Scientific Management Is Past Its Peak

Sure, algorithms and software tools can help streamline any business. But, says Roger Martin, more executives are rediscovering that gut instinct is what keeps a company vital

A couple of weeks ago, I went to a dinner on the politics and economics of global outsourcing. Primarily I went to see the bright young writer Fareed Zakaria, author of the now famous Foreign Affairs article The Rise of Illiberal Democracy, because my agent, Tina Bennett, told me I would love him and she is pretty much always right. The second speaker for the evening was Martin Baily, former chair of President Clinton's Council of Economic Advisers and currently senior adviser to the McKinsey Global Institute, which is the think tank of the world's premier management consulting firm.

Rather than focus on outsourcing, Baily gave a speech on McKinsey's annual report on Ten Trends Shaping the Future Corporate Landscape, a couple of which fortuitously pertained to the evening's subject. As he went along, things made good sense: economic activity shifting towards Asia; the emergence of a billion new consumers; resource demand outpacing supply; changing global industry structures.

Frankly I was fading a bit. Then, boom! Trend No. 9: the rise of scientific management and its triumph over gut instinct and intuition. Baily waxed eloquent about how great this was and what an advance it represented for the world of business.

Now, I'll concede that if the McKinsey folks had been referring to the recent past, they'd be right. Scientific management has indeed been on a steady rise—we have all the trappings from Enterprise Resource Planning (ERP) to Customer Relationship Management (CRM) to Total Quality Management (TQM).

However, this pitch was about trends shaping the future landscape. And as I listened, I thought that an equally plausible interpretation is that the scientific management of business is in the final stages of bloated excess and reflexive self-importance—a supernova ready to blow.

The Poker Face of Science

Intrigued by this schism, I went to the McKinsey Global Institute Web site to see what exactly they meant by Trend No. 9. Did Baily overstate the case in his speech? Or, in my post-dinner stupor, did I hear him wrong? Neither: Baily was tame in comparison to the Web site:

"9. Management will go from art to science. Bigger, more complex companies demand new tools to run and manage them. Indeed, improved technology and statistical-control tools have given rise to new management approaches that make even mega-institutions viable. Long gone is the day of the "gut instinct" management style. Today's business leaders are adopting algorithmic decision-making techniques and using highly sophisticated software to run their organizations. Scientific management is moving from a skill that creates competitive advantage to an ante that gives companies the right to play the game."

Whew! That is heady stuff: managers reducing the whole of business to a set of algorithms and some sophisticated software. No more gut instinct. "O brave new world, that has such people in't!" to borrow from Aldous Huxley who borrowed from Shakespeare—or perhaps from the infamous supercomputer HAL.

An Analytical Utopia

Having lived for many years in a high-end strategy consulting firm, I can understand the appeal to the young minds at McKinsey Global Institute of such a Cartesian, deterministic, analytical world. Arguably, the firms hire their raw talent on the basis of its capacity for high-powered quantitative analysis and train it in more quantitative analytical techniques before putting it to work for long hours crunching algorithms.

So I can appreciate why they would see the increasing use of business algorithms and software as indicative of a future world they would love to see. Yet the reality is that consumers, competitors, and clients often act in 'irrational' or 'political' ways.

So I can't help but wonder whether the McKinsey team's desire to see an analytical utopia overwhelmed the objectivity of their trend analysis.

(Of course, that would be a cosmically delicious irony: The overwhelming desire for an analytical world causing emotions to overwhelm analysis in predicting the arrival of said perfectly analytical world.)

Let me suggest an alternative trend—the rise of heuristics over algorithms; qualitative over quantitative research; judgment over analytics; creativity over crunching. Why would this be? Smart executives are beginning to recognize that the analytic, algorithmic approach to business has overreached. They read the crisp reports spit out of their ERP systems, and while they know exactly how many widgets they shipped to the Midwest the previous week, that isn't helping them figure out the next great thing that customers want.

Rather Revolting

While their CRM system lets them quantify the profitability of each and every customer, and on the basis of those data, enables them to approach each customer with a perfectly customized offer, they find customers don't feel wonderfully served but rather have the eerie feeling that Big Brother is watching them shop.

While they can draw on huge quantitative consumer research studies that are statistically significant beyond a shadow of a doubt, they wonder why products based on the results don't grab the targeted consumers. While executives think they are doing the right thing by managing the numbers for the sole purpose of 'maximizing shareholder value,' they are perplexed that employees don't find that to be a particularly inspiring reason for coming to work each day, and customers find the thought rather revolting.

While it would be crazy to argue that business management has not benefited from scientific methods, algorithms, and sophisticated software; the question is where is it going from here? And I believe the pendulum is swinging back.

Thoughtful executives are figuring out that algorithms and software, the focus of McKinsey Global Institute's enthusiasm, are at the end of a long chain that starts with mysteries such as: How do teenagers think about their cell phones? And guess what? They don't think of them as phones!

Seizing the Higher Ground

When we begin to understand mysteries, we develop heuristic ways of thinking about kids and their handheld networking devices cum fashion accessories. A lot farther down the road of understanding, we may be able to come up with an algorithm or two relating to kids and this product set—i.e., we must have a new generation of products on the shelves every six months or our market share will tend inexorably downward. And some time after that, we might be able to write software that helps us, for example, price the product line across the multiple distribution channels.

If executives want to focus on the software and algorithm end of the chain, they can manage exactly the way the McKinsey Global Institute suggests. However, while they are managing the well-understood parts of the business with dazzling efficiency, executives in other companies will be delving into the mysteries that define the future of the business, developing heuristics for understanding it, and by doing so, seizing the high ground for the future.

Who's Winning?

That is why a smart executive like Procter & Gamble (PG) CEO A.G. Lafley insists on doing in-home visits to consumers (or stream-side visits in rural China) wherever he travels. He isn't going to make billion-dollar decisions on the basis of a few in-home visits. He understands full well that what he sees isn't a representative sample. But he is delving into the mysteries of how products interact with his customers' lives in ways that a big quantitative, algorithmic survey never will.

He knows that his job as CEO is to keep pointing his company up towards the mysteries and heuristics and not let it fall prey to a focus on "algorithmic decision-making techniques and using highly sophisticated software." He and others like him are winning, and that is why I believe that the pendulum is swinging away from, not towards, the extremes of "scientific management."

Before it's here, it's on the Bloomberg Terminal.