Chapter 1
Let us begin with a few actual stories to set the tone for the book. The first one is about a leading consumer brand whose managers were perpetually enamored by technological improvements they were making to the products in their portfolio. Not surprisingly, top management had also committed to substantial funds for improving the technology across the product line, a strategy that was well in line with the firm’s long-term vision established a few years earlier. Along the way, however, the marketplace underwent dramatic changes. The most significant of these was that the product category in which the company competed was itself increasingly replaced by a better, faster, and cheaper alternative. Despite the writing on the wall, this firm continued to invest millions of dollars in enhancing its existing product portfolio and made no effort to invest in the new technology that was attracting an increasing number of customers. As a result, while the ongoing investments in technology did produce a substantially “improved” product, ironically the product class itself became “irrelevant.”
Over time, the market share and financial performance of the firm deteriorated significantly, and its misfortunes continue even to this date. While management did see the train wreck coming its way, nobody stepped up to challenge product policy decisions that were made earlier. There was widespread organizational belief in the strength of the firm’s existing product portfolio as well as its customer base. The belief created a flawed assumption among managers that the technology-driven product strategy that had served them in the past would continue to work equally well in the future. The marketing problem was exacerbated by the fact that senior management was constrained to planning from quarter to quarter, and long-term investments in an emerging product category seemed too stretched out to be explained to the investor community. Now this is not an isolated example, and we have come across several similar instances including video rental companies investing in redesigning their stores just as customers were migrating to ordering movies from the comfort of their living rooms. Similarly, there are examples of others who invested in superior quality on music CDs even as the market was moving toward downloading music directly from online sources.
Our second story is a very different scenario, which again, in our experience, is quite representative of a wide range of industries. In this case, the firm received thousands of inbound calls from its customers every month across its support centers spread throughout the state it operated in. Following industry practice, each incoming call was routed to the next available support representative, who was trained to make certain inquiries and then take appropriate actions. The call routing system, however, was antiquated and incapable of differentiating among calls from high-value versus low-value customers. To make matters worse, the representatives were not given any training or advice on how to handle the two groups of customers differentially. Instead, the focus was on cost containment and productivity—which led to the representatives attempting to maximize the number of calls handled per hour. They were also instructed to be strict about reneging late payment and other similar fines—a big reason for customer calls in the first place.
Senior management treated these call centers strictly as cost centers. It was insistent on keeping costs down through higher employee productivity and minimal cancellation of penalties and fees. Therefore, when a call came into the call center, the representatives treated the high- as well as the low-value customer groups in an identical fashion for all issues ranging from late payment to bill correction. A customer who had paid sizeable bills on time for the last several years but missed one payment because of a vacation was treated identically to another with a recurring record of missed or late payments. Not surprisingly, the system resulted in an exodus of a large number of the high-value customers who were always being solicited by competitors. Over time, the firm was left with a substantially less profitable customer base.
These remaining customers had a shorter tenure and smaller lifetime value, and the firm faced greater uncertainty in the cash flows expected from this pool. To make matters worse, given the high level of service required by these customers, the firm continues to spend a lot on servicing their needs. Suggestions to update the call center infrastructure to link a customer’s value and payment history to the incoming call identification or the account number of the customer have been ignored for years. Now in an environment of belt tightening, these investments, or “costs” as senior managers often call them, are even more difficult to justify to investors, and the status quo is maintained. Management continues to treat the call centers as mere cost centers and gauges their performance solely on metrics of productivity and cost containment. New investments in these locations contradict management belief, while the firm continues to see an exodus of its high-value customers. From an external observer’s perspective, even a cursory look at the data makes it painfully obvious that customer exodus often follows an unsatisfactory call center interaction, but the faith and belief in a well-established, productivity-driven model continues to drive decisions even in the face of compelling evidence to the contrary.
Finally, in a somewhat similar but generalized example, we often find that retail firms emphasize productivity in their individual stores. These productivity improvements are believed to have a strong positive impact on the financial performance of the firm. However, a recent engagement with one such retail firm suggests that caution should be exercised when boarding the “productivity wagon.” Productivity improvements, especially beyond a critical point, often lead to compromises in the level of service quality experienced by customers. For example, customers experience great resentment when they find fewer employees available to help them in these so-called productive stores and fewer stock-keeping units to choose from within a “rationalized” product assortment. While such adverse customer experiences are often not obvious in the short term, they lead to an erosion of customer loyalty in the long term. Extensive work, done by the American Customer Satisfaction Index (ACSI)1 research team, also supports our observation, where they find that service companies, such as airlines, often score below manufacturing organizations in the ACSI report card. This poor performance can often be attributed to attempts made by these firms to boost their productivity levels. Interestingly, these strategic choices are often not made in isolation but are the result of boarding the benchmarking bandwagon. Management feels the pressure to match its industry peers on select metrics, including those related to productivity, without giving deep thought to the ultimate consequences of adopting common industry practices and metrics. The underlying assumption, which we find often seriously flawed, is that not everyone within the industry can be wrong, especially when the short-term financial merit of emulating them can be observed relatively quickly. For example, we often read statistics about the “instantaneous” extra revenue airlines make because of new baggage fees, food for sale on board, and the removal of pillows and blankets from their aircrafts. However, we seldom hear about the potential adverse long-term consequences of such choices.
Our interactions with thousands of managers, consultants, management students, and academic thought leaders suggest that such stories can go on endlessly. In fact, we find that every day, a large number of managers make decisions based on intuition, entrenched mental beliefs, or knee-jerk reactions to competitive actions, without pausing to seek empirical support or validation. While observing the inner workings of big and small businesses, we have been a regular witness to the execution of beliefs-based decisions that rely on untested and unvalidated assumptions. Even as we write this book, we can find many senior leaders who continue to place extreme levels of confidence in the benefits of their unwavering beliefs in a variety of performance drivers, including innovation, cost control, productivity, benchmarking, and many more. In addition, the long-term effects of decisions that generate a positive short-term return, such as higher customer fees and lower levels of customer service, are seldom tested or validated.
The corporate world seems to have little time to pause and think and plan for fact-based decision making, for fear that nervous investors are ever so willing to abandon the ship and invest in alternatives. Such short and finite periods also correspond with the finite tenure of top management within most organizations. For example, in 2005, about 6 in 10 chief executive officers (CEOs) of Standard and Poor’s (S&P) 500 firms had less than 6 years in their jobs as CEO.2 In addition, as is well known, these leaders are evaluated and remunerated based on financial results produced during their tenure. This short-term orientation exacerbates the problem and the vision, and decision making at the top remains myopic. In such an environment, rapid fire, beliefs-based decision making continues to thrive at the expense of fact-based and data-driven decisions that possibly require longer periods of incubation and an alternative strategic mind-set.