Measuring business and its performance is usually done by measuring key financial indicators such as profit, turnover and return on investment. These are good measures for the overall performance of the business but give little if any information about the underlying daily work done in the company. Proper business process measuring using Lean Six Sigma tools gives the manager data and information that makes problem solving and business improvement possible.
Why do we measure?
Trust is good, measurement is better.
Lean Six Sigma business improvement revolves around the Y = f(X) concept. In other words: if you want your business results Y to change you need to change what you do X. Measuring Y, or the results, gives very little information about how to improve the system. Learning to know the inputs, the Xs and how they affect the output is the key to improving the business. Typically, for one Y there are several Xs. The key to success here lies in quantifying the inputs into measurable units and to change them in a way that improves the result Y. Hence, Lean Six Sigma is all about the X, trusting the Y = f(X) will follow.
Measure the process, not the result!
If we shall not measure the result, what shall we then measure? Meters can be divided into three categories: Result-, System- and Process Meters. Result meters are reflecting the Ys, System meters are reflecting the f(X) and Process meters reflect tha actual doing, the Xs. Once we understand the relationship between the X and Y, we can focus on improving the doing, the X. Therefore the Process meters are of most interest when improving business.
Use the X-Y matrix to select proper meters
Meter selection can be done with the help of an X-Y matrix, a matrix of expected outputs versus inputs. Each input is evaluated according to its’ weight on the output. The overall score of the inputs and the category: result, system or process, is used to select the inputs that are being monitored. A proper measurement requires a Measurement System Analysis MSA to verify the reliability of the measurement results.
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