Developing an analytical model to support decision-making is a really tricky task. I did many of them in order to decide whether it was a good idea to buy an apartment or to keep renting. What differed among them was the level of detail taken into account, which progressed slowly as I learned from my previous mistakes. While most of my models pointed out that it was better to keep money on a savings account and do not lend any instead of buying an apartment for the rent that can be earned (or that I would avoid paying since I had to live somewhere), I often forgot to regard the probability that apartments would appreciate considerably in a near future. Looking back, I see that my renter did an excellent investment by renting to me and waiting for what would come. Nevertheless, that moment is gone and it does not make any sense to bet that real estate in São Paulo will keep rising in price as it did in recent years.
When it comes to a trending topic like sustainability, that is supposed to represent the concern of people with protecting the environment for future generations while exploiting it for their own survival, I have been often told of misconceptions and lost opportunities that made many initiatives on that regard produce the opposite effect. And what is worst: as conceived, sustainability is a great but sometimes overlooked application domain to leverage analytical tools.
For instance, I was told of a workplace where someone had the idea of asking for shelves above the toilet washbasins. Since the washbasins were often wet, people got used to place a paper towel below their toiletries bags. As an experiment, such shelves were placed in half of the toilets of a floor. Long after, people started to ask when those shelves would be placed in the other half, since the experiment seemed to be successful. However, they were informed that someone had to collect data to assess if less paper towels were used in the first half of the toilets or not. As many people did not bother to walk more to use the toilets with shelves, it is very likely that the person undertaking such experiment will be surprised after realizing that the use of paper towels actually increased in that half and decreased in the other half. I hope that the person manages to sum up the use on both halves to realize what happened instead of concluding that shelves increase the use of paper towels.
It is attributed to Ronald Fisher the following quote: “To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.”. While it would be interesting to count with professional help, I believe that we would be better off if people working with sustainability were aware of the importance of developing analytical skills to avoid working against their own goals.