 Dynamic Decision Making We are what we repeatedly do. Excellence, then, is not an act but a habit. --Aristotle Completion of the first transcontinental railroad across the United States, ably told by Steven Ambrose, is a story of a very imperfect success, with numerous changes in how, where, and by whom the railroad was built. While imperfect, the railroad's completion is also a study in the flexibility of decision making where the paradigm of how, where, and by whom was always modified to fit the realities of building the road. Choices were constantly made and then modified on issues of where the track would go, how it would be financed, the construction, and, not to be overlooked, what political strings were to be pulled to get the railroad finished at a profit. Other than completing the railroad, there was not a set of proscribed rules; instead, a framework for decision making was set up, modified with new information, then choices were made and a new model put in place. Successful decision making is a process, not an event, with constant modifications and interactions among the moving parts that evolve over time. In sports, many franchises win a championship once in a while. Yet repeat championships are driven by a model of decision making that generates winners. The focus remains on the correct process that can be replicated over time and across circumstances rather than on a one-off correct decision that is more a matter of luck than skill. Good decision making must be replicable. How do we go about seeking the correct process rather than the onetime correct decision? First, in economics, a framework must be developed that accurately characterizes the driving forces about the market we are concerned with for our decision. This framework is both a filter and a structure around which we develop our decision making. The framework is a filter because it identifies the relevant information needed to address the problem. Not all facts are equally relevant. In decision making, for example, two biases can throw off the building of any framework. First, the recency bias is the temptation to take the most recent data and treat that as the critical input to any framework. Recent data is often the most readily available and often the impetus, especially if unanticipated, for an examination of operations. But recent data may also be the most distorted by other factors, such as weather, and, while easily available, may be just too convenient to the lazy researcher in search of easy answers. Confirmation bias is a second source of problems for any model/ framework builder. In this case, when decision makers are in the early stage of model development there is a tendency to grasp at models or data that confirm the initial prejudices of the researcher. Yet we know from watching mystery thrillers that the initial suspect is often not the real criminal. The same initial problem/phenomenon can be framed or interpreted differently in several ways and the great detective—as opposed to the hapless detective—chooses a framework that stands up to the evidence as it develops over time rather than as it is initially presented. Successful framework development does not attempt to force problems into conceptual boxes supplied by post-secondary education. Too often, newly minted managers are too anxious to put well-learned tools to work even if the problem itself is not carefully defined. In laymen's terms, the rookie wishes to use a hammer to solve every problem, because he knows how to use a hammer, even when the solution calls for a screwdriver. Assumptions are another problem for framework development. There is a delicate balance between assumptions that simplify a problem too much and assumptions that introduce false premises that constrain or even prevent a solution. We can simplify a problem too much in those cases where we essentially assume away a problem that comes back later to destroy us. Over the last three years, the assumption of liquidity and marketability was taken as gospel in a marketplace where neither was present to support the underlying asset prices when the system was shocked. Alternatively, certain assumptions can complicate or misrepresent the problem. In their classic book, Neustadt and May make the case for a careful use of analogies in developing proper frameworks/models of the problem at hand rather than misrepresenting the problem as something similar to what we are comfortably familiar with. Finally, there is often an assumption of symmetry in our frameworks that simply is not there in real life—especially in finance. There are often few limits on the upside for profitable companies or investment strategies, but there are limits on the downside—bankruptcy. For state and local governments there are budget and liquidity constraints that limit the ability of decision makers to adopt certain financial strategies and risky options. Education propels us forward on a body of accepted wisdom within a particular view of the world. This wisdom includes a traditional set of axioms or rules along with accepted problem-solving techniques that are consistent with the received wisdom. Our education provides the accepted theory and the accepted problem-solving techniques. However, once outside the bounds of traditional models, how do we discover a way to approach the new problems of the Great Recession, for example? The model solutions we have learned are seldom open-ended; they do not allow the practitioner room to solve new problems that are significantly different from the received wisdom. Often, unfortunately, the models and problems we are educated about reflect a tradition born of a very specific learning style that limits progress in learning. This was famously demonstrated in the case of Isaac Newton, who had to overcome the orthodox Cartesian limits of the English universities of his time to develop his insight into the workings of gravity. In our traditional educational systems, the study of problem-solving models prepares us for membership in the business/government leadership community in which we will later practice, but not necessarily stretch, the boundaries of that knowledge throughout our professional careers. A problem-solving framework reflects the accepted model or pattern for pursuing a particular solution based on our education, but is not necessarily appropriate for the new set of problems we will face later in our careers. Traditional approaches to learning match existing facts with established theory. The focus here is to develop an approach that recognizes the constant evolution of the model itself as the facts of the economic environment change, and highlights the need for leaders to recognize change and make choices in a very dynamic world. The established models can proceed without change only so long as leaders accept without question the particular problem-solving methods and solutions already achieved—but this approach is not acceptable for effective decision making over time. PROBLEMS CHANGE—WHY NOT SOLUTIONS? Our models of how the world works are often cast in concrete more often in our minds than in the real world. We give lip service to the argument that change is constant, but then build business models that are resistant to change. In his book, Leading Change, James O'Toole identifies a culture at General Motors that was unable to recognize the implications of change in the competitive environment and the breakdown of their business model. Our world poses problems of endless variety. There are two aspects of problem variation. First, each problem we confront is not representative of all problems we face. In our education, we are often given a method for addressing a type of problem which is, of course, very useful. Unfortunately, we tend to use the methods taught to us more broadly than is appropriate. We fit problems to the methods of solution with which we are intellectually comfortable. Further, we tend to look for the set of problems where our model solutions are useful and fail to recognize the possible class of problems