If you knew, you’d change! Battling bias with data
Most leaders, when confronted with the realities of our propensity toward bias, planned to improve the quality of data used in talent decision-making. Data gathered from leaders has demonstrated this. Once you have these facts to hand, will you demand change too?
The brain makes use of thinking strategies which short-cut decision-making; this is essential to the brain’s efficiency. These short-cuts can have significant down-side effects in business; for example, as they pertain to employee-related decision-making. The lack of inclusion which results from unchecked biased decision-making is limiting organizational diversity, employee engagement and innovation every day. Organisations can do more to address this.
Working with a large group of business leaders at the Balanced Business Forum in late 2015, two live experiments demonstrated our collective vulnerability to poor decision-making. Having taken ten minutes to illustrate both attribution bias and optimism bias to the audience first hand, the vast majority immediately recognized the need for change in the data collected and used to inform talent decision-making. Let us tell you why!
To demonstrate the nature of errors created by attribution bias the leaders were sequentially shown 15 words. Then all words were cleared from view. The words were: blue, sky, white, cloud, rainbow, yellow, bright, hot, green, grass, summer, flowers, trees, rays, and shade.
When asked how many remembered and recorded seeing the second word, sky, 76% recalled it. For the fourth word, cloud, 68% recalled it. For the ninth word, green, 69% recalled it. We then saw a shift in recall. When asked how many remembered seeing the word sun, 37% indicated that they had. And for the word trees, 24% said that they had.
Have you noticed the problem? Trees was the thirteenth word on the list; only about one in four people remembered this word. Yet more than one in three created a memory of seeing the word sun, which had not appeared on the list; they had unknowingly created a false memory and attributed the word to the list.In the same way, we can misremember information about people that we later rely on to inform talent decisions.
Following another experiment and table discussions, we polled the audience on their organizations’ talent decision-making practices. Most agreed that there is a strong case for reducing the use of subjective decision-making practices. (See Fig 1.) For example, only one-tenth the number of those whose organizations are currently using Performance Ratings (ranked annual performance scores) believed it would be a good idea to continue doing so.Ten times as many as currently use psychometric assessments to inform their talent decisions believed it would be a good idea to do so the in future.
IBM promotes applying psychology at work to measure, predict and enable peak performance for individuals, teams and organizations. Now that you have been confronted with the realities of our propensity to bias, will you seek to improve on the objective quality of data you use in talent decision-making?
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