Business Research

If you have ever used the phrase “research shows that…” in an assignment or conversation, you will not be doing this again. Understanding Research Methods helps us to be specific about the research we discuss, and to make sure that research comes from a valid source and was collected and analyzed appropriately. Many surveys are conducted every day throughout the world to prove a particular point, to support an ideological argument, or just to sound authoritative. We hear them and see them in the news media all the time. Some of this “research” is a “vox pop” where someone, often a journalist, has asked a few people in the street their view of a Government policy, or a product or service, or a current crisis. This is quite different from the kind of business research..
In business, and for academic research, the questions we ask must be valid and fair, relating directly to our need for information, in other words our research must have a clear objective purpose, we are not collecting information for its own sake.
We must also collect that information (data) in a fair and systematic way. For example, we should think about who we ask for information, and how they will understand our questions. If we cannot ask everyone involved, then we must be able to justify why we ask only a certain section of that population.
We must also analyze our data with great care in a systematic way. The rigour of our analysis will have a major effect on whether our research results are valid or not. If we are trying to determine which of a range of new technologies to invest in, then it will be very important that we don’t skew our results towards a technology created by someone we know, or that we don’t miss out certain relevant technologies, as these inaccuracies will lead to a poor investment decision.

Global Business Environment

Global  Business Environment
To  date,  our  world  market  is  dominated  mostly  by  many  well  established  global  brands.  Over  the  last  three  decades, there have been a steady trend of global market convergence – the tendency that indigenous markets start converge on a set of similar products or services across the world.  The end-result of the global market convergence is that companies have succeeded on their products or services now have the whole wide world to embrace for their marketing as well as sourcing.

The rationale of global market convergence lies partially in the irreversible growth of global mass media including Internet, TVs, radios, news papers and movies, through which our planet has become truly a small global village. Everybody knows what  everybody  else  is  doing,  and  everyone  wants  the  same  thing  if  it  is  perceived  any  good.  It  also  lies  in  the  rise  of emerging economic powers led by BRICs (Brazil, Russia, India and China), which has significantly improved the living standard and the affordability of millions if not billions of people.
For organizations and their supply chains, the logic of going global is also clearly recognizable from economic perspective. They are merely seeking growth opportunities by expanding their markets to wherever there are more potentials for profit-making;  and  to  wherever  resources  are  cheaper  in  order  to  reduce  the  overall  supply  chain  costs.  Inter-organizational collaborations in technological frontier and market presences in the predominantly non-homogeneous markets can also be the strong drivers behind the scene. 

One can also observe from a more theoretical perspective that the trends of globalization from Adam Smith’s law of “division of  labour”.  A  global  supply  chain  is  destined  to  be  stronger  than  a  local  supply  chain  because  it  takes  the  advantage  of the  International Division of Labor . Surely, the specialization and cooperation in the global scenario yields higher level of economy  than that of any local supply chains. Thus the growth of global supply chain tends to give rise to the need for more coordination between the specialized activities along the supply chain in the global scale.

As  the  newly  appointed  Harvard  Business  School  dean  professor  Nitin  Nohria  said  “If  the  20th  century  is  American’s century,  then  the  21st  century  is  definitely  going  to  be  the  global  century.”  The  shift  of  economic  and  political  powers around  world  is  all  too  visible  and  has  become  much  more  dynamic  and  complex.  But,  one  thing  is  certain  that  there will be significantly and increasingly more participation of diverse industries from all around the world into the global supply chain network; hence bringing in the influences from many emerging economies around the world. Their roles in the globally stretched network of multinational supply chains are going to be pivotal and will lead towards a profoundly changed competitive landscape.

 

