Fitting Marketing Organization Structure to Emerging …dtpr.lib.athabascau.ca/action/download.php?filename=mba... · 2018-04-13 · APPLIED PROJECT: FITTING MARKETING ... enrichment,

Fitting Marketing Organization Structure

to Emerging Technologies

Ken Laguë

APRJ-699 Applied Projects

Applied Project Supervisor:

Prof. Don Smallwood

September 19, 2008

Word Count: 7,901

LAGUË 2

A P P L IE D P R O J E C T : F IT T I N G M A R K E T I N G O R G A N I ZA T I O N S T R U C T U R E T O E M E R G I N G T E C H N O L O G I E S

ABSTRACT

Conventional managerial theory suggests that organizations perform better if they

adapt their structure to the environment in which they operate. In an increasingly

complex business environment where information technology plays a central role in

both strategy and operations, it has been suggested by many that managers should

adapt their department structure to better “fit” emerging technologies to gain a

competitive edge.

Here we investigate: Do marketers adapt their department structure when they adopt

emerging technologies?

This study applies contemporary technology diffusion-adoption models and organization

design concepts to the marketing department, in an attempt to explain the structural

and managerial tendencies of marketers in their technology adoption practices, and

explore whether these organizations tend to become more mechanistic or more organic

as a result.

An online survey of marketing professionals working at 68 North American companies

gathered data about the structural dimensions of their marketing departments: size, job

definition, job switching, job rotation, use of formal teams, the role of written policies

and procedures, management style, the presence of formal employee performance

evaluations, and reliance on outsourcing. Five emerging technology types (e-mail, web

site optimization, marketing intelligence, marketing automation, and marketing

resource management) were assessed for their state of maturity within each

respondent’s department. The data was tabulated and analyzed using statistical

software to explore the correlation between these structural attributes and technology

adoption.

Using their innovation-diffusion theory Nolan and Gibson Stages classified technology

adoption into four stages: Initiation, Contagion, Growth and Maturity. E-mail

technologies were found to be the most heavily adopted overall, followed by Site

Optimization, Marketing Intelligence, Marketing Automation and Marketing Resource

Management.

Most marketing departments were found to have functional structures, with the rest

classified as divisional or matrix structures. While the tendency to adopt one work-unit

structure over another could not be explained by technology adoption alone, it was

clear from the many comments that these emerging technologies have a significant

impact on job design within the structure, and that new technology contributed to job

enrichment, job enlargement and improved horizontal and vertical linkages. Also that

employee performance evaluations tend to be more formalized among marketing

departments with mature technology systems.

LAGUË 3


TABLE OF CONTENTS

1. BACKGROUND ......................................................................................................... 4

2. RESEARCH OBJECTIVE ............................................................................................. 6

3. RESEARCH METHODOLOGY..................................................................................... 7

4. FINDINGS .............................................................................................................. 16

5. CONCLUSIONS ....................................................................................................... 39

6. REFERENCES .......................................................................................................... 41

7. APPENDIX .............................................................................................................. 43

LAGUË 4


1. BACKGROUND

If we could travel back in time 20 years and observe marketing professionals in their

everyday routine, we would see that the departments in which these people operate

were very different places than they are today. Intensifying competition, downward

price pressure and the accelerated product life cycles characterizing most industries

since then have all conspired to force marketers to “do more with less.” At the same

time, new and exciting information technologies have emerged, presenting

opportunities for marketers to reach unprecedented numbers of potential customers

and interact with them at relatively low cost.

To seek out competitive advantage, or perhaps to reduce competitive disadvantages,

marketing departments have focused on “individualizing” mass markets by engaging in

direct contact with consumers (Brady, Saren and Tsokas, 2002, p.19). Coviello, Milley

and Marcolin (2001) described these strategies as enabling dialogue “with and among

customers” (p.24). These strategies are causing marketers to shift the bulk of their

spending away traditional mass-media channels such as broadcast, magazines and

catalogues, choosing instead to invest in the development of web sites, online

advertising, e-mail and emerging media such as short text messaging and social

computing.

Among these, the Web has emerged as a central channel to promote information

exchange with customers. The proliferation of online communications can also be

observed in several related channels including e-mail, search engines, text messaging

and social networking sites among many others. The imperative to develop information

technology (IT) based marketing strategies combined with the increased affordability of

these technologies has influenced many marketers to operate them in-house.

For marketing professionals, IT has not only transformed the strategies on how they

engage customers, but also represents a radical shift in the type of work they do for a

living, and the way in which work is organized.

Weber (1971) as quoted in Ruekert, Walker and Roering (1985) was among the first to

conclude that the way in which a firm organizes its work plays not just a minor role in its

success, but is in fact a primary determinant of firm performance (p.15). This view was

later echoed by Richard Daft (2004), who stated that a central premise of organization

theory is that organizations will perform better when they develop “goodness of fit”

between their structure and the conditions in the environment (p.14).

Brady, Saren and Tzokas (2002) observed that despite the growing imperative for

marketers to include IT in the marketing toolbox and improve their IT-related

knowledge and skills, its importance is often underrepresented in the structure (p.17).

The traditional focus of marketing department design has been on the macro-

organization structure used to plan, implement and monitor marketing tasks (Ruekert et

LAGUË 5


al., 1985, p.14). In a similar vein, Turban (2008) recently concluded that IT has the

potential to dramatically alter structure, authority, sources of power, and job content at

the work-unit level (p.670). He argued that the introduction of complex new

technologies increases the need for specialization, flattens hierarchies, increases the

span of control, encourages the formation of specialized work units, and increases

expert power.

While there is ample literature describing the growing role of IT in Marketing, little has

been written to guide marketing practitioners on the specifics of how to adapt their

organizational structure to “fit” these emerging technologies to become more

successful. Most research in this area is opinion-based and anecdotal.

Formal research on the relationship between marketing department structure and

emerging technologies benefits several audiences. Marketers gain insight into

contemporary organization design practices. Consultants, agencies and service bureaus

serving the industry may identify gaps where they can cater to unmet or underserved

service needs. Technology vendors serving the industry learn how to improve the

design and usability of their products and services to better fit the roles at the work-unit

level. The findings yield an improved understanding of the specific structural attributes

(centralization, formalization, specialization, etc.) which are most likely to be influenced

by the implementation of new technology, if at all, and which may benefit from further

research.

LAGUË 6


2. RESEARCH OBJECTIVE

The purpose of this study is to explore whether information technology significantly

impacts the structural attributes of today’s marketing organizations, and what these

effects are.

LAGUË 7


3. RESEARCH METHODOLOGY

This study is exploratory in nature. The hypotheses (for example, that marketing

organizations passively or actively adapt certain attributes of their organization

structure when implementing new technology, etc.) are speculative.

Research is grouped into five key questions:

1. What types of contemporary marketing technologies are generally found at the

vanguard?

2. Which organizational theories can be used to define marketing organization

structure at the work-unit level?

3. How do marketers perceive the structural characteristics of their own marketing

organizations?

4. Can contemporary technology diffusion-adoption theory be used to explain the

structural and managerial tendencies of marketing organizations? If so, which

attributes are influenced: degree of specialization, rigidity of job definitions, use

of formal teams, degree of internal versus external organization (outsourcing)

etc.? Do organizations tend to become more mechanistic or more organic?

5. What are the managerial and theoretical implications?

Research Instruments

The study combines primary research (survey) with a literature scan of extant research

spanning marketing management, information technology management, human

resources management and organization design theory and practices.

The primary research was conducted by surveying 68 marketing professionals working

at North American companies across a variety of industries, each known to have

deployed at least one major marketing technology system in the last 24 months. About

half (46%) of the panel consisted of companies in the information technology industry.

Panel representation also included business and financial services marketers (16%) and

consumer marketers (14%) among others (24%). See Figure 1: Survey Panel by Industry

for details.

LAGUË 8


Figure 1: Survey Panel by Industry

The panel included representation from a cross-section of small, medium and large-

sized organizations with good representation from medium and large companies. See

Figure 2: Survey Panel by Organization Size for details.

