of each individual employee within the production
department. The reasons which resulted from the research company corresponded with stated
reasons in literature. It will imply too much time and effort to set up and maintain a measurement
system for each individual, what is even not required because employees within a unit are closely
cooperating and together responsible for the same tasks and responsibilities. Shifting employees
between functional units will make it very complex to measure and evaluate at individual level.
Thus definitely, the option of developing ProMES at individual level will be left out.
Some major contradictions to the literature resulted from the practical analysis, which is positive
for the situation which we desire to create: visualize and measure productivity at unit level and
sum up the scores in one feedback report. The main contradiction to the literature and an
advantage for the current research is that the assumed dependencies, cooperation and
relationships between the functional units at the research company are not that complex or do not
cause that major problems as was assumed. This is because the proper production process,
structured material flow, continuously anticipation production planning and the availability of an
information system. It turned out that the importance and possibilities differed at each of the
functional units, thus the contingencies at each unit have to be rescaled to be able to compare and
sum up the unit scores. So it can be concluded that it is possible to decompose the departmental
productivity into single unit’s productivity at the company.
Most of the advantages and disadvantages found in literature about developing and applying a
ProMES system at departmental level were confirmed by the practical analysis. The big
advantage what also resulted from the practical situation, is that developing at departmental level
drastically decreases the development and maintenance time and effort of the system. Another
result is that it is not required to set up a system for the whole department because the option of
developing on unit level seemed very good possible. Developing and applying a ProMES system
at departmental level is a good possibility, but due to the large disadvantage of departmental
feedback and the very good possibilities for development at unit level; this option is not an
improvement in comparison with measuring on unit level.
High control over productivity is one of the most important requirements for a successful
implementation of the ProMES system because employees must be able to influence the scores on
the indicators. In literature it is assumed that especially job shops causes problems because in job
shops the employee’s productivity is influenced by uncontrollable factors, such as dependencies
between machines and humans, the environment in which they are operating and some other
factors. But the problems of these uncontrollable factors did not seem that high and we came up
at solutions to rule out the remaining low controllable factors. Also shifting operators is not a
problem when the measurement period is enlarged. Thus at considering the point of low
controllability at the research company, we can conclude that it is possible to implement a
ProMES system in a job shop, because the controllability is reasonably high and some solutions
are determined to decrease the influence of the remaining uncontrollable factors.
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It is assumed in literature (Van Vijfeijken et al., 2002) that there is a chance at individualistic
behaviour of the units when the productivity of each individual unit is measured, which on his
turn can lead to sub-optimization. The interviews made clear that these chances are low, because
each of the employees is managed to always do his best, to achieve a high productivity level and
to help his colleagues. The meaning of this to the project is that it is possible to separate the
production department into single units with low risks at individualistic behavior. But a comment
we can place is that, even if managed well, units will probably act in individualistic behaviour
when individually being measured and evaluated. The degree to which this problem can be
overcome is dependent on the specific situation. A cooperative culture is a necessary condition,
but will only partly prevent sub-optimization.
We will now discuss the relational model we presented in chapter 5 combined with the results
from the research company. The departmental productivity can almost fully be decomposed so
unit’s productivity can separately be measured, because the units were not as dependent on others
as supposed. This also increases the ability to influence the output of the units by the units
themselves, which increases the control over productivity. Additional findings, which were not
assumed in theory, but was a result of the practical analysis was that a central production
planning and control system and the use of a central warehouse to store parts in-between the
process, separates the units from each other. These could be defined as a factor which is related to
decomposition of departmental productivity and should be implemented in the model. The
relationships between the factor “shifting operators” with “decomposition of departmental
productivity” and “controllability” are confirmed by the research company. The difficulties which
are caused by shifting the operators between units are confirmed by the practical analyses, but can
partly be reduced by enlarging the measurement period defining the right indicators. Practical
analysis confirmed the relationship between the varying orders and control. Orders are not that
much varying as assumed in literature because a lot of standard products are being manufactured
what increases the control on productivity. Thus the relationship between “varying orders” and
“control” is weak at the research company. The fact that independent unit goals do influence
individualistic behavior is confirmed by the practical analysis. Sub-optimization will probably be
always present when units are individually being measured, but a solution to decrease chances at
sub-optimization (and competition) is to create a cooperative organization.
The conclusion is that it is possible to apply a ProMES system at the job shop of the research
company and to measure and enhance productivity at unit level, because the theoretically stated
difficulties were not that hard as assumed; departmental productivity can be decomposed into unit
productivity, control over productivity is reasonably high and chances at sub-optimization can be
kept to a minimum.
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8 Matching ProMES with a job shop
After stating the possibilities for the system at the previous chapter, we determine how the
ProMES system has to be developed for a job shop situation in this chapter. First we discuss the
minimal conditions which are required for the application of a ProMES system in paragraph 8.1.
We determine in paragraph 8.2 which of the generated ideas will be the best. Paragraph 8.3
globally describes what the system should be and presents recommendations about applying a
ProMES system to a job shop situation.
8.1 When is ProMES applicable
We approach the applicability of ProMES to a job shop on a higher level in this paragraph.
According to the literature study and the analysis of the research company, we can state what the
minimum required situation/conditions have to be for developing a reliable measurement and
enhancement system. The first that are required are the acceptance of the system and the trust in
the system by the management and the unit personnel and also the willingness to measure
productivity and to be measured. But all this is not within the objective of the current research so
we leave these facts out of consideration and assume that these requirements are satisfied.
The study of N. Huve (2005) did not lead to the desired situation as described in paragraph 5.2.
