The business world loves predictions. The future of work, the future of HR, the year’s marketing trends, the emerging technologies to watch…we’re all over the place with predictions of all kinds and we love them. The question I often ask myself when reading them is “what can I learn from this?”
Predictions? For whom? What for?
Let’s start at the beginning: why some people are fans of this type of publication and others like to write them or even excel at them.
Predictions:
- Give the outline of a vision and ideas to those who have none.
- Help those who have a vision and ideas to benchmark and complete them.
- Pushes one to think further than one’s own certainties and that’s already good.
For their author they serve to :
- To share convictions
- To establish their reputation
- Challenge their ideas with feedback from readers
- To sell something else thanks to this loss leader
Depending on the person, the goal varies, as well as the method used to establish these predictions and, consequently, the value to be found in them.
Qu’attendre de prédictions ?
“Prediction is a difficult art, especially when it concerns the future“. From Groucho Marx to Pierre Dac, we don’t know to whom to attribute this quote with certainty, but it could not be more accurate.
“In God we trust, everyone else must bring data” said Deming. This is the era of data, but here the data is of limited help. We are talking about things that are not very quantifiable. Yes, there are quantified trends, they are known, but this is not what we expect from this type of exercise. We expect business predictions to analyze these trends, to know if they are going to accelerate or, on the contrary, to slow down. We expect things that go against the evidence or popular belief. We expect things that are undetectable.
Understanding what is going to change in a specific business or field therefore requires more than data, but also the interpretation of external factors that are as varied as they are unquantifiable.
“There is the known known, that is, the things we know we know; we also know that there is the known unknown, that is, the things we know we don’t know; but there is also the unknown unknown – the things we don’t know we don’t know.” said Donald Rumsfeld and good predictions are those that hit the nail on the head about the known unknown and especially the unknown unknown.
We might as well say that the art of prediction leaves a lot to personal interpretation and is therefore never free of bias, which is the beginning of the answer to the question “what should we keep from it?”
Convictions or predictions?
I said earlier that predictions can be used to establish and share beliefs. When you engage in the exercise, the line between “what will happen? “and “what would I like to see happen? “is very thin. Our own desires, our dreams, our desires are a real bias.
The expert who shares his vision of the future of a subject has necessarily a bias, convictions and they largely influence what he is going to write, which makes me say that an expert or an opinion leader on a subject is far from being the most reliable futurist (and I include myself in this), precisely because one has opinions. A good futurist is often less committed, has more distance and relies more on a methodology than on his convictions or instinct.
Tell me who writes or sponsors it and I’ll tell you what it predicts
And then it is the case with predictions as with most of the studies published over the years: when they are written, co-authored or sponsored by a market player, we know what we are going to find before we even read them.
It will come as no surprise that the predictions on the future of work published or sponsored by a co-working actor announces the explosion of hybrid work and third places or the rise of freelancing if it is an intermediation platform between companies and freelancers. If it is a software company, its predictions on a given domain will of course be in line with its choices and inclinations in the roadmap of its products.
A little method
So how to unbias this exercise when one is not a professional in foresight? This is the question I asked myself before writing a series of articles on a given subject in which I intended to share some convictions but without letting myself be blinded by them or forgetting along the way elements that I might not see or not want to see.
I have arrived at a method that is quite simple but which seems to me to be both exhaustive and objective. In any case, it is sufficient for a non-professional in foresight.
1°) Take a subject.
2°) Identify 5 or 5 “external forces” that have an impact on it (ex: technology, societal evolution, data protection…).
3°) Break down the topic into ten or so subtopics.
4°) For each sub-topic, look at the impact of each of these forces, even develop several scenarios and estimate the probability of each.
5°) Make the synthesis.
More complicated and maybe less pleasant to write than just starting from one’s own inspiration and convictions but certainly more “solid” and objective.
And what do you expect when you read an article about trends? Are you careful about possible biases or intentions of the author or not?
