How do world-beating teams decide?

"Find a group of people who challenge and inspire you, spend a lot of time with them, and it will change your life forever" - Amy Poehler


Thank you for joining me for another blog (#38), highlighting decision-making and the brain. This is my public exploration of what drives decision-making and how we can use that information to make better decisions, resulting in better outcomes.


We are currently exploring group dynamics and how that impacts decision-making. Today's topic is around how the best teams decide. Whilst at the surface this might seem like a woolly problem there is a growing and robust evidence base.



An example of decision-making is prediction scores and have been tracked through the work of Phil Tetlock (author of "Superforecasting"). These are trials to try and predict the probability of clearly defined outcomes (e.g. Russia will invade Ukraine by February 2022) and their scores are meticulously recorded and ranked. 'Superteams' have been identified using these trials. The combinations of individual attributes and team interactions have been linked to performance. Whilst there is no one route to good teams the factors they identify are very relevant to all levels of organisations.

Why bother with teams?


The first blog in the series identified how independent judgments can be used to make some very good estimates. For example, although each individual might be quite far off, the median guess might be very close to the real answer. This boils down to the question of how we best aggregate information that a number of individuals have.


We also over highlighted that group dynamics can sometimes hamper decision-making. Sometimes groups produce wacky results. Why bother with teams?



The prediction scores showed that teams performed better than individuals on average and that teams often beat the wisdom of the crowd (unlike an individual expert). The best teams - 'superteams' more often than not beat prediction markets (e.g. the stock market, or betting websites). I had 3 main take-aways from these results:


1) Sometimes teams are less than the sum of the parts: Poorly performing teams can be worse than the independent judgments of those within the team

2) Skin in the game: Prediction markets beat wisdom of the crowd as only those willing to be impacted by the outcome got involved

3) Consistently beating the markets is unusual: The prediction markets perform better than most teams. Looking at the markets as a data point is likely to improve your decisions (although some notable exceptions recently with many political results that were incorrectly predicted by the markets)


What are the attributes of 'superteams'





1) What attributes do good team members have?


a) open-minded people who pursue the truth rather than trying to prove a big idea right

b) have skin in the game (which includes the right incentives)

c) Actively contributing

d) Strong information gatherers e.g. researching base rates and outside views, with a particularly skill of trying to find information that conflicts with their views

e) be articulate in explaining your thought process and framing questions to help tease out the thought processes of others

f) have complementary skillsets and varying backgrounds




2) How they interact


a) open discussions where challenge is encouraged. This is sometimes called 'constructive confrontation'

b) try and come to an individual view first with a clear thought process this allows for a starting point of relative independence

c) asking each other pointed questions particularly trying to expose any jumps in logic from one stage to the next

d) low hierarchy environments

e) understand that information is never complete and is likely changing too i.e. react appropriately to new information rather than continue with an idea just because it once was concluded upon.

f) they consider a wide array of credible views

g) use of pre-mortems: framing questions that depersonalise bad outcomes e.g. let's say we are sat here in a year's time and we were completely wrong, what might have happened?


3) How they keep the team functioning well

a) discussions are held in such a way that conflict is resolved through the battle of ideas not personalities

b) aim high and try and avoid complacent, lazy thinking associated with teams that think they can slack off

c) they measure the team's effectiveness so that they can actively look to improve their team metrics


The unpredictable nature of groups

Whilst this all seems very straightforward, one point kept on coming up again and again - group dynamics are complex and cannot be very easily predicted i.e. you could combine people in what would seem like an ideal way but still not produce great results. Also group dynamics do change over time so we cannot take for granted that we have a permanently winning team.


Like many complex situations we need to measure the team's effectiveness. We often see football teams that seem to underperform expectations given how good the individual players are.


The results from the 'superteams' does seem to warn against indulging 'star players' who have excellent skills but poor attitude.


So What?


How is this all relevant to decision-making? Here are three take-aways I want to leave you with before we pick it up next week:


1) Good teams can outperform the wisdom of the crowds because they can collectively gather better information


2) Open-minded people with a diverse set of skills and backgrounds can challenge and question each other to better conclusions


3) We cannot reliably predict how a group of people will interact. The results from the team should be measured to shine a light on whether it needs to change its composition or interactions.


Thank you for joining. Next week - 'Leadership of teams'.


If you enjoyed the blog, you should read my previous blog which referenced how superforecasters try and make good predictions.


10 Forecasting tips (hartejsingh.com)