Organizing an Ishikawa Chart for Complex Analysis

Introducing the Enhanced Perkin Tracker

Published: Monday, January 23, 2023 - 13:03

Almost seven years ago, Quality Digest presented a short article by Matthew Barsalou titled “A Worksheet for Ishikawa Diagrams.” At the time, I commented concerning enhancements that provide greater granularity. Indicating that he would probably have little time to devote to such a project, Barsalou graciously invited me to expand upon his work. As one of the few positive outcomes of the recent storms that have raged across the United States, I’ve finally completed that task. In thanks to Barsalou—and with tribute to his mentor—I refer to this effort as the “Enhanced Perkin Tracker.”

For those who might be unfamiliar with the Ishikawa diagram, it’s a graphic problem-solving tool used to relate multiple potential causes to a single effect in a rational manner. Based on its shape, it’s easy to understand why it’s often referred to as a “fishbone” or “herringbone” diagram.

As Barsalou points out, the Ishikawa diagram is a powerful tool for facilitating brainstorming and, to some degree, organizing ideas. But because no branch, or sub-branch, has any more or less weight than any other, it provides little help in evaluating or tracking various hypotheses (figure 1).

Figure 1: Typical Ishikawa format

Fortunately, in the vast percentage of occurrences, the potential root causes are relatively few. This makes tracking and managing the process straightforward and proportionately painless. In fact, it’s often the case that only three or four arms of an Ishikawa chart may be populated. With only a handful of options, prioritization presents few conflicts.

But consider the other end of the spectrum. Your launch vehicle rises into the bright blue sky over the Atlantic Ocean. Everything is going perfectly... and then, 139 seconds later, catastrophe strikes. The exceptionally reliable booster has exploded. Something has gone wrong! Somewhere within that finely engineered system, some single point of failure has triggered a rapid unscheduled disassembly event, scattering vehicle and payload across many square miles of the Atlantic. Significant as the immediate economic impact is, the repercussions could be far greater. Can other boosters be trusted? When can flight operations resume?

With myriad possible points of failure and potentially catastrophic economic repercussions, it becomes imperative to determine the root cause and implement corrective actions in the most expeditious and economical manner possible.

To quote Barsalou, “In an ideal world, all hypotheses would be immediately tested, but resources may be limited, so those believed to be highly linked to the problem should be tested first. Hypotheses with a weaker connection to the problem may also have a high priority for evaluation if testing them is quick, easy, and inexpensive.”

With that rationale in mind, imagine, if you will, tracking all the conceivable “what ifs” and “maybes” using only an Ishikawa chart. Of course, there would be untold hosts of supporting documents. Evidence, suppositions, possible tests.... How does one rationally organize this haystack of data and prioritize efforts in a search for the needle therein?

The Enhanced Perkin Tracker shown in figure 2 (an Excel spreadsheet that you can download here) allows the user to consolidate and organize all this information in one document, and provides a consistent method to prioritize and track investigation and testing. Obviously, all those supporting documents aren’t supplanted by the tracker, but at any moment in time, it provides immediate situational awareness.

Figure 2: Enhanced Perkin Tracker spreadsheet

With the tracker spreadsheet, hypotheses may be recorded, categorized, and given a numerical rating based on experience and past performance. For each hypothesis, one or more evaluation actions may be added and numerically rated. In the example shown, actions are rated on cost, time required, and perceived likelihood of success. (Likely, quick, and cheap will rate high; unlikely, long duration, and expensive will rate low.)

Individual ratings are multiplied together to provide an overall rating of each hypothesis.

With rankings in hand, action planning can proceed, responsible functions or persons assigned to each action, and appropriate completion dates forecast. As the investigation proceeds, anyone, at any given time, can access a real-time status. Further, should test results indicate the need, ratings may be adjusted, quickly providing revised priorities.

Categories, numerical ratings, and root cause status are all entered using drop-down menus as shown in figure 3. (Please note that, due to size, some dropdowns require scrolling to view the entire list.)

Figure 3: Drop-down menu data

To maximize utility, note that each drop-down has the capacity for both expansion and modification. For instance, the time selections could be extended or further subdivided for a specific issue. Likewise, the numerical ratings may be modified. Perhaps you would rate experience as “1, 3, 5” or “1, 3, 7,” rather than “1, 2, 3.” Since a blank entry defaults to a rating of 1, a column can be ignored without any modification.

I’m sure that in some areas there could be a desire to add another rating group; existing groups may be easily replaced by others through simple replacement of the appropriate data fields.

Lastly, rating columns may be added by judicious use of cut and paste, and appropriate editing.

Hopefully you will find this tool to be of use—but hopefully never at the 139-second mark!

About The Author

Alan Metzel

Alan Metzel is a senior principal quality engineer at Northrop Grumman Mission Systems, with responsibilities for metrology equipment, methods, and training supporting model design and fabrication, and nondestructive examination. He serves on the Coordinate Metrology Society board of directors, the CMS Certification Committee, and the executive committee of the Cumberland Valley Chapter SAE. He received his Bachelor of Science in mechanical engineering from the University of Tennessee (Knoxville) and has prior experience in high-speed sheet metal manufacturing, gear manufacturing, and building armored vehicles.