Understanding How Waves of Change Work
This chapter is from the book
This chapter is from the book
This chapter is from the book
During the last two decades of the twentieth century, economists and historians have done a great deal of research on the subject of waves of change, primarily in such areas as prices, inflation, and the rise and fall of empires. The notion they are increasingly coming to understand is that certain types of activities repeat themselves but, just like waves, are never quite the same as those that came before. Nonetheless they still pound on the shores of the beach. The analogy holds that economic behavior, such as inflation, while it never looks quite the same each time it occurs, has common features which, once you understand what they are, allow you to see when the next wave is coming. The theory holds that, like the child at the beach, you can then time the next good ride on a wave. A theme woven throughout this book is the frequently shifting nature of business environments. Understanding how to exploit change as opportunity is crucial to business success. That is why wave theories are important to understand and to leverage. It is also a body of knowledge virtually alien in the lexicon of management practices so far.
The concept is one useful to scientists as well who look for patterns of behavior leading to predictions about future activities in such things as weather, actions of living organisms, or the functioning of a physical phenomenon. The fact that waves of change are applied with positive results in the social sciences, economics, and history suggests it might help companies determine future patterns of work and opportunity. As of this writing (2000), I see almost no evidence of the model applied overtly in business. The one very clear exception is the methods of prediction now applied in gauging performance of processes using statistical process control. Given the way a process is designed and operates, it is very possible to predict within defined control limits how it will work tomorrow, next month, or even next year, so long as no element in the process is changed. This kind of prediction is well understood and a strong body of best practices exists.
Managers who have worked in business settings for more than two decades frequently think they see recurring patterns in business, typically cycles of good and bad times, inflation and even deflation, organizational changes that favor centralized vs. decentralized command-and-control, and so forth. To a certain extent they are right, because like the waves at a beach, no two cycles of business are quite the same but nonetheless are very familiar. One thing we all see quite frequently in business concerns sales: Do we deploy a direct sales force aligned by product, geography, or industry? Many twenty-plus year sales veterans recall that they have witnessed all three models implemented within the same firm, seen them come, and go, and come back. However, managers, and especially senior executives, are increasingly learning that relying solely on memory of past experiences to make decisions is also problematic. If an industry or market is changing, prior experience and personal memory may be outdated, irrelevant to the new circumstance. An incorrect lesson can also be drawn from prior experience. Coca-Cola's senior management appeared quite affected by this when they decided to retire the firm's premier product—the Coca-Cola drink—and replace it with a new variant. The results were disastrous and the firm had to bring back its main product, now called Coca-Cola Classic. The episode has gone down in business history as a classic misjudgment. Smart people just drew the wrong lessons from past events. That is why the rigors of knowledge management and analysis of market conditions must exist side-by-side with personal expertise and experience.
In periods of great change, the search for indicators of coming events is always at a premium. Missing a market can be disastrous. Great firms experience the effects at some time in the course of their history: Ford Motors in the late 1920s when it failed to see the market demand for a variety of models of cars; IBM in the late 1980s and early 1990s when the market moved away from mainframes to smaller computing platforms and more services; Apple Computers when it kept its proprietary operating systems years after most customers wanted open technical architectures; Coca-Cola in the 1990s with its momentary shift away from its base product. During periods of instability the risk of misjudgments exists, even increases; hence the rush by managers to any form of certainty of thought. In more stable circumstances, waves become increasingly predictable indicators of behavior. But even in times of transformation, waves can be helpful because they can suggest in macro form what could happen. For example, certain types of changes come sooner in some industries than in others, often simultaneously in those that have some common features, which, in turn, can suggest to others what might be probable. Information-intensive businesses such as insurance and banking firms might experience information changes before a less data intensive industry, such as distribution. On the other hand, as the retail industry becomes increasingly dependent on data for marketing programs, it can learn from banks and insurance firms how to collect, manage, analyze, and protect data. High tech firms like IBM can then teach them how to perform data mining, which is a fancy way of saying how to glean insights from that mountain of digitally stored information all these companies already collect. As historians study some of these data intensive industries, such as is going on now with the insurance industry, we have the opportunity to identify waves of change useful in other industries.
As change accelerates, time intervals between waves shorten. So we do not have to look at, for instance, price inflation of the seventeenth century caused by the influx of Spanish gold into Europe from the New World to understand what American inflation looked like in the 1970s during the presidency of Jimmy Carter. We have examples in our century of various levels of intensity to draw upon, such as the severe German inflation of the 1920s, the stubborn Brazilian inflation of the 1980s, and the effects of the swift monetary crisis in East Asia in 1998. The key is to understand patterns which, by definition, are collections of activities that occur over and over again. The notion of waves helps define why they never repeat exactly the same.
