Common Cause: How Six Sigma Can Drive Better Management Reports
It's not uncommon for a company to track its performance solely in terms of conformance -- and nonconformance -- to plan. What many organizations don't realize, though, is that this method of performance measurement can drive the wrong behaviors among employees. Nonconformance tracking can be appropriate in monitoring product quality when there is no question whether a product is satisfactory. But nonconformance tracking when comparing financial results with expectations or goals can lead to destructive behavior that actually erodes long-term business performance.
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An exclusive focus on making the month's numbers often leads to the expenditure of a tremendous amount of energy on the narrow purpose of living up to promised or budgeted financial targets. Krispy Kreme shipped donuts that managers knew would be returned so that they would meet their quarterly objectives, and the Enron management team made notoriously poor decisions to meet corporate financial goals. These examples are extreme, but they are just the tip of the iceberg. Weak assessment processes lead to wrong behaviors on a much smaller scale in all kinds of companies every day.
An approach to performance measurement that I call "Smarter Six Sigma Solutions (S4)" or "Integrated Enterprise Excellence (IEE)" can open managers' eyes to ways in which the metrics they've chosen are driving the wrong employee behaviors, and can help them focus improvement efforts on actions that can truly impact performance.
Different Solutions for Different Problems
The biggest mistake management teams tend to make is responding in exactly the same way to all instances of nonconformance. In every realm of corporate management, there are two types of variability. One is what Dr. W. Edwards Deming, known for management practices he pioneered in post-World War II Japan, called "special cause." These problems result from short-term glitches in a process, such as faulty product assembly by a new or temporary employee. Deming called the other type of variability "common cause"; these problems result from situations such as the predictable variability of suppliers' raw materials or the typical variability that a process experiences due to differences in people or machines.
When an organization responds to special- and common-cause issues in the same way, it will fail to solve most of the problems that arise. Regardless of the cause of perceived nonconformance, operations staff will go into a firefighting mode whenever they are notified that a product, service, or financial result is not meeting specifications or planned objectives. They may resort to playing the blame game, and the problem may be "resolved" temporarily with Band-Aid changes or disciplinary action.
To understand how counterproductive such a response is for most variability in a company's outcomes, consider Deming's estimate that 94 percent of problems result from common-cause variability and only 6 percent result from special-cause variation. This means that the vast majority of nonconformance situations require modification of the system itself.
Successful executives continuously analyze their systems to identify and eliminate, or at least reduce the frequency of, common-cause nonconformance. How do they do that? By taking the right process-improvement corrective actions, which they determine based on the reports they use to assess performance relative to specification limits or goals.
How Reports Drive Bad Behavior
I'm not breaking new ground by saying that what we measure is what we get. It's been said before. But many companies continue to use metrics that lead to the wrong kinds of behavior. Consider, for example, a call center's measurement of duration of hold time. This metric may make good sense from a distance for an executive who wants to assess customer satisfaction. Long hold times would presumably correlate to customer dissatisfaction. However, the metric has the potential to drive the wrong behavior unless safeguards are implemented to prevent abuse.
To see how, think about an operator striving to achieve the target for this metric during an understaffed peak call period. His strategy for meeting his hold-time goal might be to periodically pick up a line that is on hold, ask the caller to hold for longer, wait for a reply, and then quickly place the caller back on hold again. It may not be bad policy to check with callers and ask whether they can continue holding, but this behavior should not simply be the result of an employee wanting his duration-of-hold-time metric to look good. A call-center business looking at hold times as a leading indicator of customer satisfaction should,instead, capture the total time elapsed from a caller's initial connection until she speaks with the appropriate person.
Many companies, recognizing that their metrics are sending employees the wrong message and providing faulty incentives, have rethought the measures they use to gauge performance. But for most, the process stops there. That's a shame. Just as they need to put energy into selecting the right metrics, corporate managers should think about whether the data presentation and assessment formats they use will lead to the right employee behaviors.
