Decision Analysis and Risk Management: Two Sides of the Same Coin 1-800-COURSES www.globalknowledge.com Expert Reference Series of White Papers Introduction Every decision involves an analysis of possible future events (costs, outcomes, markets, etc.) and selection of a choice among competing alternatives. Making a decision is making a selection. Decision analysis is the process of dismantling a decision so as to determine the inputs and processes that went into arriving at a decision. Risk management is managing (preparing for) future uncertainties. Uncertainties are risks. They are the unknowns associated with future events . The decisions we make today create the risks that we must manage tomorrow. Risk management and decision analysis are effectively the same thing. They both involve the dismantling of choices so as to understand the uncertainty of outcomes associated with particular options that have been, or could be, made. It follows that high quality decision making serves the purpose of risk management. If our decisions include a thorough consideration of uncertainties , then future risks are simplified or minimized. But what is a high quality decision? How do we judge decision quality? This white paper provides an outline of how to judge the quality of decisions by analyzing how effectively the risks associated with various options have been analyzed. We begin with a definition for quality control in decision making. This definition is then related to the four steps of the decision making process and finally to the three types of error (risk) that occur in each of the four steps. The paper concludes with an example of how methodical decision analysis leads to an understanding of the degree of risk in a decision. Defining Quality Every decision is a balance between what we believe to be true and what we are forced to predict. Every deci- sion involves the analysis of available information and ultimately the selection of a choice among alternatives with varying degrees of uncertainty. Brian Denis Egan, Global Knowledge Instructor, MBA, PMP Decision Analysis and Risk Management: Two Sides of the Same Coin Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 2 I t follows that the better our information and the more balanced and thorough the analysis, the higher can be the quality of our decisions. Better decisions are informed, reasoned, and balanced. Making better decisions means living with less risk. Poor decisions are risky. They are made without a full understanding of what might go wrong. It is not that if you make a poor decision you are necessarily going to be proven wrong (e.g. make a bad investment or pur- chase a defect-prone vehicle), but that the decision was made without a full understanding of the uncertain- ties or risks involved. With poor decisions, risks are understated and returns exaggerated. High quality decisions imply a complete understanding of the uncertainties involved. Making high quality decisions involves recognizing what risks you are taking. It is about making informed decisions. Risks are the residual uncertainties left behind when decisions are made without perfect information. But of course we never have perfect information. We therefore make decisions based on what we believe to be true and tak e a chance (accept the risks) of being wrong. High quality decisions are decisions in which the magni- tude of the risk of being wrong is understood. The quality of decisions can therefore be judged by the degree to which uncertainties (risks) are considered in the decision making process. The highest quality decisions are the ones that have the least unknowns. In other words, they are made with the most knowledge about possible future events. Risk management (planning for possible future events) therefore begins by ensuring that an organization’s decisions are of the highest possible quality given the constraints of time and resources. Quality Decisions and Risk Management The quality of an organization’s risk management is the degree to which we understand the uncertainties (risks, implications) of future events. The quality of one’s decision making is measured according to how well uncertainties have been considered. Quality controlling decisions are based on analysis of risk. The thoroughness of the analysis determines the “quality” of the decisions. High quality decisions are not the best decisions in hindsight. They are the best decisions in foresight. A high quality decision may not prove to be the optimum choice that could have been made. Instead, it is the best decision that could have been made given the resources and information av ailable at the time of the decision. Decision Process To fully understand the risks associated with a decision, and therefore to manage risks most effectively, it is necessary to understand the four steps (broadly speaking) involved in making a decision. 