LAGUË 9


Figure 2: Survey Panel by Organization Size

The sample assured that the structural attributes of each organization could be

represented by employees with sufficient managerial responsibility and tenure. See

Figure 3: Survey Panel by Job Level and Figure 4: Survey Panel by Job Tenure for details.

Figure 3: Survey Panel by Job Level

LAGUË 10


Figure 4: Survey Panel by Job Tenure

Industrial (B2B) marketers represented the majority of the panel (77%); this is

somewhat high relative to the overall industry. Since the issues affecting consumer and

industrial marketers may not necessarily be homogenous, research questions

attempting to discretely identify the impact of information technology on each type of

marketer would need to be assessed in a follow-on study.

Potential respondents were contacted via e-mail to explain the study and invite

participation on a voluntary basis. The survey was accessed online from a web link

embedded in the e-mail. Responses were captured using a popular third-party web-

based survey system. To minimize sampling error, access was restricted to one

participant per organization. Only one respondent was removed from the sample after

they abandoned the survey mid-stream.

The questionnaire contained two sets of questions. The first section, Technology in Your

Marketing Department gathered data about the diffusion of technologies within the

respondent’s department. The scope of research was limited to five technology types to

allow the impact of each technology type on structural attributes to be discretely

identified. Definitions for each technology type were added to each question to reduce

the likelihood of semantic error. Response categories provided ordinal data (numeric

values for each checkbox response) which parallel Nolan's "Stages" theory.

The second part of the questionnaire, About Your Marketing Department contained

several closed-ended questions measuring the key structural characteristics of the

respondent’s marketing organization. These questions were phrased using plain

language and inviting respondents to classify their organization on several attributes

including size, job definition, job switching, job rotation, use of formal teams, the role of

written policies and procedures, management style tendency, the presence of formal

employee performance evaluations and reliance on outsourcing. Semantic differential

LAGUË 11


answers were used to classify the responses into ordinal (ranked) data. Consistent

labels were applied to answer values, to assure maximum comprehension and data

consistency.

Respondents were also asked to classify their organization structure according to one of

the three classic organizational forms (functional, divisional, matrix). To maximize

comprehension the questionnaire presented the forms using both descriptions and

diagrams.

To minimize the survey abandonment rate, most questions were designed without

required answers. Wherever a respondent skipped a question, these responses were

omitted from the analysis (no substitute or “dummy” values were added to the data).

Method to Analyze the Correlation of Structural Attributes to Technology Stage

One of the key research questions is to evaluate whether marketing departments adapt

their structural and managerial characteristics as they mature their information

technologies. To answer this question using survey panel data, two variables reflecting

increased technology adoption according to Nolan Stages theory were created and

measured for their correlation with the organizational characteristics as described by

respondents.

In the first test, TECHNOLOGY_TODAY was applied directly from the questionnaire. This

question asked respondents in plain language to classify their organization’s current

usage of the five technology types.

To better classify the organization’s position on the Nolan Stages model for each

technology type, a composite variable was created (ESTIMATED_NOLAN) which factored

in responses to three survey questions: TECHNOLOGY_TODAY, TECHNOLOGY_FUTURE

and PERVASIVENESS). This involved careful interpretation of the answers to each of

these questions to match the respondent to its position on the Nolan Stages model. See

Figure 5: ESTIMATED_NOLAN Codification Procedure. In a handful of responses the

answers proved to be contradictory and were discarded. Given the alternative method

of asking the respondent to self-classify lends itself to interpretation and semantic error,

this method was deemed to yield a more accurate classification.

LAGUË 12


Figure 5: ESTIMATED_NOLAN Codification Procedure

TECHNOLOGY TODAY TECHNOLOGY FUTURE TECHNOLOGY

PERVASIVENESS

ESTIMATED

_NOLAN

INTERPRETATION

(NOLAN STAGE)

0 = Not using today BLANK = Not sure (all values) 0 Not using

0 = Not using today 0 = We have no plans to use

this technology (all values) 0 Not using

0 = Not using today

1 = We have plans to

experiment with this

technology

(all values) 1 Initiation

0 = Not using today 2= We are actively

implementing this technology (all values) 1 Initiation

1= Actively experimenting

and/or piloting BLANK = Not sure (all values) 1 Initiation

1= Actively experimenting and/or piloting

0 = We have no plans to use this technology

(all values) Blank Contradictory; remove from data set

1= Actively experimenting

and/or piloting


experiment with this technology



2= We are actively implementing this technology


2= Used in some areas of our

marketing department, e.g. corp. marketing

BLANK = Not sure (all values) 2 Contagion


marketing department, e.g.

corp. marketing




marketing department, e.g.

corp. marketing



technology

(all values) 2 Contagion

2= Used in some areas of our marketing department, e.g.

corp. marketing

2= We are actively

implementing this technology (all values) 2 Contagion

3= Used throughout our entire marketing department

BLANK = Not sure (all values) 3 Growth




3= Used throughout our

entire marketing department


experiment with this technology

(all values) 3 Growth



2= We are actively

implementing this technology

1= Used by a single

specialist 3 Growth



2= We are actively

implementing this technology

2= Used by several

specialists 3 Growth



3= Used by virtually

everyone in the

marketing department

4 Adoption

Note: No responses were found outside of these permutations listed above.

LAGUË 13


Multivariate statistical testing (Spearman coefficient of rank correlation) was used to

determine if changes to the organization structural attributes could be explained by the

adoption of any particular technology type. This type of test is appropriate to measure

correlation between variables with ordinal data.1

Method to Analyze the Influence of Estimated Nolan Stage on “Organicness”

Another key question of this study is to determine if significant correlation exists

between the Nolan Stage (technology adoption) and the “organicness” of marketing

departments. In other words, does the adoption of certain technologies influence

marketing departments to become more organic or more mechanistic?

It is not practical or realistic to expect survey respondents to accurately plot their own

firm on “organicness” according to some continuum or simple scale-based measure. As

an alternate method, this study measured a series of related structural attributes using

ordinal (scale) data, and then a composite variable ORGANIC was created to aggregate

these as a sum total of the individual attribute scores. The higher the ORGANIC score,

the more organic the structure. The key assumption here is that each individual

attribute scale is essentially measuring the same phenomenon (tendency to become

more organic versus mechanistic). Figure 6: Computing the ORGANIC Composite

Variable Score illustrates the computation method.

1 Rank correlations of zero indicate no association among the ranks, while rank correlations of +1.00

would indicate a perfect direct relationship while negative rank correlations up to -1.00 would indicate an

increasingly strong inverse relationship between ranked pairs (Lind, Marchal & Walthen, 2005, p.570). The generally accepted convention is to accept the hypothesis that correlation exists between the two

variables if the computed value of rank correlation exceeds the hypothesis test critical value (t) at the 0.05

significance level.

LAGUË 14


Figure 6: Computing the ORGANIC Composite Variable Score

Attribute Question (as appeared in

questionnaire)

Contribution to ORGANIC score

LOW

(Adding +1 point)

MEDIUM

(Adding +2 points)

HIGH

(Adding +3 points)

RIGID JOB

DEFINITION

How often would you say

specialists in your marketing

department are performing work that is outside of their FORMAL

JOB DESCRIPTION?

Very seldom Occasionally Frequently

JOB ROTATION Relative to other organizations where you have worked, how

often have marketing specialists

SWITCHED JOBS within your

marketing department (i.e., lateral transfer, job rotation,

etc.)?


INTERNAL TRANSFER

In your estimation, when a new specialist job is established, how

often are INTERNAL CANDIDATES

selected to staff this role (instead of hiring externally)?


FORMAL TEAMS Relative to other organizations where you have worked, how

often do specialists participate in

FORMAL TEAMS?


POLICIES

Relative to other organizations where you have worked, which

statement best describes the

extent to which WRITTEN POLICIES AND PROCEDURES guide

your Marketing specialists?

