A MASTER’S THESIS SUMITTED TO THE FAULTY OF · This study aims at examining the cost component of project analysis with respect to the strategic budgeting and decision making process

TIME COST COMPONENT OF PROJECT ANALYSIS 1

Time Cost Component of Project Analysis

By

Clark C. Lowe

A MASTER’S THESIS SUBMITTED TO THE FACULTY OF

THE SCHOOL OF BUSINESS, MERCY COLLEGE

IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF BUSINESS

ADMINISTRATION

JULY 2013

EDITED JUNE 2015


Table of Contents

Abstract 4

Acknowledgement 5

Dedication 7

Chapter 1 Introduction 8

Background 9

Problem Statement 12

Purpose and Significance 12

Research Questions and Hypothesis 13

Definition of Terms 14

Assumptions and Limitations 15

Chapter 2 Literature Review 20

Definition of Variables 21

Major Themes in Literature 23

Contextual review 29

Chapter 3 Methodology 35

Research Design 36

Data Collection 36

Appropriateness of Design 38

Sample and Scope 38

Validity and Reliability 39


Table of Contents

Chapter 4 Data 41

Process in Action 42

Method of Analysis 49

Findings 50

Chapter 5 Conclusions and Implications 52

Research Question Conclusions 53

General Conclusions 54

Implications 55

Recommendations 55

Further Study 56

References 60


Abstract

This study aims at examining the cost component of project analysis with respect to the

strategic budgeting and decision making process within corporate enterprises. This work

suggests the decision making and execution processes and cycles can be evaluated as cost

components of project analysis frameworks. If the decision making process can be executed in

a shorter period of time, unrealized gains in revenue or cost savings could then be realized

altering many of the risk frameworks and profiles enterprises currently use. The study examines

data provided by a 2012 Fortune 25 company that spans a diverse girth of cultures, industries,

and business units. The corporation donating the data, names of the projects and the actual

dollar figures used are concealed due to the extremely propriety nature of the data and

possible negative market implications of the data.


Acknowledgement

This study could not have taken place without the key inputs of people around me who

continue to see value in me beyond what I have proven. The importance to grow, mature, and

learn has always been a lifelong evolution for me. I have always encouraged those I lead to

become bigger thinkers as have those who have always lead me and impressed upon my life in

a positive way. Specifically, I would like to acknowledge the following for having profound

impacts on this work, my life and leadership styles:

Dr. Thomas Coughlan – For the always open ears and mind as I discuss the many crazy

ideas I present and want to pursue. For the encouragement provided in completing this

thesis.

Dr. Gilda Carle – Timely advice and observation of my skills and willingness to challenge

me beyond my current state.

Dr. Raymond Manganelli – For having the confidence in me to lead in the capacity I do

and for taking the time in mentoring my thinking, analysis and decision making

frameworks.

Manual Ron – For providing the contexts necessary in winning at both business and life.

I will never forget and will always remain in debt to the risk and leadership frameworks

you have provided me.

Maureen Cross – For providing candid feedback and being a second set of meticulous

eyes on projects, papers and resumes.


Chris Murphy and Lousette Cabrera – For teaching me the importance of focusing on

family and understanding how strength in family can relate to strength in academics and

career.

Steve Nilsen – For being a wonderful student which has expanded and developed my

own leadership skills and thoughts.

Danielle Van De Weert – For the thankless work you’ve done as a partner, friend and

mother to Avery. For supporting my long days in pursuit of my degree, the work on this

study and development of my business.

Darleen McAdoo – For being a courageous mother always willing to assert a son’s

humility when he grows too confident for his own good.

Lastly a warm thanks to the Strategic Consulting Institute, Mercy College and the entire

teaching staff who have given me an amazing perspective on business and education. Thanks

for the opportunities to express myself in ways that have allowed me to grow without

restrictions. Thanks for making the quality of my education your personal concern. I’m

appreciative for the endowment Mercy College has offered me for my success through

education and hands on learning.


Dedication

I’d like to dedicate this study to my father who always insisted I develop my brain over brawn,

remain a man of integrity, and always work hard.

RIP: Kenneth Ray Lowe

I’d also like to dedicate this work to my mother who has been a voice of determination in me

following my dreams and capitalizing on opportunities even if she didn’t agree.

Thanks: Darleen McAdoo

Lastly, I want to dedicate this to my children Hannah, Hayden and Avery who mean the world to

me. I hope this work signifies the importance of education, setting lofty goals, and finding the

resolute ambition required to succeed.


Chapter 1

Introduction


Chapter 1: Introduction

The introduction will lightly cover some background information and move into the

meat of what this study covers through problem statement, research questions and hypothesis.

This chapter should build a foundation into the topics that will be discussed in this study and

provide some relevant background information and premises on which the study is conducted.

Likely the most important portion of this chapter is towards the end where assumptions and

limitations of the study are discussed. Assumptions and limitations create the environment in

which this study is conducted. Specifically, the limitations highlight areas in which the study

may not be applicable.

Background

In the corporate arena, many organizations have portfolios of competing projects,

initiatives, and/or acquisitions that shape a portion of the strategic framework. Initiatives can

be comprised of, but is not limited to projects that relate to operations, information

technology, company acquisitions, distribution and logistics, sales, customer service or

satisfaction, procurement, real-estate, and human resources. Due to rapid changes in

technology and social and business trends, project benefits and horizons are evaluated on

shorter cycles. Specifically, the mismatch between economic and budgeting cycles, with project

analysis cycles present a complexity of contending urgencies within the corporate arena

("Playing to Win," 2012).

The corporate valuation process of projects has maintained the same principles for

decades. The academic foundations of net present value (NPV), internal rate of return (IRR) and

payback, have largely stayed the same. These evaluation techniques are found in most project


management and evaluation textbooks used by practitioners and academics alike. These

processes use forecasted cash flows and a discount rate in order to evaluate the profitability of

a project (Truett & Truett, 2004). Enterprises then compare the results of these models to

hurdle rates and key leaders decide the fate of these projects. These processes often differ

among corporate bodies and the tools they use are proprietary.

In deciding on a project, a predominant portion of the process begins with decision

theory. In most corporate arenas, Schelling’s Game Theory is the predominant driver of

decisions. While game theory is not the only driver in decisions being made, large strategic

decisions, either intentionally or inadvertently, align with the principles of game theory. In

simple connotation, game theory simple exercises the thought of “how will my competitor

[industry, market, etc.] react to the decision about to be made.” Those assumptions or

predictions of the reaction may have an impact on the decision, execution and/or process in

which the project is delivered (Baniak & Dubina, 2012; Dodge, 2012). Game theory is not the

sole influence on decisions. Finkelstein, Hambrick and Cannella (2009) discuss the intangibles

executives face when making decisions. With respect to hierarchical decision making, Kang

(2010) discerns the impacts organizational structure has on decisions.

Image theory accounts for aspects of personal image or brand and how decisions may

influence image. Image theory is another driver in the corporate decision making process.

(Kuehn, 2009). Lastly, prospect and economic theory also pair nicely in the arena of corporate

decisions. Prospect and economic theory simply state that decisions are based on the economic

gains or losses and not on the final outcome of a project (Paulson, 2009).


