noise canceling, or: what Beethoven has to do with your business

You know the problem. You are on your local commute, in a train, on the plane and all you want to do to kill the time is listen to your most favorite album, audio book, radio program, or latest TV episode. And while all this audio is there, coming to you via your headphones, you also hear the train rattling, the engines bustling, and people talking. So, all the experience you area looking for is dampened by inevitable noise.

Processes are the same. The only thing you want to do in your business is provide service to your customers, build a neat product, invent the next top-notch thing, or just pay some bills. And then reality comes and puts in all that noise into your business like phone calls, non-working printers, unprovided services, telephone hotlines, late clients, ill staff, … And about all that dealing with life, you forget about what you are good at, and you don’t know where you lack support or where you could improve. The good news is, that there is some neat technique around, called process mining. Process mining  is like a consultant that can speak to your IT equipment to tell you what your business is actually doing. The problem is that this consultant has a very sensitive ear. It hears far more noise than the Beethoven sonata you thought your business will be and it will tell you not only about Beethoven but also about all the noise that it has heard.

Enter: the noise canceling headphones. They let you enjoy your favorite piece of audio in the average noisy environment by filtering your environment’s humming and chatter from the sound waves that reach your ear.

Last week, I’ve accomplished something similar for our consultant with overly sensitive ears. I’ve built some noise filtering algorithms that work a little like noise canceling headphones for process mining. So, instead of now telling you about a business process soaked in noise (on the left), you may actually get to know about the actual process in your business (on the right). And the amazing thing is: this works on real data.

filtering a mined process model

So, enjoy your Beethoven.


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