Specialists tend to follow detailed

written policies and

procedures in most areas

Specialists follow written policies and

procedures in some

areas, but use their own judgment and

peer advice in many

others

Specialists rely almost exclusively on their

own experience,

judgment and peers to guide them

PARTICIPATIVE

LEADERSHIP

In your estimation, how would

your TOP MANAGEMENT tend to respond (or how have they

reacted in the past) if the

department were underachieving

on one of its strategic objectives?

Top management

would likely decide on appropriate

corrective action

Top management

would likely consult the department, then

decide on

appropriate

corrective action

Top management

would likely let the department decide

on appropriate

corrective action

PERFORMANCE

EVAL2

Which statement below best

describes the role of technology in EMPLOYEE PERFORMANCE

EVALUATIONS?

Employees have

formal performance targets for their use

of technology, and

these constitute a significant part of

their total

performance reviews

Employees have

formal performance targets for their use

of technology, but

these are minor relative to other

performance targets

Employees are

informally monitored for their effective use

of technology

OUTSOURCING In general, which best describes

your department’s use of

OUTSOURCING (contractors, professional services, consultants,

etc.)?

Marketing staff relies

almost entirely on

outside help to operate its

technology systems

Marketing staff

operates its

technology systems with some outside

help

Marketing staff

operates its

technology systems with little to no

outside help

2 Note the use of scale inversion on this attribute.

LAGUË 15


See Figure 7: ORGANIC Composite Variable Histogram. The ORGANIC scores

approximate a normal distribution; however to be conservative, the Spearman test is

still used to compute correlation with technology adoption.

Figure 7: ORGANIC Composite Variable Histogram

Lastly an open-ended question asking respondents to comment on the impact of new

technology on their marketing department structure rounds off the questionnaire.

Comments from this question were selectively added to the findings, to provide

additional context and perspective. A handful of respondents were contacted at the

end of the study to provide additional perspective on the key findings.

LAGUË 16


4. FINDINGS

The findings are grouped into four sections. Starting with Technology Diffusion-Adoption

Theory, which explores how information technologies used in marketing departments

follow a life-cycle pattern in their adoption. Marketing Technologies at the Vanguard

outlines a framework used to classify the wide array of marketing technologies into five

broad types, and provides a baseline assessment of the survey panel adoption of each

technology type. Evaluating Marketing Organization Structure uses traditional

organization theory to describe the structure at the work-unit level, and how marketers

perceive the structural dimensions of their own organizations. Finally, Structural

Adaptation to Emerging Technologies outlines the structural attributes found among

members of the panel, identifies the structural attributes having the most tendency to

change as technology is adopted, and the results of whether organizations tend to

become more mechanistic or organic (or neither).

Technology Diffusion-Adoption Theory

While every organization does not share the same experience with information

technology, Nolan and Gibson (1974) were the first to propose a “stages” theory of IT

growth, which can be used to explain the organizational changes and design challenges

associated with new technology adoption. They researched the characteristics of

organizations implementing electronic data processing (EDP) systems and their shifting

influence on organization design over time. The four stages they proposed were

Initiation, Contagion, Control and Maturity, each with distinctive characteristics

described in more detail below.

During the Initiation stage, new technology is typically introduced to achieve cost

savings within an individual work unit (Nolan & Gibson, 1974, p.78). The Contagion

stage brings both user spread and application spread. Having overcome the initial risks

and feasibility challenges, an attitude of over-optimism can often settle in, sowing the

seeds of poor governance (p.81). The end of the Contagion stage is typically marked by

the addition of strong management which returns technical controls and administrative

discipline to the system (p.82).

The Growth stage begins after formal controls replace the loose guidelines established

by early users. Activities and relationships are increasingly governed by rules, operating

procedures and contracts. Often the transition to Growth stage is characterized by

application and data spread, but also change resistance and personnel replacements.

At the end of the Growth stage the technology reaches a steady-state, Maturity. In

larger organizations with mature technologies a steering committee is typically formed

LAGUË 17


to guide incremental system enhancement, policy and ongoing changes to the

organization (p.88).3

Since this original theory was proposed, other variations of stage-based theory have

appeared in the literature. Ruekert et al. (1985) studied ten companies in depth to

research the notion that IT adoption in turbulent and information-intensive

environments occurs in stages, and found considerable diversity among real-world

practices (p.14). The lack of conclusive evidence on the benefits of one organizational

form over another leads marketing practitioners to consider other theories for

guidance.

Ronald Swift (2001) adapted the Nolan & Gibson Stages theory to plot the growth of

enterprise customer relationship management (CRM) systems used by Sales and

Customer Service, which are close cousins to marketing technology. Swift’s model

outlines six distinct stages: Initiation, Growth, Control, Integration, Distribution and

Adoption (p.125).

During the initial stages of technology adoption, Swift concluded that organizations

attempt to solve a single problem or a challenge with limited scope. Organizations do

not alter their structure to “fit” technology early on, since proof of concept is not yet

established and the long-term viability of the technology is still suspect (p.141). As

proof of concept is established, the technology “spreads” to a wider group of users.

Control, skill-building and systems integration all became paramount issues at this

juncture. Organizations tend to seek out professional services during this stage to

acquire the specialized skills they need to operate the technology and integrate it with

other systems, as well as to develop operating standards and adapt their structure to

optimize system performance (Swift, 2001, p.141).

Marketing Technologies at the Vanguard

Marketing work is typically characterized by high task variety (individuals encounter a

high number of unexpected situations and frequent problems) and low analyzability

(individuals do not retain a store of techniques or procedures to tell a person exactly

what to do to solve a particular problem). Daft (2004) suggests that information

technologies in roles which involve high task variety and low analyzability require

“nonroutine technology” (p.86). These advanced technologies “require a greater need

for employee training and education because workers need higher-level skills and

greater competence to master their tasks” (Daft, 2004, p.91).

The growing imperative of IT as a determinant of marketing department structure is

confirmed by several respondent comments:

3 This report hereafter refers to progression through the four Nolan Stages as “technology adoption.”

LAGUË 18


“In recent months, the way our new project teams and departments have

been organized has been dictated primarily by new technology.”

–Marketing specialist for a divisionally-organized retailer

“We only recently created a formal Marketing department, and

technology has been a cornerstone of building that function... A large part

of our staffing was hiring for proclivity towards technology.”

– Business services firm executive

“Adding technologies has allowed us to address [our] market/service

expansion and company growth without greatly increasing the number of

marketing personnel.”

– Manager at a mid-size business services company

The landscape of technology products and services used in marketing departments is

highly fragmented, with many vendors providing overlapping functionality; as such, no

single classification provides an authoritative taxonomy. This study follows a

framework suggested in a recent Forrester Research report by analyst Elana Anderson

(2007) who concluded that the array of contemporary marketing technologies can be

condensed into five broad types: “E-mail marketing and deliverability, [web] site

optimization, marketing automation, interaction management [marketing intelligence]

and marketing resource management” (p.6). This is a helpful classification which applies

universally to both business-to-business (B2B) and consumer marketers. Each

technology type is described in more detail below and appears in order from most to

least adopted.

E-mail Marketing and Deliverability (E-mail) represents the set of technologies used to

design, deliver and measure targeted e-mail messages with relevant content to large

numbers of customers. According to Rebecca Jennings at Forrester Research (2007),

with most consumers getting swamped by a growing volume of e-mails, most marketers

have moved beyond basic “push” e-mail delivery systems and are now focusing on

segmentation and tracking tools to improve the relevance of their communications to

consumers (p.6). Technologies include outsourced e-mail delivery, e-mail subscription

preference systems, e-mail reporting systems, e-mail systems integration, and systems

to customize and control message frequency (Katz, J., 2008, p.3-4). Currently

technology platforms include vendors such as Acxiom Digital, Datran Media, e-Dialog,

Epsilon, Experian CheetahMail, Harte-Hanks, Responsys, and Yesmail (Katz, 2007, p.4).

Figure 8: ESTIMATED_NOLAN for E-Mail indicates that virtually all companies endeavour

to use E-mail; most are found in the Nolan Contagion or Growth Stage, with a minor but

LAGUË 19


significant proportion of firms reporting their E-mail systems have reached full

Adoption.

