In the days of “lot size 1” and “customer 1” process harmonization becomes more and more a pipe dream. If we like it or not. And with process harmonization performance, comparability goes down the tube as well. Or?
One rationale for driving process harmonization is to establish comparability between the various business entities. Why do you want comparability? Because you want to establish some sort of benchmark in order to understand where you perform better and where you perform worse. Comparability is the prerequisite for identifying best practices.
Fortunately, financial performance is easily comparable. Because it measures everything in dollars and cents. And it is naturally clear that effectiveness (profitability) and efficiency (cash) are the key finance metrics.
Unfortunately, there is no straight way to translate operational performance figures into financial performance figures. What is the financial impact of improving your customer satisfaction? What is the financial impact of improving your product quality? What is the financial impact of shipping on time? What is the financial impact of an increased number of electronic orders? etc.
The first question is whether there is a relationship between a certain operational activity and the financial outcome at all. Does it matter whether you are doing manual or automatic planning for example? This can be found out with statistical correlation analysis. If there is a relationship at all the ensuing question is how does this relationship look like. If you improve your dispatching quality by 2%, how much does it improve your free cash position? Such relationships can be determined with statistical predictive modeling.
As a side effect, such models yield also the likelihood of achieving the desired operational improvement.
Statistics rely on significant sample sizes. In business there are plenty of data. Actually millions of data. Millions of operational steps and activities. And hence hundreds of thousands of relationships between operations and finance.
Modern data base technology allows to process these very large amounts of data. Modern algorithms allow to learn these millions of relationships without manual intervention.
Voilà. No process harmonization needed for performance comparability anymore.
We at Trufa are pioneering this new approach for a number of years already. We call it TPI – True Performance Index.