A somewhat recent experience prompted me to re-read portions of Donald Wheeler’s outstanding book, Understanding Variation: The Key to Managing Chaos, with its section on the three ways people can improve a metric or a target (he gives credit to Brian Joiner):
- They can work to improve the system
- They can distort the system
- They can distort the data
I’ve always observed that people are incredibly clever in figuring out how to game a system to their advantage.I’ve seen it (in a very positive and worthwhile way) while observing an outpatient cancer treatment center, where repeat patients learned which appointment slots tend to get delayed the least (patients learning how to NOT waste time waiting for cancer treatment, you can’t argue with that).The patients’ actions aren’t purposely delaying other patients, so nobody is being harmed.
In most cases, though, somebody or some organization is being harmed by more selfish gaming of the system.It’s sometimes easier for people to distort the system or to distort the data in order to get rewards, be it a pat on the back or an annual bonus check.
One time, with a client, we were measuring the batch sizes of specimens being delivered to the laboratory.Batching of specimens (drawing blood from 10-15 patients before sending it to the lab) was a big contributor to “turnaround time” (cycle time) for the lab.We thought we had explained how we wanted specimens delivered in smaller batches, even if that meant it took more time to do the blood draws and specimen collections.We were measuring the size of the batches for a while until somebody tipped us off to the distortion.
Some of the phlebotomists (employees who draw blood) were taking a batch of 12 patients’ specimens and shipping it down to the lab in four sequential batches of 3 patients each.This made the metric look good, but the lab was still essentially getting a batch of 12.How embarrassing, I thought.I was embarrassed that we hadn’t done a better job of explaining “WHY” we needed smaller batches. Since employees were gaming the system, I felt like there was a failure on my part.
Before jumping to the conclusion that people are being malicious or don’t care, I try to stop and think how their actions might be reasonable.Someone on our team said, “maybe they didn’t understand that it was a turnaround time issue, maybe they thought the tube system physically couldn’t handle large batches?”
Rather than beating up on the phlebotomists, here are our next steps:
- Re-iterate to them WHY we need smaller batches,
- Explain what “true” small batches really are and how that benefits the patients
- Change our measurement system so we track not only the sizes of batches that arrive, but who they came from and at what time they arrived (so we can detect “fake small batches”)
- Emphasize to the phlebotomists that they need to make the extra trips to the tube station to send the smaller batches.We need to make sure that the lab will pay for enough resources to get the job done with the desired cycle time.
- Do more direct process observations and Standard Work audits to directly see if phlebotomists are following the correct process or not.
One of my own “kaizen” steps for the future will be to “FMEA” a new metric, to think through how people might game or distort the metric so we can avoid that kind of behavior.
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