Why collective illusion may beat collective ignorance

A shared set of beliefs at the start of a group project, even if inaccurate, is often better than having no plan or a mix of good and bad plans

PUBLISHED : Friday, 30 September, 2016, 3:01pm
UPDATED : Friday, 30 September, 2016, 10:42pm

Consider this intriguing story (which may be apocryphal, but is still intriguing). Once upon a time, a small Hungarian army detachment manoeuvring in the Swiss Alps was lost in a snowstorm. The commanding officer, who had sent them out, suffered agonies over two days as he expected that the unit was lost and probably frozen to death.

On the third day, he was relieved to see them march back into camp. What had happened and why had they taken so long to come back? The unit had indeed been lost and had considered themselves done for and had waited for the end. And then, one of the soldiers found a map in his pocket.

This not only calmed them down and helped give them a sense of hope and purpose, but it also helped them discover their bearings after the snowstorm had abated. Using the map, they successfully found their way back to camp.

There is nothing extraordinary about the story so far. Expeditions without maps in novel territories do get lost. Finding a map (admittedly, somewhat miraculously, in this case) rekindles the group motivation to find a way back, and the map itself helps focus the collective efforts to return in the right direction. What is extraordinary about this story is that when the commanding officer examined the map that had saved their lives, he found that it was a map of the Pyrenees, not of the Alps!

A commonly held initial plan, even if inaccurate, can beat no plan or a mix of good and bad plans

We encounter expeditions (group projects) without maps (shared understanding) not only in the frozen wilderness of the Alps, but also in prosaic organisational settings. For instance, consider a team of specialists coming together for the first time to work on a consulting project. Apart from a general understanding of what the goal of the project is, when they begin there may be no shared understanding of how the expertise of each will be involved.

At the inter-team level, consider two teams of engineers developing sub-systems within a computer. Team A and Team B might be developing the next-generation microprocessor and the graphics card respectively. Each team faces a set of choices about the design of their sub-system. They also know that certain combinations of choices on their part will lead to dramatically enhanced performance of the system as a whole, but do not share a common understanding of precisely what that combination is.

At the inter-organisational level, imagine different product divisions seeking to realise synergies for the corporation by coordinating their marketing campaigns.

Each divisional manager faces a menu of choices with regards to their product’s marketing strategy. However, there is no common understanding of the impact of pricing decisions by one division on profits of another.

How can organisations structure mutual learning so that interdependent players in situations like those above are able to make the best possible choices? In a recent research paper co-authored with Murali Swamy of the University of Southern Denmark and published in Organisation Science, we analysed computational models of interacting agents to show that standardising initial assumptions across the collaborators – even when these assumptions are wrong – is one powerful way organisations can set the stage for a successful learning process.

A commonly held initial plan, even if inaccurate, can beat no plan or a mix of good and bad plans held by the collaborators. Collective illusion beats collective ignorance.

How can that last statement possibly be true, you may ask. Let’s consider another story, this time involving a high-school romance. A boy and girl walk to school, and would ideally like to walk on the same side of the street, but don’t want to explicitly ask or appear to want to.

Let’s imagine there are shops that sell chocolate milkshakes on both sides of the street. It’s not unusual for young folks to wander into one of these shops for a malt after school. Our young boy and girl would enjoy seeing each other there, though they want to do this “casually”, without appearing to try (they are still shy). But they would also love to discover the shop that makes the best milkshakes (pocket money is scarce).

Here’s where the power of incorrect but shared beliefs comes in. Suppose the boy had a good hunch about which shop made the best milkshakes but the girl did not. He shows up alone, and leaves disappointed with that glorious milkshake undiscovered, and with a lower likelihood of returning to this shop. The same happens if the girl has the good hunch, not the boy. If neither has any hunch at all and they both just pick at random, there is still an uncomfortably high chance that one of them had in fact found the best shop, but since the other wasn’t there, never realised it (because they don’t order the milkshake unless they see each other at the shop).

But suppose they both had the same hunch as to which shop made the best shakes? If they are right, problem solved and the story has a happy ending. But even if they are wrong (and this is the key point), they escape the “false negative” problem where only one of the pair finds the best shop and erroneously crosses it off the list. This actually increases their chances of finding the right shop and each other in future trials, relative to the other cases. That’s the power of incorrect but shared beliefs over no beliefs or a mix of good and bad beliefs. Collective illusion beats collective ignorance, or indeed pockets of wisdom.

Our model produces this insight with much more rigour, if substantially less romance.

Our analysis points to several intriguing ways in which a manager could improve the efficacy of coupled learning processes. Intriguingly, the manager does not require more technical knowledge than his subordinates to add value. Organisation design, to be useful, need not be particularly intelligent design. By merely laying out a common plan (an initial shared belief), even if it is wrong, the overall process of search can be improved.

Phanish Puranam is Roland Berger chair professor of strategy and organisation design at INSEAD and academic director of INSEAD’s PhD programme