Why we manage people so poorly—and what we can do about it

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HR Leadership HR strategy HRE experts leadership Peter Cappelli column shared start-up management practices Talent Management

A couple of years ago, I started to write a book about how we actually manage employees—how we hire, how we determine pay, how we manage performance and so forth—because the reality is so different from textbook descriptions.

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What I found in researching Our Least Important Asset … was a common theme to the contemporary approaches. First, they focus on doing things as cheaply as possible (e.g., we measure cost per hire carefully but not quality of hire) but only consider up-front costs rather than longer-term costs. Keep positions vacant as that reduces payroll costs, for example, and don’t worry about how the work gets done or the effects on turnover.

Part of the explanation for that shift has to do with financial accounting standards, which punish employment costs relative to other expenditures. I wrote about this in a previous column.

But there is another part of the explanation that has to do with changes in business leadership and the backgrounds of those who lead companies. It is based on the old scientific management idea that the way to maximize performance is to have experts figure out the one best way to perform jobs and then monitor employees closely to ensure that they do it. It is as if the last hundred years of management—from the Western Electric studies on—never existed. How did we get so far back so quickly?

A paradigm problem in people management

A generation or so ago, corporate leaders likely went through years-long “management development” programs when they were hired, where they were taught lots of things but mainly about managing employees. They were required to succeed at running smaller groups before running anything bigger.

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Related to that is a striking rise in the number of engineers who now run companies. LinkedIn data suggests that almost a third of CEOs now are engineers by training where the optimization approach to problems is deeply ingrained. Even in business programs, majors like finance and accounting—let alone operations research—have the same cost-minimization focus.

To be clear, the goal here is not cost minimization, per se; it is optimization on numbers that are easily measured, such as headcount and payroll. That doesn’t include productivity, which is hard to measure, let alone employees’ discretionary effort or other big costs such as turnover. The problem is not what managers are taught in these programs, it is what they are not exposed to—anything about actual employees as humans.

Related to this is the disproportionate influence of tech companies on business thinking, and especially the views of their founders. Companies like Microsoft, Amazon, Apple, Tesla and Google are giants in their influence, and they are still largely controlled by their founders. Those founders were typically engineers (Jeff Bezos at Amazon was a finance guy) who had never run anything before. Those companies’ successes are remarkable achievements, and the founders can certainly be forgiven for not knowing anything about managing employees.

But  … Founders of wildly successful companies—especially those with no experience elsewhere—tend to come up with their own ideas about how to manage that are driven first by the idiosyncratic experience of entrepreneurial companies, and second by their engineering paradigm. Because they have been so successful financially, they get lots of attention.

They almost uniformly seem to think that big organizations can be run on the informal basis that start-ups run. How often have you heard them say something like, “Just hire great people, and you don’t need management.” Their view of employees further down the hierarchy is that they are mainly costs to be minimized. (Henry Ford and the industry titans a century ago had similar ideas.)

We see this in the fact that tech companies are outliers in reliance on contractors (a notion pushed along by Uber), who often account for as many as half of their workers. Most of them eventually grow up, to some extent, and some—Microsoft, in particular—have very sophisticated employee practices.

Some companies are walking back effective people management

In the meantime, we got practices whose influence still persists, such as the endless interviews for hiring from Google (something, to their credit, that they eventually abandoned), Tesla’s management based in part on threats and confrontation, Netscape’s notion of employees as replaceable assets in a market, Amazon’s time-and-motion approach to manual labor, Stripe’s requirement that remote workers take pay cuts and so forth.

The idea that, because these companies have been wildly successful in business performance, they must have been managing their employees well is a problem with logic: As most HR people know, employees often get their work done, at least passably, even with horrible management. They would just perform much better with good management.

The reason all this is important now is that we are walking back management practices that have been extraordinarily successful—primarily because they don’t fit with the optimization ideology and the tech “run lean” start-up model. We see this most notably in pulling back on employee empowerment.

Agile project management, which at its heart empowers teams to make virtually all decisions, has now been redefined with the notion of “agile” meaning flexible. A big part of that is to shift work to contractors and vendors, even though teams can be extraordinarily flexible.

Retraining employees appears to be cheaper and better than the preferred alternative of layoffs and new hiring but still layoffs prevail to restructure. Lean production—another employee empowerment tool that we thought Toyota had taught to the world—has also been redefined as simply operating efficiently, and the decisions that employees had made to improve work processes are now being pushed off to software to determine. Scheduling software has taken the place of teams working out their schedules flexibly.

All of this is pushed along by the vendor community that is happy to give leaders what they want. The software vendors themselves are often start-ups run by data science and engineering founders who fall right into the headcount optimization paradigm. The unfortunate lesson is that better ideas don’t always prevail—even when there is evidence to the contrary.

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