Of the numerous RCA methods used, the one you choose depends on the depth and nature of the problem. Factors such as the number of contributing causes and how many assets the problem covers can help you determine the right method.
The most straightforward way to perform root cause analysis—but also perhaps the most narrow—is the five whys method. This technique basically involves asking “Why?” five times to really drill down to the root cause of a problem. It looks something like this:
And so on until you can’t go any further.
This method is great for a problem that’s simple (not a lot of data involved) or that involves human factors. For example, an office’s air conditioner may be short-cycling due to the thermostat being set too high. Moving one level down, the thermostat is set too high because there aren’t any controls in place to keep employees from doing so, and you’d move on from there.
It doesn’t do quite as well with more complex issues involving multiple factors. In those cases, you’ll want something with a broader approach.
A visual way to handle problems with multiple moving parts is fault tree analysis. This method sorts through potential causes, and your tree branches out as you move down each line.
This tool lets you examine multiple potential causes at each level, allowing it to branch out into multiple directions. For example, a centrifuge might be running into issues due to the volume of material you’re putting into it, but there might also be some electrical or mechanical issues at play too.
Fault tree analysis works well with complex technical issues since you can logically compare multiple root causes at once. However, it doesn’t leave much room for hypothetical possibilities or for general brainstorming.
Another visual way to conduct root cause analysis is a fishbone diagram (also called an Ishikawa diagram). With this tool, you’ll look at the potential causes of an issue under different categories, each of which forms a branch in your diagram. Typically, your categories include:
Fishbone diagrams work well with a “five why” approach since it lets you plumb the depths of each category. At the end, you’ll have multiple root causes, giving you a fairly good representation of what the full breadth of systemic issues might be. However, they’re far less technical than fault tree analysis, and therefore tend to work best for general hypothesizing.
What are the most common root cause analysis (RCA) mistakes and how do I avoid them?
Root Cause Analysis
Root Cause Analysis Explained | What is RCA?
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