Problem, Risk, and Opportunity Enterprise Management by Brian W. Hagen

How to use language, data, information, and analytics that easily align with the ways we think.

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ISBN: 1-9741075-03-7. ISBN-13: 978-1-941075-03-6. Shipping the week of August 20, 2018. Total pages: 368.

Problem, Risk, and Opportunity Enterprise Management

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PRO Enterprise Management


New! Video series on YouTube!

Dr. Hagen has developed an excellent series of YouTube videos that accompany Problem, Risk, and Opportunity Enterprise Management.

Update 6/24/23: Dr. Hagen has completed two new videos that discuss tying Artificial Intelligence with PRO Enterprise Management:

  • The Ultimate Generative AI Capability: Decision-Making with PRO Enterprise Management (video 1)
  • The Ultimate Generative AI Capability: Decision-Making with PRO Analytics (video 2)

    • From the Publisher...

    Through decades of consulting practice, Dr. Hagen has tailored a decision making process to correspond with the way that our brains actually function. This comprehensive book shares his methodology and the basis for it. He presents powerful insights and distinctions that are not found elsewhere. Our challenge with this book was deciding what to include and what to leave out, as his original manuscript was very large. We're going to include quite a bit of information on this page so that you can make an informed decision – hopefully a decision to buy the book!

    I should also comment on the title: as we were working on the book, we quickly (as do most people) thought of the book as PRO Enterprise Management or simply PRO EM. You'll see the book referred to with the "PRO" acronym throughout, however, at the end of the day, we all argeed that we couldn't use the acronym as part of the title because (1) the PRO acronym has several different meanings (google it and you'll see), and (2) you won't know what we mean by "PRO" until you read (or at least skim) the book.

    Synopsis (from the Author)

    The fundamental responsibility of executives and managers is to deliver value to the bottom line of the company. The primary mechanism for achieving this goal is decision making. To be most effective, decision making must be considered—more specifically primed—from an enterprise perspective rst, then other perspectives must follow. In your personal and professional life you make decisions about only three things:

      1. How to resolve problems (P),

      2. How to mitigate risks (R), and,

      3. How to capture opportunities (O).

    You own a continuously evolving portfolio of problems, risks, and opportunities. The dilemma you constantly face is, which problems, risks, and opportunities (PRO) should you pursue at this point in time? I refer to this as the “PRO Dilemma.” To be an excellent decision maker, you must become a master of resolving this PRO Dilemma. You can achieve that by answering and exploring the five questions of PRO Enterprise Management:

      1. “What are your PRO items?”

      2. “Which erode the most value if not pursued?”

      3. “Which, if pursued, create or protect the most value?”

      4. “Which should/will you pursue at this point in time?”

      5. “What are the implications to your plan and budget?”

    While it sounds straightforward, the challenge is that our natural capabilities in decision making are constrained by the limits of a 100,000 to 200,000 year-old operating system, the human brain.

    To overcome this, we need analytics—but not just any logically sound analytics. For the results of analytics to influence our decision making, they must first influence our beliefs. We make decisions based on beliefs, and our beliefs are influenced by the way we think and form judgments. Current normative theories of decision making (decision analysis, Monte Carlo methods, real options, predictive analytics, etc.) insufficiently bridge analytics from the logic and tools to the way we think and form judgments. These methods are also resource intensive in time and cost and cannot be applied to most of the decisions we make. Descriptive theories don’t have the analytical rigor to ensure we get the right answer. PRO Enterprise Management provides the bridge from thought to decision and action through narrative-based approaches and the language of tipping points.

    Our innate system is woefully over-challenged by the vast number and complexity of the personal and professional decisions we make. The notion of a PRO portfolio overwhelms all of us, yet this is precisely the dilemma we all face. Asking the five questions of PRO Enterprise Management is the most fundamental job of an executive or manager. Managing both your personal and professional PRO portfolios (coupled with some luck) is the path to a satisfying and accomplished life.