that are too difficult to solve given our familiar models. Problems that are highly unlikely cannot be ignored. Many states of nature are possible, so that, to our chagrin, zero probability events show up more often than we expect. This is the fat tail problem or the 100-year flood that shows up more often than once every 100 years. Another dynamic characteristic of problems is that they are not solved for all time—they morph and generate new problems. In fact, we often find that decisions to address one problem generate a response from society and/or our business competitors that lead to further change along the way. We see this in the pricing wars that often accompany gas station or retail competition in America. In recent years we have witnessed a decline in information costs and accelerated adaptability to innovation by both businesses and consumers. This has shortened the life span of our solutions to problems and prompted new solutions more rapidly than many decision leaders had anticipated. Moreover, growth is not simply a function of labor, capital, and the growth of the stock of knowledge and technology. Growth and change are driven by the interaction of these factors as well as the disasters along the way. The technology of the Internet and the laptop computer had existed for some time, but in the mid-1990s the scale of these activities and their interaction generated a leap in personal productivity and innovation in software, pushing the growth in economic activity further than anyone had anticipated. Barriers to Change Often the sources of poor performance in both private and public sectors reflect the ability of decision makers to overcome the barriers to change. Unfortunately, the ability of organizations to alter operating models is hampered by our cultural/social heritage as exemplified by the concept of path dependence. The degree to which our decision-making culture can change is not well understood. Too often change is superficially incorporated in business. For example, economic models are often adapted by changing a numerical entry on a spreadsheet. This change leads to a new solution without any change in the underlying equations and does not address any relationship within that spread sheet. Such an approach may simplify learning, but it seriously misrepresents the process of decision making in the real world. There are many sources of resistance to any of the choices we make in response to any change in the exogenous environment. The institutional structure, assumed or made explicit in our models, is inherited from the past and reflects a set of beliefs that may be significantly impervious to change—either because the proposed changes run counter to the belief system or because the proposed alteration in institutions threatens the leaders and entrepreneurs of existing organizations. Change, especially if the implications of that change offer a different vision of the underlying socioeconomic structure, is very difficult to implement when trying to reach a solution within the current viable institutional arrangements that would support significant change. It seems that change is constant, but sometimes not implemented when met by entrenched interests. Enlightened management, for example, Grove at Intel, encourages open debate on the business model as standard operating procedure, much like the writers were encouraged to work on the TV program Your Show of Shows. Our inherited institutional structure reflects a set of beliefs about how the world works that is impervious to change because many in leadership roles have a vested interest in keeping the process working in a way they understand. When change runs counter to belief system or the alteration of the model threatens political/economic interests, decisions made in response to change may not reflect the economically optimal solution. Another complication to effective decisions that can occur in implementing a response to change is the recognition of interdependencies—change in just one area of business practice is incomplete and sometimes counterproductive if not complemented by changes elsewhere in the organization or the marketplace. An additional complication to responding to change is the time inconsistency among players. Not all parties have the same sense of urgency. Moreover, two further complications make any change to the inherited structure uneven in its impact. First, altering the performance of an organization in response to an economic shock takes time—often longer than the time horizon of the business leader/political decision maker who must approve of these changes. The costs of economic adjustment often show up before the benefits; selling change therefore becomes a challenge to decision makers. The costs of adjustment to higher energy costs in the 1970s led to immediate problems for the automobile industry and electrical utilities, yet over time the energy efficiency improvements led to gains in auto quality, reliability, and a better environment. Second, consideration must also be given to people and businesses that are hurt by any change. For example, British Prime Minister Peel's attempt to repeal the Corn Laws would have meant a loss of trade protectionism for English landowners who benefitted from high agricultural profits, since the Corn Laws limited grain imports. When the Corn Laws were eventually repealed, the balance of economic power in England shifted permanently away from the landed gentry to the industrialists and trading economic interests. In the United States the deregulation of airlines in 1978 lowered prices for consumers and opened up more travel options to regional markets in selected areas. Yet, for airlines such as Eastern and Braniff, the drop in fares led to eventual bankruptcy, as neither firm could compete in a lower fare marketplace. Incentives provide a focal point for thinking through our decision-making approach. A poor performance institutional matrix does not provide incentives for productivity-improving activities. Some groups within organizations have a vested interest in existing structure, and so incentives (carrots and sticks) must be found to overcome entrenched interests. In organizations there are complex relationships between formal rules and informal constraints. Organizational decision-making structures are man-made, and to function properly they must be continually altered to reflect the continued evolution of human desires and ways of living. As the cultural/economic heritage of a society changes, so must the models we use to characterize that change. Over time, there is no set formula for economic development, so there is unlikely to be one framework that will provide a magic formula for all time. Model developers must understand the process of economic growth before a framework for analysis is created. Developers must then understand that changes in society will dictate changes in our model. Sources of Change: Economics For public and private decision makers five economic factors—growth, inflation, interest rates, the dollar exchange rate, and profits—provide the context for success of any enterprise over time. The source of change in our models and our actions is often precipitated by the gap between what we expect and what we get for each of these five factors. 1. For growth, recessions are the surprises that throw us off but in 2008 to 2010, there was also the gap between how we modeled the world and what we thought was our future. 2. For inflation, the experience pre/post Paul Volcker's era at the Federal Reserve defines two very different models of the economy. 3. Interest rates take on a different character over the business cycle, along the yield curve and between instruments of different credit quality. 4. Exchange rate fluctuations have been the source of disaster for some financial institutions, including Barings and Franklin National, as well as the bane of countries over time. 5. Volatility in corporate profits influences the pace of investment in the economy and the wealth of investors. (Continues...) | 
