Which characteristics are needed for effective and efficient problem solving? Is it theoretical knowledge and experience, procedures, strong statistical background or ability to take decision base on our intuition? The key attribute needed for problem solving is ability to ask right questions and to let the work be lead by them. When right questions are asked getting right answer is just a formality. In the rest of cases it is necessary to be able to collect appropriate data, analyse them and then base on it find answer for asked questions and take correct decision.

We need to remember that problem solving approach/process is not a function of number of tools and techniques which we know. Efficiency of problem solving depends on the way how we are taking our conclusions. Problems, which we solve, are different and different need to be methods of observations, asking questions or testing. The way how engineers (not only) approach problem solving need to depend on particular situation in which we are. Usage of this tool or other should not be a goal itself but should be driven by concrete situation (its context) and question, which we’re trying to answer.

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Expected Training Results

After this training participants will:

  • Understand that type of the problem drive the way how we are going to solve it
  • Understand role of right questions in problem solving process
  • Be able to make a diagnosis of current situation and apply proper strategy to answer asked question thanks to practical and sequential usage of PDCA cycle
  • Be able to document problem solving process using available tools like e.g. Thought Map, 8D Report, DD/DW Report, A3 Report etc.
  • Process Engineers
  • Quality Engineers
  • Technologists
  • Leaders
  • Managers

Expected Training Results


Psychology of problem solving. How type of problem determines strategy of solving it lecture
Role of questions in problem solving process lecture + case study
Y= f(x) + noise, cause-effect relationship between inputs and outputs of the process with strong consideration of potential noise lecture
PDCA cycle and sequential approach in problem solving lecture
Methods and techniques used during problem solving process: 5Why, Ishikawa Diagram, Pareto Chart, Priority Matrix etc. lecture + case study
Introduction to variation and overadjusting of the process (Quincunx ? hands-on which shows why it is so important to distinguish between two types of variation) lecture + practical exercise
Process Map and Rate of Change Table as tools for increasing and retaining knowledge about processes lecture + practical exercise


Introduction to sampling ? how to plan data collection to answer our questions lecture + practical exercise
Introduction to sampling strategies ? Two-level Sampling Trees, construction and data analysis (Practical, Graphical and Quantitative) lecture + practical exercise + Minitab
Measurement System Evaluation as a MUST to effective and efficient problem solving lecture + case study
Methods of experimentation on the way to find optimal and sustainable problem solution lecture + case study
Documentation and templates which support problem solving process and knowledge retention: 8D report, DD/DW report, A3 report ? best practices lecture + case study