    Reviews

    A Note to the Decision Analysis Community (from the Author)

    My work as a decision consultant has been split between strategy projects and portfolio projects. My strategy project experience has been quite varied by industry and focus, including corporate strategy, growth strategy, supply chain strategy, manufacturing strategy, acquisition and divestiture strategy, product strategy, and tax strategy. In these projects I have followed a process and analysis that is familiar to many of you, including the use of tools such as influence diagrams, strategy tables, tornado diagrams, and s-curves. In my view the great benefit to clients in these projects is crafting a highly-tailored model that includes all of the key issues, uncertainties, decisions, and value measures that enables crisp insights into the decisions in focus. A significant fraction of the cost of these engagements in time and money is the building, testing, and vetting of the model.

    Portfolio projects have been and continue to be a large source of my client engagements. Fundamentally, these projects amount to the dilemma of having many ways to allocate limited resources and thus having to choose which expenditures are best for the organization. These have included portfolios of products, R&D projects, acquisition targets, risks, improvement projects, capital projects, and marketing and sales initiatives. For many years I approached portfolio projects like strategy projects in that I would build a portfolio model from scratch, requiring much time and cost. Over time I learned to reuse portions of the portfolio models and began wondering about a universal approach and model that could be used for most if not all portfolio projects. For me, that universal approach is what I call PRO Enterprise Management.

    There were several objectives I wanted to achieve in developing a generalized portfolio evaluation method, including:

      * Scalable level of evaluation from 15minutes as complex as deemed necessary by decision makers,

      * Consistent and logically sound accounting of uncertainty, leveraging subject matter experts, information systems, and predictive analytics,

      * Standardized structures that are easy to learn, even for individuals without mathematics or nance back- grounds,

      * Logically sound aggregation within and across portfolios, and

      * Framing and structuring that better leverages our innate strengths while attempting to mitigate our known biases and thinking limitations.

    As indicated in Figure 11.1 of Chapter 11, there is a single tree structure from which all problems, risks, and opportunities can be modeled. The tipping point of a material consequence represents the antecedent to consequences we either don’t want, as is the case for problems and risks, or to consequences we desire, as is the case for opportunities. As detailed in Chapter 11, the structure and calculation of the probability of the tipping point occurring can be as complex as we deem necessary or as simple as a direct assessment of the probability by a subject matter expert.

    The biggest difference between standard decision analysis practices and PRO Management practices is in the framing, assessing, and modeling of consequences and the creation of the distribution of the outcome variable(s). In effect, PRO Management uses a direct assessment of the outcome distribution given the tipping point has occurred. This is done by performing a 10-50-90 assessment of the outcome variable, not numerically, but as three narratives:

      * 10th percentile NPV narrative,

      * 50th percentile NPV narrative, and

      * 90th percentile NPV narrative.

    The narratives then need to be numerically assessed using a net present value of discounted free cash ow model yielding the 10th percentile, 50th percentile, and 90th percentile of the NPV given the tipping point has occurred.

    A key benefit of this approach is that all involved parties, especially executive decision makers, can be involved in the definition of the narratives. If there are disagreements in the definition of the narratives it is straightforward to change narratives and determine the impact on the results of the analysis such as the impact to investment productivity. Disagreements on the narratives rarely result in significant changes in investment productivity. As an example, if the investment productivity of a PRO item is about 22, changes to the narratives might move it between something like 17 to 28. But it does not become negative or less than 10 or more than 50. PRO items have a great spread in investment productivity, much more so than what executives and managers realize. In practice I have found that the priorities specified by an investment productivity curve do not change much if at all given extensive sensitivity analyses and assuming the PRO item frames hold up to executive scrutiny.

    Another key advantage is modeling on an incremental basis of value to the enterprise. The impact of PRO items to the enterprise can be modeled on an incremental basis if we use the net present value of discounted free cash as the outcome variable. Many in the decision analysis community understand this notion and use it in practice. This means we do not need to calculate the enterprise’s entire cash ow when evaluating investments in problems, risks, and opportunities. We only need to model and calculate the incre- mental changes in sales and costs and their incremental impact to net present value. Mathematically, this can be done because the net present value of discounted free cash flow is a linear operator with respect to delta changes in the income statement line items or after tax cash flow adjustments.

