The human mind reacts differently depending on the thoughts that ‘cross’ it. The latter may generate an analytical response depending on which areas of the brain are most stimulated.
What goes through the mind of a manager of an important business area, when he thinks about the problems he is facing? Typically, numbers, reports indicating cause-and-effect, probabilities and other aspects that are much more scientific, quantitative rather than a qualitative approach.
If we were to believe that all that was required was a solid and well calibrated mathematical/quantitative approach to better manage every aspect of the business, then there should be a perfect positive correlation between ‘ability of calculation’ and the success of a business. This would be great news; however, it is not the case.
In many cases, correlation is certainly important: Google’s success lies in its very secret and complicated algorithms. Amazon, on the other hand, has engineered its logistics processes so well that it can handle orders and deliveries at record times and without errors. In fact, it is no coincidence that these companies attract talent with elevated analytical and problem-solving skills, as well as equip themselves with exceedingly rare and expensive innovative technologies.
Some producers of non-durable consumer goods, however, are more frequently experiencing the lack of a strong correlation between rational/scientific approach and entrepreneurial success.
So, what do the executives of these major multinationals need to use to trigger a process of continuous performance improvement and to achieve year-on-year goals? Why isn’t a robust analytical approach enough to cut costs, improve customer perceived quality or increase market share?
An analytical approach contributes a lot to a company’s success, as long as you keep in mind that measuring and analytics are not enough. In addition, often we fall into the temptation to delegate, perhaps to more junior employees, activities considered ‘automatic’ to then use the results to define strategy or make critical decisions.
Imagine that we are in the role of the general manager of a multinational company that produces mineral water. Every morning, when he arrives at his desk, he has a lot of information in his head obtained from company reports or his team and from learnings he has acquired from previous experience in the role.
At this point we can systematically analyse the issue as follows: if ‘things are going well’ the problem does not exist. If ‘things go wrong’, the need to react emerges. In the latter, if the problem is clearly identifiable, the manager can immediately start collecting data and information to process and improve performance knowing exactly what he needs. If, as is increasingly the case, the problem is having an impact, but it is difficult to trace its causes, the general manager finds himself in the situation of not knowing what to ask and to whom.
Usually we start from the data which we have always used, incessantly going over the numbers, coming to assumptions already reached in the past and no matter how much drilling down into the data is done, no effective solution is found.
The quantity and accuracy of the analysis is no longer related to success. So, what should we do?
In this case, the first thing to do is to ask new questions. Are sales of water bottles in the last quarter dropping in a specific channel? Are margins at risk? Is the market share shrinking compared to last year? Does the ROI from advertising makes sense?
On another level, it would be interesting to ask, is thirst the primary ‘need’ which is satisfied by the water we sell? In both cases, there is a need to ‘measure’, now even more given the current economic environment, and the effects that Coronavirus has had on the needs of consumers. For this reason, it is crucial to adopt with extreme flexibility and speed a new observation point when facing problems.
The second step is to equip yourself with the appropriate tools. ‘What do I know to know and how can I get the information?’, it seems a philosophical question, but it is the real dilemma of modern organizations. We can measure revenue by geographic area, point of sale, channel, or single area. However, the new questions we asked ourselves in the previous step, could require ‘new’ data which is difficult to obtain without agile and adequate tools.
The third step is to make this approach a natural part of one’s managerial process, accepting that even with numbers we sometimes have to create, experiment and perhaps even improvise.
Measuring your business means, above all, looking inside for new tools. Just like people, companies are evolving, grow in a sometimes-unexpected way and develop skills according to the environment. It is not just a matter of formulas and numbers.