Risk is a sensitive subject in nearly all organizations. Some organizations have an

extraordinary appetite for risk while others are extremely risk averse. Like the project analysis

process, although much less precise, all organizations have a process which assess and measure

risk. The ideas and philosophies with respect to risk management will vary greatly among

organizations, academic texts, and personal beliefs. Risk is one of the areas in which corporate

leaders vary the most. Only one thing is certain and remains a consensus among enterprises:

risk must be evaluated and managed. The “how” this is done among corporate organizations is,

again, often proprietary information. Key principles of risk such as value (Wallis, 2012),

relationships between risk management and strategic planning (Kelly, 2012), quantifying risk

(Hampton, 2009) and individual bias (Achampong, 2010) outline some probable assumptions

with respect to risk and how companies evaluate, understand and accept risk.

Time is an age old principle in business that can be both an inhibitor and component of

success. Time value of money is a widely accepted principle and it should be noted, that further

exploration of this concept with regards to this study will only strengthen the position of the

study. Also the variations in which time value of money can be calculated and the realized gains

are too broad for this study. The important thing is to note that time value of money has not

been figured into any cost savings or revenue generation in the analysis that follows in this

work.

This study will aim to put these three concepts together, risk, project evaluation and

time to develop a new perspective on how projects are evaluated in today’s corporate arena. In

“Playing to Win”, 2012, Research-Technology Management’s interview with William Banholzer,

the Chief Technology Officer for The Dow Chemical Company, asserts that understanding the


competing priorities between business, planning and execution cycles is necessary to maintain

competitive in the current global landscape.

Problem Statement

Competing priorities between being strategic while developing competitive advantage

have led companies to lengthy processes ensuring everything is covered from risk, financials

and frameworks to execution, manpower, and expectations. Many organizations place little or

no value in the decision making process from a risk, economic cost, or competitive advantage

perspective. In essence, many companies measure their projects with a micrometer, mark them

with a crayon and cut with an axe.

While some studies and literature exists on all parts of the problem (risk, budgeting,

execution, decision theory, project management, etc.), a major deficiency in literature exists in

tying the fourth dimension, time, into the process. Time both possesses an economic cost and

an opportunity for creating strategic advantage. Strategy is no longer defined plans over

decades rather short term focuses that maximize competitive advantage over the short term in

an attempt to tie short term efforts into long term results.

Statement of Purpose

The purpose of this study is to quantify the decision making process and how this

process can potentially negatively and positively affect project assessment. The study will try to

tie time, risk and the decision making process together and provide recommendations on how

to optimize the decision making process in order to maximize potential for returns on

investments on corporate initiatives. The purpose of this study is also to create profound


evidence that the most important part of project and initiative evaluation may not lie in the

execution or the idea, but the process in which projects are decided.

Significance

The significance of this thesis is to ascertain significant quantifiable data to associate the

consequences (positive or negative) of the decision making process with respect to the true

economic costs of an initiative by percentage of cash flows. The actions taken out of this study

is for corporations and stakeholders to evaluate decision making processes and associate the

costs and risks. Companies that are able to shorten decision horizons will find significant

advantage over their competitors through strategic agility. The significance of the decision

making process can be argued in the fact that the difference between a project that generates

significant revenue and one that does not, can be determined simply by time. Time has the

ability to differentiate between a great idea changing the course of a company forever, and an

average idea yielding mediocre results. In the shortened playing field and time horizons of

strategic business in the 21st century, time has become the most valuable component of the

decision making process.

Research Questions

The research of this study will be aimed at answering three questions that develop a

quantitative understanding of how the decision making process affects the costs and revenues

of initiatives.

1. What are the impacts on Net Present Value (NPV) of the decision making process?


2. What would the impacts to NPV be if the decision making process were shorter?

3. In aggregate, how would a portfolio of projects change given a shorter decision

making process?

Hypothesizes

Hypothesis 1: The decision making process will have a significant impact on the NPV of a

project or initiative.

Hypothesis 2: A shorter decision making process will lead to larger realizations of NPV.

Hypothesis 3: A shorter decision making process will impact a portfolio of assets in a

positive way.

Definition of Terms

Some common terms are used throughout the study and may pose a different meaning

based on the readers’ backgrounds, industries of employment, and levels of education.

Common terms throughout this work are defined in order to maintain the clarity and integrity

of the message.

Cash flow(s) – The future revenues projected to be realized in a project or initiative.

Decision horizon – The time it takes for a project to be initiated until the first cash flow is

realized.

Decision making process [model] – The procedure in which all projects are evaluated,

accepted or rejected, budgeted, developed and deployed.


Economic cost(s) – The potential cost(s) realized or saved due to some lapse of time.

Economic revenue(s) – The potential revenue(s) gained or lost due to some lapse of

time.

Project [initiative] – A proposed venture in order to generate revenue (internal or

external) or cut costs within a company. A project can generate revenues or cut

costs in any organizational unit. A project could also improve an existing process,

develop a new process or be a product or service.

Strategic Agility – The time it takes an organization to reach a decision and the

availability for a member of management to make a decision.

Assumptions

Assumptions are generated within the study to generate a baseline framework in which

decisions are made. Recognition exists that all companies have different processes and models

for evaluating, budgeting, measuring, and comparing initiatives. For many assumptions, these

differences in processes carry no impact because the end result is the measured amount of

time it takes to complete a task. For instance, the time it takes an organization to initiate,

choose, fund and execute a project does not matter because all this study focuses on is the

start to finish time of six months.

The assumptions outlined in this study have much to do with experience, normal

strategic and fiscal patterns many companies exercise, and an understanding of popular

decision theory models that will be covered in more detail during the literature review. The


following assumptions are made for the integrity and congruence of this study’s message to

translate well to all organizations regardless of the types of initiatives or the process used in

evaluating them. The following assumptions should be maintained throughout the rest of this

study:

There are four quarters in a fiscal year and many companies close books and

measure success quarterly.

Companies meet and convene to discuss large scale planning for budgetary purposes

once a year to outline next year’s budget goals.

The average time it takes a company to create, execute and deploy, (meaning the

time it takes to generate the first real cash flows) a project or initiative, is six months

(this is my definition of the cost of execution).

The timeframe of measuring the success of a project and the lasting impacts of the

project are limited to about three to five years.

The tools to measure the validity of most projects are Net Present Value (NPV),

Internal Rate of Return (IRR), and Modified Internal Rate of Return (MIRR), and

Payback methods.

Specific “hurdle rates” companies often have are not taken into consideration (this

study solely focuses on the processes as “hurdle rates” are largely proprietary

philosophy of an organization).


Every project is weighted equally as having significant importance to the

organization (meaning a project is not listed as vital to the success of an

organizations strategic success… obviously these types of projects will precede any

discussion around discretionary budget dollars).

The money used to fund the projects is of a capital budget nature where a certain

risk profile and asset portfolio are created – Not all projects or initiatives are funded

but some processes exists to extrapolate those that are and are not funded.

Project analysis and modeling happens in multiple business units, across multiple

planes of an organizational hierarchy.

The benefits of a project can be measured (either implicitly or explicitly – this can,

and is often done, through speculative cash flows).

Benefits of the project can be a combination of external revenue, internal revenue

or cost savings.

All dollars (revenue or cost, internal or external) are created equal (this may not be

the case in all organizations and would add another layer of complexity).

Time value of money does exist for every company but is not needed or computed

for the generalization of this study

Limitations

This study has some limitations and may not translate well to all businesses across all

industries. Limitations also exist in the availability of project data of companies across multiple


industries. As the principles of NPV, IRR, MIRR and payback all hold true across all industries,

the principles and frameworks outlined in this study will also hold true. However, like there are

limitations to the aforementioned valuation methods, the framework of this study has the

following limitations as perceived at the time of the study:

The framework does not transfer well with projects extremely long in nature or

projects that may have large amounts of research and development expense over

the course of many years. An example of this may be a pharmaceutical project that

may require five years of research and development to come up with the product

then another five years to test that product and get Food and Drug Administration

approval.

