Confusion Over Analytics

The term analytics emerged in November, 2005. In the chart shown above, the relative number of Google searches on the term analytics from 1/1/04 to the present are displayed.

In addition to the dramatic growth in the use of the term analytics, there has been a proliferation in the way it is used, with phrases such as text analytics and healthcare analytics common.

Numerous definitions of analytics have been proposed, but consensus and clarity have been elusive:

• The lead article in the December, 2013 issue of OR/MS Today was entitled ‘The Evolution Of Analytics’. In the body of the article, the authors presented a 200 year history of statistics!
• In recent surveys, operations research professionals have expressed widely differing views on the relationship between operations research and analytics.

However, there is one point on which there is agreement — analytics is related to many different disciplines:

• Davenport, Cohen and Jackson, in the May 2005 research report ‘Competing on Analytics’ mention statistics, operations research, industrial engineering, econometrics, and mathematical modeling as examples of analytics.
• Rahul Saxena, co-author of the December, 2012 book ‘Business Analytics’, on slide #5 of a slideshare presentation, lists 14 disciplines as being antecedents of analytics. The list includes Business Intelligence, Computer Science, Statistics, Operations Research, Industrial Engineering, and Finance Planning & Analysis.

A Simple Explanation

How can we explain the sudden appearance of the term analytics and its connection to so many different disciplines? Did a new meta-discipline, representing a new problem solving paradigm, suddenly emerge?

Let me offer a simpler, and more plausible explanation. In November, 2005 a new concept emerged, and went viral: the idea that it is useful to be able to group together several distinct disciplines, and refer to them collectively with a single term.

This concept makes it possible for statistics, computer science and operations research to be represented by the word analytics in the same way that biology, chemistry, and geology are represented by the word science. Organizations can now consider quantitative decision sciences collectively for purposes of planning and resource allocation.

In current practice, the term analytics is used to represent two different groupings of disciplines:

• a base grouping (statistics and computer science) - e.g., data analytics;
• an extended grouping (all quantitative decision sciences) - e.g., business analytics.

Conclusion

When analytics is understood to be a conceptual grouping of quantitative decision sciences, confusion disappears:

• the sudden emergence of analytics and its relationship to other disciplines is explained simply and logically;
• the varied usage of the term analytics becomes understandable;
• it is not necessary to postulate the emergence of a new meta-discipline;
• there is an additional way of thinking about the quantitative decision sciences.

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Robert Rose is president of Optimal Decisions LLC where he is developing decision support systems in the areas of employee scheduling and forward buying optimization.

His website is www.optimaldecisionsllc.com

His blog is www.humancenteredor.com