Will knowledge of a bias eliminate its impact?

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This is the second post in a series on decision errors, and in this installment we will take a look at “bias correction” and how to deal with it in a decision scenario.Ironically, once we are sensitive to our potential biases, we have a natural tendency to overcompensate for them. This is the decision error of bias correction.

I just recently finished going through a group simulation called “The Beer Game” as part of some training at MIT on System Dynamics. In this game a group of people operate independently at different stages of a supply chain that produces beer. As information is passed down the supply chain, participants try to adjust supply to fluctuating demand. In each iteration of the game, individuals go through a process of estimating what future supply will be, and the resulting chaos and fluctuation demonstrates our inability to operate in complex systems with limited knowledge. Lesson learned. If you want to try the Beer Game out yourself, here is an online version.

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Here is the kicker. At one table was a group of individuals who had played the game before. The hypothesis was that this group understood that the game expected us to overreact. They would be more careful because they understood our natural bias to react to short term signals. They would do better we thought….

Actually, they were one of the worst performing groups. Their awareness of the “game” caused an over correction in their actions, which lead to an equally or more destructive set of decisions.

At this point we make throw our hands in the air and give up. It seems bias will get us either way. I highlight this as the second post in the series on bias (the first post was on the ambiguity effect) to quickly highlight that knowledge of bias alone is necessary but not sufficient to ensure good decisions.

To make good decisions, and to deal with bias correction, we need to understand what the biases are but also manage how much they affect our decision process and at what points in time they come into play. This is where “modeling” is useful.

When I mention the word modeling, I am sure the first thing that comes to mind are complex, data intensive models. These are important for big complex systems, particularly as “big data” becomes more accessible but modeling can also be appropriate for smaller decisions.

For this post I would like to highlight three modeling approaches along this axis of complexity.

System Dynamics specializes in the mapping of complex, dynamic behavior. Unlike traditional two dimensional models, System Dynamics allows us to model out multidimensional dynamic behavior in a visual format.

In addition, System Dynamics tools such as iThink or Vensim do an excellent job of allowing you to run simulations on your model. With System Dynamics you can understand and calibrate you actions to avoid an overreaction or bias correction.

Utilizing System Dynamics is not for the faint of heart or those with attention deficit disorder, but it is an extremely powerful tool for addressing particularly complex issues.

If you are looking for something a little more light weight, I might suggest using a hierarchical approach such as decision trees. Decision trees will allow you to map out possible futures and then model probable outcomes.

Unlike system dynamics they address issues in a linear fashion, but still allow the user to explore and experiment with the probable outcomes from different strategic actions. Here is a link to more information on decision trees.

http://www.mindtools.com/dectree.html

A Business Model Canvas is a recently popularized version of business planning that includes mapping out a variety of possible scenarios in a quick organized way. This rapid iteration and refinement of a plan can be useful in uncovering our biases and in avoiding any “over correction” of our biases. For more information on the Business Model Canvas, check out “Business Model Generation”, “Lean Canvas” or pick up Steve Blank's foundational read, “The Four Steps to the Epiphany”

So whether it is Bias or Bias correction, consider putting on a modelers hat. If you are interested in further help building your own model, please contact us.

 

About Brian

Innovation & Strategy Specialist; Focus on Innovation Roadmapping & Business Modeling; Husband, Father, Systems Thinker, Babson MBA, Triathlete. View all posts by Brian →

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