Our (not always) rational decision-making process

Many years ago, I was told that supply chain management is the job of coordinating a flow of products versus a counterflow of information. Soon after, I was introduced to the concept of logistical trade-offs and how supply chain professionals deal with decision-making cycles seeking to optimize results. It seemed that logistics was the 'art of making decisions with little information in a short period of time'.

Needless to say that today, part of that sentence must be revised. In recent years, the flow of information has grown exponentially, a quick online search is enough to see the amount of data that is generated daily. The challenge is no longer that of little information available in the hand of the decision maker, but rather that of interpreting the information in a very accurate way to make quick decisions in an environment of constant change.

This challenging scenario is evident in the demand planner's decision process. Before, this professional dealt with a few SKUs and few information breaks. Today there are thousands of SKUs, hundreds of CDs, countless points of sale. In addition, market uncertainties end up pressuring the planner to make very quick decisions.

In this scenario, our brain, seeking to interpret this huge amount of information in an agile way and with time constraints, resorts to mental shortcuts, or simplifying rules that help us make a decision. These strategies are called heuristics and, despite their value and importance in our daily lives (imagine having to process all the information we receive from the environment, from the temperature of the environment to the color of the wall, to decide with which foot we are going to get up from the bed?), they can lead to inaccurate or biased conclusions.

For example, if you tossed an unbiased coin 6 times. Which of the sequences below is most likely to appear?

I'm pretty sure your first answer was sequence 1. However, if we analyze the probability of a coin coming up heads or tails as 50%, the chance of occurrence of the two sequences is the same. So why does the first sequel seem more likely to us? This happens because the first seems to us to be more random than the second and, as we assume the coin toss is a random event, we tend to think that the first is more likely to occur than the second.

Of course, you could even say that this doesn't happen in a professional's daily life because we are rational beings and that our decisions are always based on facts and analysis. However, heuristics are more present in the daily life of the supply chain manager than we think.

Imagine yourself in the role of the demand planner for a product that has had a huge sales success in recent weeks because of a successful promotion. Its director was happy, but complained that the planning didn't perceive the sales growth correctly and there was disruption and extra expenses with emergency orders. What would you do in the next planning cycle?

You would probably find that your predictive models are conservative and that an adjustment is in order, after all, demand is hot and you don't want to hear the word collapse anytime soon. Sounds like a reasonable decision, right?

In the following cycle, however, sales are well below expectations. What happened? The reality is that customers took advantage of the promotion and stocked up on the product, which reduced demand in the next cycle. However, this information did not have as much significance for you as the fact that there have been recent ruptures at the end of your chain and this has led you to overestimate demand.

Did you relate? We have just experimented with the availability heuristic. In a more formal definition, it is the phenomenon that occurs when people tend to judge the likelihood of an event occurring based on how easily they can remember instances or occurrences of the event.

It is important to reinforce that this heuristic has its importance and value, when applied in the correct situation. Just remember that time when you forgot the headlights on with the car turned off, causing the battery to drain, and consequently, the car would not start. I'm sure, at least in the first few months, the recent event (depleted battery) made us super aware of the importance of checking whether we turned off the car lights before taking the key out of the ignition (something positive).

It is automatic for our brain to seek these heuristics as a way to simplify and reduce our cognitive load. In the case of availability, it is essential that the manager is aware that the intensity of an event impacts his perception of the probability of occurrence of that event. Fortunately, technologies such as machine learning and statistical techniques somewhat mitigate the effect that these simplifying rules have on the decision-making process, but of course, recognizing and being aware of these biases is essential for making more rational and accurate decisions.