Six Sigma Definition

Definition of Six Sigma
Before we study the subject of Six Sigma in any depth, we need to define the term. Perhaps unusually, Six Sigma has 3 distinct elements to its definition:
•     A Measure: A statistical definition of how far a process deviates from perfection.
•     A Target: 3.4 defects per million opportunities.
•     A Philosophy: A long term business strategy focused on the reduction of cost through the reduction of
variability in products and processes.
Accordingly, it is defined in a variety of ways by several authors, but for the purposes of these notes the definition from Pande et al (2000) focused on the more comprehensive philosophy of Six Sigma will be used:
“A comprehensive and flexible system for achieving, sustaining and maximizing business success. Six Sigma is uniquely driven by  close  understanding  of  customer  needs,  disciplined  use  of  facts,  data,  and  statistical  analysis,  and  diligent  attention  to managing, improving, and reinventing business processes.”
A  strong  structure  and  clear  alignment  to  organizational  goals  (particularly  financial)  are  a  key  part  of  the  Six  Sigma approach as defined by Eckes (2001). Leadership is provided by a team of Champions – Senior Champion, Deployment Champion, Project Champion at corporate, unit and department levels respectively supported by a team of experts. The experts are referred to as Black Belts (who work full time on projects at process level to solve critical problems and achieve bottom-line results) and Master Black Belts (who provide mentoring, training and expert support to the Black Belts). Ingle and  Roe  (2001)  note  that  that  this  significant  organizational  structure  can  range  from  4000  Black  Belts  in  a  corporate population of 340,000 in GE to 120 Black Belts in a corporate population of 100,000 in Motorola. Black Belt training is typically 16 –20 weeks in GE and a year in Motorola (Ingle and Roe, 2001), although both are interspersed with projects that bring value to the organization.

Decision Model (Normative)

Normative Decision Model
When beginning a home repair project, it is helpful to have all necessary tools close at hand. It is often advisable to even have extra tools within reach should the project be more complicated than originally thought. The larger the variety of tools in a handyman’s toolbox, the more likely he will be to fix the problems that he encounters.
In a way, a manager is like an organizational handyman. Managers identify and solve many types of problems (e.g., personnel, planning, scheduling, budgeting, technology, operations, facilities, policies, resources, etc.) with the best interests of their organizations in mind. Some problems are straightforward and predictable, and others are more complicated. A good manager, like a good handyman, is able to quickly determine the types of tools that he needs to fix the problems that he encounters.
Sometimes the tools that are needed to solve organizational problems are co-workers and the knowledge, insight, and creativity that they possess. People use the knowledge that they gain from past experiences to define and remedy the problems that they encounter. Knowledge can be gained from direct personal experiences or from the experiences of others. Groups are able to outperform individuals on mental tasks in large part because of the diversity of experiences that members bring to their groups. When the experiences of group members are used to solve problems instead of just those of a single manager, better solutions usually arise. The benefits of group problem solving, however, come with costs—primarily, the time spent by group members away from their normal work responsibilities.
Not all of the decisions that managers make need to be solved with the help of coworkers. Managers can make some decisions with little or no input from workers. Effective managers know when to solicit input from others and when to solve problems by themselves.  The Normative Decision Model, developed by Victor Vroom and his associates, gives explanation to the appropriate level of worker involvement in the decision-making process. Decision acceptance and decision quality drive the model. When it is important that workers buy into and accept the decision, they should be included in the decision-making process. Likewise, when it is important that exceptional and high-quality solutions be developed, more people should be included in the process. Time should also be considered when selecting the appropriate degree of worker involvement—as time available to make decisions decreases, more autocratic decision styles are appropriate. 

The model also describes five decision-making styles that range on a continuum from “autocratic” to “group.” The autocratic style is one where managers make decisions independently and autonomously. The middle dimensions involve the manager collecting relevant information from others, consulting with individual coworkers, and consulting with groups of workers before making decisions. Under the “group” style, managers allow their workers to solve problems. The appropriate decision-making style is dictated by characteristics of the situation—acceptance, quality, and time. Like tools, different decision-making styles are appropriate for different types of problems and skilled managers know when and how to use each of them.

Strategy and Information System

Strategy and Information Systems
Traditionally business organizations are divided into three levels. These are operational, management and strategic  levels. They exist in nearly all businesses irrespective of their size or sector of operations, although in small companies some levels may converge.
At the  operational level  decisions are made to ensure smooth running of operational processes or day-to-day business. At this level it is necessary to oversee that resources are used efficiently, inventory is up to date, production levels are as planned, etc. Decision making at this level requires information almost entirely internal to the company, although it may be extremely detailed and real-time.
Information for decision making at management level has a typical time-frame ranging from weeks to several month or a year. Middle management usually controls medium term scheduling, forecasting and budgeting operations. These rely on internal as well as occasional external information. For instance, setting the quarterly budget requires the knowledge of current expenditure as well as external pricing information.

