Conquering Uncertainty:
Understanding Corporate Cycles and Positioning Your Company to Survive the Changing Environment

Theodore Modis (McG raw- Hill/Business Week, 1998)

In Conquering Uncertainty, Modis takes us on the “S-curve” journey of anticipating the future. One of the first three Business Week books, Conquering Uncertainty is clearly aimed at business managers.

Modis is a former physicist who portrays the evolution of any organization or activity with the S-curve, which many readers will know as the logistic curve or the sigmoid curve from the well-known work of Charles Handy . It is the integral of the normal distribution curve (bell curve), and John Casti also discusses it his book Complexification (HarperCollins, 1994). Modis largely draws on the work of Cesare Marchetti, currently Institute Scholar at the International Institute for Applied Systems Analysis in Austria. The latter is a physicist who collected large volumes of data on diverse systems in the 1970s and 1980s, and developed S-curve and normal curve mathematical models to predict events.

Modis wanders over the course of human history, claiming to model accurately the lives of people such as Hitchcock and Mozart, the growth of cars in society and the population of rabbits, and brings in sunspots, Stonehenge, Van Gogh, communism, and Da Vinci. Although the appendices contain some preliminary mathematical elements behind this type of modeling, many readers will find the lack of supporting information frustrating, especially considering the difficulties inherent in such models. Further, most readers will probably consider the book as an immodest promotional overture to Modis’s consulting services.

However, business managers who apply these techniques of appraising their future can certainly benefit. Modis uses a novel metaphor of the four seasons to assist managers in planning changes for their business. Implementing such techniques into the corporate management culture can significantly help management make corrections to their course, before change is thrust on their company and it is too late to prepare adequately.

The science of these curves can be understood simply. Exponential growth is essentially a natural result of system processes incorporating feedback. Bacteria begin to grow in a nutrient medium, and the amount of nutrient available (feedback) limits growth. As the growth slows, the resultant curve is S-shaped. Fundamentally, all systems start relatively slowly, move through stages of more rapid evolution, and inevitably slow down. Typically, in nature, another “system” takes over as the old one wanes, and the cycle is continued.

Clearly, social constructs such as business organizations follow similar cycles. Applying a singular model often leads to disaster, with the complexity of social organizations fooling the modeler with any number of surprises along the way. Most important, the human inertia inherent in organizations presents the most difficult hurdle in attempting to stay ahead of change factors such as technology, regulation and competition. Humans are wonderfully apt at waiting until the obvious before reacting, rather than preparing.

Rigorous scientific modeling considerations might be applied to advancing Modis’s science. For instance, with today’s environment accelerating the pace of life cycles, many businesspeople find it hard to understand just exactly where they are in Modis’s 4-seasons cycle, and may even consider themselves on a different part of the curve. The hysterisis of perception is a common problem among business managers, and that lag often causes new product introductions to fail, competitive responses to be inadequate, or technology innovations to be behind. Another area for improvement is in accommodating overlapping cycles. Multiple product and service lines often dissonate with out-of-phase cycles, and comprehensive strategic planning can be quite confusing when differentiating between conflicting and often opposite-moving forces for each of them.

While the word complexity is used only once in the text, by default, complexity science is promoted nicely to the business world by Modis’s consulting practice training managers to use these ideas. I believe that most businesspeople will find this methodology compelling, especially those who are searching for better ways to understand their limitations in exploring future possibilities for their firm.

The book is well written, and most management people should learn from it and the author’s particular take on how business reflects nature. Modis does bring much to the table from the perspective of implementation of complexity science into the corporate environment. While we may decry the lack of hard science, corporate management does not make a habit of driving decisions on a day-to-day basis with mathematical algorithms. Illuminating difficult business planning problems with scientifically driven graphical techniques coupled with strong metaphoric reference systems is a laudable talent. Modis is to be congratulated for using his physics background as part of his successful consulting practice, with clients including AT&T, DEC, Baxter and the World Health Organization.

Reading between the lines, I hope that Dr. Modis will raise the flag higher, especially imparting to his corporate clients that his techniques are part of the larger body of complexity science. On a personal note, I was pleasantly surprised to learn another view into complexity, and found myself considering use of these techniques in one of our firms, a consulting services practice, for our own clients.

One purpose of science, hopefully, is to provide useful tools for the nonscientific world. I suspect that even without understanding integrals or harmonics, Modis’s clients who implement forward-looking thinking with the S-curve tools that he espouses will consider themselves ahead of the curve.