They can also run experiments to test the impact of changes in pricing or packaging and then rapidly observe the quantities sold. Retailers gather real-time information about customer behavior by monitoring preferences and spending patterns. Where models work wellĮxamples of successful decision models are numerous and growing. Here, positive thinking-indeed, a healthy dose of management confidence-can make the difference between success and failure. In this case, the task isn’t to predict what will happen but to make it happen. However, when a senior manager can have a direct influence over the outcome of a decision, the challenge is quite different.
For things that executives cannot directly influence, accurate judgments are paramount and the new modeling tools can be valuable. In this article, I’ll address an important distinction between outcomes leaders can influence and those they cannot. Yet when organizations embrace decision models, they sometimes overlook the need to use them well. Models can be immensely useful, often making very accurate predictions or guiding knotty optimization choices and, in the process, can help companies to avoid some of the common biases that at times undermine leaders’ judgments. See these recent articles: Brad Brown, Michael Chui, and James Manyika, “ Are you ready for the era of ‘big data’?,” McKinsey Quarterly, October 2011 Erik Brynjolfsson, Jeff Hammerbacher, and Brad Stevens, “ Competing through data: Three experts offer their game plans,” McKinsey Quarterly, October 2011 Brad Brown, David Court, and Paul Willmott, “ Mobilizing your C-suite for big-data analytics,” McKinsey Quarterly, November 2013 and Stefan Biesdorf, David Court, and Paul Willmott, “ Big data: What’s your plan?,” McKinsey Quarterly, March 2013.
Combining vast amounts of data and increasingly sophisticated algorithms, modeling has opened up new pathways for improving corporate performance. The growing power of decision models has captured plenty of C-suite attention in recent years.
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