The New Science of Fixing Things: Powerful Insights About Root Cause Analysis That Will Transform Product and Process Performance

by David J. Hartshorne

In order to solve any problem, a reasonably deep understanding of how and why things happen is required. This knowledge, however arrived at, provides the capacity to take action. Making the link between what we see happening and such knowledge is a process called diagnosis. But how can we go about diagnosing performance and reliability of engineering systems when the required knowledge is not immediately to hand? This book shows that truly excellent performance is achievable, and it is not that difficult. These insight are powerful, and yet seem to be largely unknown, almost secret. This is a management overview of what effective diagnosis should entail, and what is possible, highlighting both the core principles, and the very small number of strategies that are both effective and efficient. Their application is illustrated with case-studies.

122 pages, Paperback

Published March 20, 2020

Reviews

[Shhhhh Ahhhhh · Rating 5 out of 5]

Fascinating as a primer but it really just made me feel that I needed to read the case study book they referenced within. Especially interesting is the idea of using search methods in meat space for problem solving. This is different from many problem solving methodologies that I've dissected and is utterly foreign to what I experienced in my graduate program around data analytics. However, this isn't unfamiliar to me from the perspective of the theory of constraints. In fact, this procedural breaking of assumptions to shrink probability-space seems all too familiar in that way. Nevertheless, the idea that there is greater complexity involved in the tools that can be used here and that there are hard and fast rules is immensely interesting to me for personal and professional reasons. Along with a few ideas below:

1) Problems should be analyzed through limited scale experiments, not massive data collection (anyone who has worked as a data analyst will tell you that one look at a case study is worth days and weeks of munging and analysis).

2) Nothing "below the line" matters to root cause analysis. The types of data coming out of failure states typically (such as 'how many widgets were broken by this defective machine') tell us absolutely nothing about the root cause involved and can safely be discarded as useless.

3) All meaningful measures come as functions of movement. Rates, pairs of measurements as vectors, rather than singular dimensions or counts.

4) Understanding systems in terms of energy and movement is superior in that it exposes the problem to inferential and mathematical search tools that allow precise, quick, energy-efficient problem isolation.

5) These methods are not difficult once you know how to use them. (Unlike TOC) this methodology appears to be simple enough that you could codify it on a tear-sheet and keep it by your desk to save yourself a ton of headaches (and I intend to as soon as I can annotate it and after I've read the other book referenced).

6) [This is an implied point that appears nowhere explicitly in the text] Since all systems are about the movements of energy or material, all systems can be diagnosed and manipulated using this exact methodology, despite the fact that this was a guide written specifically for a manufacturing context.

[Ebie Tubbs · Rating 5 out of 5]

Amazing insight by the author with a world of industry knowledge and wisdom. Hartshorne shows such an ability to simply and accurately break down concepts, processes, and ideas. A great read for engineers, managers, and execs! I'd recommend this book whether you're just starting out in your career or you're an experienced veteran wanting to shed some of your industry's misconceptions.

[Renee Gagne · Rating 5 out of 5]

Excellent consultation firm!