In this week's simulation, one of the most critical aspects to successfully determining which experiments to run and how to design the experiments involved asking the right questions. A basic skill taught in DOE (design of experiments), Six Sigma, and Root Cause Analysis courses is how to ask the key questions. This usually involves starter questions like: "what is the current problem state", "why is this important/what impact does it have", "what is the measurable objective and outcome needed". From there, the problem needs to be broken down into where the failure is in the design and where it is in the process. What other key questions are there at the start of a root cause analysis?
When starting a root cause analysis, There are a few key questions that need to be well thought out. How to identify the issue at hand? Clearly define the issue being investigated. This sets the foundation for the analysis. What are the timeframes to achieve the issue? Determine the timeframe during which the problem has been present. Knowing when it started offers insights into potential causes. Where has the problem occurred within the issue? Identify the specific area where the problem occurred. This helps pinpoint possible factors related to specific processes, equipment, or environments.
In addition to the questions mentioned above, other key questions that can be asked include: When did the issue first occur? Where does the issue occur? Who is involved or affected? How frequently does the issue occur? What are the potential causes or hypotheses? Are there any recent changes or events that might be related?
All these questions need to be asked to determine the root of the issue and determine a solution to these issues.
Thank you for the question. I agree with others. However, I want to add some more questions which might be useful.
what are the conditions at the time of the problem? I think it is important. If proper conditions are not applied then the result will be different. I have also witnessed it during this course simulation. Therefore, this question is very important.
What are the consequences of the problem? It is important to evaluate the consequences. Therefore, we can understand the importance and urgency of the problem. In addition, whether it is affecting the desired outcome.
All of the questions above are excellent and I would like to add a few other important ones. "How frequently does the problem occur?" and "Are there any variations between instances?" can help gauge the broader impact of the problem. Distinguishing variances between instances can help provide a more holistic idea of the root cause, possibly clarifying whether is it a fundamental systemic issue or a sporadic anomaly.
Another good question may be "Is there a possibility that a recent change or development caused the problem?" This question implores the analyst to view any recent changes that may have caused the issue. Unexpected outcomes of changes can often lead to problems down the line.
One more question I would like to add is "Is there a record of precedence or a similar problem occurring?" If there have been similar problems, documentation on it certainly exists, and potential causes and solutions from those previous problems may be helpful in identifying and correcting the present one.
Many of the past responses include questions like what, when, and where. I think these are important questions to ask, and I'd like to add questions about conditions, reproducibility, and the overall effect. At the start of a root cause analysis, examining the conditions present during failure—such as environmental factors, user handling, or system interactions—helps identify contributing variables. Assessing whether the issue is reproducible distinguishes between random occurrences and systemic problems, which helps guide the investigation. Understanding the overall effect on performance, safety, and reliability ensures the root cause is addressed in a way that prevents future failures and minimizes impact.
You're absolutely right—asking the right questions is the foundation of a solid root cause analysis. In addition to the ones you mentioned, another key question at the start of an RCA is:
"Has this issue occurred before, and if so, under what circumstances?"
This helps identify patterns, past failures, and whether the problem is recurring or new. It also provides insights into whether previous solutions were effective or if something was overlooked.
There are various factors that are asked when the task is to find the root cause. Root cause analysis can be likened to a never ending nested doll stack, where one doll is opened to find another. When the engineering team performs a root cause analysis, it begins a wider scope, asking questions such as "How does this failure affect the entire entity" and "what are related components to this failure". Then, the team takes a detailed look, including various testing in order to validate their theories, as to why the failure occurs, and what key or minute factors attribute to it. This can be especially difficult when it is not so clear what is causing the failure to occur. Therefore, every proposed root cause needs to be validated in order that the real root cause is not overlooked. This can be from the physical components of the device, to the manufacturing, or any step in the process. It is important to look at trends in data of when and how failures have been occurring, and to come up with a basic conclusion. Then, the aforementioned dive into digging deeper begins. When a root cause is found, design changes and component reconfigurations, or design process changes, can be made and implemented so that the failure is reduced.