The researcher was not able to create a situation in which to recognize which changes at unit level
resulted in which changes at departmental level. The most important reasons why that system was
developed on a (too) high level were the specific situation at the company with its complex
relationships between groups and the limited availability of production data. Thus the researcher
was forced to develop one general system on departmental level, what is not most the effective,
because a system on that level does lead to fewer increases in people’s motivation to change their
working behaviour, what will lead to less productivity improvements. Thus the study of N. Huve
(2005) indicated that for an effective ProMES system for a job shop (thus on unit level), the
availability of detailed production data is highly required. So we state that the most general and
important element what is required, is the ability to really measure productivity, because this is
the basic element required for the development and implementation of the ProMES methodology.
One has to be able to exactly determine what and how the operators are performing at each
functional unit at each day, is able to measure what is required, administers everything correctly
and uses a detailed information system. The outcome from the chapter described up till now is
that it is not possible to develop a reliable and valid measurement system when only productivity
data is available in detail. A second aspect what is of major influence is the controllability over
the unit’s productivity. The second most important requirement for the development of the system
is that employees are able to influence their productivity, thus are in control over their activities
and output. When the units are measured and evaluated on indicators which are beyond their
control, it is very frustrating to employees because they will not be (enough) motivated and will
decrease the effectiveness of the system.
We conclude that when detailed production data is available and the indicators are developed in a
way that these can be influenced by the operators, the ProMES system can be applied to a job
shop with the highest probability of success (i.e. substantial productivity improvement). These
required conditions are satisfied by the production situation at the research company. But the
degree of applicability and success of a ProMES system is dependent on much more elements
which have to be developed, adjusted or optimized to be an effective and successful measurement
system.
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8.2 Determining the best idea
Before we analyze which of the four ideas proposed in chapter 5 is the best option and thus the
most optimal for the situation of the research company, we shortly repeat the situation which we
want to be created. That situation is; when productivity changes are recognized at departmental
level, we want to be able to determine which factors at unit level influenced these changes. And
also, when changes applied on unit level, we want to be able to determine to which changes in
total departmental productivity that will lead. Note that the proposed ideas are only considering
the level of measurement and application, thus the main result at this stage is the level at which it
is best to measure productivity.
This desired situation led to the proposal of the idea 1: “Develop a ProMES system for the
department, and measure each functional unit individually”. The first question which immediately
rose at this proposal was if the total departmental productivity could be decomposed to single
unit’s productivity so the units could be measured individually. The practical analysis at the
research company showed some contradictions to assumptions from literature and it is very good
possible to measure productivity at each functional unit. The interdependencies and relationships
between the units are not very complex. Also the assumed difficulties of shifting employees,
chances at sub-optimization and the removed cooperation between units do not cause important
problems or difficulties what would hinder the development and application of a ProMES system
at unit level. A small disadvantage of this option is that it requires more effort to maintain the
measurement system because the scores on each indicator have each period to be registered at
each functional unit. Thus the idea which we desired is practically possible. The best idea is thus
to develop one ProMES system for the department and information about productivity is gathered
and evaluated at unit level. This implies that the desired situation can be created, and also it is not
needed to further evaluate the remaining three ideas here, because these ideas all had
disadvantages and were less effective than the initial idea. Concluding we can state that the first
idea; a ProMES system for the department and measure each functional unit individually is the
best potential to be used for developing a ProMES system for a job shop system of the research
company.
8.3 Description of the system and recommendations
8.3.1 Description of the system
The outcome of the previous chapters was that measuring productivity at each individual
functional unit is the most optimal and is also possible in practice. The application of the system
begins with clear statements or organizational objectives. The characteristics of the system are
that productivity of each unit is measured at each unit and feedback is provided according the
sum of the unit’s productivity. Thus we want to make clear that the ProMES system has to be
developed according to common products and indicators which for each unit, contingencies will
be drawn for each unit, and the feedback report contains the departmental score, but also shows
the individual contribution to the overall score. At each functional unit, periodically
measurements have to take place, which measures the scores on the indicators. Then according to
the contingencies it can be determined what the productivity of each of the units was in that
period. The individual unit scores on the products have to be summed up and have to be recorded
in one feedback report. This general feedback report is then build-up out of the unit scores and
represents the overall score of the department on each product and a total departmental
productivity score. Employees are forced to maximize both unit and departmental productivity by
using one feedback report.
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In other words, the system indirectly provides departmental goals and feedback which enhances
strategy development and coordination among units and within units.
We have also considered defining products and indicators which are different for each functional
unit. What follows is that each functional unit gets feedback according to a single feedback
report. But this is NOT a good idea because:
- Product are derived from departmental goals which are related to organizational goals,
thus units together have to try to maximize the same productivity aspects, which will be
summed up and represents scores on the departmental goals
- Then the scores on the indicators of each unit can not be compared and summed up, so it
recognizable who is responsible for which changes in overall productivity
- It will require much more time and effort for determining different products and
indicators and measuring and giving feedback to each unit separate
- Unpractical to form a design team for each single unit
8.3.2 Recommendations
The recommendations which will lead to the most effective application of the system will be
described below. The recommendations presented here can generally be applied to situations
which differ from the situation of the research company.
8.3.2.1 Recommendations for reducing dependency relationships
A job shop is a highly complex production environment with complex dependency relationships
between the different units (work on the result of previous units). This leads to the fact that the
units are strongly dependent of others if it comes to exchange of information and products.
When for example a preceding unit is the bottleneck in the production process, thus cannot finish
tasks on time, products are not present at the right time at the succeeding unit. The result is that
the measured score on an indicator that period does not represent the actual possible productivity
of that unit, because they cannot work on the right products. This can be ruled out by specifying
the indicators in the way that the measurement takes place from the moment the right amount of
orders are present at the concerning unit till the time the unit finishes its work. Another
recommendation for removing the dependency relationships is to take care for a good production
planning and scheduling process, which decreases the dependency on the work of a preceding
unit, by anticipating on the changes in production, what resulted from that preceding unit. When
units do have to cooperate to fulfill a task, a recommendation is to define one or more indicators
in a way that these measures the degree to which the different units cooperate and enables each
other to improve productivity. Then the indicator(s) define the way parts and products have to be
transferred between working units and additionally the tasks a unit are responsible for. An
example of an indicator is the percentage correct amount transferred to the succeeding unit, or the
percentage correctly stacked up.