Figure 8: ESTIMATED_NOLAN for E-Mail

Web Site Optimization (Site Optimization) technologies are used to improve an

organization’s presence on the Web and manage the content itself. These include the

broad array of technologies used for search engine marketing, content management,

online performance testing, and selective offers and content to end-users based on

combinations of business rules and predictive models (Vittal, S., 2006, p.3). Site

Optimization technologies includes packaged solutions from vendors such as Memetrics,

Offermatica, Optimost, Kefta, Touch Clarity, WebTrends and [x + 1] among many others.

Figure 9: ESTIMATED_NOLAN for Site Optimization illustrates that most survey

respondents are actively implementing site optimization technologies, but that these

systems are currently somewhat less mature than E-mail technologies.

LAGUË 20


Figure 9: ESTIMATED_NOLAN for Site Optimization

Marketing Intelligence refers to the group of technologies used to measure customer

behaviour and responsiveness for campaign analysis, predictive insight, and advanced

segmentation. Jennings (2008) classifies measurement needs into five categories: Reach

(numbers of customers), Efficiency (spending per customer action), Consumer (brand

preference, purchase intent, etc.), Cross-channel (influence of discrete activities in

different channels on total customer impact), and Emergent (longer-term measures of

brand perception and overall customer engagement) (p.3). Examples of vendors which

provide marketing intelligence products vary widely and include ClickTracks,

CoreMetrics, Google, Knowledge Networks, Responsys, Unica, Visual Sciences, and

WebTrends among others (Jennings, p.7).

Figure 10: ESTIMATED_NOLAN for Marketing Intelligence suggests that there is a

considerable spread between panel respondents on their usage of these technologies,

although a significant proportion of organizations are in Contagion and Growth stages.

LAGUË 21


Figure 10: ESTIMATED_NOLAN for Marketing Intelligence

Marketing Automation (also referred to as enterprise marketing automation) refers to

the group of technologies which enable analytical and workflow-driven processes such

as lead scoring, lead nurturing and routing to optimize contact with customers or

between customers and their sales force or other channels. These technologies are

provided by vendors such as Eloqua, Extraprise, Experian and SmartFocus (Vittal, 2006,

p.6).

Figure 11: ESTIMATED_NOLAN for Marketing Automation suggests that many marketers

are adding marketing automation solutions, although similar to Marketing Intelligence

there is a considerable spread in the adoption of these systems, with most companies in

the Initiation stage.

Figure 11: ESTIMATED_NOLAN for Marketing Automation

LAGUË 22


Survey comments indicate that Marketing Automation allows marketers to undertake a

broader array of sophisticated activities and increase their overall productivity:

“We found that less staff was required with the efficient adoption of

technology, especially marketing automation tools. For example there is

no longer such a heavy requirement for e-mail and web design and

development with the advent of marketing automation tools and

systems.”

- Security Products and Services company

“Our marketing automation system has allowed us to do more

sophisticated nurturing programs with very small staff - a team of three.

It is allowing us to quickly change campaigns in response to results and to

learn from more A/B testing [experimentation].”

– Computer Software company

Marketing Resource Management (MRM) is used to automate, track and manage

budgets, marketing assets and projects within the marketing process (Vittal, S., 2006,

p.3). Examples of vendors offering MRM applications are Aprim, Orbis and Unica.

Figure 12: ESTIMATED_NOLAN for Marketing Resource Management illustrates the low

adoption rates among respondents. We can conclude this technology is at the vanguard

for most marketing organizations.

Figure 12: ESTIMATED_NOLAN for Marketing Resource Management

LAGUË 23


Evaluating Marketing Organization Structure

While contingency theory suggests that no particular structure is ideal for all firms and

situations, three organizational forms are frequently observed in marketing

departments: functional, division, and matrix structures. Each of these is described in

context below.

Functional structures allow marketing departments to organize their efforts to benefit

maximally from specialization. Poole (1999) suggested that functional structures offer

several important benefits relative to other organizational forms:

• Expertise is pooled, maximizing the resources within each function

• Clear reporting responsibilities and decision-making authority

• Better upward mobility for specialists to move into supervisory roles

• Avoidance of role conflicts and shallow loyalties resulting from frequent lateral

moves (p.460)

In this form, product, brand, segment and area marketing managers as well as several

other support functions typically report up to directors and a vice-president overseeing

the coordination of all marketing tasks (Achrol & Kotler, p.146). Rigid adherence to job

definitions, well-established procedures, low job rotation, heavy use of outsourcing, and

authoritative managerial style are all symptomatic of highly functionalized structures.

See Figure 13: Typical Functional Structure for an illustration of the vertical linkages.4

Figure 13: Typical Functional Structure

Typical Functional Structure

4 Note: These sample organization charts also appeared in the questionnaire to help respondents classify

their own organization.

LAGUË 24


Organizing people into carefully-constructed roles can enhance their problem-solving,

process innovation and flexibility where tasks are non-routine and the task environment

is complex or unstable, such as that caused by the introduction of new technology.

This survey comment illustrates the effect of new technology adoption on increased

specialization:

“Recently a new sub-department within Corporate Marketing was formed

(eMarketing, formerly known as Marketing Operations). The eMarketing

department encompasses one senior manager, two specialists and two

interns who are responsible for managing all of our CRM, Marketing

Automation, E-mail Marketing, Website, etc.”

– Technology company manager

As technology becomes more pervasive among employees within the work unit

however, less specialization is necessary in the structure to manage it (Achrol & Kotler,

p.146). A manager working at a small software company in the Growth Stage of E-Mail

and Site Optimization technologies suggested how new technologies can contribute to

job enlargement, as an expansion in the number of different tasks performed by

employees:

“[Our] new technology hasn't affected the number of employees in our

marketing department, but it has definitely changed the roles by adding

new responsibilities such as database segmentation, lead nurturing,

marketing dashboards and scorecards, etc.”

As organizations get larger and the span of control within the department grows beyond

the capacity of single line managers, marketing departments are typically split into

product-specific, segment-specific or regional groups. Organizations with a wide

product mix may employ market managers to replace product line managers to

coordinate activity for a well-defined set of customers. Figure 14: Typical Divisional

Structure illustrates the vertical linkages within a divisionally structured marketing

department.

LAGUË 25


Figure 14: Typical Divisional Structure

Typical Divisional Structure

One manager at a large telecommunications services division commented on the

success their highly specialized structure has afforded them with new technology

adoption:

“Due to the size of our marketing department - divisionally organized with

over 200 people in my functional area - we all tend to be very specialized,

even in managerial teams like mine. There is one team devoted

exclusively to marketing communications for e-mail and direct marketing,

another team for marketing communications strategy, another team for

web content, another for web marketing and advertising, etc... [Our

marketing systems] are quite progressive, but we find that by using this

structure the level of specialization and focus allows us to absorb new

technologies into these teams fairly easily.”

In divisional structures, disparate employees may be familiar with each other's

technologies, but sometimes this is not the case (Lamb & Davidson, 2005). This can

result in technologies used by only one group in isolation from others, which can

contribute to efficiency loss. A marketing specialist at a consumer product

manufacturer illustrated the challenges of implementing E-mail technology, perhaps the

most mature technology type, across a large, distributed marketing organization:

“Right now we only use an 'e-mail blasting' tool and have few two-way

interactions with our customers. Our campaigns are executed at our pace,

not that of our customers. We are looking into ways to change this but

are encountering organizational challenges, as this technology touches

upon many businesses and organizations across the entire company,

things move slowly.”

LAGUË 26


The informational requirements of being on the pulse of consumers means that today’s

marketing organizations must be flexible enough to let its members rapidly transmit,

learn and respond to changing lifestyle, product and consumption patterns. Richard

Daft (2004) posited that departments working in uncertain environments and with

complex, non-routine technologies are prone to adopt more organic structures (p.86).

