Long Hours in the Business World
Our two previous posts on the effects of long hours on errors and reduced productivity focused on two professions, doctors and lawyers. We picked those two rather than further explore the issue in the military because long hours for doctors and lawyers are purposely selected by managers whereas soldiers work long during wartime or training for wartime. This choice to impose long hours implies acceptance of the costs and benefits that result; the professions also have higher duties to the public, not just their patients and clients, that are codified in various ethical codes as well as actual statutes.
The original article sparking the discussion, however, came not from the professions but from the business world, and so we thought it would be helpful to discuss these issues in light of two additional fields where long hours are already on the table: consultants and business in general. We think that exploring the reasons why long hours in these fields might not be so readily discovered as a source of problems will help design appropriate experiments for firms to undertake as they seek continuous improvement.
Let’ start with consultants. We have had substantial experience with the consulting world, and long hours are almost a badge of honor in the field. Travel is an additional duty for consultants, and an extra 10 hours a week of travel is not unusual, even for those who work all week at a single client location. If long hours reduces productivity and increases the likelihood of errors, why aren’t these problems apparent or acknowledged by consultants?
First, like lawyers, consultants typically bill by time (even if their firms do not, consultants are tracked by hours per project). This hourly approach creates, if not a perverse incentive, the complication that it is hard to distinguish between lots of optimal work and lots of inefficient work. This lack of clarity affects the consultant, the firm, and the client, all without any bad faith. Indeed, benchmarking one consultant against another to compare the time taken for various tasks would likely show the same sorts of performance losses and hence be taken for normal performance. In other words, two folks performing at 80% would each give the appearance of 100% if matched against one another; of course, that’s the wrong question.
Second, unlike doctors, whose “mistakes” often have immediate effects, any errors caused by consultants may never be discovered or be revealed to have any effect. (Of course, the counter-argument is that if a mistake doesn’t have any ill effect, it’s not a mistake.) But the lack of revelation is different from the actual mistake. For example, imagine a spreadsheet that contains errors in formulas used to support part of a decision analysis. If the right decision doesn’t get made, in part because of the spreadsheet calculations, it may be invisible to the participants, but the end result will not be. Companies regularly miss earnings projections (at least they would if they weren’t so heavily managed) and often fail to earn their cost of capital. Those are certainly “mistakes,” broadly construed, and virtually impossible to connect to a specific action.
It’s clear that this second point is the one most likely at work in the corporate world. Once we moved most work from factory or manufacturing work that is relatively easy to measure to much fuzzier knowledge work, we exposed ourselves to productivity problems and cures of all kinds, all equally undefinable and unreliable. In the same way that it is difficult to determine the effects of fatigue on productivity, it is difficult to sort out what benefits in performance may be expected from other changes. This disconnection is one reason that usability experts are still focused on getting businesses to implement changes that are easy to measure, such as intranet structure for common activities.
If it’s hard to observe and measure real-world effects of chronic fatigue and long hours, where can we get evidence about the likely effects that is convincing enough to allow leaders to implement changes, or at least tests, in their organizations? Well, some of that research already exists and was referenced in the original article. The Belenky article describes the pattern of failure from sleep deprivation. Performance slowly degrades until a critical failure is reached because the time available to make a decision or analysis arrives while the decision-making process is not complete. “Thus, a gradual decline in performance during simulations or laboratory studies maps into a long period of apparently adequate, if not good, performance in actual operations, and then, suddenly, failure. ” This paradigm is supported by our personal experience in Ranger School (described in the article as 3.6 hours of sleep — we wish we saw that much every day!), in military training, in Ivy League graduate school, in careers in professional services organizations, and in our current roles leading our own portfolio of businesses.
Is knowledge work like that described by Col. Belenky? We think so. The dichotomy between the sustained ability to complete physical tasks and the degraded ability to maintain situational (or strategic) awareness, the context for those physical tasks, describes very well the difficulties facing people in the corporate world. It remains possible to read and type, to even modestly edit and review presentations and spreadsheets and documents, but the strategic viewpoint, the stream of constant background analysis that is the hallmark of good decision-making, is lost. This continuing failure to appreciate the big picture, if it affects all those folks involved in strategic decision making as a result of long hours at work over time, could explain the almost random performance of corporations and the failures we have seen to make even the most basic decisions right on a consistent basis, namely ensuring that the firm earns its cost of capital.
This degradation results in a constant watering-down of analysis since the simple tasks are done and the obvious connections made. But the competition can be assumed to make the same simple connections as well. Working smarter, not harder, has been a theme for the last 15 years, since automation and knowledge management become more accessible through the ready availability of information technology resources to almost all workers. While that may be true, What we’re learning, however, is that working harder is almost certainly not working smarter.