Analytics: A Conceptual Framework

In the 12/17/14 INFORMS Today Podcast, Glenn Wegryn observes that analytics is divided into two distinct camps. He notes that they tend to come from different organizational backgrounds and he describes them in the following way:

  • Data Centric – use data to find interesting insights and information to predict or anticipate what might happen;
  • Decision Centric – understand the business problem, then determine the specific methodologies and information needed to solve the specific problem.

That analytics appears to be divided into distinct camps should not be surprising, since, as I explained in Confusion Over Analytics, analytics should be understood as a conceptual grouping of the quantitative decision sciences as a whole. Therefore, it is to be expected that disciplines within the quantitative decision sciences have distinctive backgrounds, methods and approaches.

The data centric/decision centric categorization can be a useful way to think about analytics, since two disciplines contained within the analytics conceptual grouping fit these categories perfectly: data science (data centric); operations research (decision/problem centric). Using this categorization, a framework can be constructed, within which, the various types of analytics, data science, and operations research can be  related to each other in a logically consistent way.

Diagram of an Analytics Framework

Analytics Framework

Both common uses of the term analytics appear in the preceding diagram: to represent statistics and computer science and to represent all the quantitative decision sciences. This conceptual framework highlights a promising area for collaboration between data science and operations research (prescriptive analytics), while recognizing that most prescriptive quantitative analysis does not require intensive data analysis.

Confusion Over Analytics

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

Chart Showing Searches For Analytics
Searches For Analytics

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.

At The Heart Of Analytics

“operational research – at the heart of analytics”. This phrase is the banner headline on the home page of the website of the British OR Society. (http://www.theorsociety.com/) The January 12, 2015 blog post of The OR Society begins with the following statement:

‘Part of the OR Society’s mission statement is that the Society “effectively promotes the use of OR”; and this is something we do extensively through our publications, our events, our training, our OR in schools initiative, our web sites and elsewhere.’ (http://www.theorsociety.com/Blog/features/20150112093937.aspx)

Clearly, The OR Society believes that they can use the interest in analytics to promote operations research. If we, in the United States, want to do the same thing, we should keep two basic marketing principles in mind:

1) If you want to market a product, you must tell your prospective customers, THE NAME OF YOUR PRODUCT. In our case, the name of our product is operations research. If we use an amorphous name such as analytics, or the name of a different discipline such as data science, our customers will be confused, and they won’t know what to buy.

2) It is usually helpful, if you explain to your prospective customers, THE BENEFITS OF YOUR PRODUCT. In our case, we could explain to people with an interest in ‘big data’, that operations research can be used to turn insights from a ‘big data’ analysis into an optimal marketing plan.

It is possible, that by positioning operations research ‘at the heart of analytics’, we can promote operations research more effectively. Perhaps, we could even persuade the British OR Society to let us borrow their slogan.

Going With The Flow

Somewhere in an alternate universe…

The INFORMS board members sat in the conference room and wrestled with a recurring question: what should they do about analytics? They had hoped that the problem might just fade away. After all, expert systems, neural networks, and most recently big data, had all come and gone. However, interest in analytics had continued to grow. They were frustrated, and so they decided to engage the prestigious consulting firm of McKinsey, Boston & Yoda to help them develop a strategic plan. They were thrilled when Professor Yoda, one of the firms managing partners, agreed to meet with them.

One month later…

After listening for awhile, as the INFORMS board members described their situation, Professor Yoda rose from his chair and strode toward the white board. There was great anticipation in the room: would he draw one of the matrix diagrams that his firm was famous for? Instead, he wrote two words on the white board. He replaced the marker in the tray; returned to his place at the table; closed his briefcase; and left the room. He didn’t return, and after a few minutes, he was seen driving away.

Everyone was stunned. What had happened? What did it mean? What should they do? They kept staring at the white board ……………………. and then ……………………. they understood! It was so simple really: all they had to do was to align their strategy with THE FORCE.

The way forward was now clear to them, but the INFORMS board members knew that it would not be easy. So they asked the membership for help. They were not disappointed. It turned out that INFORMS members had already created a lot of content that would be valuable to people interested in analytics. There were lectures, tutorials, white papers, podcasts and videos. This content was organized and presented on a special section of the INFORMS website. New content was created, and then promoted through social media. After a while, people began to notice these efforts.

Meanwhile, two years earlier, INFORMS had begun an initiative to encourage the submission of applied papers to its journals. These papers were now beginning to flow in. The INFORMS board members thought: why not summarize these papers and feature them on the INFORMS website? And that, is exactly what they did.

Eighteen months later…

Steve Jobs sat in his office and played with the iPad 6 prototype. He was trying to decide on the perfect shade of white for its case when he got a call from Tim Cook.

“Hi Tim.”

“Hi Steve. I think I have a solution to the problems we’ve been having on the iTV production line.”

“Oh?”

“Yes, we have some people monitoring the INFORMS website; they came across a new article on the optimal sequencing of subassemblies. I think we can use that approach to improve our process.”

“That’s great Tim. Why don’t we just go ahead and buy INFORMS?”

“Ah…. Steve, I don’t know if we can do that. INFORMS is a non-profit professional society.”

“Oh. OK, then let’s hire the people who wrote the article.”

“I’m already on it. They’re coming in on Wednesday to meet with us.”

“Great. Listen Tim, how do you feel about antique eggshell white?”

Twelve months later…

The featured article in the journal Foreign Affairs is entitled “The On-Shoring Craze – Should Operations Research Get All The Credit?”.

Twenty months later…

Time Magazine names operations research discipline of the year.

Sixteen months later…

Each of the INFORMS board members was announced as they entered the East Room of the White House. When the president asked them how they had achieved such great success, the reply came back immediately: “Madam President, we owe all of our success to our belief in THE FORCE”. The audience applauded, cameras flashed, and the president smiled as she presented each of them with the Presidential Medal Of Freedom.

The End.