Optimizing Processes with Design of Experiments

Design of experiments, or DOE, offers a practical approach for exploring multifactor opportunity spaces. By actively manipulating factors according to a pre-specified design, you efficiently gain useful new understanding – even when you lack all the data needed to solve a problem.

This paper includes real-world case studies that describe how two organizations discovered best practices for collecting and analyzing new, relevant data simply and quickly. It is recommended reading if:

  • You need an efficient way to determine which process changes will yield the greatest gains.
  • Your organization has outgrown one-factor-at-a-time experimentation.
  • In the rush to get answers, you are sometimes forced to cut corners, limiting your understanding of the real drivers of process robustness, effectiveness and efficiency.
  • The time devoted to attempts at problem-solving curtails opportunities for innovation and process improvement.
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