The Future of Competitive Strategy

Introduction

5

©2022 MIT. This excerpt is from The Future of Competitive Strategy by Mohan Subramaniam, published by The MIT Press.

operational parameters can boost productivity. For example, sensors that track and maintain temperature levels in the right range while super heating molten steel, improve production quality and yield. Sen- sors embedded within products, in addition can drive revolutionary user experiences. Many of Ford’s new features, such as lane change assists, automatic braking, alerts for the car’s charging status, or apps to order coffee, are based on real-time insights—and feasible only through using interac- tive data. Similarly, GE’s jet engines interact with pilots during flight to help them optimize fuel consumption. They do so by tapping interac- tive data when the jet engine is in use, such as data on headwinds, tail- winds, turbulence, and the plane’s elevation. Babolat’s tennis rackets capture interactive data that can track a player’s skills and recommend ways for improvements. Tempur Sealy International’s mattresses inter- act with users, helping them change body positions to improve their sleep quality. The company achieves this by using real-time data on heart rates, breathing patterns, and body movements. 9 Legacy firms can also use web- or app-based sensors to capture inter- active data. With the help of such data, for example, the Washington Post recommends journalistic stories that may particularly interest readers as they browse for news on the company’s website. Bank of America’s app, named Erica, interacts with its users, tracking spending behavior to enable features such as refund confirmations from vendors, analysis of weekly spending, or reminders of bill payments due. Allstate Insurance’s app-based sensors help users adopt safer driving habits. This is because of interactive data obtained during driving. In sum, legacy firms can adopt several sensor-driven approaches to capture interactive data (see figure 0.1) Real-Time and After-the-Fact Data: New Kinds of Insights Real-time data from product-user interactions eventually turn into after-­ the-fact data that can be analyzed to generate retrospective insights. But these after-the-fact insights, when derived from accumulated sen- sor data, have some noteworthy attributes. To begin with, sensor data