Organic structures are characterized by loosely-defined and broad-based job roles;

sharing activities and decisions horizontally as well as vertically; employees are guided

by experience and intuition as opposed to detailed policies and procedures; specialists

rotate through jobs frequently; there are more internal transfers due to the low entry

barriers of job switching from one role to another; more of the work depends on teams;

and top management tends to be more participative, as opposed to authoritative (Daft,

p.91). By contrast, organizations scoring low on “organic” structure are labelled

“mechanistic,” with the exact opposite structural characteristics (Daft, p.87).

Matrix structures are a good example of structural form that uses both vertical and

horizontal linkages to increase flexibility and responsiveness. In a matrix structure, the

managers retain primary authority but service delivery is coordinated by specialists

working in multiple marketing teams with “dotted-line” accountability. Specialists

coordinate a wide array of activities by working in several project-based groups or

teams across product lines or markets, or both (Ruekert et al., p.13-4). Matrix

structures are used by marketing departments that depend on combined

product/market management. Sometimes the horizontal linkages are formalized into

full-time equivalent employees who play an integrative role across the entire

organization. See Figure 15: Typical Matrix Structure for an illustration.

Figure 15: Typical Matrix Structure

Typical Matrix Structure

LAGUË 27


Information technology is widely accepted to be a key enabler for coordinating the

activities of specialists in matrix structures. One manager working at a technology firm

illustrated the role of their Marketing Resource Management (MRM) system to

coordinate dozens of employees across their large marketing department:

“Our marketing database system is used to set up projects, track

progress, manage revenue & expenses and authorize projects. The tool is

also used to generate reports and ensure proper controls are in place for

compliance to company policy and guide ethical behaviour.”

The majority of the survey panel classified themselves as having pure functional

structures (56%), with the rest reporting divisional structures (24%), and matrix

structures (20%).5 See Figure 16: Survey Panel Marketing Organization Structure for

details.

Figure 16: Survey Panel Marketing Organization Structure

Ultimately, extant research on the “ideal” structural adaptations for new technology are

inconclusive (Ruekert et al, 1985, p.19). On one hand, supporting more organic

structures are Achrol & Kotler (1999) who stated that companies should adapt to

today’s “networked” economy by “flattening” their marketing departments, choosing

more informal authority structures and outsourcing non-core functions to enhance their

flexibility and level of innovation (p.147).

5 In all frequency tabulations (pie charts) appearing in this report, the percentages are estimated to be

accurate within a margin of error of ±10%, 9 times out of 10 due to sampling error.

LAGUË 28


On the other hand, recent research by Thorpe and Morgan (2006) counters the trend

toward organic structures, recommending instead a return to centralized structures to

assure the successful implementation and rapid execution of strategy. The contextual

and process characteristics of strategy formulation include a “change management”

approach to technology implementation where senior management get closely

involved; this yields better mid-level managerial support, and more consensus and

clarity on goals and tasks (p.665).

Achrol & Kotler (1999) cite examples of larger firms attempting to break the trade-offs

of these conventional forms by experimenting with new organizational forms to replace

hierarchies (p.148). Among these are layered networks, where employees are drawn

from a functional “home base” to join an operational layer of cross-functional teams

responsible for achieving process-based outcomes. These teams leverage a

companywide repository of marketing, finance and operating and research data formed

by the functional silos. These horizontal and vertical connections enhance the

information sharing, mutuality, trust and transparency of linkages between individuals

and teams (p.149).

To advocate the take-up of strategic technology, Tassabehji, Wallace and Cornelius

(2007) advocate the rise of a new functional specialty, the “e-centred role” which acts as

a horizon integrator and supplements technical expertise to the conventional

product/market functions (p.26). One industrial manufacturer commented on the

impact of new technology on their divisional organization supports the idea of an

emerging “e-centered” role:

“The biggest impact of technology in our organization has been the

creation of two groups of marketing people. One group uses, masters

and understands the technology, while the others are somewhat

"technology illiterate", understanding the outcomes and benefits of these

systems but relying on the first group for campaign execution. As a result

we have a parallel language understood by some members of the team,

but not others.”

One manager at a large media publisher illustrated the effects of new technology on job

enlargement within their “flattened” work-unit:

“Our department responsibilities now span several new service areas

including search engine marketing and optimization, editorial, Web site

operations, and Sales.”

New technology has also contributed to job enlargement, enabling individuals to

perform a higher variety of tasks as illustrated by these comments:

LAGUË 29


“Prior to implementing our marketing automation system, we relied on

corporate marketing to develop and deploy e-mail campaigns for us.

We're doing that function for ourselves now. We're also being more

proactive in monitoring and measuring our own campaign results, as well

as using technology to segment and target marketing messages to our

specific audiences.”

– Manager at a large technology company

“New technology has caused us to re-think our roles and responsibilities.

In the past, our department used a centralized model to execute

marketing campaigns. Now all of our marketers are able to execute

campaigns independently.”

– Specialist at a technology company with 100+

Marketing employees

New technology also increases the integration between department members,

according to this comment:

The biggest impact of new technology has been to take people out of

their silos. In our department you must be able to work on everything

through our technology systems (except things like copywriting).

– Manager at an Education services company

Structural Adaptation to Emerging Technologies

The majority of the survey panel (57%) reported that marketing specialists were

occasionally performing work outside of their formal job description, while a minority

(33%) reported they were frequently doing so. Only a fraction (10%) reported that the

job description was sufficiently well-defined to cover all activities, symptomatic of

mechanistic organizations. See Figure 17: Results for RIGID_JOB_DEFINITION.

LAGUË 30


Figure 17: Results for RIGID_JOB_DEFINITION

Nearly half of marketers (48%) reported that specialists switched jobs very seldom

within the department.6 This was followed by a minority reporting occasional job

rotation (41%) followed by frequent job rotation (11%). See Figure 18: Results for

JOB_ROTATION.

Figure 18: Results for JOB_ROTATION

6 Due to sampling error, percentages are estimated to be accurate within a margin of error of ±10%, 9

times out of 10.

LAGUË 31


About half of respondents (48%) reported that internal candidates were occasionally

selected to staff new specialist roles, followed by those who cited that this occurred

very seldom (26%) or frequently (26%). See Figure 19: Results for INTERNAL_TRANSFER.

Figure 19: Results for INTERNAL_TRANSFER

Specialists appear to participate frequently in formal teams (44%), with another 35%

reporting occasional participation and 21% reporting that this happens very seldom.

See Figure 20: Results for FORMAL_TEAMS.

Figure 20: Results for FORMAL_TEAMS

LAGUË 32


Only a minority of marketers (8%) report that their specialists are guided almost

exclusively by well-documented policies and procedures, with most (53%) relying on

intuition and experience and the rest (39%) stating that written policies and procedures

play almost no role whatsoever. See Figure 21: Results for POLICIES.

Figure 21: Results for POLICIES

Autocratic top management behaviour is the hallmark of a mechanistic organization,

especially when managers take full control in a situation involving corrective action.

Survey respondents indicate that only a minority (25%) would take corrective action

without consultation; another 55% would likely be consultative in their approach, but

only 20% of marketers estimate that their managers would follow a participative

managerial style. See Figure 22: Results for PARTICIPATIVE_LEADERSHIP.

LAGUË 33


Figure 22: Results for PARTICIPATIVE_LEADERSHIP

Not surprisingly, the majority of marketers (70%) operate their technology ecosystem

using some help from outside technology vendors and services. A minority (22%) report

having a very high reliance on outside vendors while a much smaller minority (8%)

operate their systems self-sufficiently. See Figure 23: Results for OUTSOURCING.

Figure 23: Results for OUTSOURCING

Many respondents who were asked about the single largest impact of new

technology on their structure commented on the increased external orientation:

LAGUË 34


“We currently have just two specialists to run our operational systems, so

we have had to outsource additional work in many cases.”

– Director at a small software publisher

“We work with outsourcing companies more often as there is a general

lack of knowledge about new technologies.”

- Manager at an entertainment industry company

“New technology has definitely caused us to rely more heavily on outside

consultants and contractors.”

– Director at a telecommunications equipment provider

“Our department is still trying to find an ‘owner’ for our new technology.”

