Wrench time and wrench time studies are two of the most misused, misunderstood, and painful to deal with elements of maintenance benchmarking for three reasons:
- different definitions and standards
- data that is skewed by the act of collection
- overzealous comparisons of dissimilar metrics from different locations
The first struggle is around the definition or standard for wrench time. What is in? What is out? Is travel time part of wrench time? How much is too much? Is prework wrench time? Is trouble shooting wrench time? You need to answer these questions and more to get something standardized for your location. A good place to start is the SMRP Metric for wrench time but my guess is that you will need to add additional clarifications to make it relevant to your site.
The data is not accurate. By virtue of focusing on the data it changes the behaviors. If you tell me you are going to watch me type out this blog and count my mistypes I will by nature slow my typing and make less errors. The same thing happens when we do wrench time studies so the numbers we get will be different than actual. I suggest the use of something known as a DILO instead of typical stop watch time studies or other tool driven methods. In a DILO or Day In The Life Of you work with the craftsman to understand what gets in his way or what irritates him as he tries to complete his daily work. You are with him or her through their day learning based on their experiences. This approach is more about helping them and less about "watching and judging" them. In the end, you identify problems like missing permits, lost parts, and wrong tools and you see first had what that is costing them in time and patience without driving a wedge between parts of the organization. If you want to talk more about DILO send me an email and I will share with you tips and tricks based on my experience.
Some days it seems that everyone thinks they should compare their wrench time numbers to everyone else. This one is common for many metrics and KPIs but as I have suggested in the past it would be best if the sites looked at their ability to improve the metric and talked about what their delta over the last quarter was as opposed to the raw number. Then they could talk about the specific actions they have taken to get that delta. The raw metric are just too different in most cases to be compared and bad decisions can be made with bad data from bad comparisons.
Now I know I did not necessarily solve anything here but I hope I have provided a few ideas that might help as you calculated and evaluate your maintenance wrench time on your quest to reliability now.
You make some very good points about wrench time and how studying the data will change it. Unfortunately, I've seen individuals that instead of straightening up and putting on their best face, they actually overemphasize the obstacles in their way to get a reaction.
ReplyDeleteI've had really good luck with DILO (although I admit that I've never used that term). I'm constantly surprised at how much useful information I can get that would have taken me 10 times as long to glean from the data. I might even suggest WILO (Week In the Life Of).
Interesting and spot on article. I have found shadowing equipment operators on a factory floor - taught me more than any set of data I imposed on them to collect. Sure, tracking some things makes sense, and it has to make sense to those collecting and recording the information. Cheers, Fred
ReplyDeleteShon,
ReplyDeleteGreat post with a valid argument for not putting a lot of value in such a KPI, especially for comparison across different companies and organizations for the reason listed. We must seek out better ways to measure our productivity on the shop floor.
Mark J. Cundiff
Probably the problem lies in the fact that benchmarking is kind of dated. Even in the industrial sector, certain techniques tend to get "dated" real quickly.
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