1. Identify a problem 2. Identify options or choices 3. Comparative analysis 4. Make a decision or choice Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 3 W hen we speak of identifying a problem we mean recognition and interpretation of the problem. Your car is dying of old age and you need to get to work every day. The problem might therefore be identified as “what to do in terms of replacing the car”, or “how will I get to work if the car dies tomorrow”? How one perceives the problem under consideration ultimately determines how the problem is analyzed in the decision-making steps that follow. Do you need a new car or do you need inexpensive, flexible transportation to work? How you frame the “problem” affects what choices are identified as possible solutions and how the choices are ultimately compared. Step 2 is the identification of options from which the selection will ultimately be made. The breadth and depth of choices is determined by both the way the problem has been framed and the creative effort put into gener- ating alternative choices. If the problem is thought of as “inexpensive transport to work” rather than “I need a new car”, then anything from bicycles to roller blades are possible solutions, and not just the options of a new or used car. Step 3 is comparing the alternatives that have been identified in step 2. This involves a comparison of the pros and cons, costs and benefits of each alternative based on criteria, and standards established by the person doing the analysis . Roller blades are less expensive than a car , but a lot more work and slower. Step 4 is making a decision. Whether roller blades are the best decision depends on the decisions maker’s pref- erences, distance to work, and physical abilities. There is never (or very rarely) one obvious or “correct” choice on which a variety of different decision makers would unanimously agree . Instead, a preferred choice reflects the decision maker’s interpretation of the avail- able information and their unique sense of risk and return. Risk in the Decision-Making Process Analyzing risk requires an understanding of the types of uncertainty that can be incorporated into a decision. There are three sources of uncertainty inherent in decision making. • Known unknowns • Unknown unknowns • Analytical bias Known unknowns are areas of uncertainty that are recognized and integrated into the decision-making process . T his is the stuff about which we know we should be concerned. In the example of choosing which type of new car to purchase, the known unknowns include future repair costs (after the w arranty period is over) for one brand versus another , or residual value (sale price) after a number of years of use. These are issues that we know to worry about but do not know just how worried to be. Unknown unknowns are risks (uncertainties) that are relevant to the decision but that are not included in the analysis. This is the stuff that is ”off our radar”. Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 4 W hen choosing a new car the unknown unknowns are possible events like: the car manufacturer going bank- rupt which voids the service warranty; repair parts being unavailable when needed; or the car being under- insured in the event of a major accident. Unknown unknowns are those possible events that you just would not normally think of in advance but could crop up to cause problems. Unknown unknowns are determined by your level of knowledge about a particular situation. The more informed you are the fewer (or more obscure) the unknown unknowns. For example, a lawyer can enter a courtroom with a full understanding of what to expect when defending a client. They may be surprised by some events but the likelihood of surprise declines with a lawyer’s increasing experience and knowledge base. On the other hand, a layman who enters a court, preparing to defend himself, is likely to encounter many unknown unknowns . These are issues the layman was unaware needed to concern him. The more research and education the layman undertakes before entering court, the fewer surprises there are likely to be. Unknown unknowns are therefore the issues that increasing degrees of expertise will reveal. The less you know, the more unknown unknowns there are—that is, the fewer known unknowns that you know. The third element of risk, analytical bias , relates to imperfections in our understanding and analysis of choices. This is the stuff of habit, prejudice, and mental laziness. Analytical bias may be referred to as the unknown unknowns of the known unknowns . (Whew!) It is a conse- quence of being human. Every analysis is a reflection (to some degree) of the person doing the analysis. Analytical bias is the difference between what we believe to be true and what is actually true. It is the differ- ence between fact and perception. Critical thinking is the tool that is used to reveal bias. It involves deconstructing the way someone is thinking into the elements or processes involved in the reasoning process. Through critical thinking it is possible to develop a thorough understanding of what inputs (biased or otherwise) have gone into the reasoning process. For a brief introduction to critical thinking, see the white paper, The Role of Critical Thinking in Effective Decision Making , at www .globalknowledge .com/resourcecenter . Risk in Decision Making For the purpose of discussion, let’s assume you have decided to buy a new car and have selected a particular make and model. What are the risks associated with this decision? Broadly speaking, the risks inherent in a decision relate to the four steps in the decision making process. 