Also, a the use of a central warehouse, in which products and part may only be stored when
satisfying the requirements, decreases the dependent relationships between the functional units. A
recommendation is also to develop an information system, were each of operator’s handlings and
product conditions can be registered. This enhances the exchange of information and decreases
the dependency relationships between the units. This information system also provides improves
the cooperation between units, what was partly removed by exactly appointing tasks and
responsibilities to each unit.
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The complex material flow and the many different routings have to be ruled out for the most part,
to be able to separate the unit’s productivity from the overall departmental productivity. When
developing a ProMES system at which productivity is measured at unit level, the organization has
exactly to clarify the roles of the people within the units. The responsibilities, roles and activities
have exactly to be appointed and applied to one of the functional units, so no misunderstanding
exists about who is responsible for which operation. This is recommended because the
productivity which is measured at the units is really the outcome of that specific unit, and not of
any other unit. But as told above, the units together have to maximize the productivity of the total
department, at which good cooperation between units is indispensable, so there are always some
aspects which others have to take care for.
Because all the scores on the indicators have to be measured and recorded at each functional unit,
it would be very helpful to develop a information system and a database in which the information
about the productivity, such as hours worked, parts passed quality check and machine utilization,
etc, can be stored. This increases the cooperation between separated units. It would be effective
when all employees do have access to this information system, so he or she can enter his or her
productivity at each place and time.
The contingencies have to be rescaled because all the units are often performing different
activities, have different interests and work in different situations and circumstances. When the
contingencies are rescaled, the relative importance and the circumstances of each unit are taken
into account, so it is possible to compare and sum up the individual productivity of each
functional unit to one overall departmental score.
8.3.2.2 Recommendations to overcome the problem of low controllability
Employees do not have high control over the outputs of the units due to the dependencies
between units, shifting operators and the vast changing production orders. To create the situation
in which the employees can influence their productivity scores, so have a high control over their
work is to: enlarge the measurement period to average out the variation in productivity, restrict
the responsibility to tasks that are completely controllable (e.g. do not cover all parts of the tasks)
and/or form the indicators such that the interdependencies are removed (e.g. start measuring at the
right time), (Algera and Van Tuijl, 2004). But disadvantages are involved at these three solutions.
The measurement period should not be too long; otherwise the provided feedback does not have
the motivational power. This is because when feedback is provided after a too long time, it does
not have enough meaning to the employees anymore. There is a possibility that not the most
important productivity aspects are being measured and evaluated when only the indicators are
measured which are fully controllable. The disadvantage is than that the company will not profit
optimally by the system and not in accordance to the organizational goals. When too many
interdependencies are removed, the total departmental productivity decreases because it might be
that some vital dependencies can not be removed. The solutions to enlarging the measurement
period and define indictors such that interdependencies are removed, are both preferred, because
these solutions will slightly influence the success of the system. Increasing control by defining
only indicators which can be influence by the personnel increases the change that not the most
important indicators are used, thus that option is less preferred.
One of the basic needs for the development of the ProMES system is the availability of historical
production data. But a job shop is typically characterized as a production process in which
demand and the nature of the orders at the units are highly varying between periods. We
recommend making use of a constantly updated data base. So more productivity data will become
available and increases the control over the unit’s output over time.
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8.3.2.3 Recommendation to reduce the chances at sub-optimization of units
Individualistic behaviour of the functional units and sub-optimization can partly be prevented by
management. Chances at individualistic behavior can be kept low by creating a cooperative
culture, at which people are willing to help each other and together are striving to both maximum
unit and department productivity. This will result in a situation in which employees also to look
outside his or her unit, what results in better cooperation and higher departmental productivity.
This recommendation will not fully overcome the problem of sub-optimization because units act
in individualistic behavior when goals are set and feedback is provided to each units individually
(Van Vijfeijken et al., 2002), even though the management “requires” a cooperative culture. So
even within a cooperative culture units will probably act in individualistic behaviour what can
lead to sub-optimization and competition. Thus a cooperative culture is a necessary condition, but
will only partly prevent sub-optimization.
A second recommendation is that individual unit scores have to be summed up to one overall
departmental score. This will contribute to closer relationships and better cooperation between
units which on his turn will lead to higher improvements of departmental productivity and
decreasing chances at individualistic behavior (Van Vijfeijken et al., 2002).
To explain what we have described in this chapter and to show how to apply the solutions and
recommendations, we present a global design of the ProMES system in the next chapter. In that
chapter we describe how the ProMES system should be applied to a job shop production process
with the characteristics of the research company.
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9 Developing ProMES for a job shop production process
This chapter provides a global design of a ProMES system as it could be applied to the job shop
of the research company. We do not actually implement the system, because that is not within the
objective of the project and the time it would take would exceed the time available for the project.
According to this design we explain how the system has to be developed for a job shop situation
and give the recommendations and requirements which resulted from the current research.
The basic method of ProMES is to work with a design team which develops the productivity and
measurement system for the units of the department. The design team is composed of facilitators,
supervisors and unit members and their role is to be responsible for designing and implementing
the system. But because we do only set up a general design with some aspects in detail for the
remainder of this research, we do not appoint a design team at the research company which is
responsible for the development of the system. We recommend involving (at least) one member
of each working unit to act as representative for each unit. It is not needed to involve more than
one person because often a small amount of operators belong to one functional unit.