- Director at a large industrial manufacturer

The statistical tests reveal there is weak correlation between TECHNOLOGY_TODAY and

ESTIMATED_NOLAN and the department structural characteristics. 7 This indicates that

progression on the Nolan Stage model alone cannot be used to explain change on most

structural attributes. See Figure 24: Spearman Coefficients of Rank Correlation for

output reports from the two statistical tests.

7 Spearman Coefficient of Rank Correlation was weak among most paired observations (rs = 0.339 or less).

LAGUË 35


Figure 24: Spearman Coefficients of Rank Correlation

8

TECHNOLOGY_TODAY

ESTIMATED_NOLAN

There are two exceptional trends. First, according to both tests, most of the significant

correlation between technology adoption and structural attributes is concentrated on

Marketing Intelligence. As organizations move up the Nolan Stage model with their

campaign analysis, predictive insight and segmentation reporting tools, they also tend

to increase in size, have a stronger tendency to use formalized teams, and have more

formalized employee performance evaluations which include technology performance

targets.

At this point it should be stated that the adoption of marketing intelligence systems

does not necessarily cause organizations to increase their size or their degree of

formalization. Most likely it is the exact opposite that is true: larger organizations are

more inclined to have mature marketing intelligence systems because of their size.

However the survey data does not provide this certainty; we can only assert a

correlative relationship.

8 These tables were condensed for presentation purposes.

LAGUË 36


The test results also confirm that as technology adoption increases, there is a significant

across-the-board change in a marketing department’s tendency to formalize its

employee performance evaluations and make technology targets a significant part of

these evaluations.9 This correlation is particularly significant among the sophisticated

technology types “at the vanguard”, notably Marketing Intelligence (rs = 0.410) and

Marketing Resource Management (rs = 0.523).

Figure 25: Performance Evaluation for Late Stage Marketing Intelligence/MRM

illustrates the difference between employee performance evaluation practices in

organizations reporting mature Marketing Intelligence and MRM systems versus the

entire sample.

Figure 25: Performance Evaluation for Late Stage Marketing Intelligence/MRM

The significance of this relationship is reinforced by the comments of a marketing

manager at a large international retailer, who elaborated on their analytical applications

and the presence of detailed performance targets:

“Since we are the end-users of analytical applications and programs,

ultimately the company wants to know if we are maximizing its

9 Significant correlation exists between the PERFORMANCE EVAL attribute and TECHNOLOGY_TODAY

(Spearman coefficient of rank correlation, rs varies between 0.315 and 0.587 depending on the technology

type). ESTIMATED_NOLAN showed similar results (rs between 0.251 and 0.523).

LAGUË 37


investment in software, training and licenses. In our performance reviews

we are evaluated on how often we use the technology, our knowledge of

how to operate the software, and also our opinions of how well they

work.”

This key finding is also corroborated by the vice-president of a large media company

who elaborated on the specifics of their employee performance evaluation program,

which involved heavily adopted Site Optimization, Email and Marketing Intelligence

technologies, each spanning several teams and involving detailed performance targets:

“All people [in our department] who touch our content are measured on

their ability to get the word out on the Web. We are giving out employee

bonuses to marketing specialists when they are successful at traffic-

building on our affiliate web sites. For the specialists to hit their bonus

targets per article, they must leverage social networking sites such as

Flickr, Facebook, Twitter, Technorati, DIGG, etc.

Our Web Operations team uses myriad marketing applications such as

Hitbox and Google Analytics to track the traffic and see how well each

campaign is doing, and report the results back to the department. The

reports are generated weekly and then dispersed amongst the teams.

The system was set up specifically for editorial and Web Operations staff,

but now incorporates us all.

As of this year my own performance review will be partially based on

technology-related business development which drives both traffic and

revenue. For example I am working on projects to add new technologies

which are intended to improve our e-mail delivery for newsletters and

lead generation programs for our advertisers, and also to get our

technology lined up with other departments such as circulation, technical

support, production, sales and accounting.”

The statistical test on the ORGANIC composite variable indicates there is no significant

correlation between technology stage and a firm’s position on the “organicness”

composite scale. Weak correlation is found among most paired observations (rs = 0.181

or less). See Figure 26: Spearman Coefficient of Rank Correlation (Partial), ORGANIC.

LAGUË 38


Figure 26: Spearman Coefficient of Rank Correlation (Partial), ORGANIC

LAGUË 39


5. CONCLUSIONS

What are we to make of all this? First of all, the test results confirm we should reject

the idea that marketing departments make evolutionary changes to become more

mechanistic or organic when they adopt emerging technologies. Notwithstanding some

notable exceptions, the Nolan technology innovation-diffusion model does not have any

obvious relationship to the overall structural and managerial characteristics of

marketing departments.

Swift (2001) once cautioned managers that sales and marketing systems “do change

over time and that most managers don’t foresee change coming” (p.156). Yet based on

the checkered findings of this research, it is easy to believe that managers turning to

their peers for advice on how to anticipate the changes associated with new technology

might become confused on exactly what these changes are or how to steer their

organization design to avoid the landmines. A wide variety of survey comments

illustrate the wide-ranging and often contradictory viewpoints; further, the effects of

new technology on department structure do not seem to be fully appreciated or even

understood by many respondents.

On a more tactical level, the findings do illustrate how the availability of reliable data on

departmental performance increases and as technology becomes more central to the

strategy, it becomes possible to link this performance to employees by establishing clear

performance targets and then tying commitments and financial incentives to their

achievement. We can see from the comments how marketing professionals in the more

technologically sophisticated organizations have a clear line of sight to the metrics on

which they are measured.

A majority of marketing departments continue to be organized functionally and this

does not seem to change with increased technology adoption. The functionally

organized department is an intuitive way to organize marketers, since most marketing

campaign management requires several discrete, non-routine activities which can

typically be performed more efficiently by specialists.

Suggestions for Further Research

Do the findings mean that marketing department managers should pay less attention to

organization design? Just because organizations may not create an observable shift in

their structures to adapt to new technology, this does not mean that it is “wrong” or

“right” not to do so. Studying a group of organizations with highly effective marketing

departments (as determined by their productivity, efficiency, creativity or some other

measure of performance) might yield very different results over the general population.

Apart from this, the study yielded considerable insight on how to design future research

to yield more reliable conclusions. Sampling frames used in future research on this topic

LAGUË 40


should provide access to potential respondents who have clear visibility into the

technology strategy in their organizations, and who are able (and willing) to accurately

relay the current state of technology usage. Gathering response data on the current

state of technology alone does not yield the firm’s position on the Nolan Stage model.

For instance, respondents who state that they are “not using” a certain technology type

may very well be in the planning stages and actively staffing its organization for the new

technology (i.e., Initiation). The sampling frame should also contain a large proportion

of experienced professionals, since the measurement of structural attributes will

inevitably involve qualifying statements, thus depending on outside experience and

relative comparison.

Another challenge with this type of research is avoiding the pitfalls of semantic error

associated with technology definitions. For an extreme example, consider general

purpose software such as Microsoft Outlook. Outlook can be used to send e-mail

messages. Should a marketing team using Outlook consider it to be part of their E-mail

technology? Any difference in interpretation will contribute to non-sampling error.

Successful follow-on research must therefore clarify the specific technologies which are

in versus out of scope.

This analysis relied exclusively on linear regression models, where the actual

relationships between variables may not be linear. The use of logarithmic scales may

reveal significant correlation between variables that otherwise went undetected using

linear modelling.

LAGUË 41


6. REFERENCES

Achrol, R., Kotler, P. (1999). Marketing in the network economy. Journal of Marketing

[Electronic version] retrieved May 18, 2008 from ABI Inform.

Anderson, E. (2007). Marketing Technology Adoption 2007: Forrester's Q4 2006

Marketing Benchmark Online Survey. Forrester Research [Electronic version]

retrieved May 21, 2008 at

http://forrester.com/Research/Document/0,7211,41431,00.html

Brady, M., Saren, M., Tzokas, N. (2002). The assimilation of it into marketing practice.

Irish Marketing Review [Electronic version] retrieved May 31, 2008 from ABI

Inform.

