We are all too familiar with the indispensable task of business process modeling.
“Business process modeling (BPM) in systems engineering is the activity of representing processes of an enterprise, so that the current process may be analyzed or improved. BPM is typically performed by business analysts, who provide expertise in the modeling discipline; by subject matter experts, who have specialized knowledge of the processes being modeled; or more commonly by a team comprising both. Alternatively, the process model can be derived directly from events’ logs using process mining tools. The business objective is often to increase process speed or reduce cycle time; to increase quality; or to reduce costs, such as labor, materials, scrap, or capital costs. In practice, a management decision to invest in business process modeling is often motivated by the need to document requirements for an information technology project.”
And we are all too familiar with the daunting shortcomings of this approach. Even considering the fact that modern process mining might speed up the detection of the as-is processes the modeling of the to-be processes continues to be an unsolved problem. Because you still have to have the endless discussions which process variants are to be discarded and which ones are to be improved for example. Since you have no decision criteria for which process scenario is preferable over the other.
Using the navigation system as analogy process mining gets you a tracking of which way you have gone and how fast. But process mining cannot help you with deciding which route is the fastest. Nor does it remind you to start your journey early enough to arrive in time. Process mining has no notion of commonly applicable decision criteria to make such recommendations.
This would require to understand the performance characteristics of your business to predict the results of your operational activities. And obviously, this is needed for every angle. In our customers’ situation sometimes 200 millions of those details are to be understood.
Unfortunately there is another complication in business. Like in the navigation situation there is constant road construction work taking place. In the business world there is constant process optimization at work. And actually this is becoming worse with the digital transformation. So your to-be business process model is continuously changing as well.
There must be a better way. And indeed there is: Machine Learning.
“Machine learning is the subfield of computer science that “gives computers the ability to learn without being explicitly programmed” (Arthur Samuel, 1959). Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data – such algorithms overcome following strictly static program instructions by making data driven predictions or decisions,:2 through building a model from sample inputs.”
The recent advances of artificial intelligence and machine learning to tackle big data problems lend themselves to be applied to the world of business management. And this is indeed what we at Trufa are doing for quite some time now.
Our machine does a continuous to-be process modeling. It simulates the relationship between operational activity and financial outcome. On this basis our bots constantly recalculate a commonly applicable performance score. And this score can then be used as decision criterion for ongoing business process improvement actions. Or it can be leveraged to alert the business early enough about deviations in its planned business performance.
That’s all what it needs. Because the machine works for you!