Problem-solving when you do not know the root cause Innovation Mike Cardus

In earlier posts, I shared some steps for identifying the problem using creative problem-solving through exploring the current condition selecting a type of problem,

Problem-solving is systematic and organized into six stages:

  1. Identify the problem
  2. Select the type of problem
  3. Apply the analytical tools
  4. Define a specific problem
  5. Apply solutions tools
  6. Compile ideas and implement solutions
Step 3: Problem-Solving Analysis

You examine the problem situation, background information, and data during the analytical stage. Creative thinking tools reveal possible causes and solutions—the tools to apply depending on the type of problem. For most problem-solving, we distinguish between the root cause, known and unknown.

3.1 Root Cause Unknown

With a problem for which the root cause is unknown, we must troubleshoot the problem, observe challenges, and determine the mechanism to create a solution.

Investigate Root Cause

Review the information gathered in earlier steps and propose potential models of the cause. Capture them in the “Propose Preliminary Cause Models” below. Identify gaps in knowledge or information collected or analyzed to help support or eliminate a cause model. Some key actions are:

  • Look for commonalities. Is the failure mode common only to a particular resource, machine, tool, person, batch of materials, time of day, time of year, particular environmental conditions, storage conditions, temperature, or specific combinations of resources and circumstances?
  • Look for Interactions. Is the failure mode associated with specific combinations of resources, machines, tools, etc.?
  • Look for Trends. Did the failure occur gradually over time, or usage due to an “aging effect,” etc.? What change(s) is coincident with the time or aging effect?
  • Run Segmentation Experiments. Perform experiments to isolate (segment) where, when, or what circumstances are needed to create the problem.

Summarize Conclusions

Summarize the information gathered in earlier steps and from the root cause investigation above. List critical conclusions that can be drawn and how the data was validated.

Data Conclusion Table

 Data / AssumptionsConclusionHow data was validated

Psychological inertia, erroneous data, wrong assumptions, and false conclusions are often why most root causes are not identified. It is essential to keep an open mind and eliminate psychological inertia. It is critical to validate and challenge all data and assumptions. It is necessary to prove the user data is valid and ensure the correct conclusions are drawn. Below is a list of the common reasons the root cause is not identified and recommended actions that the problem solver should take to address those issues. 

Frequent reasons root cause is not identified.
  • Experience: too much experience can lead to psychological inertia and drive thinking in a “trained” direction closing off new ideas.
  • Fixed thinking techniques: repeating the same steps and using the same methods leads to repeating the same result and creating the same ideas.
  • Group Think: over time, a set of individuals working on a project will tend to think the same way and believe the same conclusions and results. This group mindset leads to psychological inertia. As new members are introduced, instead of pursuing new ideas provided by “a fresh pair of eyes,” the group tries to assimilate new members to current thinking.
  • Model Worship: a specific “favorite” model is pursued, and alternatives are dropped.
  • False Information/Incorrect Data/False Assumptions: this may be due to how the data or information was collected. For example, incorrect calibration of measurement standards or inaccurate information and facts have been obtained or assumed.
  • False Conclusions: for example, the sun rises every day in the east. False conclusion – the sun revolves around the earth.
  • Hidden Resources: contaminants or secondary or derived resources cause the problem.
  • Hidden Mechanisms: mechanism may be a new or unusual phenomenon or be an effect outside the problem-solvers field of knowledge.
  • There is More Than One Problem: therefore, more than one root cause.
  • Insufficient Technical Knowledge: this is rarely the reason for a problem’s root cause not to be identified. Commonly such gaps in knowledge are quickly closed and problems solved.
Actions to address common issues that impede root cause determination
  • Have new people check all data and information to provide fresh thinking.
  • Determine whether the conclusions can be wrong (be highly critical of all findings).
  • Check the information is indisputable; assign a specific person (owner) responsible for checking the data.
  • Physically check and visually witness information or data rather than accepting validation from others.
  • Constantly challenge calibration methods.
  • Determine what potentially hidden or secondary resources might be present and how they could cause the problem.
  • Describe a new or unusual mechanism that would have to exist to cause the problem.
  • Demonstrate the problem is not merely an outlier (a rare but expected event, therefore not a “problem” at all).

Independent validation of each piece of data, assumption, and conclusion is needed. It is helpful to list all assumptions and conclusions and challenge each in turn. Re-checking the information and using different personnel is necessary to avoid psychological inertia.

As the problem-solving team moves through the steps, they discover and construct solutions.