StableOps: a faster pace with data based learning
Roy Koers
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Have you ever wondered why Formula One teams perform better every year? It’s not only about having the right car, gear or driver. It is data based learning that makes the difference.
Sure, we all want to improve our business. But how do you know where to improve and where to invest in? For those who are unfamiliar with Formula One: Sunday is race day and the two days before are used for practice runs and qualification. The goal of practice sessions is to learn how the car is performing on that specific track and how to get stability. After these sessions, the team analyses the data and takes learning from slow laps.
When they find the root cause, improvements are made immediately; not only on the car, but also by the driver. Every round on the circuit should be the same, so he has a driving standard and should be able to learn from standard deviations to improve.
During qualification, the only goal is to drive one perfect lap (read: as fast as possible). Learning and improving is different here. Teams analyse their fastest lap and find opportunities to get faster, which is a matter of thousands of seconds and mm’s of track space. During the actual race, it is all about being constant and saving tyres and equipment, rather than going for the fastest lap.
Data based learning in your business
How does this apply to your business process? Products on your production line flow every single day in the same way, like F1 cars do on the tracks. If you want to improve your capacity without CAPEX, it is essential that you learn from the production performance. The data shows what the fastest production days were in the past.
So, you can set your production target on the 25% best output. Then implement a data based learning structure that enables your operators to explain daily why production was below target. From these explanations root causes need to be found with a multidisciplinary team. To increase stability, work out and implement the solutions for the 25% worst days of the last 4 weeks.
Now you can drive a more stable race every day and you’ve created a data driven learning environment. Once you have found sufficient stability, try to find opportunities to improve your best days. At detailed levels of your installation, there are always weak spots, which can be improved, often without CAPEX.
In a high-tech performance sports like Formula One, where rules prohibit teams to do big investments during the race season, teams are forced to analyse the data and solve root causes. I think we all can learn from them and use it to improve our daily business.
At R&G we help clients getting the right metrics and data, guide them in analysing, finding root causes and improve the business. In the data, we see opportunities to improve, whether it’s coming from the human part, from the machines or other sources. Ladies and gentlemen, start your engines!
Roy Koers is Business Process Consultant at R&G Global Consultants in The Netherlands.