This study does not take into account the appreciation of assets. For instance, if an

initiative could be sold at a later date due to intellectual property patents. This

would vary greatly among organizations and is an estimation at best.

The study places a value on time that is equivalent to forecasted cash flows. The

value of time is different for every organization, however, in order to maintain

consistency, time is valued at the projected cash flow rates of a project.

The study does not compute the time value of money. The study is done under the

fact that a time value of money exists for every company.

Projects with over three to five years of cash flows do not fit into this framework. For

instance, the evaluation of buying a Boeing 747 or a huge real estate project (may have cash

flows that extend over 30 or 40 years). In extremely long term projects, a few quarters of a


decision making process have limited impact to the decision analysis of a project. Because

longer projects often forecast cash flows well over five years, the impacts of the decision

making process are absorbed more efficiently.


Chapter 2

Literature Review


Chapter 2: Literature Review

Definition of Variables

The study uses a variety of variables in order to evaluate the projects. Many of the

variables are independent to a project or initiative. The independent and dependent variables

are used to generalize conclusions across a wide variety of initiatives. The table below outlines

and defines the independent and dependent variables used.

Independent Variables

Variable Definition

Benefits The expected generation of a revenue or cost savings in a given quarter.

Net Present Value The Net Present Value (NPV) of the project

Cost Total cost (development, maintenance, materials, etc.) of the project

Dependent Variables

Variable Definition

Decision Cost The cost of the decision making process expressed as a loss of benefits.

Decision Cost Impact The impact of the decision making process expressed as a percentage of the cost.

Lost Value Value of unrealized benefits due to the decision making process.

Table 1

The independent variables are those that are related to each project as a measure of

the initiatives’ worth. Independent variables are those as estimated by doing the necessary

research for any project. The actual process of researching the impact of each of the variables is

not covered in this study and differs greatly among organizations. However the end value is

reached is regardless to the framework of this study. Also, the time to research these projects is

not considered in this thesis as this is a given cost for any project or initiative. However, some

discussion should be generated around any process consuming time as a resource to find or

negotiate ways to streamline this process. The estimations provided with regards to the


independent variables can be researched and proven in a relatively short period in most

business cases. The calculations for NPV and IRR do not follow any specific form and the

discount rates used are regardless of the results. While the value of NPV and IRR may change,

the percentage of change in the dependent variables will remain constant. Thus, the individual

rates used and values of cash flows are not determinates of the concept this work is seeking to

prove. Each enterprise will have a proprietary system in generating cash flows and interest

rates but the impact of the decision making process will remain the same.

The important notion to understand with respect to the independent variables, is the

computations of NPV and IRR will change from company to company but the philosophical

framework behind the execution of the initiatives will remain constant. To be clear, the value of

benefits, NPV, IRR and cost only mater in the respect as it pertains to a single initiative. Many of

the resulting dependent variables are all percentage based so the framework works on an

infinite array of independent variable values to outline the resulting theories and scopes within

the study.

The dependent variables are then calculated and manipulated using the independent

variables. Keeping the assumptions and limitations outlined in Chapter One in mind, the

dependent variables are all calculated based on the same weight and will be outlined further in

depth in the following sections. The dependent variables seek to create an understanding of the

value of time (different from time value of money) and equates this value of time as a cost

component of the project. For example, if a company takes one year to evaluate a project with

a lifespan of three years, then you could equivocate 25 percent of the cost of the original

project to the decision making process. In short, this study aims to quantify the decision making


process as an original cost of the project because the decision making process is a variable in

which cost savings and revenue generation can be realized. In the aforementioned example, if

the same company only needed one month to decide on the project, the cost of the decision

making process would be significantly less.

Major themes in literature

Much literature exits on the decision making process, who is involved, how to create

organizational structure around decision making, organizational leadership hierarchies, how to

quantify decisions, and the like. What no study has looked at is the cost of the actual decision

making process itself as a component of the total cost of a project. This piece of the puzzle can

drastically change the risk profile and frameworks of many projects. As strategic agility,

innovation and speed to market continue to be economic drivers in the current globalized

economy, the decision making process has become an equitable component of all tactical and

strategic processes. Before getting into the literature review, a few themes will be highlighted

here from a high level and will encompass the general thoughts of all works cited.

Decision theory

The overarching theme in decision theory that extends from behavior to economics to

project analysis and management is game theory. The framework in which this theory is applied

depends largely on the industry a company is associated and the impact on that industry they

have. Game theory has minimal relevance in perfectly competitive industries where many small

companies compete in a finite pool of resources and become more profound as the scale of

business increases. Large organizations such as Wal-Mart and Target make decisions that align


extremely well in game theory as they are true competitors in their market and industries. In

the last decade, the most prolific examples are the release of iTunes and the iPod.

While game theory remains at the heart of all decision making regardless of company or

industry, economic principles of analyzing potential projects still exist in quantifying where in

the framework of the decision a project rests. Net present value (NPV), internal rate of return

(IRR), and payback are all modules used to calculate the value of a project or initiative. What

these economic principles do is generate a risk profile in which the cost and returns are

compared and company weighs the benefits and then decides whether or not to accept the

project and associated risks. In the simple diagram below, the high level decision making

process is outlined and this is largely true for all companies. While each company may have a

different process or framework to evaluate value and the decision hierarchy may look wildly

different, every piece of the decision making process will fall into one of the following

categories:

Relationships of Frameworks

Figure 1

In understanding figure 1, the process is left to right and the top buckets drive initiation

and execution of the buckets underneath. For instance, company ethos will generate idea

Idea creation

Valuation Risk Decision Execution

TIME

Company Ethos Internal Processes Decision Theory Constraints


creation and part of the valuation process. A company focused on innovation will be seeking to

create new ideas and innovate which then has an impact on the valuation process. A different

company may focus on improving existing products which will lead to a different idea creation

and valuation process. Then internal processes kick in and begin speculating on value and risk.

These internal processes are almost always unique and proprietary to a company. Then the

frameworks of decision theory drive the decision. This internal conversation around how this

new or improved product will be responded to by competitors and consumers. Finally,

constraints will either allow a project to be accepted or rejected. Constraints often involve

resources (such as money, time and people) but can extend into other areas such as short and

long term strategy, perception, industry trends, etc.

Risk management

Risk management varies among enterprises and how risk is assessed and managed

depends on the tactical and strategic positioning of the organization. The basic framework of

risk is the same for all companies and the perception of risk among the leaders of a company

plays a large role in risk analysis. Each person analyzes risk differently based on a multitude of

factors including but not limited to life and work experience, professional and political beliefs,

ethics, vision, and innate generational attitude and leadership differences. An entire study

could be conducted on how risk is treated through different generations, personality types,

genders, race, upbringing, social status, and the like.

Every risk analysis follows this simple framework although the components and analysis

may be extremely complex. For the purpose of this study, only an overall understanding of the

risk architecture is necessary. An abundance of literature does exist for every point in the risk


matrix. A key component to keep in mind is, in the last 10 years, the idea and perception of risk

has changed drastically. Depending on the industry, companies may or may not have the same

level of emphasis on risk and reward. Due to the financial collapse of 2006 to 2008, many

companies have revisited their risk analysis processes and built constraints to prevent future

market failures. Constraining the risk process is a double edged sword as this theory has also

seen businesses go bankrupt. The necessity of risk in the market place is essential to the life of

Western economies.

