Methods-Based ManagementBreakthrough Performance on Leaner Budgets

By Kenneth B. Tingey, Ph.D.

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Methods-Based Management

Breakthrough Performance on Leaner Budgets

By Kenneth B. Tingey, Ph. D.

Utah State University

Copyright © 2009 by Kenneth B. Tingey, Ph. D.No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, without permission in writing from the publisher. University Reader Company, Inc. is NOT affiliated with or endorsed by any university or institution.

First published in the United States of America in 2009 by University Reader Company, Inc.

Cover design by Monica Hui Hekman

13 12 11 10 09 1 2 3 4 5

Printed in the United States of America

ISBN: 978-1-934269-58-9

Contents

Table of Figures xi

Table of Tables xiii

Acknowledgements xv

Comment on the Cover xix

Chapter One: Where We Stand 1

The Basic Business Models Are Sound 7There Are Serious Integrative Issues in the Management of Organizations 8

Chapter Two: The Abundance of Opportunities

for Management 11

Biological Systems as Touch Points 12Lean/Quality Movement 14Logical Parsimony and Fluidity 14Complexity Science and Networks 15

The Centrality of Dual Control 15Grounded Methods and Models 16Information Technology’s Place in the Organizational Firmament 19Taxonomy-Driven, Secure Enterprise Systems 19The Full Organizational Model 20Capstone Opportunities from McGregor Onward 20

Chapter Three: Why the Fruit Is Lying So Low 23

Why Me? 23Wow—So This is What Management-Related Academia Is, Really 26Saved by the (School) Bell 28Specific Experiences in Business Research 29

First Fluidity Submission 29Vanishing Innovation 31Teflon and the Three Journals 33

Not Only Are They Not Finding, They Aren’t Looking 34

Chapter Four: Lean/Quality Findings 39

Introduction to Quality, Lean, and Six Sigma Models and Perspectives 40Understanding of Information Processing Implications of These Programs 41History of Modern Approaches to Quality 41Comparison of Quality, Lean, and Six Sigma Programs 46Overall Characteristics of Quality, Lean, and Six Sigma Programs 47Implementation Issues and Information Technology Implications 52Summary 55

Chapter Five: Fluidity and the Missing

Information Processing Model 73

Complexity by Default or Design? 73Why Is Fluidity Even an Issue? 74Information Processing Commentary in Favor of Simplicity and Fluidity 75

Computer Science 75Programming Languages 75Artificial Intelligence (AI) 76Accounting Systems 76Management Information Systems 77Instructional Technology (The Other IT) 78Knowledge Management 79Sociology 79Market-Based References 80Government-Sponsored Research Initiatives 81

What Kind of Knowledge Matters in Achieving Fluidity? 82Benefits of Tacit, Explicit, Expressive (TEE) Knowledge Model 83

Specific Tacit Knowledge Limitations 84People Can Forget 85Tacit Knowledge Will Become Stale 85Tacit Knowledge Alone Provides No Audit Trail 86Tacit Knowledge Tends Toward Simplification 86Available Solutions Can Be Limited When Depending 87 on Tacit Knowledge Alone 87Tacit Knowledge Walks Out the Door Every Night 87

Critical Explicit Knowledge Challenges and Benefits 88Explicit Knowledge Is Inefficient 88Explicit Knowledge Can Also Become Stale 88Explicit Knowledge Provides No Specific Audit Trail 89

Expressive Knowledge Challenges and Benefits 89Expressive, Process-Oriented Content Can Be Very Expensive to Produce 89Expressive Content Can Be Difficult to Maintain 90Expressive Knowledge Can Provide an Automatic Audit Trail 90

Expressive Knowledge Can Support Very High Levels of Detail 90Knowledge Translation Using the TEE Knowledge Model 91

Expressive Knowledge and Generative Taxonomies 91Foundation for Frames and Generative Taxonomies 92Organization of Logic Elements Within Frames 95Semantic Drivers of Frame Logic 97Frame Design Models 97Fluidity and the Knowledge Swirl 98

Developing Conclusiveness in Knowledge Dissemination 99Context Targeting 99Semantic Pull 99

Conclusiveness 100

Chapter Six: Complexity Science

and Networks 103

Complexity Science in Your Life 103Network Wars 104Social Network Analysis—The Search for Centrality 105Network Science as per Physics—Scale Is the Thing 107Hope for a Consolidated Approach 108The First MBM Social Network Studies 109

Social Network Graphics 111Social Network Numbers 112

Chapter Seven: The Centrality of

Dual Control 117

History of the Dual Control Concept 117Dual Control Basics 118Dual Control and Organizational Sovereignty 119Why Control Is a Good Word 120