IDENTIFYING PRODUCTS The first step in the development of the ProMES system is to identify the products. Products are a
set of activities the unit/organization is expected to perform, or a set of objectives or results that is
expected to accomplish by the unit. By identifying the products, the people at the units can state
some questions which help to identify the products. The questions are; “What are some of the big
things the organization expects you to accomplish?” and “What are the groups of tasks you are
expected to do?” The criteria for identifying good products, stated by Pritchard (1990) are:
- they have to be clearly defined;
- they have to be complete, the list of products have to contain all the unit’s work;
- the unit has to be able to influence them;
- the unit has to be responsible for these products, not other people;
- if the unit did exactly what the products say, the organization would benefit.
The design team has to make sure that the list of products is complete. The result may be that too
many products are defined, thus they have to decrease the number of products on the list. At the
end of this phase, the units will have between three and six products. The products provided by
the people of the research company are explained below.
Production speed is of high importance for a company like the research company. The production
department has to satisfy the production planning and so products can be delivered within the due
date. Thus the first product which is identified is to produce the amount of products/parts planned
for each unit. This product can be influenced by the personnel because they are responsible for
processing the products at the units by themselves. At each unit the production speed can be
measured, thus the measures on this product are the result of the concerned unit and not the result
of other people or units. The influences of others are ruled out by measuring from the moment the
parts are available and by comparing the planned processing time with the actual working time.
The operators at the units are responsible for producing products with the quality in conformance
with specs. Products and parts have to satisfy the quality which is agreed with the customer. Thus
the second product identified is to manufacture product with the quality in conformance with the
specs.
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T. de Boer 63
The unit is able to influence this product, because they are themselves responsible for the
delivered quality of their work. The quality of the delivered work will not be dependent on the
quality of the work performed by the preceding units when the quality is only checked on the
performed work by the actual responsible units. If the specific responsibilities are appointed to
each specific unit, is it easy to determine which specific unit is responsible for the eventual
decrease in quality. This partly removes the dependency between units, so this product is not
influenced by other units. The company requires an as high as possible attendance of employees.
Production problems occur, like not satisfying the production planning, when employees are not
attendant due to illness or accidence at the company. The third product is to maintain high
attendance. The people at the units are fully able to influence the level of attendance, because this
product concerns the people itself. This product is only influenced by the unit’s personnel
because attendance can simply not be influenced by other people or units. Another important
aspect which is objected by the organization is the degree of occupations of the machines at the
different units. This is most important for the cutting unit, because here are big and costly
machine situated. This product can be influenced by the unit’s personnel, because they are
operating the machines by themselves, thus personnel can influence the time the machine is
running (except at machine breakdowns). This product will not be influenced by other units,
when the measurement is properly executed; the planned utilization should be compared with the
actual utilization. So the eventually delays or other problems resulting from other units do not
influence the score of the concerning unit so dependency between units is removed. Thus the
fourth product is to maintain a high level of machine utilization. The final product is about the
safety the employees are working with. The employees are responsible to safely operate the
machine and “live by the rules of the house”. The employees have to work according to safety
rules and procedures which prevent accidences and complaints of the operators. Thus the fifth
product is to correctly follow housekeeping and safety rules. The people of the units are assumed
to know what the safety rules are, thus they can influence the way they follow these rules. The
way the safety rules are followed is measured at each unit and can be followed without influences
of other units, so the measured score on this products is exactly the output of the concerning unit.
The list of products that could be used for the research company is the following:
Product 1: Maintain a high level of production;
Product 2: Make products with the quality in conformance with specs;
Product 3: Maintain high attendance;
Product 4: Maintain a high level of machine utilization;
Product 5: Correctly following housekeeping and safety rules.
We believe that the criteria for good products are satisfied. The products are clearly defined, and
highly probable understandable for the employees. The list of products is provided by the
research company and contains the most important aspects the organization is aiming at. Each of
the products can be influenced by the employees of the unit, so they have control over their
performed work as told by explaining the products. Thus at each unit it is clear that only the
unit’s personnel is responsible for each of its own products, so no people of other units are
responsible for the activities of other units. Finally, the products stem from organizational goals,
so if the unit does exactly what the products say, the organization would benefit from it.
DETERMINING INDICATORS When the products are defined, the second step in the development of the system is to develop the
indicators. There can be one or several indicators for each product. An indicator is a concrete
measure of how well the organization was generating the product.
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T. de Boer 64
The questions that can be stated by the personnel at the units to help developing the indicators can
be; “how would you measure how well the unit was doing on each of the products?”, “what
would you point to show your boss how well you are doing? Typically the number of indicators
ranges from five to fifteen (Pritchard, 1990). The numbers of indicators have to be that high that
it is still manageable, otherwise the system will become too complex. The criteria for developing
good indicators, stated by Pritchard (1990) are:
- the indicators are relevant for the products;
- the set of indicators has to be complete; cover all the products and cover each product;
- they are valid (what is measured is an accurate index of product accomplishment);
- they are controllable; the group has the ability to influence the score on the indicator;
- collecting scores of the indicators is costs effective;
- they are understandable and meaningful to the personnel of the unit;
- productivity is both on a short and long term of importance for the company;
- the essence of the tasks and responsibilities have to be measured by the set of indicators.
The indicators to measure how well the unit is doing on each of the products are provided by the
people of the research company. We present the list of indicators belonging to each of the
products below.
Product 1: Maintain a high level of production Indicator: Efficiency of working hours – Planned working hours divided by actual
working hours
Product 2: Make products with the quality in conformance with specs Indicator 1: Percent passed inspection – Products passed divided by all products
Indicator 2: Number of customer complaints – Complains made by customers
Product 3: Maintain high attendance
Indicator: Percent hours present – Hours present divided by maximum hours possibly
present
Product 4: Maintain a high level of machine utilization
Indicator: Machine utilization - The time a machines is in use divided by the maximum
possible run time of the machines
Product 5: Correctly following housekeeping and safety rules Indicator: Number of violations – Violations of the housekeeping and violation rules
Efficiency of working hours - This indicator is already used by the research company. The
company has calculated a maximum processing time required for each product or part. This
processing time encompasses all activities and tasks required for the operation, the so called
planned working time. The actual time required for processing the products is registered. Then,
the efficiency is determined by dividing the planned working hours by the actual worked hours.
