How Do We Harness the Wisdom of Crowds in Supply Chain Forecasting? A little over two years ago, I posed this question to you. I got a few responses, mostly private, who were thankful that I pointed out that you cannot just blindly follow the wisdom of just any old crowd, because expert judgements often demonstrate logically inconsistent results, but not a lot of advice on how we could successfully approach the task of integrating the wisdom that crowds could provide in our supply chain processes. The reason that we wanted to tackle this problem is because it is true that teams of forecasters often generate better results (and decisions) than individuals as long as the teams include a sufficient degree of diversity of information and perspectives.

But this is the caveat. The wisdom of crowds only holds if the crowd is large enough to contain the necessary diversity of information and perspectives in a statistically significant way. In other words, you will need a lot of people, and these people will need to be from diverse backgrounds and possess diverse skill-sets. But even this might not be enough in some situations.

As pointed out in this great blog post over on the World Future Society blogs by Thomas Frey from last August on The False Wisdom of Crowds, the decision between flying on a plane piloted by a single AI or the combined intelligence of 3,000 people is not as simple as you think. While it is true that the combined IQ and skill-set of 3,000 people is much greater than any AI on the planet, as you Next Generation Trekkies aware of the quick adaptability of the Borg will be quick to point out, it is also true that if all 3,000 of these people are farmers from the MidWest, it is likely the case that not one of them will know how to fly a plane! In contrast, the AI might be the best autopilot software in the industry, successfully used problem-free on tens of thousands of flights. The only way you’d beat that is if you had a collective of 3,000 of the best airline pilots in the industry. But the statistical likelihood of selecting that crowd from the global population is astronomical.

As Drew Curtis, founder of Fark.com, points out, “Crowds are dumb. The reality is that, while people are very good at knowing what they personally want, they are generally very bad at understanding the truths of the world around [them]. If you want proof, consider the examples given by Thomas and Drew, which include:

• In the ’50’s, it was common knowledge that if a nuclear bomb went off in your city, you’d be safe if you simply learned to “duck and cover”.
• Until 2007, it was a well-known fact that real-estate was a great investment where you would virtually never lose money.
• Only once percent of Web comments have any value and the rest are just garbage.

In other words, diversity is not enough. You need expertise. And you need the right expertise. But as pointed out in SI’s post from 2010 and Thomas’ blog post, ‘social influence’ diminishes the range of opinions and tends to lead crowds in the direction chosen by the most respected and/or socially powerful individuals. So you have to gather data from a “blind crowd” that cannot see each other.

In other words, when you put it all together you need:

• diversity, as addressed in our previous post,
• privacy, as partially addressed in our previous post,
• expertise, as demonstrated by Thomas’ blog, and
• statistical significance, as not adequately addressed yet.

Taken together, these requirements pose a bit of a problem, which is made clear in Thomas’ post where he quotes a recent study by McKinsey and Company that calculated an immediate shortage in the US of almost 200,000 people with analytical expertise and 1.5 million managers and decision makers with the skills to understand and make decisions based on the analyses provided by the analytical experts. Overall, we’re starving for expertise in Supply Chain, as evidenced by the fact that less than 10% of companies truly employ advanced sourcing techniques! The average company just doesn’t have enough people to meet the diversity, expertise, and statistical significance required to guarantee that a crowd decision will be better than the decision of their “leading expert” in that area. And since most firms don’t want to share expertise, sourcing processes, or suppliers, especially where strategic or high-value categories are concerned, they’ve essentially cut-off external sources of expertise. The result: beyond non-strategic / low-value categories they would be willing to hand off to a GPO, their chances of truly harvesting the wisdom of crowds for many Supply Management processes are low, at best — and this leads us to wonder if we really can harness the wisdom of crowds in supply chain forecasting in practice.

New Thoughts? Comments? Criticisms?