Fixes that Fail: Why Faster is Slower


Mqost of us are familiar with the paradox that asks, “Why is it that we don’t have the time to do things right in the first place, but we have time to fix them over and over again?” Or, more generally speaking, why do we keep solving the same problems time after time? The “Fixes That Fail” archetype highlights how we can get caught in a dynamic that reinforces the need to continually implement quick fixes.

The “Fixes That Fail” Storyline

In this structure, a problem symptom gets bad enough that it captures our attention; for example, a slump in sales. We implement a quick fix (a slick marketing promotion) that makes the symptom go away (sales improve). However, that action triggers unintended consequences (diverts attention from aging product line) that make the original symptom reappear after some delay—often worse than before.

Some people know this dynamic from mismanaging their finances. Whenever they run short of cash, they use their credit cards to “solve” this shortfall. Unfortunately, the additional debt increases their monthly credit-card payments, causing them to run short of cash the next month. They again “fix” the problem by using their credit card to cover an even greater shortfall (because more dollars are going to pay the finance charges on the debt). Many juggle their debt among several credit cards by paying one card off with checks written on another. But with each round, the debt burden grows heavier and heavier, which may be why we currently have the highest consumer debt levels in history and record personal bankruptcies—all in a booming economy! This is the basic storyline of the “Fixes That Fail” archetype Let’s take a closer look at how and why this systemic structure behaves the way it does.

Of Heroes and Scapegoats

Many managers report that their organizations experience certain problems over and over again. Most seem to accept these challenges as a fact of life. Only a few see the cause as “hard-wired” into their businesses. However, from a systemic perspective, whenever patterns of behavior recur over time, they must be driven by structures that are designed into the way the system operates—intentionally or not. To better understand why we would create such structures, we need to take a closer look at the behavior of this archetype (see “The Hero-Scapegoat Cycle”).



When a problem symptom becomes a crisis, we look for a hero to drive it back to acceptable levels using quick fixes. By the time the unintended consequences of those fixes cause the problem symptom to reach crisis level again, we’ve promoted the hero. We therefore scapegoat the new manager for failing to keep the problem under control.

Organizations usually have target levels against which they monitor performance; for example, inventory levels. If a problem symptom exceeds its desired level, such as excess inventory, we may notice this trend but not act on it right away, because we’re focused on other, more dire crises. When the symptom eventually reaches crisis proportions, we then shift our attention to that problem. At this point, because the situation has become so dire, we often look for someone who can “save the day” (e.g., slash inventory levels). Sure enough, we find a person who can drive the symptom down to the desired level in a hurry and then reward her with a promotion.

In the meantime, the delayed consequences of the hero’s actions (lack of product availability due to low inventories) begin to have an impact, and the problem symptom returns (higher inventory levels). When it again reaches the crisis level, we blame the person who is currently overseeing that function for failing to do his job, fire him, and look for our next hero. However, in this archetype, it may well be that the first hero is the person who put the current crisis in motion and that the scapegoat is the person who set the stage for a more lasting solution to take hold. But, because of delays in the system, these realities are often obscured.

Win Today, Lose Tomorrow

So, why do so many organizations fall into the “Fixes That Fail” trap? Why can’t people recognize the vicious cycle that keeps repeating the same patterns of events? One of the reasons is that the delays in the system mask the true nature of the cause-and-effect relationship. The narrow time frames that often drive decision-making in organizations also compound the problem.

For instance, our results are more likely to deteriorate over time if the delay for the unintended consequences to affect the system is long than if the delay were shorter. This is because, without the feedback supplied by the unintended consequences, the “improvements” actually appear to make things better in the short term (see “Fixes That Fail over Time”). And yet, when we view the situation from a longer time horizon, we find that today’s “desired” levels are far higher than yesterday’s “crisis” levels. From a longer perspective, we see that those short-term successes are part of a series of steps toward longterm failure. This pattern shows how companies can go bankrupt even as individuals are continually rewarded for doing a great job.



Over the short term, we applaud the progress we are making. And yet, when we view the situation from a longer time horizon, we find that the current “desired” levels are far higher than yesterday’s “crisis” levels used to be. Thus, those short-term successes are actually part of a series of steps toward long-term failure.

What Alarm Bells?

Another problem associated with this archetype can occur even when we do make changes so that quick fixes are no longer needed. Now, this may sound like a good thing, but it all depends on how we do it. Unfortunately, many organizations solve the problem by adapting to the poorer performance level, which then becomes the new norm (or desired level).

For example, we may have had a desired first-run capability of 95 percent or better from our production line (that is, 95 percent of our motorcycles run the first time off the assembly line), but we often find ourselves operating at a crisis level of only 90 percent. Because our plans are based on the higher level, our ability to provide predictable performance drops.

In order to improve predictability, we lower our desired level to one we know we can achieve (90 percent), with plans to eventually bring our capability back up to 95 percent. The danger of such a move is that once we have factored the poorer performance into operating plans, it becomes less visible as an issue that needs attention. In other words, what once caused alarm bells to ring no longer rings any bells, because we have in effect disconnected them. Although we no longer reach the crisis level or require frequent fixes, we have embedded the poorer performance in our system, and we no longer notice it.

In this situation, we have fixed our problem by getting caught in a different archetypal structure called “Drifting Goals.” We end up “fixing” things by changing our criteria of what constitutes a crisis.

Finding Fixes That Last

Of course, the answer is not that we should never apply quick fixes. There are many circumstances for which we absolutely have to implement short-term solutions. The danger lies in failing to recognize that all quick fixes are merely stopgap measures that buy us time to get to the root causes of those problem symptoms.

One of the most important points to address about this archetype is the relationship between the delay for the unintended consequences to show up and the timing of organizational performance assessments. If you suspect that you may be caught in a “Fixes That Fail” dynamic, look for a repeating pattern of quick fixes, determine how often these fixes occur, and compare that to the frequency with which you typically review performance. If the review time horizon is about the same as or shorter than the time between fixes, then try lengthening the time frame so that it’s at least three or four times the delay period. This will help provide a more accurate picture of the actual “progress” being made.

Daniel H. Kim, Ph. D., is publisher of THE SYSTEMS THINKER and a member of the governing council of the Society for Organizational Learning.

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