The higher the efficiency is, the better it is. To remove the dependency with other units and to
obtain more control over this indicator, should the planned working time be calculated as
following: the time required for processing the parts, should be measured from the moment the
parts are available till finishing the parts.
Percent passed inspection - The products produced at the company, go through a quality
inspection before they are shipped to the customer. When a product does not pass the quality
inspection, it is returned to the production department and the problem has to be fixed. The
people of the inspection have to determine which functional unit was responsible for which part
of the product, and thus responsible for a fault in production. The indicator is determined by
dividing the number of products which did pass inspection by the total number of products
checked. The higher this value is, the better the score on the indicator.
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Number of customer complaints - Customer can be unsatisfied with the results after shipping and
installing the products at the customer site. The customer will probable contact the company and
explains the problem. The number of these complaints has to be as low as possible. The lower the
number of complaint is, the better the score on the indicator. This indicator is defined by the
number of complaints per delivered product.
Percent hours present - Employees working at the company can sometimes be not attendant
because they are ill or have other reasons not showing up. The indicator is determined by the
number of hours the employees were present in a specific period divided by the maximum
possible hours the employees could be present.
Machine utilization - From an economic viewpoint it is required to let the machines run as much
as possible, because idle machines do only cost money. Thus the more time the machines are
running, the higher the score on this productivity indicator will be. The indicator is determined by
dividing the number of hours the machine were actual running by the number of hours the
machine was possible to run. The possible run time is defined by taking the preventive
maintenance time, set up time, etc, into account.
Number of violations – for the safety of the employees itself and his or her colleagues, it is best to
strictly follow the safety rules determined by the company. The violations of these rules have to
be noticed and counted. The number of violations has to be kept as low as possible.
The indicators are determined so they satisfy the criteria for good indicators. The indicators are
relevant for the product and are valid, because the score on the indicator is a measure of how the
units are doing on the product. The most important and clear indicators are used, thus we assume
that the list of indicators is complete. The people at the units are themselves responsible for the
output of the unit, thus unit is fully able to influence the indicators as the processing time, quality,
attendance, machine utilization and the following of safety rules. It is difficult to analyze the
effectiveness of the system when it is about the costs of maintaining the system compared to the
profit the system gains. We assume that the indicators are not difficult to understand by the
employees of the company. The indicators are developed according to the products, which on his
turn stems from the organizational goals. Often these goals are determined for the short and long
term, so we assume that the measured productivity is both on a short and long term of importance
for the company. The same counts for the essence of the tasks and responsibilities; they are
measured by the set of indicators because these are the main things the organization is aiming at
and the main expected activities to be accomplished by the units.
ESTABLISHING CONTINGENCIES After the products and indicators are determined and reviewed and approved by the higher
management, the next step is to establish the contingencies. At this stage for each indicator a
function has to be generated that shows how much the different amount of the indicator
contribute to the overall effectiveness (productivity) of the unit. Contingencies are graphs that
show the different levels of the indicator on the horizontal axis and the contribution of that level
of the indicator on the vertical axis. “A contingency is the relationship between the amount of an
indicator and the effectiveness of that amount of the indicator”, (Pritchard, 1990, p. 22). The first
step in developing the contingencies is determining the maximum and minimum values and the
zero point of the indicators. The maximum value is “the best possible performance a group could
expect on an indicator if they did everything correctly for a given time period” and the minimum
value is “the worst possible performance the group could imagine actually happening to
them”.The zero point is “the expected level of performance or the level that is neither good nor
bad performance”, (Pritchard, 1990). The maximum, minimum and zero point values for the
indicators are partly determined by the research company.
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T. de Boer 66
The values for the percentage passed quality inspection and the number of violations are assumed
to be as in the table 9.1.
Indicator Max. possible value Min. possible value Zero point
Efficiency of working hours 90% 75% 80-85%
Percentage passed
inspection
100% 95% 97%
Customer complaints 0 per product 1 per product 0,25 per product
Percentage hours present 97% 95% 96%
Machine utilization 95% 90% 85%
Number of violations 0 15 5 Table 9.1: Indicator values
The second step in developing the contingencies is ranking the maximums and minimums. We
start with the maximums. The question here is: “which of the maximums would contribute the
most to the effectiveness of the organization?” The design team has to rank order the maximums
in terms of the contribution of each indicator to the overall effectiveness of the unit.
That maximum that contributed most to the organizational effectiveness is rank with 1; the
maximum which contributed second most receives a 2, and so forth. The maximum with the
highest importance rank is then given an effectiveness value of +100 and the other maximums are
ranked as percentage of the +100 maximum. The maximums of the indicators could be ranked
and rated as following:
Maximum Effectiveness score
90% Efficiency of working hours +100
100% Percentage passed inspection +70
0 Customer complaints +50
3% Percentage hours present +30
95% Machine utilization +75
0 Number of violations +10 Table 9.2: Effectiveness values maximums
The reason why for example customer complaints could be rated with +50 is because this
indicator is half as important to the effectiveness of the unit.
Then the minimums have to be ranked. The minimum that detracts most from overall
effectiveness was given the ranking of 1, the minimum that detracts the second most is given a 2,
and so forth. The minimum that receives the highest rank (thus a 1) does not automatically
receive a value of -100 effectiveness points. Thus the question is: if the unit is producing the
maximum on an indicator, how low should producing the minimum at an indicator be rated? If
producing the minimum would harm the organization as much as producing the maximum would
help the organization, than maximum and minimum are rated with +100 and -100 respectively.