Chapter Eight: Grounded Methods

and Models 123

What Qualitative Research Is All About 123Qualitative Studies and Complexity 126Establishing the Legitimacy Model That Underlies Methods-Based Management 128Initial Integration Model 130Implementation Issues from Second Grounded Theory Study 132Operationalizing the Legitimacy Model 133Next Steps for Integration Study 134The Legitimacy Discussion 136Fluidity and Cognitive Legitimacy 138

Responsiveness to the Voice of the Process 139Organizational Cognition and the Voice of the Process 140TEE Modeling 144Socio-Cognitive Networks 144Career Builders and Killers 147Agent–Individual Preparation

148

Immersion and Sociopolitical Legitimacy 149Useful Information Processing Technologies 150Safe Information Processing Technologies 152Required Information Processing Technologies 154Layered Approach to Information Technologies in the Enterprise 155

Original Political Model 157

Chapter Nine: Information Technology’s

Place in the Organizational

Firmament 159

The Good News for Information Technologists 159The Bad News for Information Technologists 159The Layered Approach to Information Processing in Organizations 160

The Problem from the Bottom Up 161The Problem from the Top Down 162

The Layers Themselves 162Layer 9 - End Users - Checkered 166Layer 8 - Governance - Purple 166Layer 7 - Management - Blue 167Layer 6 - Logic - Green 168Layer 5 - Access/Security Gateway - Yellow 168Layer 4 - Application Infrastructure - Orange 169Layer 3 - Data Management - Red 171Layer 2 - Operating and Network Systems - Brown 172Layer 1 - Processors & Devices - Black 173

Using Layers in Support of Fluidity and Immersion 173

Chapter Ten: Taxonomy-Driven, Secure Enter-

prise Systems: Closing the Back

Door While Beckoning from the

Front 175

Front Door/Back Door Security Issues 177The Paradox of Institutional Computing—Averaging Out Computing Functions and Security 177Conclusive Security Policy Based on Encryption and Classification—Closing the Back Door 179Addressing the Need for Fluidity—Beckoning from the Front Door 181Opportunities for Improved Security 182

Chapter Eleven: The Full

Organizational Model 183

Chapter Twelve: Capstone Opportunities

from McGregor Onward 187

End Notes 193

MBM Quality/Lean Reading List 215

Index 221

Where We Stand • 1

Chapter One

Where We Stand

W e obviously have problems in the management of enterprises, large as well as small. We live in an era of organizational nihilism, where there is little hope that solutions can be found to fundamental problems of

organizational life. In the current environment, a high level of depersonalization takes place within organizational cultures. Social environments in enterprises and institutions in our times tend to foster dysfunction. As a result, there is a crisis of disillusionment and failure.

Why do the most egregious elements of popular culture with regard to the futil-ity of organizational life enjoy center stage? The sardonic Dilbert combine of Scott Adams’ creation runs rampant. Television, movies, and other forms of entertain-ment demonstrate dysfunctional organizations without limitation.

Of course, dramatic effect loves dysfunction. Even in the best of times, we enjoy viewing the mishaps of the Keystone Cops episodes and similar demonstrations of futility. Unfortunately, we face a much deeper organizational crisis than is solely represented by our art. The organizational management literature includes many references to a perceived lack of relevance in the field.1 Certainly, the recent failure of many stalwart organizations, particularly in the financial services field, under-scores a failure to substantively identify problems and implement scientifically valid solutions.

I have written on this subject before. My consideration of dual control weighed the possibilities for declaring a scientific revolution in management.2 This work is a continuation and amplification of that declaration—that sufficient progress has been made to be able to declare a scientific approach to governance and management. In that respect, we will readdress that topic with some added perspective.

2 • Methods-Based Management

We need to understand the promise of science, lest we be vague. As outlined earlier, the question is far from new. Science constitutes a search for the truth. Most specifically, it is a search for causes, a process of identifying relationships that we can rely on. Faith has much to do with the objectives of science. Science and religion have much in common in their search for stability, if not meaning.

Scientific solutions are fundamental. To be scientific, something must be reliable as well as valid. A common example of these concepts is in the familiar realm of a dart board. If the darts you throw end up in a cluster, you have achieved reliability. There is a pattern to your efforts. If the darts are clustered around the bull’s eye, the effort has high validity—you were able to achieve the desired objective in a reliable manner. Of course, if you occasionally hit the bull’s eye, but your darts are not clustered in that desirable location, your efforts are not reliable. Having not achieved a dependable result, your efforts fall short of science.