Below is a simple version of a risk framework. Again, each piece may have a dedicated

process within a firm and the complexity of that process will change.

Risk Framework

Figure 2

In figure 2 above, one can understand how the risk process works with the

organizational hierarchy to get information from the bottom to decision makers at the top.

Info

rmat

ion

Tim

e

Organizational

Hierarchy


Depending on the organization, this process can be a quick straight forward process where

ideas go through a quick cascade of models and a decision is made, or extremely complex

where every box in the model has an owner and at the top of the process are a group of

decision makers that collaborate in making a decision. Again, time becomes a component and

cost within the process. Time can be present both as a cost and as a means of revenue

generation.

Time

A common phrase exists in business: “time is money.” The principle is derived from the

academic scope around time value of money. Essentially, the shorter the process or transaction

or the shortest time in which money is recognized or costs are saved, the better. Time is

extremely important in business especially as the global economy evolves and more businesses

are placing emphasis on speed to market and innovation. The overarching theme around time

is the same regardless as to what business context you read, less time, more profit.

The competing priority is that some perception exists that time can help delude risk. For

instance, due diligence that is completed in a week versus a month, some perception that

decision makers may have is that the project completed over a month will be much more

robust than those due diligence projects completed in a week. However, the question this study

asks is: “What if, a vast majority of the time, both types of analysis comes up with the same

answer?” It would be much more profitable to come to the same conclusion in a shorter period

of time. Shortening time will often alter the risk profile as discussed above. If decisions are

made quicker, companies may be willing to alter their risk profiles to account for some of the

savings of shorter process. A shorter process does not mean being less accurate or incomplete,


rather focus on those pieces of the process that add the most value in the quickest manner

possible.

Putting the pieces together

Understanding how decision theory, risk management and time all effect each other is

essential in building (or rebuilding) business processes to encompass the most value.

Associating a cost or revenue to the time it takes to get a proposed project from infant stages

to a profitable adulthood is a revolutionary thought. Much of literature dives into each of these

components on their own, but nothing develops an understanding of how cost may begin to

highlight proposals in a different, more colorful light. A simple value equation would look

something like this:

Projected cash flows – cost of time = true value

In the figure below, the equation will be broken down to encompass the three

overarching themes (decision theory, risk analysis and time) discussed above. Each theme has a

role to play in the entire process and each part of the process is considered critical (meaning an

entire role may not be removed to save time).

Value Equation

Figure 3

Cost and Execution

Initiation and

valuation Risk analysis

Decision

process

End to end

process

Projected cash flows (over X time periods)

End to end process time (over Y time

periods) Project Gains

TOTAL TIME


The visualization of the above model sheds some light on why many projects are

evaluated over a five year time period. Decades ago, during the era of conglomerates of the

1950’s and 1960’s, the strategic horizon may extend over 10 to 15 years, thus, further the roles

of project gains. The longer the scope of the project, the less impact the pieces of the end to

end process play on the cost of the project. As the decision horizon in the corporate world

continues to move closer to today, companies are finding that the time horizon on strategic

decisions may only be three to five years. Does it make sense to take 18 months to make a

decision that may only last three years? This area is where enterprises have significant updating

to do with respect to current processes and also where significant value and competitive

advantage can be obtained. Generally speaking, the cost and execution of a project is fairly

inelastic, but the process in which a decision is made is where the opportunity lies.

Contextual Review

The contextual review will cover two main topics: decision theory and risk. The

contextual review is designed to provide some background from stated sources that will

provide additional information to supplement the background information found in Chapter 1.

This review is a narrative that dives into more profound information from the sources. While

each of the sources has more in depth information, this section pulls the most pertinent

information for this study with keeping the assumptions and limitations in mind.

Decision Theory

Introduction to decision theory

Decision theory has a long lineage dating back to the beginning of mankind when

caveman had to make a decision on where to live, what to eat and how to sustain. The modern


ideas of decision can be described as eccentric mathematical models that vary in perception

depending on the researcher. The frameworks in which these theories work are generally the

same: a cause and effect bombardment of corporate decision making for competitive

advantage and industry position. For that point, the most relevant decision theory is game

theory (Buchanan & O’Connell, 2006).

The basics

Dodge (2012) showcases Schelling’s Nobel Laureate awarding winning work in

economics with respect to game theory and application. Dodge covers the foundations of game

theory and how organizations interact with each other both in the same industry and across

different industries. The themed concept is that no decision can be made without the

consideration of what competition will do in response to that decision. Like a large game of

organizational chess, this form of decision theory takes on huge act and react responses and

translates well on a large strategic scope. Within the scope of project evaluation, game theory

brings an interesting twist in rationally choosing one project over another.

Baniak and Dubina (2012) build a comprehensive review of game theory and the

impacts on the innovation process. Baniak and Dubina also discuss a varying degrees of

organizational interactions including how game theory applies to strategic competition and

cooperation. The main impacts develop the necessity for decision theory and how impacts of

innovation and business trends can be analyzed. Most notably, the authors dive into an

elaborate discussion on game theory and innovation. This is especially relevant given the global

condition of the economic and competitive world today where innovation has enormous

leverage.


A strategic perspective exists when making decisions. Many boards and executives have

a myriad of priorities when making decisions from organizational focus to shareholder

profitability. These decisions also have an intangible avenue that is difficult to measure.

Finkelstein, Hambrick and Cannella assert that an organization’s success or failure can be traced

back the actions or inactions of the organizations executives, top management teams and

boards of directors. Their work dives into the intangible areas of decision making such as

company ethos and aversion to risk and how these areas may impact strategy and success. The

authors also dive into less noteworthy areas such as business fatigue, social connections,

personality, and experiences, to name a few (Finklestein, Hambrick & Canell, 2009).

Tougher to measure

Decisions often depend on an individual’s appetite for risk. Individual perspectives to

risk essentially become the organizations acceptance towards risk. Many factors exist towards

the acceptance or aversion to risk. One study theorizes that children will assume more risk than

adults. This study adds some creative thought in the world of decision making and risk doing a

nice job tying the two subjects together. This may also lead to why organizations experience

different risk perspectives depending on the level of management and experience that is

responsible for managing risk (Grieggs, 2010).

With age often comes position, responsibility and influence. Another influence in

decision making can be found inside the hierarchical aspects of an enterprise. In an attempt to

optimize accuracy, organizational focus and innovation, all organizations install a process that

feeds information to the right levels of decision making process. Kang discerns the variation in

decision making and equates these variations to aspects such as a leader’s perceptions of


subordinates and the information they are providing and a view into predictability of human

nature (is someone choosing something because they have done so in the past). This work

breathes more color into the decision making process and help create a distinction that the

process may be as much art as it is science (Kang, 2010).

Kuehn (2009) asserts image theory provides an interesting paradox to decision theory

models. Essentially, image theory asserts that, a vast majority of the time, there are not many

alternatives but only one and the real choice is to either accept or reject that alternative. This

perspective is equally important to game theory in the idea that organizations may not have

alternatives or have the information readily available to fit into game theory. In this case, an

organization will likely accept or reject the alternative based on the merits of the alternative

alone. This devolves away from game theory and has a different strategic perspective.

Paulson (2009) researches prospect and economic theory and how these two theories

may impact individuals (the framework can be paralleled to the enterprise level). Paulson

relates prospect theory to economic theory and delves into utility theory, all of which are

relevant to enterprise decision making practices. This article further adds that evaluation

processes for proposals need to be robust covering a multitude of perspectives.