Minimum Effectiveness score
75% Efficiency of working hours -85
95% Percentage passed inspection -100
1 Customer complaints -65
5% Percentage hours present -75
85% Machine utilization -40
15 Number of violations -15 Table 9.3: Effectiveness values minimums
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T. de Boer 67
An additional step in establishing the contingencies for each indicator at each unit is to think
about the relative importance of each unit to the overall productivity. It could be that the
maximum, minimum and zero point differs between the units, because the work of a unit is more
critical that that of the others, due to different conditions, possibilities and circumstances. Factors
influencing the productivity of the functional units are for example:
- the relative contribution of the units;
- the number of tasks the unit is performing;
- number of machines and operators;
- the nature of the work;
- production speed of machines and people.
Because the job shop department is composed of several units, is required and valuable to have a
measure for each unit and to combine the measures of each unit into a single measure for the
whole department. To be able to sum up the scores per unit, an additional step has to be taken,
called scaling, when it is assumed that the relative importance of the units differs. Thus to
overcome the problem of unequal possible productivity and importance of each unit, scaling has
to be done. Scaling has to be done because one unit’s effectiveness would contribute more to
overall effectiveness than that of the other unit(s). The improvement is that the relative
importance of each unit is considered, thus now we are able to sum up the performances of each
single unit and use a single measure for the whole department. We will shortly explain how the
values have to be rescaled. In the previous steps, each of the most important indicators at each
unit is given a value of +100. Assume that at each unit, the indicator which is given +100 is the
efficiency of working hours of 90%. Then the design team have to rank these levels, by asking
themselves which of the outcomes would make the greatest contribution to the production
department. For example, a unit which has more operators and produces more parts makes a
larger contribution to the overall productivity of the department. The design team decides which
unit is most important, second important, etc. The most important indicator maintains the +100
score, and the remaining indicators are rated relative to this most important indicator in terms of
percentages. The next step is to rescale the contingencies of each indicator by reducing the
effectiveness score of each level of each indicator at each unit by the percentage its own
maximum indicator was reduced. For example, when a unit’s maximum score was reduced from
+100 to +90, the original positive values of that indicator have to be reduced by 10%. The same
rescaling process has to be done for the negative values.
The final step in this phase is drawing the actual contingencies. The first step is to determine the
size of the intervals between the maximum and the minimum points. The more intervals, the more
detailed the contingencies will be, but then (too) many fine judgments are required. The second
step is to place the maximum and minimum values on the contingency as is rated earlier. The
final step is to determine the points on the contingency from the zero point up to the maximum
and from the zero point down to the minimum. Contingencies can be both linear and nonlinear,
depending on the presence of a big step (increase or decrease) in effectiveness.
We will only draw the contingencies for two indicators because are drawn without accordance of
the research company and they do only have the meaning to explain how it could be. The
horizontal axis of the figure is the amount of the indicator which ranges from its worst feasible
level to the best level that is realistically possible. The effectiveness values of the various levels
of the indicator are shown on the vertical axis of the figure. For the example in the figure we have
chosen the efficiency of working hours and quality check passed. The best possible efficiency of
working hours is supposed to be 90% and the worst possible efficiency is supposed to be 75%.
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T. de Boer 68
The zero point is determined at 80-85%. The best possible percentage passed inspection is
supposed to be 100% and the worst possible is supposed to be 95%. The zero point is determined
at 97%. The contingencies are shown in figure 9.1.
Figure 9.1: Contingencies for the indicators: “efficiency of working hours” and “quality check passed”.
PUTTING THE SYSTEM TOGETHER The final step is to put the system together by putting the measures into a formal feedback
system. This is done by collecting the indicator data for a given period of time. The time span
over which productivity is measured has to be determined by the design team. The length of the
measurement period depends on the degree of variations in productivity due to the highly varying
orders and demand and the amount and skills of operators in each period.
This final phase involves (Pritchard, 1990):
- developing a feedback report;
- obtaining management approval;
- training of a team to use a computer program to generate the feedback report.
The basic information in the feedback report is the indicator and effectiveness data for the period.
Thus the products with its indicators are listed and also the level of each indicator with the
resulting effectiveness values for the period is given. The total effectiveness for each product is
the sum of the indicators of each product and the overall effectiveness is the sum of the product
effectiveness. See appendix E for an example of the feedback report. The productivity scores are
added to the report after each period, so the personnel are able to compare productivity between
the periods and allow seeing improvements or decrements in productivity. Regular meeting have
to be hold to review the feedback reports. During these meetings, the feedback report would be
reviewed and areas where productivity increased or decreased can be explored. The group has to
focus on the reasons for improvements or decrement in each area. Points of discussion after
providing the feedback reports are (Pritchard, 1990):
- Causes of the low or high scores on the specific products and indicators
- Strategies to follow by the unit/department to maintain or improve the productivity
Production
-100
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
10
20
30
40
50
60
70
80
90
100
110
75 77,5 80 82,5 85 87,5 90
Efficiency of working hours %
Eff
ecti
ven
ess
Quality
-110
-100
-90
-80
-70
-60
-50
-40
-30
-20
-10
0
10
20
30
40
50
60
70
80
90
100
95 97 100
Quality check passed %
Eff
ecti
ven
ess
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T. de Boer 69
10 Conclusions and recommendations
We first start to repeat the objective of this research along with the stated research questions. The
objective of the Master Thesis Project was to analyse the applicability of ProMES into a job shop
setting; thus to study whether and in what way ProMES could help to improve productivity in a
job shop production process. The four research questions were:
