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Follow-up investigations with binary classifications

Generally, there are three steps for an organization to be effective at problem-solving, but many groups may implement just two. The first step is to have an organization willing to thoroughly problem-solve by selecting the right tools. The organization must acknowledge that each problem cannot be solved with something as simple as a 5-why, nor does every problem require the assistance of complex problem-solving tools such as the Shainin System™. The second step is to commit to having a set of triggers that classify the problem as complex and worthy to allocate the necessary resources to solve due to its statistical significance. Flippantly deciding to solve or not solve a problem based on organizational authority is not sustainable. Third, you must have a process that evaluates the effectiveness of the corrective actions. Yes, we need to follow up.

Regardless of whether the problem has occurred again or not, the follow-up component is essential for the organization to grow and mature at problem-solving. The tools and approaches used to accomplish an effective follow-up are not as mainstream because they do not have a heroic appeal. However, the corrective actions require an evaluation of their effectiveness with binary classifications and definitions. If we define our binary classifications correctly, we can look at our completed corrective actions as one of the four options; true-positive, true-negative, false-positive, and false-negative.

Table 1 - Binary classifications for investigation follow-up


This is the one that we strive for when applying our problem-solving approach. There is an endless list of tools and resources that glamorize an ability to identify solutions that become true-positive. Regardless, each problem-solving technique is designed to uncover actions to prevent or reduce the probability of the problem reoccurring. However, the corrective action is only labeled as a true/positive if the problem has not reoccurred, and there is ample evidence that the corrective action addressed the cause to prevent reoccurrence.


Sometimes we implement corrective actions from an investigation due to scope creep, an emotional lineage to the problem, or not addressing the right cause. Supplemental to these corrective actions, we may sleep better at night because the problem hasn’t necessarily come back yet regardless of the corrective actions. These corrective actions are true/negatives, or situations where the problem has not returned, but the corrective action was not necessary after further review. These true/negatives can be looked at simultaneously as waste or maybe a little bit of luck.


Sometimes when the problem returns, the corrective actions previously identified and applied get questioned. If the problem has returned due to not identifying the underlying cause, these previously completed corrective actions are called false/positives. These could be implemented as corrective actions derived from the investigation of inaccurate data or false assumptions due to not identifying the actual cause.


Similar to the false/positive, unfortunately, the problem has reoccurred. However, the difference between a false/positive and a false/negative is that the false/positive is the corrective action implemented based upon not identifying the actual cause, whereas the false/negative is the corrective action implemented where addressing the wrong cause. Therefore, the false/negative is when the problem has returned, and the investigation identified the wrong cause. The investigation led us to believe that the actual cause was insufficient and the cause addressed with corrective actions was the wrongly selected cause.

Following through to verify the effectiveness of your corrective actions identifies a variety of opportunities. Not only does it address the problem initially investigated to determine the corrective action’s effectiveness, but it also identifies the effectiveness of your problem-solving techniques. It is the departments that put this analysis in place that become the problem solvers that are credible in solving the next problem that surfaces.



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