Problems resolved based on genuine scientific groundings remain solved. They embody the application of sound models at the critical junction of study and ap-plication. For example, from a scientific perspective, the study of biology without knowledge of genetics would be incomplete. There is a level of complexity and order in the makeup of living organisms and viruses that you would not understand, skewing your results in unknowable ways. Similarly, social study without under-standing of individual variation and the use of structural and network models would be weakened by inadequate methods and misapplied units of study.

Apart from the reflexive definition—science is that which scientists do—the question is an important one with regard to management of organizations. Social scientists themselves have not universally resolved this issue, though there has been some progress.3 There are active debates over the relative importance of words over numbers. Words, of course, convey meaning, while numbers can bring precision. These distinctions lead to “qual” versus “quant” debates that rage now as much as ever.

According to the Oxford English Dictionary, documented quotations referenc-ing science in English can be found as early as the 1300s. From an application standpoint, the antithesis of science is and has been art. Religion factors in as well, representing the realm of belief as contrasted from science’s claim to knowledge. Indeed, scientia is the Latin term for knowledge.

Management has generally been considered an art, falling shy of scientific un-derpinnings. In the previous century, there was an attempt to bridge the chasm from art to science by Frederick W. Taylor and the Gilbreths, but those efforts became mired in confusion, social unrest, and concern for the well-being of line workers

Where We Stand • 3

who were thus required to engage in repetitive, ergonomically-compromising, mind-numbing labor. In the aftermath, management philosophy has been driven by practical approaches to the various accepted business models with little substan-tive, integrative success. I received my MBA in 1981. At that time, environmental and social implications of business activities were known as externalities. They were to be considered, particularly in the case of public utilities and other regulated enterprises, but in a distant, dispassionate way. Business was on one side of the isle, fronted (and confronted) by science, but with a decided gulf between the two.

Nonetheless, management in the current environment has much to commend itself. Based on centuries of commercial activity since the Middle Ages, the man-agement of people and of things in organized fashion is supported by many valid functional models. Among these are sales and marketing approaches that have shown to succeed at drawing attention to the offerings of enterprises and creating demand for their products and services. Accounting and finance models provide dependable means of tracking financial and other resources. Production efforts—organization of services and manufactured products—provide stunning examples of conversion processes of materials to end products and from unfinished thoughts to coherent services.

All of this stops short of science, however—a problem that in particular presents itself where integration and consolidation of models are concerned. The difficulty is that the standard business management models, proven though they are from centu-ries of refinement, are limited in their scope to the functional areas of activity that they were designed to represent. Furthermore, the narrow, inward focus inherent to the principal business models has extended to computerized implementations of them that make integrative efforts even more challenging. Even in the latest enter-prise system environments, integrative efforts are compromised by conceptual and technical limitations that can be traced to the presumption that each functional area is unique and different, requiring different data structures, unique logical imple-mentations, and far-flung design assumptions. In complex, global environments, well-meaning managers and others face insurmountable problems when attempting to sort through mazes of complexity represented by their organizations’ systems. Arbitrarily complex systems are not effective in resolving integrative problems that cross functional areas.

As a result of these two negative developments from the last half century—the abandonment of scientific management as a viable objective and the lack of technological models and approaches to functional integration in organizations—management practice has suffered. Evidence of such a dilemma can be found in

4 • Methods-Based Management

control dilemmas faced between business organizations, financial and environmental regulatory agencies, investor groups, labor organizations, and consumer advocacy groups. Problematically, these dilemmas exist in spite of the fact that knowledge of many viable solutions exists, but bargaining structures and information channels block them.

There is little optimism regarding the prospects for viable management ap-proaches that could be used to resolve such problems. In spite of the manifest ben-efits we enjoy from the output of commercial enterprises and government service organizations, a general malaise has set in with regard to work. We read acerbic comic strips that characterize poor behavior and arbitrary decision-making on the part of imaginary business people. There are similar television shows that focus on outrageous shortcomings of executives, managers, and supervisors—fictional and real—strongly implying that such negative, unwarranted behaviors and resulting poor working environments are inevitable.

In the face of such challenges, I offer a description of science of a kind that could serve the needs of management in environments where complexity, expan-sive scope, and change are omnipresent. Science as applied to management should present permanent solutions to problems that would incorporate social issues. In other words, a scientific approach to the problems of managers in this world of uncertainty, ambiguity, and competition would result in understanding, knowledge, and conclusive direction that would incorporate the perspectives and eccentricities of people. Once acted upon, science-based solutions taken on the part of manage-ment and others would be conclusively resolved.

