X-Raying the Transactional data When the X-Ray was first invented some 125 years ago it forever changed medicine and brought about a whole new field within health science.
X-rays meant that doctors could decide what to do based on knowledge about what was happening to the patient but not visible without an operation. Taking interviews with the patient (if the patient was conscious) was important but lacked data to confirm what was suspected to be the case and as some patients presented symptoms so obscure that opening up to take a look was the only way to attempt to cure the patient.
Not knowing what you would find during an operation was the norm, not the exception. Today imaging technology assists in every field of medicine, but in the early days it could be something as simple as finding out exactly how many bones were broken or in which organ the bullet was located.
Needless to say, surgery carried a huge risk in the early days of medicine so monitoring a situation by simply taking a picture was an absolute game-changer. In fact, X-rays where so helpful that they became addictive even to healthy patients. It was science at its best because it made the interior of a person completely transparent with the touch of a button and it completely did away with assumptions and led to less guesswork and quite literally actionable insights for the hospital staff. End result, people didn’t die as often.
Getting a clear picture of the data that affects and in created by your SAP software (what we call transactions) may not be a life or death situation, but it is a similar game-changer for someone in a digital environment to have that x-ray, that map, of all the data flow because it shows them how events are interconnected and it does so based on reality, not on assumptions about reality. Not a slice of the data, but all the data. The problem is that getting that full picture is counter intuitive to most ways of working today, simply because getting the full picture traditionally carries too much cost and takes too long.
With Machine Learning this is no longer the case.
Whether you are exploring your options to migrate, transform or upgrade your system or you are doing root cause analysis or perhaps getting a clear picture of how a system solution is actually being used after a series of rollouts. Or maybe you have decided that you and your business partner would like to study user and software behavior because you realize that doing exactly that gives you knowledge of what is technically feasible which is a great way of spotting opportunity proactively!