Coviello, N., Milley, R., Marcolin, B. (2001) Understanding IT-enabled interactivity in

contemporary marketing. Journal of Interactive Marketing [Electronic version]

retrieved May 18, 2008 from ABI Inform.

Daft, R. L. (2004). Essentials of organization theory and design. Cincinnati, Ohio: South-

Western, Thomson Learning.

Jennings, R. (2007). European Email Marketing Spend Hits €2.3 Billion In 2012. Forrester

Research [Electronic version] retrieved May 31, 2008 from Forrester secure web

site.

Katz, J. (2007). The Forrester Wave™: Email Marketing Service Providers, Q4 2007.

Forrester Research, January 2, 2008 [Electronic version] retrieved May 31, 2008

from Forrester secure web site.

Katz, J. (2008). How To Move Email Marketing Forward In 2008. Forrester Research,

February 22, 2008 [Electronic version] retrieved May 31, 2008 from Forrester

secure web site.

Kotler, P. (2003). Marketing Management (11th

Edition). Upper Saddle River: Pearson

Education Limited

Lamb, R., Davidson, E. (2005). Understanding Intranets in the Context of End-User

Computing: Database for Advances in Information Systems [Electronic version]


Lind, D. A., Marchal, W.G., Wathen, S.A, (Ed.). (2005). Statistical Techniques in

Business & Economics (12th ed.): McGraw-Hill Irwin.

LAGUË 42


Nolan, R. L., Gibson, C. (1974). Managing the four stages of EDP growth. Harvard

Business Review [Electronic version] retrieved May 15, 2008 from ABI Inform.

Poole, M.S. (1999). Organizational challenges for new forms. Thousand Oaks, CA: Sage

Publications.

Ruekert, R., Walker Jr., O., Roering, K. (1985). The Organization of Marketing Activities:

A Contingency Theory of Structure and Performance. Journal of Marketing

[Electronic version] retrieved May 14, 2008 from ABI Inform.

Swift, R. (2001). Accelerating Customer Relationships. Pearson-Hall PTR: Upper Saddle.

Tassabehji, R., Wallace, J., Cornelius, N. (2007). E-technology and the emergent e-

environment: Implications for organizational form and function. Journal of High

Technology Management Research [Electronic version] retrieved May 17, 2008

from ABI Inform.

Thorpe, E., Morgan, R. (2006). In pursuit of the "ideal approach" to successful marketing

strategy implementation. European Journal of Marketing [Electronic version]


Turban, E. (2008). Information Technology for Management: Transforming

Organizations in the Digital Economy, 5th Edition. Wiley & Sons: Danvers.

Vittal, S. (2006). Marketing Optimization Defined. Forrester Research, December 19,

2006 [Electronic version] retrieved May 31, 2008 from Forrester secure web site.

LAGUË 43


7. APPENDIX

Appendix A: Research Ethics Statement

The following statement appeared at the beginning of the survey questionnaire:

There have been no known adverse effects for participants in this study. The e-mail

providing access to the survey contained an explanation of the survey purpose and

process, confidentiality, privacy, anonymity and their right to refuse. All response data is

kept confidential and anonymous to everyone except the applicant and project

supervisor. Any quotes added to the report are attributed to the organization but not

the individual. Responses that need clarification may require a follow-on phone call or e-

mail to the respondent (one attempt). At the end of the data collection period, all

response information is downloaded to the applicant’s personal computer and the

response data is deleted from the third-party software. Electronic files are subsequently

deleted from the applicant’s hard drive one year after study completion.

LAGUË 44


Appendix B: Questionnaire

Note: This is a reproduction of the questions from the survey. The appearance of these

questions was not exactly as shown below.

Please read the question below carefully and for each row in the table below, check the box that best describes your situation.

1. How is your marketing department using the following technologies TODAY?

Not using today Actively experimenting

and/or piloting

Used in some areas of

our marketing

department, e.g. corp.

marketing

Used throughout our

entire marketing

department

E-mail Marketing and

Deliverability � � � �

Website Optimization � � � �

Marketing

Automation � � � �

Marketing

Intelligence � � � �

Marketing Resource

Management � � � �

Definitions: E-mail Marketing and Deliverability: Technologies used to manage large-scale e-mail deliverability, and measure message performance. Website Optimization: Technologies used to improve web presence and manage content. Marketing Automation: Technologies used to optimize contact with customers such as lead scoring, lead nurturing, lead routing. Marketing Intelligence: Technologies used for campaign analysis, predictive insight, and advanced segmentation. Marketing Resource Management: Technologies used to improve internal processes and resource allocation.

2. What are your department’s plans to implement these technologies IN THE NEXT 24 MONTHS?

We have no plans to

use this technology

We have plans to


technology

We are actively

implementing this

technology

Not sure




Marketing


Marketing


Marketing Resource


3. How pervasive are these technologies in your marketing department?

LAGUË 45


Not used/ not

applicable

Used by a single

specialist

Used by several

specialists

Used by virtually

everyone in the

marketing department




Marketing


Marketing


Marketing Resource


4. Relative to other expenditures such as advertising and promotion, has your department spending on technology

increased or decreased over the last two years?

technology spending has increased significantly

technology spending has increased about the same as other expenditures

technology spending has declined slightly

technology spending has declined significantly

not sure/can't say

Part 2 of 3: About Your Marketing Department

For each question below, please select the answer that best describes the current situation at your organization.

5. Approximately how many employees currently work in your MARKETING DEPARTMENT?

1 – 5 employees in Marketing





More than 100 employees in Marketing

Not sure/can’t say

6. Approximately how many employees currently work in your OVERALL COMPANY/ORGANIZATION?

1 – 10 employees worldwide

11 - 100 employees worldwide

101 – 500 employees worldwide

501 – 1,000 employees worldwide

LAGUË 46


More than 1,000 employees worldwide

Not sure/can’t say

Please consider the three diagrams below.

7. Which diagram best represents the structure of your marketing organization?

Diagram A – Functional Structure

Diagram B – Matrix Structure

Diagram C – Divisional Structure

None of these adequately represent our structure (please explain):

Diagram A – Functional Structure (all marketers report to a single marketing executive)

Diagram B – Matrix Structure (all marketers report to one marketing executive, but may also report “dotted-line”

to other non-marketing executives)

LAGUË 47


Diagram C – Divisional Structure (all marketers report to a marketing executive in their respective division)

8. How often would you say specialists in your marketing department are performing work that is outside of their

FORMAL JOB DESCRIPTION?

very seldom

occasionally

frequently

9. Relative to other organizations where you have worked, how often have marketing specialists SWITCHED JOBS

within your marketing department (i.e., lateral transfer, job rotation, etc.)?

LAGUË 48


very seldom

occasionally

frequently

10. In your estimation, when a new specialist job is established, how often are INTERNAL CANDIDATES selected to

staff this role (instead of hiring externally)?

very seldom

occasionally

frequently 11. Relative to other organizations where you have worked, how often do specialists participate in FORMAL

TEAMS?

very seldom

occasionally

frequently

12. Relative to other organizations where you have worked, which statement best describes the extent to which

WRITTEN POLICIES AND PROCEDURES guide your Marketing specialists?

Specialists tend to follow detailed written policies and procedures in most areas

Specialists follow written policies and procedures in some areas, but use their own judgment and peer advice in many others

Specialists rely almost exclusively on their own experience, judgment and peers to guide them

13. In your estimation, how would your TOP MANAGEMENT tend to respond (or how have they reacted in the past)

if the department were underachieving on one of its strategic objectives?

top management would likely decide on appropriate corrective action

top management would likely consult the department, then decide on appropriate corrective action

top management would likely let the department decide on appropriate corrective action

14. Which statement below best describes the role of technology in EMPLOYEE PERFORMANCE EVALUATIONS?

employees are informally monitored for their effective use of technology

employees have formal performance targets for their use of technology, but these are minor relative to other performance targets

employees have formal performance targets for their use of technology, and these constitute a significant part of their total performance reviews

LAGUË 49


15. In general, which best describes your department’s use of OUTSOURCING (contractors, professional services,

consultants, etc.)?