1. What are the characteristics of a job shop production process?
2. What are the characteristics of ProMES?
3. Can productivity be measured in a job shop situation?
4. How can ProMES be applied to a job shop situation?
After studying scientific literature about the characteristics of job shop production processes and
the ProMES methodology we were able to determine which difficulties arise and which
possibilities were available for matching both. We wanted to check the theoretically assumed
problems and the ideas in practise so we assessed the production department of the research
company to be able to check theory and to make statements about the practical possibilities of
applying a ProMES system to a job shop system. By matching the theoretically developed
statements with the results of the practical analysis, we were able to determine how the ProMES
system has to be developed, and how it leads to increases in motivation and the highest gain in
total productivity of the overall job shop floor, thus representing a successful measurement and
enhancement system. Productivity can valid and reliable be measured in the job shop situation of
the research company by applying the ProMES methodology, what also leads to productivity
improvements of the job shop department. Additionally, a ProMES system is designed for the job
shop department of the research company to explain and clarify how the developed ProMES
system and the recommendations have to be applied to a job shop situation. The
recommendations resulted from the research are determined as following:
1. The ProMES system has to be developed by determining common products and indicators for
each unit, contingencies will be drawn for each unit, and the feedback report contains the
overall departmental score and also shows the individual unit contribution to that score.
2. This general feedback report is then build-up out of the unit scores and represents the overall
score of the department on each product and a total departmental productivity score.
3. Remove the interdependency relationships by; proper development of indicators, by detailed
planning and scheduling processes and by the use of a central warehouse.
4. Rescale contingencies so each unit’s productivity can be summed up.
5. The responsibilities, roles and activities have exactly to be appointed and applied to one of
the functional units.
6. Develop an information system for; exchange of information, increase cooperation between
units, generating and registering productivity and decreasing time and effort to maintain the
system.
7. Decrease chances at sub-optimization between units and create a cooperative organization.
8. Enlarge the measurement period to average out the uncontrollable variation in productivity.
9. Restrict the responsibility to tasks that are completely controllable (e.g. do not cover all parts
of the unit’s tasks).
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T. de Boer 70
We now shortly looking back on the solutions presented in the study by considering the four
presented ideas. Each of the four ideas are stated as a one-way solution, but can be worked out in
different ways, what creates alternative ideas. We believe that the four ideas we developed in this
research are really encompassing all possible options. Each alternative option will always be a
derivative of the four ideas defined in this study. For example, an option is to apply the ProMES
system at multiple organizational levels, with a top-down approach, as been described by De
Haas and Kleingeld (1999). This option can be interpreted as a derivative from the second idea
presented in this study and is an option for future research.
Another thing we want to look back on is to what extend the productivity department can be
interpreted as a self-working-unit (as we assumed). Then ProMES has to be focused on only the
work within the department without taking the external responsibilities into account. The question
is; “Does the ProMES system optimally improve the productivity of the production department
itself and does also the organization as a whole optimally benefit from the system?” Some
responsibilities of the production department are not included in the work of the units, but there
are some tasks the units are as a department responsible for.. Examples are the coordination with
the sales department and managing the inputs from, and outputs to other departments. We did not
focus on these relationships within this study, because we only focused on the inside of the
department. We analyzed the influence of a job shop structure on the success of the ProMES
system, and not on the relationships between departments. But these relationships have to be
taken into account to fully benefit, as an organisation, from a ProMES system. So we believe that
departmental productivity cannot optimally be improved without taking the responsibilities to
other departments into account. A solution according to Pritchard (1995) might be to measure
both on unit level and on departmental level, thus also to measure how well the department is
working together with other departments. This might be an option for future researches.
Even though we have designed an effective and efficient ProMES system for the research
company, and determined some important recommendations, people have to bear in mind that the
implementation of a ProMES system is also dependent on other factors such as: ProMES is labor-
intensive and takes a considerable amount of time to develop and maintain, both management and
lower level personnel have to trust and accept the system with its side effects, many meetings
have to be rearranged and it has to fit with eventually other performance measurement systems
already used by the organization. The reaction to the ProMES system can be, as described in
paragraph 4.2; acceptance, compliance or rejection. The design team has to take care for that the
system is accepted by all people involved, so the accepted control loop is complete (also over a
longer period of time). The organization can only optimally benefit from the productivity
measurement and enhancement system when the system is accepted.
This research shows that the characteristics of both the job shop production process of the
research company and the ProMES methodology can be matched so productivity can be
measured and a ProMES system can properly be applied. We were able to do this because the
situation of the research company did not lead to the difficulties and problems as were assumed in
literature. Some of the theoretical stated assumptions (e.g. the complex interdependencies
between units) were not valid at the research company, so it was possible to apply ProMES at unit
level, in comparison with the study of Huve (2005). After analyzing scientific literature, we
expected some important difficulties, but a part of these expectations were not be confirmed by
our research company. Thus more companies have to be analyzed to check if the part of the
literature which is not confirmed by our research company, is confirmed by other situations. Then
one able to develop more significant solutions and conclusions about the ability and the way
ProMES has to be implemented in a job shop.
Measuring and improving productivity in a job shop environment
T. de Boer 71
We also analyzed the research company along with scientific literature to define
recommendations. These can generally be applied to other situations to help to increase the
effectiveness and success of ProMES because these are not dependent on this specific situation.
On the other hand, the design of the system is applicable to the research company because of the
specific situation in which the study is conducted.
This research increases the chances at a successful development and implementation of the
ProMES system, but the success is also dependent on factors not considered here. This research
can be considered as a start which has to be further worked out in future studies because there are
some more interesting aspects which are not covered here and are required to be able to give
better and more detailed solutions and recommendations. Some recommendations for areas of
interest for future researches are:
- Research several companies to determine if job shops at these companies do differ from
the situation in this research.
- Actually develop and implement a ProMES system in detail because some unforeseen
problems might show up.
- An area of future research could be to research conditions which increase the trust and
willingness to cooperate in developing the system.
- Developing a ProMES system at both the unit level and the departmental level to take the
meaning of a department to the remainder of an organization into account.
