Predictive analytics will only get you so far in picking the right people. And sometimes it will get you so wrong. Teams are about more than just skills and abilities. Tired teams outperform fresh teams when making key decisions 

four candles or fork handles

A core theme this year at IBM Connections (formerly LotusSphere)is creating a smarter workforce through social media tools and insights from ‘big data’ analytics.

One customer case study during the keynote described using one of IBM’s acquisitions – Kenexa – to perform predictive analytics in recruitment decisions and helping select the right people to participate on a team or project. Based not just on their profile, but feedback from previous actions – what content are they contributing to, what activities are they participating in. All being captured as real-time updates thanks to social media tools.

Whilst the technology behind predictive analytics is powerful and has lots of potential uses, it should never completely replace ‘in the moment’ intuition. Aside from the obvious flaws – some people may ‘game’ the system to ensure they get picked, whilst better candidates may be missed because they are less boastful. What if you don’t want to select the best people for a team? What if you want to develop skills and mix-up the experience levels? What if you know certain individuals simply don’t work well together despite the predicted synergy in expertise? How much do the expected outcomes influence decisions – are you looking for a ‘safe pair of hands’ or a disruptive innovator? Is the project predictable? If not, how do you know what skills to look for versus picking those you know are good at adapting and picking stuff up as they go along?

Predictive analytics can uncover fascinating insights from the oodles of data being captured continuously, both from our explicit contributions and data gathered automatically in the background such as who we communicate with, in what formats, at what times and locations etc. But, as Dave Snowden wisely said:

We always know more than we can say, and we will always say more than we can write down

In the book Sources of Power: How People Make Decisions, by Gary Klein, examples are given to demonstrate why team work is not just about skills and abilities when making decisions.

One example given involves flying airplanes.  Accident investigations have shown that the majority of incidents caused by human error are due to a failure of different members of the crew understanding what the others wanted to do. A study performed for NASA (Foushee, Lauber, Baerge, and Acomb 1986) investigated the effect of fatigue on performance, as a possible cause. Here’s a couple of clips from the book, emphasis in bold is mine:

Flight crews were asked to fly eight-hour missions in a high-fidelity simulator. The researchers presented the same malfunctions at the beginning of the flights for some crews and at the end for others. They expected that the crews would react better at the beginning, when they were fresh. The results were the opposite: the crew members did better at the end of their missions. Their advantage was all they had learned about working together. They learned to anticipate how each member woud react, and they became adept at reading each other’s mind.

If we can work with people who understand the culture, the task, and what we are trying to accomplish, then we can trust them to read our minds and fill in  unspecified details. A team that has much experience working together can outperform a newly assembled team

Predictive analytics will only get you so far in picking the right people. And sometimes it will get you so wrong.


And finally, for anyone unfamiliar with the image at the start of the post. A 30-second clip from a classic episode of the TV series The Two Ronnies… Showing how asking the right question can get you the wrong answer. Enjoy!

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