    PRO Management methods are new and different from what has been typically practiced in the decision analysis community. You likely have many questions. This book is the result of reducing the content from a much larger draft book that includes all of the mathematical proofs, many example applications, and issues such as addressing dependent PRO items and making a single investment that impacts multiple PRO items. This larger detailed book will be available in the future.

    Problem, Risk, and Opportunity Enterprise Management Table of Contents

    
1 A Day in the Life  ................................................................... 1
    The Great Corporate Decision Analytics Gap....................................... 7
    A Vision for Organizational Decision Making...................................... 9
2 Decision Quality and Empowerment .................................................... 13
    Our Decisions De ne Our Lives.................................................... 13 
    What is a Decision? ............................................................. 14 
    Decisions versus Good Outcomes .................................................. 14
    The Eight Elements of Decision Quality .......................................... 15 
    Measuring the Quality of a Decision................................................ 19 
    Does it Mean to be Empowered to Make a Decision? ................................ 20 
    The Emerging Requirement of Decision Process Transparency ....................... 20
3 Problems, Risks, and Opportunities .................................................. 23
    Deliberate (Intended) Strategy versus Emergent Strategy ........................ 23
    The Process of Strategy Development and Implementation.......................... 25
    What is a Risk?................................................................. 28
    What is a Problem?.............................................................. 29
    What is an Opportunity?......................................................... 31
    Creating a Consistent Basis for Decision Making ................................ 31
4 There Are No Facts About The Future ................................................. 33
    Practical Probability........................................................... 34
    Approximations for Estimating Ranges of Outcomes ............................... 36
5 Know Your Decision Value ......................................................... 41
    Mired in Measures .............................................................. 41
    What is Your “Priming Measure?” ................................................ 42
    Cash Flow is King .............................................................. 43
    Intrinsic Value of an Enterprise ............................................... 44
    Reconsidering the Movement to the “Triple Bottom Line” ......................... 44
    Measuring the Impact of Corporate Decision Making .............................. 45
6 Beliefs, Emotions, and Cognition.................................................. 47
    Thinking, Thoughts, and Sensations ............................................. 48
    The Three Layers of the Human Brain............................................. 52
    The In uential Subconscious Brain............................................... 55
    Priming......................................................................... 58
    Truth, Belief, and Knowledge ................................................... 60
    The Human Brain as a Belief-Generating Engine................................... 62
    The Importance of Patterns ..................................................... 63
    System 1 versus System 2 Thinking .............................................. 66
    The Predict-Perceive-Con rm Model of Human Cognition ........................... 70
7 The Eight Basic Mistakes ............................................................ 77
8 Judgment Under Uncertainty: Heuristics and Biases ................................... 99
    Organizational Motivational Biases............................................. 103
    Cognitive Biases that Impact Judgment Under Uncertainty........................ 104
    Errors in Logic ............................................................... 105
    Groupthink..................................................................... 107
    Heuristics Used in Judgment Under Uncertainty.................................. 108
    Improving Your Thinking and Judgment Under Uncertainty ........................ 112
    Seven Ways to Improve Organizational Decision Making........................... 113
9 Outcomes, Impacts, and Consequences................................................. 117
    Estimating Surprising Outcomes, Impacts, and Consequences ..................... 118
    Decision Quality Requires Reliable, Material Information ...................... 123
    The Clarity (or “Clairvoyance”) Test .......................................... 127
10 The Unnatural Act of Being Risk Neutral ........................................... 131
    Prospect Theory: Decision Framing and the Psychology of Choice ................ 131
    Neurobiological Explanation for Loss Aversion ................................. 137
11 Tipping Points and Decision Frames................................................. 141
    Sketching the Decision Frame: Act versus Not Act............................... 141
    Tipping Point of a Material Consequence ....................................... 143