Risk

Introduction to risk analysis

This section of literature review is dedicated to business risk and how companies

identify, understand, process, mitigate, and absorb risk. Tolerance for risk will be different in

each organization. An understanding of how theories around risk affect organizations will help

develop a framework for which the decision horizon can be quantified. Risk is an unavoidable


fact in all facets of business so understanding how generational perceptions differ on risk will

be imperative to understanding why dissimilar generations make the choices they do.

Forming a foundation for risk

Enterprise risk management is how companies quantify risk in order to make business

decisions. Risk may mitigated through research, due diligence, and methodically making

decisions. Each process through measuring, assessing and deciding on an opportunity comes at

a cost. That cost may present itself as an economic cost (market study for example) or as an

opportunity cost (the time it takes to process risk). All of these areas require time and this is a

competing priority in today’s global arena where strategic organizations create competitive

advantage through strategic agility (Hampton 2009). Kelly (2012) asserts that risk should be

assessed in all phases of strategic planning and should align with organizational goals across all

platforms of an organizations.

Value and risk become difficult to measure especially when innovation is in the

discussion. Being able to develop a value proposition and maintain acceptable levels of risk can

be difficult. Wallis (2012) develops an understanding of value around risk management. Wallis

further develops a framework in which the decision horizon operates by quantifying the value

the decision making process has with respect to risk. The process will either add to or take away

from this value.

Achampong (2010) discusses key components to risk management and how risk relates

to strategic planning. The literature also discusses key pieces of risk theory such as SWOT

analysis. An understanding for both internal and external risk factors must exist in order to


understand how those variables may impede strategic planning. The SWOT analysis is a well-

established tool that aids in defining and understanding risk from both an inner and outer

organizational perspective.

Individual bias has an important role in risk management. Connecting personal

philosophy and human traits such as generational and cultural differences and beliefs to the

implications they have on risk management (Blaskovich & Taylor, 2011). Individual bias has a

unique role in a person’s willingness to take on risk. Taleb (2010) discusses highly improbable

events and how they affect the world. Taleb’s thoughts lend well to any section but when

looking at the literature through a risk framework, the book provides perspective around cause

and effect of events. This book both makes the case for and against ventures of great risk with

improbable results.


Chapter 3

Methodology


Chapter 3: Methodology

Research design

The research design evaluates the impacts of the decision making process on the NPV of

a project. The project uses data collected from a 2012 Fortune 25 United States based

company. Due to the nature of the projects, the names have been removed and the company

the data was received will not be named. The data encompasses projects from several

industries and span across all business units (human resources, information technology,

research and development, finance, operations, sales, and more). The data clearly has

limitations because the data is derived from a single organizations, however, it would be

reasonable to make some broad generalizations. The numerical figures of the data have also all

been equally multiplied to maintain integrity and agreement with non-disclosure contracts. The

research and design of the study will primarily talk in percentages to maintain equality of

numbers.

Data collection

The data was received from a 2012 Fortune 25 company (over $100 billion in sales). The

data was received as a table of projects and projected cash flows for either three or five years

(depending on variables of the project and speculated returns). The method in which the cash

flows are calculated and reached are unknown, but the same model was used in calculating all

cash flow value (as well as execution and run time (maintenance) costs of the project). This

portion of the data collection remains proprietary to the company and cannot be disclosed.

However, this process is consistent with nearly all businesses with respect to data collection

and processing for strategic projects. Since all projects went through the same framework, their


cash flows represent actual data the company uses to make high level tactical and strategic

decisions.

Here is a sample piece of data and a walkthrough of what each piece is (the data is

forecasted and repeated for subsequent years by quarter). For evaluation purposes, and

purposes of presentation within the paper, they will be consolidated into yearly cash flows

whenever possible. All value are in millions of United States Dollars.

Table 2

Execute cost – The cost in the first year to execute the project.

Cost under Q# - The run or maintenance cost of the project for that given quarter.

Income under Q# - Projected cash flows (revenue or cost savings) for the given quarter.

Year #:

o Cost – Total cost for the year (during year 1 the execute cost is also added in).

Though this cost may actually accumulate over the assumed six month execution

period, the expense falls into the first year of revenue realization.

o Income – Total income for the year

It should be noted, that beyond the first year, the cash flows are simply figured by subtracting

total cost for the year out of the revenue generation. This represents the yearly cash flow in

figuring net present value (NPV).

Cost Income Cost Income Cost Income Cost Income Cost Income

Project 1 3.65 0.62 1.43 1.46 3.01 1.46 4.71 0.62 6.41 7.82 15.56

Execute

Cost

Q1 Q2 Q3 Q4 Year 1


Appropriateness of the design

The design is relevant to business from both an academic and practiced perspective. All

companies use NPV, IRR, MIRR and/or payback methods to evaluate projects. Although each

company will have a different framework or module to plug data into, the results will yield the

same structure as seen above (obviously of different formats). The model will yield some sort of

cash flows that can be mathematically plugged into NPV, IRR, MIRR and payback calculators

(these calculators also differ among organizations, but the principles on which they are built are

the same). Because enterprises have different discount and interest rates, the results of each

project will be different. For instance, if these cash flows were placed into another companies

NPV tool, the results may look different because of the given variables. For this study, that is

inconsequential because the base of the information is the same.

This design spans across many industries and can take a myriad of projects from

operations to human resources. The reason for the project is not important but the

fundamental implementation of how the decision making process may affect the profitability of

a project is important. This study aims to value the impact of the decision making process on

the Net Present Value of a project.

Sample/Scope

The sample consists of 67 projects currently being considered for funding. This data

does represent that of only one company, however, the company is a significant organization

and the data represents a myriad of cultures and industries. The company operates

internationally across multiple industries and markets. The company also has an unusual variety

of business units which also strengthens the data in a dynamic way.


A unique perspective this data offers is that the data is all analyzed with the same

embodiment of corporate framework. Obtaining data from multiple companies may yield large

discrepancies in how the data was initially handled and presumed cash flows figured. The use of

one, multinational organization with a variety of business units and industries was necessary to

maintain the integrity of the data. While the scope of the data is with one company, the

significance of the company is also important to the validity of the data.

Some projects are international and risks such as exchange rate are not directly

evaluated in this context. The rates are converted to the United States Dollar for evaluation.

Because the data is taken from such a large company impacting many industries, this data is

relevant in speculating the costs of decision making across multiple markets, industries and

business units. Much like the frameworks of NPV, IRR, MIRR and Payback do not change among

markets, industries, and business units, only the decisions based on the results of these tools

will change. This data can and will work across a myriad of businesses both large and small

across a multiple array of markets and industries. As described in the limitations, the thought

processes of this type of project analysis is not designed for large projects that may have large

number of cash flows expected over decades. This sample and scope is limited to those projects

which have a relatively small yet relevant life cycle.

Validity and Reliability

The data is both valid and reliable because the data is real projects being considered by

a large Fortune 25 company. The data is most relevant because the data encompasses the

current business landscape on a global perspective. The data is not limited to a single business

division or unit and the data encompasses an array of projects. The reliability of the data lies in


the fact that many of these projects will go on to be funded ventures by this company in the

coming years. The company is making real time decisions of these projects as these study is

being conducted.


Chapter 4

Data


Chapter 4: Data

Process in action

The following is a walkthrough of the process and manipulation of data in order to reach

the conclusions. Each step will be spelled out in order to provide clarification through the

process and be specific through the handling of the data. Here is another look at Table 2 which

is a view of the initial data.