A scientific approach to management would clarify the unit of analysis in organi-zations. It would provide a complement of analytical models that would incorporate both qualitative and quantitative approaches. I would also point toward predictive and protective actions that would bring definitive results that people would find appropriate and acceptable. One of the fundamental tenets of science is this: If you study the wrong things, you will not get a dependable result, regardless of your method. Similarly, if you target appropriate subjects, but in ineffective ways, your results will be suspect.

Isn’t dependability what science promises? The historic moon launches of the Apollo program did not end up on Mars or in the silent expanse of outer space. Polio is no longer the menace it was. Instantaneous communication around the world has brought distinct interpersonal, organizational, and political benefits. The gears keeping the Internet running keep on running.

Where We Stand • 5

And yet, most do not believe. This is to say that they cannot accept the proposi-tion that science can be applied to management in any appreciable way. To propose so is to risk derision. For one thing, with people in the mix, prediction is surely impossible. Who could be so naïve as to hope that human conditions could im-prove, given our understanding of mankind’s cupidity, greed, and shortsightedness? Although some hope may be allowed, who would condone the idea that science could serve to eliminate the negatives that vex our organizations and compromise society? The nihilism that has overcome the business community exists as well in society. We would rather wallow in despair. At some point, however, absurdity may cease to be funny, leaving us in a perilous state.

The point of this book is that such negativity is unwarranted, though many of us have been conditioned to enjoy negative expectations. Walter Shewhart, a young physicist working at Bell Laboratories in the 1920s, developed the beginnings of a scientific approach to management that has proven itself many times on several continents and a few islands. Aspects of this approach are well-known. To my knowledge, where applied according to known principles, it has never been found to be wanting in its contribution to management decision making and to predictably providential outcomes to customers, clients, and other targeted recipients of goods and services.

Deming spurred on a movement based on Shewhart’s model that almost rivals religion in terms of the zeal of its adherents, the mutually-exclusive claims of its various denominations, and the confusion experienced by novitiates as they come to learn of some aspect of Shewhart’s legacy. I started to learn of Shewhart’s contribu-tions in the early 1990s as I searched for the answer to a question when I learned of a new generic tool for defining logic that could be learned in minutes and applied to any subject area: “Assuming that a manager had such a tool, what should he or she do with it?” “Would such a capability be a good thing?” My thought was that the outcome of designing logical output without some guiding structure could prove chaotic. Such a development in the age of computing was certainly unprecedented, though it had originally been presumed.4

Most challenging to me was the insight that my MBA, earned from a very good school in 1981, about a decade earlier, had provided little guidance in the matter. My Dual Control book—its various chapters representing white papers that I wrote in the 1990s to memorialize my journey from a generic MBA to a budding science practitioner—documents what I often wondered with regard to my business train-ing.5 This current effort in many ways mirrors that quest.

6 • Methods-Based Management

Several questions have dogged me for many years. Why did I never learn of Shewhart prior to 1991? Similarly, why didn’t the seminal nature of his findings work their way into the curriculum of my business school and others in the late 1970s? True, I did tangentially learn of Deming in 1990 in a graduate course in competitiveness at UC San Diego where we read The Machine That Changed the World.6 Why didn’t I learn in these studies of the fundamental nature of the process—the quintessential unit of analysis underlying all of the business models?

Surely, some answers can be found in that I graduated in the early 1980s, some months before Deming, Shewhart’s leading disciple, was rediscovered in the West, too late for my MBA training. There is a more fundamental question, however: Why did Deming and the legacy of Shewhart need to be rediscovered? Didn’t Deming lead out in sponsoring the training of Shewhart’s fundamental method to some 30,000 U.S. production managers during World War II, underscoring the mi-raculous production effort supporting the Allied effort in that war? Working under General MacArthur in Japan, certainly there was some awareness of the effects of his support of the Japanese in rebuilding their industries.

Kuhn, in his study of scientific revolutions, surely could provide answers to these questions.7 Deming had his own ideas, which he was not shy about voicing,8 but which may not have helped to stimulate adoption rates in the industrial West. Some aversion to Deming’s habit of publicly criticizing business leaders surely contributed to the declaration of the immaculate conception of Six Sigma, which though held to have been developed at Motorola, General Electric, and other erst-while American firms,9 is clearly based on Shewhart’s work.10

The most important question in considering the scientific underpinnings of this approach is whether in the first place Shewhart was well-founded in his method. Has it proven its merit in its various implementations since Shewhart’s time? His publication on the subject, Economic Control of Quality of Manufactured Product,11 outlines an approach to study and understanding of processes that introduces both statistical and procedural approaches to management that are not only unique, but well-tested. It serves as the basis for many business management approaches that have shown their validity, but not from center stage. The validity of quality/lean model has not been fully recognized from the perspectives of governance and management. Understanding of the benefits of controlling processes within the firm and along the value network is derived from the point of view of production, but not general management.