David Hackett Fischer, a distinguished historian, spent many years cataloging economic characteristics of price waves, suggesting specific features we might want to think about as we explore how business waves affect our firms. These features concern duration, magnitude, and range. Several appear quite relevant.
Change occurs in the rates of change, with prices, for instance, caused by expanding markets and institutionalized price increases.
Ranges of annual fluctuations often diminish from one wave to another, such as the price ranges in highly available items (e.g., food in good times).
Crises are profoundly affected by human demographics, with a propensity for increased political radicalism and economic uncertainty when populations expand.
By implication, anybody curious about waves in business has to be at least minimally curious, even introspective, about his or her world. Formal processes for "sense and response" are not the same thing because just surveying customers or suppliers, then responding quickly to changing circumstances, is a tactical reaction to an immediate situation. But if someone is looking for broader implications and patterns, for the less obvious trigger events that initiate changes that hurt or help, that person must find a different way to look at the world. Any new way requires an open mind receptive to ideas from multiple sources, including as we say in baseball, from "left field." How can you apply the notion of waves to business intelligence? Five steps can be taken; each requires extensive work, but, as wave experts and data mining gurus would argue, they are worth it.
First, use best practices as a strategy for constantly polling all aspects of the business environment to understand patterns of behavior and degrees of change in performance and actions. This should range across economies, industries, performance indicators, yields on investments, and definition of what is bought and sold.
Second, discipline your business to apply process management to those key sets of work activities essential to the firm's success, including the use of statistical process control methods over multiple years. Process management experts and highly experienced accountants and financial analysts learned after many decades of hard work that a minimum of three years' worth of data on the performance of a process is about what is needed to understand fully the impact of a collection of work steps. We also know today that several months' worth of information begins to deliver actionable insights.
Third, look over your fence to find what business models and value chains are emerging in other industries, such as those industries merging to form new industries and coalitions. Ask if these patterns are applicable to your own industry and firm, and whether they teach you something about how to run either your enterprise or a portion of it.
Fourth, become a student of the history and evolution of things relevant to your business. The most obvious candidate is telecommunications and the Internet, which means you should probably understand how the telegraph and telephone diffused throughout an economy and what the intended and unintended consequences were on firms, customers, and society in general. There is much economic and historical literature to inform the curious, and increasingly, information from business professors looking at case studies of the effects of specific technologies on business practices. The richness of this kind of material and its easy accessibility is a relatively new phenomenon of the past two decades. These almost match in volume and value what has long been available to politicians and military officers.
Fifth, exploit the notion of the prepared mind. Unfortunately this cannot be taught easily, but it can be encouraged as both an attitude and as a behavior, one that can be acquired over time. If you read widely across many subjects, not just about business, discuss business issues with others across numerous industries, and develop a knack for making sense of disparate pieces of information, patterns emerge which experience teaches you to act upon. The Warren Buffett type of manager is a good example of the individual who can take action based on this skill set. However, even if you do not believe you have the talent, others do have it and you can go to them for help. The key is to entertain diverse opinions from within and outside the enterprise about what is happening and determine how best to apply those observations in guiding business activity. To a large extent, this book is an exercise in this fifth step because it taps into economics, business practices, history and political science, quality management practices, information technology, and business experiences to create a description of business practices for the emerging business ecology.
Are there limits to historical insight and what we are learning about waves? There are several that cannot be denied. One of the limitations frustrating to managers is the fact that good research on economic waves, for example, leads to lessons applicable to whole centuries. The manager wants to know what the economic waves are going to be in the next year or two. Economists not using wave theories provide opinions and prognostications while historians won't touch the issue because they think it is outside the purview of their discipline and cannot be done. Managers also frequently have difficulty understanding how patterns of behavior from, say, the seventeenth century, can teach them anything about what will happen in 2005. Historians of waves normally stop short of answering the question, "So what does this mean for me now?" They hate to speculate about the future; it runs against a basic practice of the profession because historians are painfully aware of the enormous mounds of inaccurate projections that have been made over time. They also recognize the reality of the unintended consequence that so frequently protrudes into the affairs of people.
In addition to the reluctance of professional historians to help, for those of us who wish to understand better, we do not have as many specific analogies about what waves of change teach us. We do not know well, for example, the effects of information technology on business management practices, although there is now an army of social scientists, historians, business management professors, and others rushing into print with their thoughts. Much work has yet to be done because it has only been since the late 1980s that many people have realized that the history of information technology can provide some answers to management's questions.
I do not want to end this discussion about waves and historical precedence on a negative note, just to caution that as a source of insight it has some limitations. What is very positive, however, is the trend evident in many academic disciplines of looking for patterns applicable to management practices. Also comforting is the growing trend of cross-disciplinary study of issues, bringing to that effort the skills of multiple disciplines, from those of the business manager to the historian or economist.