Quality of Information - A Critical Input to Industrial Problem Solving

Jun 2, 2015 4:25:26 PM

Fruitless debate occurs often when intending to solve industrial problems.  Such time waste is a function of (1) poor problem solving process and (2) worthless data and information. This short review will focus on the quality of problem solving information.

When  a problem occurs, we can in a reasonably short space of time determine an initial problem statement, and this should drive our data collection for problem solving. There is now hope of forming logical and usable knowledge in respect of a problem, unless we start at a focused problem statement.   The important point is that lots of data is available when a problem occurs, however, only the minority of the problem data, properly collated will provide information of sufficient quality to solve our problem.

How would you then go about ensuring quality information for industrial problem solving?


  • Principle 1:  Identify the correct sources of information.  Determine “Who has the information?”

o   Find the people who were there, who observed the problem and those who experienced the effects of the problem (a purely interested party is unlikely to be a good source of information).

o   Identify all manual and automated data recording sources.

  • Principle 2:  Ensure that you have the “Correct Fault” and “Object” before proceeding to classify an information source as relevant.

  • Principle 3:  Focus on information sources who can point out the unique characteristics  of the problem.

  • Principle 4:  Ensure that you include at least a reliable subject matter expert in the problem solving team to assist with the logic and understanding of information.

  • Principle 5:  Use a structured and reliable problem-solving tool that will facilitate optimal team collaboration and will eliminate non relevant data and information, such as KandF CauseWise.

o   Answering each question in CauseWise carefully will ensure that the information describing what the problem “IS” and what it could be “BUT is NOT” will generate quality information that facilitates problem solving.

  • Principle 6:  Develop viable theories relevant to the problem solving information in the problem specification.

  • Principle 7:  Experienced people from the problem space have quality problem data in their heads that does not exist anywhere else.

  • Principle 8:  You can only determine the cause of a problem that can be substantiated by the information available.

Learn more about Industrial Problem Solving...

Adriaan du Plessis

Written by Adriaan du Plessis

Johannesburg, South Africa | Managing Director of the Global IT CSI Practice
Adriaan provides consulting, facilitation and implementation services for root cause analysis, decision making and business improvement as well as people development using proven KEPNERandFOURIE™ tools and techniques. As a world-class facilitator he focuses on the use of a divergent set of improvement and thinking tools to assist businesses to enhance value, specifically in Root Cause Analysis, IT Root Cause Analysis and Decision Making.


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