Figure 2

The original data is in the format as shown above. The data is extended out over 3-5

years as a projection of expected cash flows. When the data is consolidated the following was

formed summarizing the data into yearly cash flows.

Table 3

Notice, the highlighted zeros mean those projects are only analyzed over three years.

This table just summarizes the quarter data into years for ease of evaluation for the next set of

calculations. The negative cash flows on some projects may be an indication that projects are

Cost Income Cost Income Cost Income Cost Income Cost Income

Project 1 3.65 0.62 1.43 1.46 3.01 1.46 4.71 0.62 6.41 7.82 15.56

Execute

Cost

Q1 Q2 Q3 Q4 Year 1


no longer projecting profits or there may be intrinsic or intangible variables of those projects

that make them of intrinsic value versus a hard calculated value. There is no clear indication or

answer for the negative cash flows, but they remained in the data and evaluated. These

happened to be the first 10 projects of the data and other portions of the data will exclude

these “outliers” in projects.

Table 4

In the table above, Net Present Value is calculated. A rate of 5% (0.05) is used as a

baseline for all calculations. This rate should be an easily attainable rate for nearly all

corporations. The specific rate will differ between enterprises and a wide variety of theories

and recommendations exist regarding an applicable rate to use when in doubt. Likely, the most

relevant, many companies use Weight Average Cost of Capital (WACC) as the rate. Other

companies may adjust their rates depending on the business unit or division. These calculations

are very straight forward with no twists. The NPV of each project is stated in the right column.


Logic to continue

At this juncture some logic needs to take place in order to frame the next few

calculations. Currently, for many organization, the execution of the project will look something

like this:

Table 5

The decision cycle includes the time it takes to research, evaluate and decide if a project should

be funded. The execution cycle is the time it takes to initiate the project from ground zero to

recognizing cost savings or revenue generation. In all, the timeline of the projects would look

something like this:

Table 6

In the above table, the decision cycle is added into the cash flows because this is a

substantial portion of the process. This is where this study differs in the evaluation of projects

over other studies and thoughts around Net Present Value. The new costs for the projects begin

to take on a different look once the decision cycle is considered a cost of the project. The cost

of the execution cycle will often stay relatively inelastic because speeding up the process of

execution is often costly. The execution cycle is also much shorter and finding savings in this

cycle can be much more difficult.


Table 7

In the new logic, the decision cycle is greatly shortened, thus cash flows are realized three

quarters earlier. Essentially, over the same period of time, in a five evaluation, you gain three

extra quarters (a 15% gain) in revenue or cost savings. Looking at the decision cycle as a cost

and finding ways to shorten this cycle may provide significant increases in project evaluation. In

order to compute this, the numbers will be calculated in two ways. First, as realizing the entire

decision making cycle as a cost component of net present value. And secondly as realizing an

additional three quarters of revenue as an income and the impacts of the scenario on NPV.

Decision cycle as a cost

In defining the cost of the decision cycle, the first four quarters or revenues are

speculated as cost. These revenues can be thought of as an “opportunity cost” to the decision

making process.

Table 8

Cost Income Cost Income Cost Income Cost Income

Project 1 3.65 0.62 1.43 1.46 3.01 1.46 4.71 0.62 6.41 15.56 23.38

Project 2 5.42 1.48 5.41 2.07 5.41 1.37 6.24 0.75 6.24 23.31 34.39

Project 3 1.11 0.78 0.25 0.28 0.25 0.28 0.25 0.28 0.25 1.00 3.74

Project 4 0.00 0.00 5.07 0.00 6.10 0.00 11.22 0.00 11.57 33.97 33.97

Project 5 8.59 5.01 11.88 4.84 22.57 4.84 35.44 4.84 34.01 103.90 132.02

Project 6 12.21 5.02 2.59 5.25 4.40 5.48 5.24 5.25 8.74 20.98 54.20

Project 7 1.50 0.38 0.70 0.42 1.17 0.45 1.17 0.42 1.63 4.66 7.83

Project 8 6.04 1.94 0.42 2.20 1.04 2.26 9.77 1.99 14.75 25.97 40.41

Project 9 0.74 0.29 3.00 0.30 5.96 0.31 6.17 0.30 7.18 22.31 24.25

Project 10 3.84 0.25 0.90 0.27 0.90 0.29 8.09 0.27 8.09 17.98 22.88

New CostDC Cost

Execute

Cost

Q1 Q2 Q3 Q4

Current

New


In the above table, the “DC Cost” column represents the unrealized revenue gains or

cost savings of Q1 through Q4 and the “New Cost” column encompasses the cost of the

decision making process as well as the execution cost and first year Q1 through Q4 costs of the

project. To look at this idea another way, in order to generate $15.56 million in revenue, the

entire process (decision making and first year run and execute costs) actually cost the project

$23.38 million to generate. In doing this for the first year of realized incomes actually generated

a $7.82 million loss. While the subsequent years would generate a positive revenue, the

decision cycle has impacted the NPV of the project. In taking the new costs into account, the

new calculations for NPV would look like this:

Table 9

The newly figured NPV is significantly less than the original NPV as the costs of the

decision making cycle are now figured into the projects. The following table shows the delta

between the two NPV evaluations and what percentage of the original NPV was lost to the



Table 10

In aggregate, across the entire data set of 67 projects, the difference between these two

net present value calculations was $4.96 billion. This is a significant cost, even over five years,

for a company generating revenues of over $100 billion. This would relate to nearly $1 billion a

year in revenue or cost savings for a company just in the decision making cycle. Again, this

revenue and cost savings do not take time value of money or any reinvestment value into

account.

The new income

In this portion, the same projects will be evaluated with an extra three quarters of

income. Bringing back Table 7, this evaluation will use Q1 as an expense for the decision making

cycle, Q2 and Q3 as execution cycle and use the revenues of Q4, Q5 and Q6 as revenue

components of the NPV evaluation. We then can compare the difference, in this scenario, of

getting through the decision making process three quarters quicker to being realizing revenues

and cost savings earlier in the project life cycle.

NPV

Project 1 44.17 29.34 33.56%

Project 2 67.35 45.15 32.96%

Project 3 -2.91 -3.86 -32.74%

Project 4 140.03 107.68 23.10%

Project 5 345.87 246.92 28.61%

Project 6 -11.22 -31.20 -178.09%

Project 7 6.37 1.93 69.65%

Project 8 66.79 42.06 37.04%

Project 9 86.74 65.49 24.50%

Project 10 61.50 44.37 27.85%

New NPV

% Dec in

NPV


Table 7

In figuring the new NPV based on the new income, the new revenues (Q4 through Q6)

are added to the first year’s income. This will still keep the project ending on the same timeline,

yet add three additional quarters of income to the project. Since the project has already been

executed, the cost for Q4 through Q6 is also taken into account. The following table has the

new calculations:

Table 11

The “Q4-Q6 Revenue” column is the NPV calculation with the newly recognized

revenues of the new execution process. While the decision making process is still seen as a cost,

the cost has been significantly reduced. In Table 12 the differences in the NPV calculations are

listed below.

Q4-Q6

NPV Revenue

Project 1 44.17 29.34 52.25

Project 2 67.35 45.15 74.45

Project 3 -2.91 -3.86 -3.27

Project 4 140.03 107.68 161.41

Project 5 345.87 246.92 404.19

Project 6 -11.22 -31.20 -12.23

Project 7 6.37 1.93 8.08

Project 8 66.79 42.06 83.43

Project 9 86.74 65.49 100.53

Project 10 61.50 44.37 75.36

New NPV

Current

New


Table 12

In aggregate, making a decision in one quarter versus one year would net a $2.63 billion

increase over the original NPV of the projects. This type of revenue generation and cost savings

allows a company to take on a much different risk profile with respect to the decision making

process. In aggregate, the total revenue gains of an optimal decision making and evaluation

process would be worth over $7.5 billion over five years.