Senior management will focus on general, or strategic , issues related to overall business development in the long term. At this level decisions tend to relate to issues with long term such as restructuring, major financial investments and other strategic undertakings related to company’s future rather than present. Information necessary for decision making at this level is comprehensively gathered not only from the internal sources of the company itself, but also involves external information, such as data related to economic situation or sectors as a whole.
Businesses that heavily rely on information develop an information strategy to establish how to manage information for business advantage and to comply with government regulations. An Information Strategy  is a planning document usually created at the strategic level by the Chief Information Officer (CIO), possibly together with a Chief Technology Officer (CTO) and IT manager. 
An information strategy is developed to support the overall business strategy of an organization and explains how information should be captured, processed, used and disposed of throughout its life cycle. Although the structure of an information strategy varies from business to business, there are some common areas included in most information strategy.

To provide specific guidelines to their employees, contractors, trading partners and other external stakeholder on the processing, storage and communication of various types of information, business firms usually create an  information policy  document. This document is extremely important when an organization handles security sensitive data or is subject to government guidelines related to information processing. It defines sensitivity levels of information and lists who has access to each level. The aim of the information policy is to make sure that information assets of a company are appropriately protected from threats.

Hoshin Kanri Planning Principles

 Hoshin planning is not a strategic planning tool in itself, but can be thought of as an execution tool for deploying an existing strategic plan throughout the organization, although it can facilitate the strategic planning process. It does depend on having a clear set of objectives articulated by the Chief Executive/Company President. Application of Hoshin Kanri will then translate the strategic intent into required day-to-day actions and behaviours. Hoshin planning principles are formulated around companies knowing what their customers will want in five to ten years, and understanding what needs to be done to meet and exceed all expectations. This requires a planning system that has integrated Deming’s “Plan-Do-Study-Act” language, and activity based on clear long-term thinking. The measurement system needs to be realistic, with a focus on process and results and identification of what’s important. Groups should be aligned with decisions taken by people who have the necessary information. Planning should be integrated with daily activity underpinned by good vertical and cross-functional communication. Finally, everyone in the organization should be involved with planning at local levels, to ensure a significant buy-in to the overall process. Figure 5.3 shows a model of the Hoshin planning system.

The major elements of the model can be summarised as:
•     Five-year vision :  This should include a draft plan by the president and executive group. This is normally an improvement plan based on internal and external obstacles, and revision based on input from all managers
on the draft plan. This enables top management to develop a revised vision that they know will produce the desired action.
•     The one-year plan:  This involves the selection of activities based on feasibility and likelihood of achieving desired results. Ideas are generated from the five-year vision, the environment and ideas based on last year’s performance. The tentative plans are rated against a selection of criteria and a decision made on the best action plans.
•     Deployment to departments: This includes the selection of optimum targets and means. It focuses on the
identification of key implementation items and a consideration of how they can systematically accomplish the
plan. The individual plans developed are evaluated using the criteria that were used for the one-year plans.
•     Detailed implementation:  This is the implementation of the deployment plans. The major focus is on contingency planning. The steps to accomplish the tasks are identified and arranged in order. Things that could go wrong at each stage are listed and appropriate countermeasures selected. The aim here is to achieve a level of self-diagnosis, self-correction and visual presentation of action.
•     Monthly diagnosis:  This is the analysis of things that helped or hindered progress and the activities to benefit from this learning. It focuses attention on the process rather than the target and the root cause rather than the symptoms. Management problems are identified and corrective actions are systematically developed and implemented.
•     President’s annual diagnosis: This is the review of progress to develop activities which will continue to help each manager function at their full potential. The president’s audit focuses on numerical targets, but the major focus is on the process that underlies the results. The job of the president is to make sure that management in each sector of the organization is capable. The annual audit provides that information in summary and in detail.

Hoshin Kanri Planning Principles

 Hoshin planning is not a strategic planning tool in itself, but can be thought of as an execution tool for deploying an existing strategic plan throughout the organization, although it can facilitate the strategic planning process. It does depend on having a clear set of objectives articulated by the Chief Executive/Company President. Application of Hoshin Kanri will then translate the strategic intent into required day-to-day actions and behaviours. Hoshin planning principles are formulated around companies knowing what their customers will want in five to ten years, and understanding what needs to be done to meet and exceed all expectations. This requires a planning system that has integrated Deming’s “Plan-Do-Study-Act” language, and activity based on clear long-term thinking. The measurement system needs to be realistic, with a focus on process and results and identification of what’s important. Groups should be aligned with decisions taken by people who have the necessary information. Planning should be integrated with daily activity underpinned by good vertical and cross-functional communication. Finally, everyone in the organization should be involved with planning at local levels, to ensure a significant buy-in to the overall process. Figure 5.3 shows a model of the Hoshin planning system.