1. Identification and interpretation of the problem. a. Known unknowns – Have I defined my transport needs correctly? b. Unknown unknowns - Should I be considering alternative transport options? c. Analytical bias - Would someone else interpret the situation differently? Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 5 2. Identification of options a. Known unknowns – Have I considered all possible manufacturers? b. Unknown unknowns - Is it possible that there are custom-made vehicles that would provide the best value? c. Analytical bias – Why did I ignore the Eastern European brands? 3. Comparative Analysis a. Known unknowns – Have I considered the most important selection criteria? b. Unknown unknowns – How will future technologies affect resale value? c. Analytical bias – What selection criteria would my spouse use? 4. Selection a. Known unknowns – one of the other choices may prove to have lower maintenance costs, and therefore to have been a better choice in the long run. b. Unknown unknowns – What vehicles and options are going to be available in the upcoming model year that might have changed my decision? c. Analytical bias – What weighting would my spouse give to the selection criteria? Quality Decision Making Decision quality is measured in terms of residual risk left behind as a result of imperfections in knowledge and analysis. The highest quality decisions have little or no uncertainly, the poorest are based on ill informed guess- work; they are “a stab in the dark.” So, to understand the quality of a decision we must understand the weaknesses in the inputs that have gone into the decision making process and in the approaches tak en to reaching the decision. The degree to which the v arious sources of risk in a decision are considered determines the quality of the decision. Decision quality is risk management. Asking Questions to Determine Quality When it comes to the decision about which car to choose , in order to judge quality we would ask questions about each of the decision steps and the areas of uncertainty. • Have the transport needs be properly defined? • What considerations other than transport are important aspects to choosing a car, such as price or image? • How much effort went in to reviewing the product offerings that appeared to meet the decision maker’s needs? • What criteria were used to compare choices? • Were these criteria equitably applied? • Can the final choice be explained in terms of the selection criteria or did some extraneous factors drive the decision? The answers to these questions will ultimately determine the score that an observer would give to the decision that has been made. Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 6 Quality Advice What is “good” advice? It is advice from someone who thoroughly understands a situation so that they know: • What is the key question under consideration • The choices or options that are available • The implications (risks) associated with the various choices (options) The person receiving the advice is responsible for the final step in decision-making: making a choice. Good advice helps us to manage risk. We seek professional help from lawyers, doctors, and accountants so as to make better quality decisions. Better quality decisions are ones where all options are considered and risks are understood. Good advice is informed advice. Informed advice is imaginative, balanced, and comprehensive. Quality decision-making requires consideration of uncertainty in all four steps in the decision making process. T he more thorough and balanced the analysis, the greater the potential for high quality decision-making. When Are We Ready? When is the analysis complete? When has enough effort gone in to quantifying risks? The answer depends on the relative importance of the decision. It is necessary to understand the magnitude of uncertainty in a decision in order to determine whether or not a well-enough informed decision can be made. Do the benefits of making a decision now (given what we know) outweigh the costs of taking the time to seek more and better information for a decision later? Whether we can make a decision now depends on our sense of risk and risk aversion. Whether it is a “high quality” decision depends on our degree of understanding of the uncertainties around which we must make a decision. In order to become better decision makers we must learn to judge the quality of our decision analysis. This involves quality control of inputs to the analysis . • Quality control of information – is it correct, complete, and adequate? • Quality control of reasoning – is it fair and unbiased? • Quality control of analysis – is the comparison of options balanced, complete, and correct? T he objective of quality control is to minimize unknown risks . T here will alw ays be some residual risk. The question is whether we are well enough prepared to mak e an informed decision. Whether we feel adequately informed is a personal choice that reflects the significance of the decision. A Decision Example: An example of how a decision can be brok en down and analyzed will help to illustrate where and how risks are identified and what constitutes a high quality decision. Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 7 F or arguments sake, let’s assume that you have developed a chronic pain in your hip and are wondering what to do about it, if anything. Step 1: Problem Statement: What should I do about my sore hip? Known Unknowns – my medical knowledge is limited so that my diagnoses of how serious the problem is is prone to error. Unknown Unknowns – could be a radiation leak at work Analytical Bias – my mother had a hip problem and therefore this is probably the same thing, only worse. Step 2: Formulating Choices: Go to family physician, go to specialist, go to several specialists, go to cancer clinic, do nothing. Known Unknowns – My family physician may never have seen this kind of thing before and will be unable to diagnose it properly. Unknown Unknowns – My neighbor just went through a diagnosis for exactly the same symptoms. Analytical Bias – Family physicians never take enough time to do a thorough diagnosis. Step 3: Comparing Choices: Primary considerations are time required, cost, and thoroughness of diagnosis. Known Unknowns – Family physician is least inexpensive but least well equipped to do fancy testing. Unknown Unknowns – There are specialists who do nothing but treat hips. Analytical Bias – Family physicians never assume the worst, and the pain is definitely from something serious. Step 4: Choose an Option: Go directly to the cancer clinic. Known Unknowns – It will be expensive. Problem may not have anything to do with cancer. Unknown Unknowns – Cannot go direct to cancer clinic because patients must be referred by family physician. Cancer clinic is actually very poorly equipped and operated. Analytical Bias – Cancer runs in the family and therefore a tumor must be what is causing the pain. Looking Back at the Decision How good was the decision to go directly to a cancer clinic in order to have a painful hip diagnosed? Based on the brief analysis above it is easy to imagine someone being much more thorough in their analysis of all four steps. In addition, all stages of the analysis are badly skewed by the decision maker’s biases. The analy- sis does not seem thorough or balance and would therefore receive a poor rating. When judging this decision, and any other, it is necessary to review the thoroughness and balance with each step when it has been analyzed. High quality decisions are reached through a methodical and imaginative analysis of each step in terms of the uncertainties associated with them. Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 8 H igh quality decisions minimize risk. Poor quality decisions are conducted quickly in a haze of bias and prejudice. They understate risks and over- state the significance of information that the decision maker believes to be true because of his or her biases. Poor quality decisions put companies at risk. Risk management begins by ensuring that decisions are of the highest quality possible. Conclusion Understanding how a decision was reached is central to understanding how “good” a decision is. “Good” means how thoroughly and effectively uncertainties have been considered in the pre-decision analysis. Decision analysis is the process of dissecting the inputs to a decision. It clarifies the degree of understanding of issues involved and helps to ensure that choice selection is reasoned and balanced. It is the basis of risk management. We never have perfect knowledge. Understanding how imperfect is our knowledge is key to understanding the riskiness of a particular decision. Decision analysis is how we determine the weaknesses in our information and approach. Effective managers take the time to develop high quality decisions, because they know that good decisions are low risk decisions. And low risk decisions are ones that will result in the fewest headaches in the future . Learn More Learn more about how you can improve productivity, enhance efficiency, and sharpen your competitive edge. Check out the following Global Knowledge course: Critical Thinking, Problem Solving, and Decision Making For more information or to register, visit www.globalknowledge.com or call 1-800-COURSES to speak with a sales representative. Our courses offer practical skills, exercises, and tips that you can immediately put to use. Our expert instructors draw upon their experiences to help you understand key concepts and how to apply them to your specific work situation. Choose from our more than 700 courses, delivered through Classrooms, e-Learning, and On-site sessions, to meet your IT, project management, and professional skills training needs. About the Author Brian Egan is the CEO of the Book Box Company and principal of Briny Deep Consulting. He has been involved in strategic management since 1985 as both a project manager and a management consultant. Brian refers to himself as a “serial entrepreneur”. He has started several companies in such diverse fields as: fish farming, furniture design, gift manufacturing, and, most recently, catering. He is the author of three train- ing courses in management science and several white papers. Copyright ©2005 Global Knowledge Network, Inc. All rights reserved. Page 9 . Sides of the Same Coin 1-800-COURSES www.globalknowledge.com Expert Reference Series of White Papers Introduction Every decision involves an analysis of. control of reasoning – is it fair and unbiased? • Quality control of analysis – is the comparison of options balanced, complete, and correct? T he objective of