Data Science vs Strategy – 2016 election a casestudy

AIG was one of the first companies to appoint a Chief Science Officer in 2011. Murli Buluswar reports to the CEO and utilizes statistics on large data sets to identify trends and helps AIG make strategic decisions.

For the last 5 years, Corporate America is heavily utilizing data science to make predictions and make decisions. The strategic decisions that were taken by CEOs based on strategy principles are heavily influenced by data science now.

However, the US presidential election has raised questions about data science.

Mrs. Clinton utilized a team of data scientists led by Elan Kriegel who built many statistical data models to help Mrs. Clinton’s campaign. These were highly paid staff.

On the other hand, Mr. Trump spent almost nothing on data science and led his campaign based on his own gut feelings. On the day of the lection, 30 polls based on data science were predicting a win by Mrs Clinton.

Sanjeev Sharma, founder of Boringportal and author of the award winning book ‘5 Core Methods of Innovation’, on the other hand explained in a Radio Interview with Ed Tyll, that based on his model, Mr Trump would be winning. He also explained that the election of 2016 was very similar to election of 2000. ( You may listen to it here )

Though we do not know the factors that Mrs Clinton’s data scientists were using, it is obvious that they would have been different from the ones used by Mr Trump or the ones that Sanjeev Sharma used for his analysis before the Radio Interview.

The results of the election now raise a doubt about the power of data science. Data Science would only work if you can clearly identify which factors to use in your statistical modeling.

Sanjeev Sharma

Consultant and Author of '5 Core Methods of Innovation'

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