    More Complex Tipping Points ................................................... 147
    Narrow versus Broad Decision Frames ........................................... 155
    Personal Frame versus Project Frame versus Enterprise Frame ................... 156
    The Relationship of Project Plans and Risk Behavior ........................... 161
    Risk Triggers and Key Risk Indicators ......................................... 162
    Risk Tolerance, Risk Appetite... .............................................. 163
12 Narrative-Based Analytics.......................................................... 167
    The Paradox of Business Modeling .............................................. 167
    A Univeral Decision Making Structure........................................... 168
    Revisiting Discounted Net Free Cash Flow ...................................... 168
    Narrative-Based PRO Management Framing and Assessment ......................... 174
    Templates for Recurring Problems, Risks, and Opportunities .................... 185
    “Pay Now” versus “Maybe Pay More Later”........................................ 187
    Data Derived Impact Assessments ............................................... 192
    Monte Carlo Methods and Other Approaches ...................................... 194
    A “Cost Savings” and “Cost Avoidance” Fallacy.................................. 195
    Black Swans and the Antifragile ............................................... 195    
13 Five Questions to Resolve the PRO Dilemma ......................................... 201
    Three Requirements to Resolve the PRO Dilemma ................................. 204
    PRO Management and Budgeting Processes ........................................ 205
    The Five Questions of PRO Management .......................................... 209
    The Five Questions of Risk Management.......................................... 225
    PRO Portfolio Analysis with Dependent PRO Items................................ 226
14 Delegation, Escalation, and Collaboration ......................................... 229
    The Building Blocks of PRO Enterprise Portfolio Management .................... 231
    ERM as a Decision-making Escalation Process ................................... 234
    A Common Hurdle: Cross-functional Collaboration ............................... 235
15 Beyond ERM to PRO-EM .............................................................. 237
    The Current Standard for Enterprise Risk Management (ERM)...................... 238
    ERM: Good in Theory, Not So Much in Practice .................................. 243
    The (Confusing) Language ofEnterprise Risk Management.......................... 244
    Geopolitical Risk ............................................................. 256
    Reputational Risk ............................................................. 259
    Meta-Risks .................................................................... 260
    Eliminating or Modifying “Dead End” Risk Management Practices ................. 261
16 Implementing PRO Enterprise Management............................................. 265
    Why Change Now? ............................................................... 266
    Integrate the Five Questions into Decision Making ............................. 267
    Taking the First Step ......................................................... 269
    Advice on Meetings and Presentations........................................... 275
Appendix 1: A Five-Step 10–50–90 Value Range Assessment .............................. 281
Appendix 2: Managing Quality and Risk ................................................ 285
    Extending Quality Management and Risk Management .............................. 285
    Juran’s Quality Management and PRO Enterprise Management ...................... 286
    Additional Perspectives on Quality ............................................ 287
    The Natural Link: Quality Management and Risk Management ...................... 288
Appendix 3: PRO Management Compared to Other Methods.................................. 291
    Decision Analysis (DA) ........................................................ 292
    Multiple-Criteria Decision Making (MCDM ........................................ 293
    Analytic Hierarchy Process (AHP) ............................................... 295
    Monte Carlo Methods ........................................................... 296
    Real Options Analysis (ROA .................................................... 299
    Game Theory ................................................................... 301
    Risk Matrices and Risk Heat Maps .............................................. 303
Appendix 4: Information Systems and Data Analytics ................................... 305
    The Three Classes of Data Analytics ........................................... 306
    The Gap between Data Analytics and Decision Making ............................ 307
    The Role of “Big Data” ........................................................ 312
Appendix 5: Beyond Risk Alchemy ...................................................... 315
    Why Risk Matrices Are a Dangerous Brew ........................................ 315
    Top Ten Reasons to Avoid Risk Matrices ........................................ 318
    Comparison of Risk Assessment Approaches ...................................... 323
Index ................................................................................ 333