The major elements of the model can be summarised as:
•     Five-year vision :  This should include a draft plan by the president and executive group. This is normally an improvement plan based on internal and external obstacles, and revision based on input from all managers
on the draft plan. This enables top management to develop a revised vision that they know will produce the desired action.
•     The one-year plan:  This involves the selection of activities based on feasibility and likelihood of achieving desired results. Ideas are generated from the five-year vision, the environment and ideas based on last year’s performance. The tentative plans are rated against a selection of criteria and a decision made on the best action plans.
•     Deployment to departments: This includes the selection of optimum targets and means. It focuses on the
identification of key implementation items and a consideration of how they can systematically accomplish the
plan. The individual plans developed are evaluated using the criteria that were used for the one-year plans.
•     Detailed implementation:  This is the implementation of the deployment plans. The major focus is on contingency planning. The steps to accomplish the tasks are identified and arranged in order. Things that could go wrong at each stage are listed and appropriate countermeasures selected. The aim here is to achieve a level of self-diagnosis, self-correction and visual presentation of action.
•     Monthly diagnosis:  This is the analysis of things that helped or hindered progress and the activities to benefit from this learning. It focuses attention on the process rather than the target and the root cause rather than the symptoms. Management problems are identified and corrective actions are systematically developed and implemented.
•     President’s annual diagnosis: This is the review of progress to develop activities which will continue to help each manager function at their full potential. The president’s audit focuses on numerical targets, but the major focus is on the process that underlies the results. The job of the president is to make sure that management in each sector of the organization is capable. The annual audit provides that information in summary and in detail.

Six Sigma

Six Sigma

There are those who will tell you that Six Sigma is radical and new. The fact is that Six Sigma (done properly) is a recognisable evolution of TQM. De Mast (2006) sees it as an on-going phase in the evolution of methods and approaches for quality and efficiency improvement. Six Sigma can be seen as the accumulation of principles and practices developed in management statistics and quality engineering, all of which matured significantly over the course of the Twentieth Century.
The Six Sigma approach was first developed in the late 1980s within a mass manufacturing environment in Motorola (Harry, 1998) as they struggled to meet demanding quality targets on complex manufactured products; and become widely known when GE adopted it in the mid-90s (Folaron and Morgan, 2003; Thawani, 2004) when, arguably, it evolved from being a  process  improvement  methodology  to  a  broader,  companywide  philosophy.  Both  companies  still  consider  Six  Sigma as the basis for their on-going strategic improvement approach. Since the 1980s Six Sigma has become one of the most popular improvement initiatives; widely implemented around the world in a wide range of sectors (by companies such as Boeing, DuPont, Toshiba, Seagate, Allied Signal, Kodak, Honeywell, Texas Instruments, Sony, Bombardier, Lockheed Martin) that all declared considerable financial savings (Harry, 1998; Antony and Banuelas, 2001; Kwak and Anbari, 2006).
Other benefits claimed for Six Sigma include increased stock price, improved processes and products quality, shorter cycle times, improved design and increased customer satisfaction (Lee, 2002; McAdam et al, 2005). Six Sigma has undergone a considerable evolution since the early manifestations (Folaron and Morgan, 2003; Abramowich, 2005). Initially it was a quality measurement approach based on statistical principles. Then it transformed to a disciplined processes improvement technique (based on reducing variation within the system with the help of a number of statistical tools).  For  example,  Snee  (1999)  defined  Six  Sigma  as  an  ‘approach  that  seeks  to  find  and  eliminate  causes  of  mistakes or  defects  in  business  processes  by  focusing  on  outputs  that  are  critical  importance  to  customers’.  The  definition  given in 1999 by Harry and Schroeder (1999) also defines Six Sigma as ‘a disciplined method of using extremely rigorous data gathering and statistical analysis to pinpoint sources of errors and ways of eliminating them’. In  its  current  incarnation  it  is  commonly  presented  as  ‘a  breakthrough  strategy’  and  even  holistic  quality  philosophy (Pande,  2002;  Eckes,  2001).  It  is  now  generally  accepted  that  Six  Sigma  is  applicable  to  various  environments  such  as service, transactions or software industry regardless the size of the business (Pande, 2002; Lee, 2002) and being adapted Six Sigma may lead to nearly perfect products and services. Moreover, Six Sigma is widening its areas of application very rapidly and there are examples of applying Six Sigma to predicting the probability of a company bankruptcy (Neagu and Hoerl, 2005) or finding opportunities for growth (Abramowich, 2005).
In  the  past  five  years,  hundreds  of  organizations  have  indicated  their  interest  in  making  Six  Sigma  their  management philosophy  of  choice.  While  many  of  the  businesses  attempting  to  implement  Six  Sigma   are  well  intentioned  and  want to implement  Six Sigma  properly just as General Electric did, there are also those impatient executives who now look on Six Sigma  in the same way as they look on downsizing. This quick-fix approach to  Six Sigma  is a sure path to the same short-term results that prevent long-term profitability.It  is  worth  noting  that  the  evolution  of  Six  Sigma  is  continuing  with,  for  example,  the  integration  of  Lean  Principles, development of a product/service variant (Design for Six Sigma) amongst others (De Mast, 2006). 