- Another interesting aspect is the area of information systems. A sophisticated information
system has to be developed for optimizing the development and maintainability of the
ProMES system.
Measuring and improving productivity in a job shop environment
T. de Boer 72
11 List of references
J.A. Algera, A. Kleingeld and H. Van Tuijl, 2002, “Enhancing performance through goal-setting
and feedback interventions”. In S. Sonnentag: “Psychological management of individual
performance”, John Wiley & Sons, Ltd, ISBN 0471877263, pp. 229-248;
J.A. Algera and H. van Tuijl, 2004, “Fifteen years of research on ProMES: State of the art in
performance management of work teams”. In J. Wegge and K.H. Schmidt: “Förderung von
Arbeitsmotivation und Gesundheit in Organisationen”, Hogrefe, ISBN 3801717828, pp. 267-277;
J.W.M. Bertrand, 1983, “The effect of workload dependent due-dates on job shop performance”,
Management science, Vol. 29, No. 7, pp. 799-816;
J.W.M. Bertrand, J.C. Wortmann and J. Wijngaard, 1998, “Productiebeheersing en material
management”, 2nd ed., Houten: Educatieve Partners Nederland, ISBN 9011043995;
K.F. Cross and R.L. Lynch, 1988, “The “SMART” way to define and sustain success”, National
productivity review, Vol. 8, Iss. 1, pp. 23-33;
M. de Haas and A. Kleingeld, 1999, “Multilevel design of performance measurements systems:
enhancing strategic dialogue throughout the organization”, Management accounting research,
Vol. 10, pp. 233-261;
N. Huve, 2005, “ProMES binnen in job shop omgeving” Master thesis paper, Industrial
Engineering, Technical University Eindhoven;
G.K. Kanji, 1998, “Measurement of business excellence”, Total quality management, Vol. 9, Iss.
7, pp. 633-643;
R.S. Kaplan and D.P. Norton, 1996, “The balanced scorecard: Translating strategy into action”,
HBS press, ISBN 0875846513;
A. Kleingeld, H. van Tuijl and J.A Algera, 2004, “Participation in the design of performance
management study: a quasi-experimental field study”, Journal of organizational behavior, Vol 25,
pp. 831-851;
T. Lee and M.E. Posner, 1997, “Performance measures and schedules in periodic job shops”,
Operations research, Vol. 45, Iss. 1, pp. 72-91;
A. Neely, C. Adams and P. Crowe, 2001, “The performance prism in practice”, Measuring
business excellence, Vol. 5, Iss. 2, pp. 6-11;
R.D. Pritchard, S.D. Jones, P.L. Roth, K.K. Stuebing and S.E. Ekeberg, 1988, “Effects of group
feedback, goal setting and incentives on organizational productivity”, Journal of applied
psychology, Vol. 73, Iss. 2, pp. 337-358;
R.D Pritchard, S.D. Jones, P.L. Roth, K.K. Stuebing and S.E. Ekeberg, 1989, “The evaluation of
an integrated approach to measuring organizational productivity”, Personnel psychology, Vol.
42, Iss. 1, pp. 69-115;
Measuring and improving productivity in a job shop environment
T. de Boer 73
R.D. Pritchard, 1990, “Productivity measurement and improvement: organizational case
studies”, Praeger, ISBN 0275939073;
R.D. Pritchard, G.W. Lawrence, A.H. Goode and L.A. Jensen, 1990, “Measuring organisational
productivity with ProMES”, National productivity review, Vol. 9, Iss. 3, pp. 257-271;
R.D. Pritchard, 1995, “Measuring and improving organizational productivity: a practical guide”,
Praeger, ISBN 0275936686;
R.D. Pritchard, H. Holling, F. Lammers and B.D. Clark, 2002, “Improving organizational
performance with the productivity measurement and enhancement system: an international
collaboration”, Nova science, ISBN 1590332229;
T.R. Rohleder and G. D Scudder, 1993, “Comparing performance measures in dynamic job
shops: economic vs. time”, International journal of production economics, Vol 32, pp.169-183;
E.A. Silver, D.F. Pyke, and R. Peterson, 1998, “Inventory Management and Production Planning
and Scheduling”, 3rd ed. John Wiley & Sons, ISBN 0471119474;
D.S. Sink, T.C. Tuttle and S.J de Vries, 1984, “Productivity measurement and evaluation: What
is available”, National productivity review, Vol. 3, Iss. 3, pp. 264-287;
P. Tesluk, J.E. Mathieu, S.J. Zaccaro and M. Marks, 1997, “Task and aggregation issues in the
analysis and assessment of team performance”. In M.T. Brannick, E. Salas, and C. Prince (Eds):
Team performance assessment and measurement. Mahwah, NJ: Lawrence Erlbaum;
H. van Tuijl, 1997, “Critical success factors in developing ProMES: Will the end result be an
“accepted control loop”?, Leadership and organisation development journal, Vol. 18, Iss. 7, pp.
346-354;
H. van Tuijl, A. Kleingeld, K. Schmidt, U. Kleinbeck, R.D. Pritchard and J.A. Algera 1997,
“Measuring and enhancing organizational productivity by means of ProMES: three practical
implications”, European journal of work and organizational psychology, Vol. 6, Iss. 3, pp. 279-
301;
A.H. van de Ven, D.L. Ferry, 1980, “Measuring and assessing organizations”, John Wily &
Sons, ISBN 0471048321;
H. van Vijfeijken, A Kleingeld, H. van Tuijl, J.A. Algera and H. Thierry, 2002, “Task complexity
and task, goal and reward interdependence in group performance management: A prescriptive
model”, European journal of work and organizational psychology, Vol. 11, Iss. 3, pp. 363-383;
N. Viswanadham and Y. Narahari, 1992, “Performance modelling of automated manufacturing
systems”, Prentice-Hall Inc, ISBN 0136588247.