Method of analysis

The method of analysis was purely quantitative leaving all qualitative impacts out of the

analysis process. This method uses the traditional Microsoft Excel computation of Net Present

Value at a 5% (0.05) rate. The analysis simply compares what would happen to the NPV of

projects given the circumstances outlined above. An understanding does exist that shortening

decision making cycles may entail an enormous shift in corporate frameworks, budgeting and

accounting practices, and risk profiles. The aim of this study is to provide the framework that

significant value exists in making decisions in an optimal environment where risk profiles are

enhanced to encompass a shorter decision making timeframe.

Q4-Q6 % Inc

NPV Revenue NPV

Project 1 44.17 29.34 33.56% 52.25 18.31%

Project 2 67.35 45.15 32.96% 74.45 10.53%

Project 3 -2.91 -3.86 -32.74% -3.27 12.63%

Project 4 140.03 107.68 23.10% 161.41 15.27%

Project 5 345.87 246.92 28.61% 404.19 16.86%

Project 6 -11.22 -31.20 -178.09% -12.23 8.98%

Project 7 6.37 1.93 69.65% 8.08 26.78%

Project 8 66.79 42.06 37.04% 83.43 24.91%

Project 9 86.74 65.49 24.50% 100.53 15.90%

Project 10 61.50 44.37 27.85% 75.36 22.53%

New NPV

% Dec in

NPV


The method excludes other areas that could be further explored such as time value of

money, speed to market, and competitive advantage; all of which would strengthen the case of

this study. The study also limits the impacts of risk in the evaluation as risk could likely be

argued both for and against this study. An increased appetite for risk would need to exist to

make decisions in shorter timeframe, however, the significant increase in revenues may also

influence this appetite in a positive way.

Findings

The study was extremely conclusive in the idea, that regardless of the project, nature of

the project, costs, revenues or timeframes, the NPV of a project is significantly impacted when

the decision making process is also seen as a cost to the project. In some cases, the decision

making consumed any positive cash flow from the project. This may be an indication as to why

some companies experience negative cash flows within their finances while all numeric

research would suggest positive outcomes. The findings are summarized below and the

conclusions and recommendations will be outlined in the following chapter.


Table 13

As seen above, the original value of the portfolio of projects was $17.45 billion. When

considering the decision making process as a cost, the portfolio decreases nearly $5 billion in

value. When making a decision in one quarter versus one year, the value of the portfolio

increases $2.6 billion in value. One could argue, the long decision cycle costs $7.6 billion in

value of the portfolio. This is a significant opportunity for revenue enhancement among both

Fortune 500 corporations and midsized corporations that have large strategic projects in the

evaluation process.

Q4-Q6 % Inc

NPV Revenue NPV

Project 35 87.42 65.53 25.03% 108.26 23.84%

Project 36 158.76 107.01 32.59% 178.63 12.52%

Project 37 535.59 390.34 27.12% 616.79 15.16%

Project 38 112.94 73.09 35.28% 128.99 14.21%

Project 39 187.30 139.09 25.74% 214.30 14.42%

Project 40 476.23 344.19 27.73% 544.43 14.32%

Project 41 50.48 38.55 23.64% 55.45 9.85%

Project 42 90.98 66.24 27.19% 95.79 5.28%

Project 43 375.75 280.67 25.30% 404.30 7.60%

Project 44 47.21 30.40 35.60% 52.43 11.06%

Project 45 240.04 163.52 31.88% 270.38 12.64%

Project 46 1301.90 956.22 26.55% 1592.11 22.29%

Project 47 453.12 334.19 26.25% 499.53 10.24%

Project 48 42.79 27.57 35.57% 56.14 31.19%

Project 49 21.96 12.29 44.04% 25.41 15.74%

Project 50 120.03 89.33 25.58% 133.32 11.07%

Project 51 60.08 28.59 52.41% 67.37 12.13%

Project 52 603.15 451.87 25.08% 664.92 10.24%

Project 53 1208.98 937.06 22.49% 1337.44 10.63%

Project 54 510.03 375.88 26.30% 628.85 23.30%

Project 55 23.54 -1.20 105.11% 32.35 37.47%

Project 56 272.25 201.77 25.89% 298.67 9.70%

Project 57 2.05 -0.30 114.59% 1.95 -4.76%

Project 58 67.59 43.17 36.13% 80.39 18.94%

Project 59 31.39 -0.63 102.01% 39.99 27.41%

Project 60 253.17 182.76 27.81% 300.23 18.59%

Project 61 18.25 6.60 63.81% 23.05 26.34%

Project 62 -18.78 -24.38 -29.81% -20.59 9.66%

Project 63 302.52 213.09 29.56% 356.76 17.93%

Project 64 138.21 98.70 28.59% 172.68 24.94%

Project 65 445.38 330.25 25.85% 513.18 15.22%

Project 66 1377.77 1031.21 25.15% 1692.93 22.87%

Project 67 77.33 34.52 55.37% 82.28 6.40%

Totals 17451.02 12493.38 28.41% 20081.81 15.08%

New NPV

% Dec in

NPV

Q4-Q6 % Inc

NPV Revenue NPV

Project 1 44.17 29.34 33.56% 52.25 18.31%

Project 2 67.35 45.15 32.96% 74.45 10.53%

Project 3 -2.91 -3.86 -32.74% -3.27 12.63%

Project 4 140.03 107.68 23.10% 161.41 15.27%

Project 5 345.87 246.92 28.61% 404.19 16.86%

Project 6 -11.22 -31.20 -178.09% -12.23 8.98%

Project 7 6.37 1.93 69.65% 8.08 26.78%

Project 8 66.79 42.06 37.04% 83.43 24.91%

Project 9 86.74 65.49 24.50% 100.53 15.90%

Project 10 61.50 44.37 27.85% 75.36 22.53%

Project 11 202.79 140.93 30.50% 242.89 19.78%

Project 12 153.65 99.73 35.09% 166.94 8.65%

Project 13 731.50 478.35 34.61% 799.48 9.29%

Project 14 146.31 59.73 59.18% 207.31 41.69%

Project 15 717.00 542.56 24.33% 792.66 10.55%

Project 16 17.22 10.91 36.65% 20.94 21.60%

Project 17 149.35 113.51 24.00% 170.25 13.99%

Project 18 365.33 200.90 45.01% 422.18 15.56%

Project 19 17.27 10.92 36.73% 22.07 27.81%

Project 20 69.86 45.82 34.41% 86.12 23.29%

Project 21 30.35 17.98 40.76% 35.82 18.03%

Project 22 198.12 144.21 27.21% 219.54 10.81%

Project 23 115.73 84.58 26.91% 136.26 17.74%

Project 24 61.06 40.73 33.29% 65.15 6.69%

Project 25 166.35 127.46 23.38% 138.69 -16.63%

Project 26 86.81 62.69 27.79% 105.69 21.74%

Project 27 363.50 274.05 24.61% 403.30 10.95%

Project 28 17.23 5.52 67.96% 16.23 -5.81%

Project 29 224.34 144.11 35.77% 259.37 15.61%

Project 30 647.07 487.23 24.70% 731.65 13.07%

Project 31 13.18 -0.53 103.99% 9.78 -25.75%

Project 32 681.89 511.75 24.95% 761.34 11.65%

Project 33 488.35 349.60 28.41% 540.25 10.63%

Project 34 1306.67 965.52 26.11% 1534.99 17.47%

New NPV

% Dec in

NPV


Chapter 5

Conclusions and Implications


Chapter 5: Conclusions and Implications

Research questions conclusions

The conclusions for the research questions are interpreted from the data presented in

Chapter 4 as a general theme to the data. Because each project varies in cash flows and

expenses, the conclusions will aim to generalize the study in terms of percentages as an

aggregate portfolio of assets and use specific projects as an example.