Our marketing staff relies almost entirely on outside help to operate our technology systems

Our marketing staff operates our technology systems with some outside help

Our marketing staff operates our technology systems with little to no outside help

16. In which industry does your organization primarily operate? (Please select one)

(picklist) 17. Which best describes your primary target market?

We primarily sell to Businesses (incl. non-profits, government, non-government organizations, etc.)

We primarily sell to Consumers 18. What is your current job level within the marketing department?

Specialist

Supervisor/manager

Director/executive

Contractor/consultant

Other (please specify)

19. How long have you worked for your organization?

More than 24 months

Between 7 and 24 months

Between 1 and 6 months

Less than 1 month

Not employed

To ensure complete privacy and confidentiality, all identifying information (individual names, organizations) will be removed from comments appearing in the final report.

20. What would you say the biggest impact of new technology has been on the STRUCTURE of your marketing

department (department size, roles, managerial span of control, use of specialists, teams, etc.)?

LAGUË 50


21. Do you have any comments or suggestions regarding this study?

22. May we contact you if we need to clarify your response?

Yes, you may contact me if any of my responses need clarification.

Please enter your e-mail address and/or phone number:

23. Would you like to receive an invitation to the webinar where the findings of this research will be presented?

Yes. I understand that my e-mail address will not be used for any other purpose.

Your e-mail address:

LAGUË 51


Appendix C: Data Table

Variable Survey Question Variable Name Type of

Data

Codes and Legend

A 1 TECHNOLOGY TODAY – E-MAIL Ordinal 0 = Not using today 1= Actively experimenting and/or piloting

2= Used in some areas of our marketing

department, e.g. corp. marketing 3= Used throughout our entire marketing

department

B 1 TECHNOLOGY TODAY – WEBSITE Ordinal 0 = Not using today 1= Actively experimenting and/or piloting


department, e.g. corp. marketing


C 1 TECHNOLOGY TODAY – MARKETING

AUTOMATION

Ordinal 0 = Not using today

1= Actively experimenting and/or piloting 2= Used in some areas of our marketing

department, e.g. corp. marketing


D 1 TECHNOLOGY TODAY – MARKETING

INTELLIGENCE

Ordinal 0 = Not using today


2= Used in some areas of our marketing department, e.g. corp. marketing

3= Used throughout our entire marketing

department

E 1 TECHNOLOGY TODAY – MRM Ordinal 0 = Not using today



department, e.g. corp. marketing 3= Used throughout our entire marketing

department

F 2 TECHNOLOGY FUTURE – E-MAIL Ordinal BLANK = Not sure 0= We have no plans to use this technology

1= We have plans to experiment with this

technology 2= We are actively implementing this technology

G 2 TECHNOLOGY FUTURE – WEBSITE Ordinal BLANK = Not sure


1 = We have plans to experiment with this technology


H 2 TECHNOLOGY FUTURE – MARKETING AUTOMATION

Ordinal BLANK = Not sure 0 = We have no plans to use this technology

1 = We have plans to experiment with this

technology


I 2 TECHNOLOGY FUTURE –

MARKETING INTELLIGENCE

Ordinal BLANK = Not sure


1 = We have plans to experiment with this technology


J 2 TECHNOLOGY FUTURE – MRM Ordinal BLANK = Not sure 0 = We have no plans to use this technology

1 = We have plans to experiment with this

technology


LAGUË 52


K 3 PERVASIVENESS – E-MAIL Ordinal 0= Not used/ not applicable

1= Used by a single specialist 2= Used by several specialists

3= Used by virtually everyone in the marketing

department

L 3 PERVASIVENESS – WEBSITE Ordinal 0= Not used/ not applicable 1= Used by a single specialist

2= Used by several specialists

3= Used by virtually everyone in the marketing department

M 3 PERVASIVENESS – MARKETING

AUTOMATION

Ordinal 0= Not used/ not applicable

1= Used by a single specialist

2= Used by several specialists 3= Used by virtually everyone in the marketing

department

N 3 PERVASIVENESS – MARKETING INTELLIGENCE

Ordinal 0= Not used/ not applicable 1= Used by a single specialist

2= Used by several specialists

3= Used by virtually everyone in the marketing department

O 3 PERVASIVENESS – MRM Ordinal 0= Not used/ not applicable

1= Used by a single specialist

2= Used by several specialists 3= Used by virtually everyone in the marketing

department

P 4 SPENDING Ordinal 4= technology spending has increased significantly 3= technology spending has increased about the

same as other expenditures

2= technology spending has declined slightly

1= technology spending has declined significantly BLANK = not sure/can't say

Q 5 DEPARTMENT SIZE Ordinal 1 = 1 – 5 employees in Marketing

2 = 6 – 10 employees in Marketing 3= 11 – 25 employees in Marketing

4 = 26 – 50 employees in Marketing

5= 51 – 100 employees in Marketing 6 = more than 100 employees in Marketing

BLANK = not sure/can’t say

R 6 ORGANIZATION SIZE Ordinal 1 = 1 – 10 employees worldwide

2= 11 - 100 employees worldwide 3= 101 – 500 employees worldwide

4= 501 – 1000 employees worldwide

5= more than 1000 employees worldwide BLANK = not sure/can’t say

S 7 FUNCTIONAL Nominal 1 = checked

0= unchecked

T 7 MATRIX

Nominal 1 = checked 0= unchecked

U 7 DIVISIONAL

Nominal 1 = checked

0= unchecked

V 8 RIGID_JOB_DEFINITION Ordinal 1 = very seldom 2 = occasionally

3 = frequently

W 9 JOB_ROTATION Ordinal 1 = very seldom 2 = occasionally

3 = frequently

X 10 INTERNAL_TRANSFER Ordinal 1 = very seldom

2 = occasionally 3 = frequently

Y 11 FORMAL_TEAMS Ordinal 1 = very seldom

2 = occasionally 3 = frequently

LAGUË 53


Z 12 POLICIES Ordinal 1= Specialists tend to follow detailed written

policies and procedures in most areas 2= Specialists follow written policies and

procedures in some areas, but use their own

judgment and peer advice in many others

3= Specialists rely almost exclusively on their own experience, judgment and peers to guide them

AA 13 PARTICIPATIVE_LEADERSHIP

Ordinal 1= top management would likely decide on

appropriate corrective action 2 = top management would likely consult the

department, then decide on appropriate

corrective action 3 = top management would likely let the

department decide on appropriate corrective

action

AB 14 PERFORMANCE_EVAL Ordinal 1 = employees are informally monitored for their effective use of technology

2 = employees have formal performance targets

for their use of technology, but these are minor relative to other performance targets

3= employees have formal performance targets

for their use of technology, and these constitute a significant part of their total performance reviews

AC 15 OUTSOURCING Ordinal 3 = Our marketing staff relies almost entirely on

outside help to operate our technology systems

2 = Our marketing staff operates our technology systems with some outside help

1 = Our marketing staff operates our technology

systems with little to no outside help

AD 17 TARGET MARKET Nominal 1 = We primarily sell to Businesses (incl. non-

profits, government, non-government

organizations, etc.)

2 = We primarily sell to Consumers

AE 18 RESPONDENT JOB LEVEL Nominal 1 = Specialist

2 = Supervisor/manager

3 = Director/executive 4 = Contractor/consultant

BLANK = Other

AF 19 RESPONDENT TENURE Nominal 4 = More than 24 months 3 = Between 7 and 24 months

2 = Between 1 and 6 months

1 = Less than 1 month

0 = Not employed

AG 16 INDUSTRY Nominal (tba)

AH 20 IMPACT Text Capture

AI 21 COMMENTS Text Capture

AJ 22 CONTACT ME Text 0 = No 1 = Yes

AK 23 WEBINAR Text 0 = No

1 = Yes

Documents

Fitting Marketing Organization Structure to Emerging …dtpr.lib.athabascau.ca/action/download.php?filename=mba... · 2018-04-13 · APPLIED PROJECT: FITTING MARKETING ... enrichment,