Data is now considered the new oil. Although not all data are in the form of numbers, the earliest forms of data analytics in business had to do with quantifiable information. Management by numbers, popularized in the 19th century by the father of scientific management, Frederick Winslow Taylor, may be considered as the first approach to business analytics, apart of course from the practice of accounting invented in the Western world by the Italians in the 15th century, A.D. In fact, in the middle of the last century, the famous management guru, Peter Drucker, quipped “If you can’t measure it, you can’t manage it.” Some business commentators today consider this once-famous phrase as a hyperbole. Fortunately, Peter Drucker had other very famous aphorisms that had nothing to do with numbers, such as “The purpose of organization is to enable ordinary human beings to do extraordinary things.” Or “Profit for a company is like oxygen for a person. If you don’t have enough of it, you’re out of the game. But if you think your life is about breathing, you’re really missing something.” Or “Management is doing things right, leadership is doing the right things.” And finally, “There is nothing quite so useless as doing with great efficiency something that should not be done at all.” These and other Druckerian phrases imply that there is more to management than numbers and metrics.
As business commentator Rana Foroohar wrote in the Financial Times (July 15, 2019) in a column entitled “The Fallacy of Management by Numbers,” management by numbers could sometimes be the ultimate in penny-pinching, pound-foolish thinking. She gave the example of the crisis at Boeing precipitated by two separate crashes involving the Boeing 737. Her analysis of the causes was as follows: “There were many factors behind the disaster, but an important one seems to be risk-taking at Boeing in order to maximize profit. The plane maker has been criticized for outsourcing work to engineers who were paid just $9 an hour, charging extra for certain safety features, and rushing the aircraft to market sooner than might have been wise in order to try to nab business that might otherwise have gone to Airbus.” There are so many examples of management by numbers leading to imprudent cost-cutting that endangers lives not only of workers but the consumers of the final products or services. Another example given by Ms. Foroohar was that of the California energy utility Pacific Gas & Electric, which according to a Wall Street investigation, knew for years that hundreds of miles of its power lines needed upgrading, lest they fall and spark fire. Unfortunately, in the name of management by numbers, the company decided not to invest the money for upgrading. Tragically, the century-old transmission line failed and started a massive wildfire that killed 88 people. Thanks to the obsession with shareholder value, PG&E is now facing more than $30 billion in potential legal claims and has filed for bankruptcy protection.
We may be witnessing the counter reaction by younger generations of business people to the focus on management by numbers. We now hear a lot about impact investing, the interest of those managing funds in the over all contribution to society of the enterprises in which they invest, which may mean sacrificing maximum profit for such other goals as protecting the environment, promoting the over all welfare of their workers or strengthening family ties. As Ms. Foroohar observes, there can be more focus on corporate governance by managers. Young consumers may care about the values of the companies that make the products they buy. There is also the increasing number of emerging market corporate giants that do not have the pressures of quarterly capitalism. All these can run counter to management by numbers. There is, however, a danger that these positive trends may again be countered by the era of Big Data. Thanks to more powerful computers and the digital revolution, many more things can be measured these days. The increased use of data analytics may tempt business people to refocus on metrics rather than on unquantifiable value judgments which are necessary for human flourishing.
In a recent magisterial lecture at the University of Asia and the Pacific, Dr. Jose Maria Mariano, a philosopher-mathematician and former president of UA&P, examined the moral dimensions of Big Data and data analytics. I quote from his lecture: “We are aware that, in the last few decades, the Internet economy has developed a business model offering free services for end users, while generating commercial profit by mining, analyzing, and aggregating data. This has already raised issues about monetizing assets some feel properly belong to the end user. The advent of big data-surely the defining buzzword these times-and the advanced data analytics that has been evolved to handle it has raised new issues. We observe a two-way development. On the one hand, digital technology spreads into every aspect of our lives through personal computers, smartphones, and soon the Internet of things. While we merrily click into our dazzling toys, the sensors they are fitted with are constantly spouting off data feeds-our data that creates an internet history of what we say, where we go, how we feel, what we choose, and generally what makes us who we are.” Indeed, during the era of Big Data, there is so much of our private lives that is exposed to the public gaze. Our very intimate thoughts and desires are now considered public property. We no longer have control over what other people will do with what they know of our free choices in our ordinary lives.
As Dr. Mariano continues to point out: “…business and other organizations make greater use of digital assets, data services, especially data analytics, to evolve subtler and more pervasive ways of working on our data. They will then filter our communications with family and friends, determine what features we see in online searches for commercial goods, deliver personalized news, personalized ads, driving directions, and, increasingly, inform critical decisions concerning our employment, education, health, and financial well-being. There is no complete agreement on what exactly big data is, but the general idea is that the volume, variety, and velocity of data now being generated can engender new insights beyond anything that sampling and extrapolating can achieve. These new insights promise many benefits. But they too bring potential for great harm.” (To be continued)