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Data Science Center Tilburg

Business Analytics: better decisions with data

DSCT Blog - November 2015 | Dick den Hertog- Professor of Operations Research

An important field in Data Science is Business Analytics. INFORMS, the worldwide society for Operations Research and Management Science, gives the following definition:

“Business Analytics - the scientific process of transforming data into insight for making better decisions.”

Business Analytics: smarter decisions, better results

In the book “Competing on analytics, the new science of winning” (Harvard Business School Press 2007, written by Thomas H. Davenport and Jeanne G. Harris), several reasons are discussed why analytics is important for companies nowadays. They conclude:

“What’s left as a basis for competition is to execute your business with maximum efficiency and effectiveness, and to make the smartest business decisions possible.”

Hence, analytics is often the only way to get competitive advantage. Many leading companies are building their competitive strategies around data-driven insights by using analytical techniques and tools.

In this book four different levels of degree of intelligence and competitive advantage are distinguished for Business Analytics:

  1. Statistical analysis – why is this happening?
  2. Forecasting and extrapolation – what if these trends continue?
  3. Predictive modeling – what will happen next?
  4. Optimization – what’s the best that can happen?

Why do some companies become industry leaders?

In the remainder of this blog, I would like to concentrate on the fourth level. I start with mentioning an influential book on the impact of Optimization in our society: “The Optimization Edge; Reinventing Decision Making to Maximize All Your Company’s Assets” (2011), written by Steve Sashihara, president and CEO of Princeton Consultants Incorporated. In the first part of the book he discusses the following question: “Why do some companies become industry leaders, while others never rise to the top?” “Why is McDonald’s much more successful than Roy Rogers?” Same question for Walmart versus Kmart, Marriott versus Howard Johnson’s, Google versus Yahoo!, UPS versus Airborne Express, Amazon versus Borders.

The author of this book shows in a convincing way that the basic answer to this question is that the leaders of industry posses an ability to make complex decisions faster, more accurately, and more consistently than their competitors”. These companies are able to do so because they are big users of Optimization!

Optimization for public interest 

It is also striking to see that Optimization not only plays a crucial role in the commercial world, but also in many ‘public’ environments. I give two examples that I know from my own applied research. The first example is the determination of the new safety standards of all dike ring areas in the Netherlands, in which Optimization played a crucial role. The second example is the crucial role of Optimization in cancer treatment. Nowadays, hospitals are using optimization techniques to find optimal radiation treatment plans for patients.

Big Data and Optimization

An important development that makes the use of Optimization more crucial is the ICT development. In the past the lack of data was a big problem for many companies, but nowadays often huge amounts of data are available. Some time ago I visited the IBM research lab in Dublin, and they showed me many impressive examples in this respect. One example is that they use the huge amount of data of mobile telephones in a city to make transport "smarter". Notice, that this ‘Big Data’ development also leads to new optimization challenges. Solving really large-scale optimization problems is one of them. In most applications the speed is important. It is more important to obtain a robust, good solution in time, than an exact optimal solution too late.

The future is bright for Business Analytics!