Mean Variance Efficiency

The Role of Mean-Variance Efficiency

We began the Chapter with an idealized picture of investors (including management) who are rational and risk-averse and formally analyses one course of action in relation to another. What concerns them is not only profitability but also the likelihood of it arising; a risk-return  trade-off with which they feel comfortable and that may also be unique.

Thus, in a sophisticated mixed market economy where ownership is divorced from control, it follows that the
objective of strategic financial management should be to implement optimum investment-financing decisions using risk-adjusted wealth maximizing criteria, which satisfy a multiplicity of shareholders (who may already hold a diverse portfolio of investments) by placing them all in an equal, optimum financial position.

No easy task!

But remember, we have not only assumed that investors are rational but that capital markets are also reasonably efficient at processing information. And this greatly simplifies matters for management. Because today’s price is  independent  of yesterday’s price, efficient markets have  no memory  and individual security price movements are  random. Moreover, investors who comprise the market are so large in number that no one individual has a comparative advantage. In the short run, “you win some, you lose some” but long term, investment is a  fair game  for all, what is termed a “martingale”. As a consequence, management can now afford to take a  linear  view of investor behavior (as new information replaces old information) and model its own plans accordingly.

 Like Fisher’s Separation Theorem, the concept of linearity offers management a lifeline because in efficient capital markets, rational investors (including management) can now assess anticipated investment returns (ri) by reference to their probability of occurrence, (pi) using classical statistical theory. What rational market participants require from companies is a diversified investment portfolio that delivers a maximum return at  minimum risk.

What management need to satisfy this objective are investment-financing strategies that maximize corporate wealth, validated by simple  linear  models that statistically quantify the market’s risk-return  trade-off .

If the returns from investments are assumed to be random, it follows that their  expected return (R) is the expected monetary value (EMV) of a symmetrical,  normal  distribution (the familiar “bell shaped curve” sketched overleaf). Risk is defined as the  variance  (or dispersion) of individual returns: the greater the variability, the greater the risk.

Incremental IRR (Internal Rate of Return)

The Incremental IRR

Despite their apparent wealth maximization defects, IRR project rankings that conflict with NPV
can be brought into line by a  supplementary  IRR procedure whereby management: 

Determine the incremental yield (IRR) from an  incremental investment,
which measures marginal profitability by subtracting one project’s cash
inflows and outflows from those of another to create a  sub-project 
(sometimes termed a  ghost or  shadow project).

To prove the point, let us incremental the data from Section 3.1.Two projects that not only
differ with respect to their cash flow patterns ( size  and  timing ) but also their investment cost.

Project  Year 0  Year 1  Year 2  Year 3  Year 4  Year 5  IRR(%) NPV
                                                                                   15%        (10%)  
1 less 2  (35)      (30)     -           20     40   50   11.1

You will recall that IRR maximization favored a higher  percentage return on the smaller more
liquid investment (Project1), whereas NPV maximization focused on higher money profits
overall (Project 2). Now see how the incremental IRR (15%) on the incremental investment
(Project 1 minus Project 2 = £35k) exceeds the discount rate (10%) so Project 1 is accepted.
Moreover, this corresponds to Equation (1) on single project acceptance. The incremental NPV is
positive (£11.1k) because its discount rate r < incremental IRR.