Controlling is constantly fighting for their place within the corporation. Today, there is an opportunity for controlling to break out of their “bean counter” jail.
The essence of controlling is planning and reporting. Planning is challenging because, as a Danish proverb says, “Prediction is difficult, especially when dealing with the future.” Along the same vein, reporting is tough because it answers only those questions where the potential answer is already known. As a consequence, controlling contributions are perceived more or less as “too little, too late.”
This is the reason why controlling has been in a standstill situation for more than 25 years (1990 saw the birth of the Balanced Score Card).
Now, the “business of predictions” is experiencing its second wind: artificial intelligence is back. Machine Learning is the buzzword of the day. In our daily lives, we have become reliant on predictions; might it be Google or Amazon proposals of all sorts, or might it be the car navigation system which brings us safely and quickly to our destination. Actually, I must admit that I sometimes find it nearly scary what systems know about my intentions and behavior. We abound in algorithms.
Algorithms have evolved for a long time. Machine learning was first mentioned in 1959, and Artificial Intelligence in 1956. I personally lived through the first hype cycle of Expert Systems in 80’s. Those systems worked in highly specialized niches but they never conquered broader grounds.
How come? Computers were just not fast enough. Data could not be processed fast enough.
This situation caused the “fall of mankind”—the introduction of OLAP technologies which, in essence, attempted to pre-calculate all foreseeable variants of looking at your corporate universe. Obviously, a fallacy from its inception. But since the introduction of data warehouses in the early 80’s, we have piled up technology stack upon technology stack on this from its inception shaky ground. We have sunk billions of dollars in these. Many, if not most, of us in controlling have never seen it differently, with the consequence that we take such false technologies for granted. This is the reason for the straightjacket that controlling is wearing today.
Ok. That sounds easy to overcome. Because technology has experienced a breakthrough in the last five years. There are “big data” databases now. The technical constraints that held back artificial intelligence and machine learning are gone. Forever. Cases in point: Amazon, Facebook, Google, you name it.
Yep—autonomous planning has become feasible, as well as ad-hoc queries instead of reports. And automatic detection of business drivers. And crawling of improvement opportunities. And FICO scores for the performance of your enterprise. A controllers dream has become true. Or has it?
There is one more obstacle to overcome: our own set of beliefs.
Controllers are trained to be precise, and this is good. Hence, controllers regard their world as being deterministic. This is obviously not true when looking into the future. But it is also not true when trying to explain the past. Reports do not get it. Financial models, as what the name suggests, are just models—not the reality.
What does this mean for the future work patterns of controllers? It means that insights will come with a certain margin of error. This is obvious for predictions. But it is also the case for past phenomenon. The question is no longer whether the insight is true or false, but how large the inherent error is. Scientists like mathematicians and physicists are used to this thinking. Economists are used to such procedures. Controllers are typically not.
To sum it up: if and only if controllers are willing to change their behavior, then they will find a bright future. Brighter than ever before. Controllers would be invited to “play with the big boys.” Let the controllers come to the party.