Shewhart didn’t need to concern himself with computational systems to the degree that we face information technologies in our day. My object in this book is

Where We Stand • 7

to introduce his work and that of his followers and collaborators in the light of their possibilities for substantially improved information processing. From that point, I introduce information processing concepts that could serve to support process control as a natural and beneficial aspect of daily management of an enterprise.

My belief is that scientific management is possible. Unfortunately, it is not inevitable. If it were, we would probably have it now. Nonetheless, it is possible. Anyone wishing to take a strong position to the contrary should refute the validity and reliability of statistical process control. This should be done scientifically, not by means of a vague debate. I see an absence of concern for the issue in the business management literature.

Of course, successful application of statistical process control techniques requires that certain social conditions exist, as has been widely documented. In parallel, the centrality of process as a management construct should be studied, along with related concepts such as classification, taxonomy development, and the logic of implication—Aristotle’s’ hypothetical syllogisms and categories.

From this point on, you are invited to join in my voyage of discovery—from a generic MBA to an optimistic “process wonk.”

The Basic Business Models are soundThere is substantial criticism of management education and practice by those who accuse the field of a “silo” approach to organizational problems.12 This is to say that the various management disciplines are not well-integrated in practice and in the process of resolving complex, multidisciplinary problems. This is not to say that the various organizational disciplines, such as sales, marketing, production, resource planning, accounting, finance, human resources management, etc., are not valid areas of study and practice. On the contrary, they are the result of centuries of experience and study. They have been proven for effectiveness in all sectors and under many critical circumstances.

The various business professions are not considered to be equal, however. There is a pecking order, in large part a function of the stage of development of the or-ganization in question.13 In new, entrepreneurial organizations, where traditional markets are held in question, marketing and sales are held in the highest regard. The legitimacy of such new enterprises is held in the balance. Each sale supports the growing proposition that is the organization. As the enterprise matures and success becomes the norm, marketing tends to lose relative importance to integra-tive, operational functions such as accounting, production, and finance. Given the

8 • Methods-Based Management

preponderance of large organizations in the economy, this gives general precedence to those functions.

Under this scenario, the potential for recognizing commonality between the functions is diminished. Given the inherently numeric nature of the second group of functions, they have tended to be more easily computerized, supporting their preeminence.14 The phrase “accounting is the language of business,” for example, is not questioned or qualified, though all of the business functions are based on a similar classification structure.15 While underscoring the importance and the benefits of Pacioli’s model,16 we must look at a larger truth. Accounting is one of several classification models that make businesses and other social organizations possible as we know them. Classification is the language of business and as such is the key to eliminating the now-famous functional silos that restrict the performance and upset the cultures of organizations.

There are serious inTegraTive issues in The ManageMenT of organizaTionsIs an organization more substantial as a whole or is it merely the sum of its parts? Either may be the case based in large part on its degree of integration and coopera-tion. An organization that is characterized by vertical, or functional integration, but little horizontal, or value network integration—either internally or in conjunction with partner organizations or individuals—may prove to be a sump of misinforma-tion and denial. It may be cut off from the realities of the market or environment it was intended to serve. This integrative problem has been well documented in business and organizational research and in the popular business press, but little has been done to resolve the problem by academia, which is concerned with its relevance,17 but unable to rise above the “faddish” nature of the field.18

Some organizations have overcome related problems, but they have incentives to keep such gains to themselves. In the absence of a scientific body of theory and practice in management that can be learned, replicated, and shared in complex, changing environments based on rich classifications, such innovations are limited to technologies and models that embody separatism between the business disciplines, technological barriers to knowledge creation and sharing, and poor communication among provider organizations.

Given that integration is the sine qua non of organizations, it seems odd that separatist models prevail. Think of the organizations, even entire industries that capi-talize on the digital logic divide. These include many software vendors, consulting

Where We Stand • 9

firms, developer organizations, and even hardware vendors. Furthermore, consider the many parties that gain from current levels of organizational dysfunction. These include firms—many of them large and well-established—that mask a lack of mar-ket relevance and poor execution in the general perception that better performance is not possible.