Maybe you have seen a formula similar to OEE = A x P x Q. I see this formula often, but for me it is a very impractical way to calculate the OEE. Let me show you why by comparing the three different ways to calculate an OEE.
In the last two posts I showed you the basics of the A3 report and the (possible) content of the A3 report. In this last post of this series, I would like to talk about common mistakes and the limitations of the A3 report. Overall, for me the A3 report is a minor tool to help organize the real work of problem solving, despite all the fuzz some make about the A3 report.
In my last post I wrote about four basic factors for an A3 report (one sheet / A3 size / with pencil / on the shop floor). This week I would like to show you what goes in an A3 report. The important framework here is PDCA (Plan, Do, Check, Act). However, in my view there is no single perfect A3 template that will fit all of your problems. Rather, an A3 is created on the go. Make the tool fit the problem, not the other way round!
If you know your way around lean, you surely have hear about the A3 report, famously named after the DIN-A3 paper size. It is also known as the A3 problem-solving sheet. The goal is to get all the necessary data on one sheet of A3 paper using pencil while you are on the shop floor. The A3 report is commonly used for problem solving, but also for project management or status reports.
Your production capacity is one important aspect of your production system. The capacity has to match your demand. If your demand is higher than your capacity, then you will not be able to supply the customer. On the other hand, if your capacity is higher than the demand, then you will have lots of idle workers and machines, which is not good either. The name is actually a bit of a misnomer, since capacity is the ability to contain things, whereas for a production system we are much more interested in the number of parts that are completed. In any case, capacity is important!
There is an inflation of key performance indicators (KPIs) in industry. In my last posts I have explained how KPIs are often wrong, and why bad and fudged KPIs are a huge waste. Yet, you cannot really run a larger corporation without KPI. In this post I will finally give some advice on (1) what you need to do to measure good KPI, and (2) how to avoid fudged KPI.
Modern manufacturing works with a lot of performance measures, often called key performance indicators (KPIs). Unfortunately, they are rarely accurate, and often even intentionally misleading. In my previous post I described some examples of commonly manipulated KPIs. In this post I would like to explain the ugly consequences of incorrect or manipulated KPIs. In a final post I will also show some ways that you can reduce this negative effect. But first, how do bad KPIs (and hence most KPIs) hurt your company?
Statistical measurements, usually called key performance indicators (KPIs) are found on pretty much every shop floor and in every company. Many management decisions are made based on KPI. Unfortunately, these numbers often are not reliable at all.
Mark Twain popularized the phrase “Lies, damned lies, and statistics.” Winston Churchill famously said, “I only believe in statistics that I doctored myself.” Hence, both men were wary of trusting numbers. You should be too!