Webinar instructor: James F. Leonard – Senior Consultant, Process Improvement and Statistical Methods
For decades, management consultants, academicians and practitioners have been searching for effective approaches to solving problems. The size of the problems may range from major non- conformance issues captured in an audit to small glitches in completing a capital project on schedule to massive, catastrophic failures of critical components or equipment. Regardless of the problems’ scope, American managers have nonetheless been searching for the Holy Grail – a foolproof approach to solving their problems.
Shewhart, Deming, Ishikawa, Wheeler, Chambers, Taguchi and others developed statistical approaches and methods for analyzing problems and testing solutions. Analytic statistical methods like statistical process control (SPC) and design of experiments (DOE) can yield a better understanding of problems and their causes in dynamic processes. Some people, however, question whether statistical methods can effectively harness people’s creativity and intuition when searching for solutions to challenging problems.
Kepner, Tregoe, Erickson and others developed and applied intuitive yet structured techniques for problem analysis. Brainstorming, cause-and-effect analysis, 5 Why and basic problem-solving methodologies have also been used with some success. Unfortunately, these approaches sometimes aren’t successful in capturing systemic variation and problems that may be due to interactions between and among several factors or causes, as opposed to one, single, identifiable “root cause.”
So, the search continues.
Join us as Jim Leonard introduces a technique that connects a structured methodology for root cause analysis to a statistical understanding of the nature of work to yield better, faster and more effective solutions to work problems. This webinar will open with an operational definition of the term “problem” and examine common pitfalls in problem solving that must be avoided. Next, we will examine a procedure for clearly defining and analyzing problems, followed by techniques for generating and testing possible causes of those problems.
Too often, however, the missing ingredient in basic problem analysis is applied knowledge of the theory of variation. In the face of one type of variation, systematic root cause analysis works very well. In the face of a different type of variation, apply this technique at your peril! It is not enough to be skilled in problem investigations; we must connect our skill with knowledge – knowledge of theory of variation. Connecting our skill to knowledge of theory is what moves us out of reactive, basic root cause analysis and into Advanced Problem Solving.