What is the impact on Net Present Value (NPV) of the decision making process?

The decision making process negatively impacted (caused the NPV evaluation of the

initiative) to decrease in nearly all instances. While the sample size was limited, the conclusions

came from project across a broad range of industries but each company and industry would be

impacted differently based on the decision making process. On average, the drop in NPV was

28.41%. The largest drop was 114.59% completely taking the project out of profitability (there

were four projects that experienced a 100% or more decline in NPV).

What would the impacts to NPV be if the decision making process were shorter?

The NPV valuation had a positive impact given a shorter decision making process (one

quarter versus one year) in all evaluations. On average, the rise in NPV was 15.08%. The largest

increase was 37.47%. A reasonable conclusion can be made that an equitable portion of a

project’s cost is attributed to the decision making process. Depending on the cost to cash flow

ratio (as well as the rate used) will dictate the economic and opportunity cost of the decision

making process.


In aggregate, how would a portfolio of projects change given a shorter decision making

process?

The initial NPV valuation for all projects was $17.45 billion. Including the decision

making process as an expense, the entire portfolio was now worth $12.49 billion. This equated

to a 28.41% drop in portfolio value. This decrease means it cost this company almost $1 billion

per year to decide on these projects (over a five year time horizon). Under a shorter decision

making process, the same portfolio is worth $20.08 billion. The portfolio experienced a swing of

$7.59 billion in assets done under current decision making process versus a streamlined


General Conclusions

The decision making process has enormous impacts on NPV of the projects and

initiatives being examined. Since many enterprises make decisions based on yearlong cycles,

these general conclusions would suggest that enterprises may have opportunity to generate

increased revenues and cost savings by evaluating their decision making processes. Since the

study does not evaluate items such as speed to market, time value of money, market share

leverage, reinvestment potential and other intrinsic properties of money, the conclusions

would further be amplified through these analysis. This study can make the following general

conclusions under the assumptions and limitations outlined in chapter 1:

When the decision making process is assumed as the cost of a project, the NPV

evaluations experience a decline in value.

A shorter decision making process can lead to economic costs savings and revenues of

significant impact.


The nature of risk profile may change given shorter timelines due to increase in

aggregate portfolio performance.

Implications

The implications of this study may have corporate managers and executives evaluating

the time in which it takes to generate, research, analyze and execute projects. These

implications may also call enterprises to evaluate corporate finance and budgeting structure to

support more dynamic decision making process to support the findings of this thesis. Other

implications may include a review of how decisions are made from a hierarchal perspective and

evaluating the bodies involved during the process. The larger implications lie in enterprises who

are able to adopt shorter decision timelines and realize revenues and cost savings and shift risk

frameworks in a globalized market that reward this type of execution. Lastly, this study implies

that, to a certain degree, a large portion of project expense can be attributed to the decision

making process. While a shorter process may add more revenues, the implications of a shorter

strategic decision timeline may also add intrinsic value found in areas such as speed to market

and competitive advantage.

Recommendations

The recommendations from this study are threefold. While these recommendations

may look different and be executed different from enterprise to enterprise, the importance of

understanding the impacts of a corporation’s decision making process with respect to strategic

project evaluation is critical to success. For this reason, the following recommendations are

made based on the conclusions of the data:


1. Invest time in understanding the decision making process. In many corporations this

process came as a byproduct of the corporate finance and budget models and has gone

unchanged as the basic frameworks in which a corporation was rendered. Invest in

updating these process to flow with what the global economy rewards (speed,

ingenuity, and consistency).

2. Under the notions of game theory and hierarchical decision theory, don’t spend too

much time sizing up the competition. Often times, the largest delay in making project

decisions may be attributed to these areas. Time is money and these competitive

analysis studies in conjunction with the decision making process may not be adding as

much value as perceived.

3. Risk is another area that may be worth observing to see if an enterprise spends too

much time analyzing risk. In this study, the cost of the decision making process was

nearly $1 billion a year. That is an immense cost and risk profiles can be impacted in

large ways through unrealized revenues due to this process.

Further Study

Following study of this thesis could stem in a bunch of different directions. This section

will be framed in questions that compliment this study and may provide added value to the

decisions corporate executives make in regards. The areas this study could be further

broken down into may take two directions: (1) psychological/behavioral and (2) corporate

structure. Further study in other areas may exist, but these two areas will likely provide the

most impact.


Psychological and Behavioral

In this areas, studies could be conducted to answer a few overarching questions with

regards to this study as to why the decision making process exists the way it currently does

(again this would be different for every organization). This type of study would likely be best

conducted within each enterprise to fully grasp how psychological behaviors and attitudes

affect the critical processes of business. To some extent, Myers-Briggs type testing has given

some framework in this area, but specifically to project evaluation and decision making an

extension of the tool could be used. Here are some questions that would need to be

answered from this perspective:

What are the impacts of generational attitudes and experiences on the decision

making process?

How does risk aversion impact the decision making process?

What inherent company history impacts psychological and behavioral decisions?

How do company frameworks and hierarchical lines of communication impact the

decision making process?

Corporate Structure

No doubt exists that a change in strategic decision making timelines may have deep

impacts to corporate frameworks and structure. A large difference between old corporations

and those created in the 21st century, are that the newer corporations have the ability to create

a 21st century business framework that works well with the time in which the company

operates. Older corporations, do not have this commodity and they may be experiencing

friction from decades old frameworks that do not allow a company to operate as efficiently as


necessary to drive a shorter strategic decision making cycle. That being said, a follow on study

would examine the differences of corporate structures and provide insight to the following

areas:

Acquisition performance – Old structure versus new, how do newer companies perform

within larger and older firms once they are acquired? This would indicate the impact

that new business structures have versus those of older businesses. If a business is being

acquired, they are likely performing very well within their own corporate framework

and their performance under an “older” framework would be interesting to analyze.

Financial and budgetary – What impact does finance and budgeting cycles have on

decision making processes? What would need to change within these frameworks to

support a shorter decision making process?

Hierarchical – Does current business hierarchies support a succinct decision making

process? What hierarchical changes need to be made in order to do so? Are these

changes cost saving or revenue generating?

Summary

This study aims to explain the impact of the decision making process has on the

valuation of short term projects when the process is applied as a cost and an economic

opportunity to generate revenue. The study has concluded that opportunity exists in the

decision making process that may be worth further exploration in order to drive new revenues

or realize quicker cost savings. In the data evaluated in this study, the portfolio of assets

realized a 28.41% decline in value when the decision making process was applied as a cost.

Furthermore, a condensed decision making process (one quarter versus four quarters)


increased the valuation of the portfolio 15.08%. The net swing in economic cost was $7.6 billion

for this portfolio of assets. Over a five year span, the cost of project analysis is concluded to be

$1.52 billion or $380 million per quarter.


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Documents

A MASTER’S THESIS SUMITTED TO THE FAULTY OF · This study aims at examining the cost component of project analysis with respect to the strategic budgeting and decision making process