Читать книгу The Exponential Era - David Espindola - Страница 14

“Predictions are hard, especially those that pertain to the future.” This comical proverb was allegedly first expressed in Danish, but the author remains unknown.

Given the difficulty in making predictions, how do you deal with the uncertainties of the Exponential Era? How do you stay on top of all the emerging trends and converging technology factors? How you do spot inflection points in business before they happen? Rita McGrath has written an excellent book titled Seeing Around Corners, that expands on this subject. In the book, she contends that inflection points, though they may seem sudden, are not.⁶ In an exponential curve, there is a long period of time in which the curve is basically flat, before the inflection point. Then it hits the elbow and goes straight up (see Figure I.1). It is during this flat period and the beginning of the elbow that, armed with the right perspectives and tools, smart leaders can anticipate changes and leverage them to create competitive advantages. Please note that we are using the exponential curve here for illustrative purposes only and not in its precise mathematical sense. For a more extensive discussion on this subject, please refer to the Appendix.

Figure I.1 Inflection point.

The key is to detect the signals of change and respond early enough, before it is too late. The challenge is always separating the signals from the noise which is often pervasive and distracting due to variations in the data. Startups have to be very good at detecting inflection points and making distinctions between signal and noise in order to survive. Most companies have a difficult time seeing inflection points and positioning themselves to take advantage of the opportunities these changes represent before they become threats. Technology startups tend to be nimbler, closer to the action, and demonstrably more willing to experiment and change directions than their more established counterparts. In the startup world it is very common to pivot to a different business model if the first one tried does not achieve the expected results. But for many legacy companies, it is a lot harder to pivot, partially because of their commitment to past investments, but in some cases also due to their intrinsic belief that what has worked in the past will also work in the future. Many legacy companies are focused on short‐term metrics derived from strategies that yielded results in the past, and their resources are allocated accordingly. However, allocating resources to conduct the necessary explorational experiments intrinsic to growth, but that requires taking some risk, is not common practice in these types of companies.