New MIT Sloan Management Review study: An advanced analytics culture outweighs all other factors — David Kiron

The Need for Culture

The Need for Culture

What distinguishes the winners from the losers among companies converting data and analytics into a positive force in their strategies and operations? And what practices are keeping the winners ahead?

The Analytics Mandate, a new research report from MIT Sloan Management Review and SAS Institute, takes several steps toward answering these questions.

Our most significant finding? Our study shows that an advanced analytics culture outweighs other analytics-related factors -including data management technologies and skills-among companies that strongly agree they are gaining a competitive advantage from analytics. Essentially, a strong analytics culture is the lynchpin in moving from competitive parity to competitive advantage.

The need for change within a corporation’s culture, and the best way to achieve it, are both nicely illustrated in a case study included in our report.  WellPoint, the largest for-profit managed care organization within the Blue Cross Blue Shield umbrella, knew that sharing insurance data with physicians would provide doctors with a 360-degree medical view of every patient. This in turn, would better enable them to spot patients more likely to go to the emergency room or be readmitted to a hospital, contributing to expenses that drive up the high cost of health care delivery.

Within WellPoint, creating the data reports for physicians initially became a classic showdown between IT and interests from the business side.

The initial reports, prepared by the IT team, were late and lacked fundamental functionality.  For instance, different units within the company reported an emergency room visit in different ways.  The IT team’s explanation: no one told them the definitions had to be the same. This much was true — the business side didn’t think it needed to specify that emergency room visits be consistent across reports. They had assumed this was a given.

The high-profile project was subsequently placed in Red status. At this point, senior management got involved. Problems were brought to executives who, in turn, ensured resources were allocated. Outside consultants and experts were hired. More resources were diverted to the project.

Finally, after many challenging discussions, IT and the business side began working together using an iterative development approach called “Agile”, which focuses on “user stories.”. This meant understanding the perspective of the end user—the provider—and the context in which he or she would be using the data, as opposed to just developing according to a static set of  requirements.

Early reaction to the data system from doctors has been highly positive.  Over time, WellPoint believes that the proactive, coordinated-care model made possible when providers have actionable insights at their fingertips can cut health care costs by as much as 20%. That could work out to billions of dollars, given that WellPoint reimbursed more than $99 billion in health benefits for commercial and individual members in 2013.

In short, to create strategic benefits with analytics WellPoint had to change its organizational behavior. Without an effective collaboration between the business side and IT, the program would have remained in jeopardy. Without leadership’s involvement, the program would have remained in jeopardy. Preparing data for a strategic role often means changing business conduct and that, more often than not, requires a top down process to create the necessary alignment of incentives and goals.

To read the full report, please visit “The Analytics Mandate.”

David Kiron is Executive Editor, Big Ideas initiatives, for MIT Sloan Management Review.

Maybe the search for the Malaysian Airlines plane needed a chief data officer — Stuart Madnick

MIT Sloan Professor Stuart Madnick

MIT Sloan Professor Stuart Madnick

From Quartz

The search for an airplane lost on a 2,500-mile international journey requires consolidating information from many organizations, both public and private, from all over the world. It involves analyzing vast amounts of radar, sonar, and satellite data, coming from many diverse sources, including military bases, air traffic controllers, naval ships, and other airplanes.

What if the authorities investigating the missing plane had been prepared to manage big data the way many corporations do? What if the investigation had an executive level position responsible for collecting and analyzing all of the dispersed and diverse data that were available and potentially relevant to the search? What if a multinational chief data officer (CDO) had been in place to manage all of the information that was available?

Companies have recognized the value of just such a position for some time. The first reported chief data officer was established in 2003 by Capital One Financial Corp., Yahoo, and Microsoft Germany were early adopters. In little over a decade, hundreds of organizations, including US federal and state agencies, have created chief data officer positions, although the jobs often are given different titles. In time, the initials CDO may become as familiar as CEO, CFO, and CIO.

Driving the trend is the phenomenon of big data—the explosion of information made possible by the great advances that we have seen in recent years in communications, computers, and storage.

Read the full post at Quartz.

Stuart Madnick is co-head of the MIT Total Data Quality Management and MIT Information Quality programs. He is also a professor at MIT Sloan School of Management.

How bad data can lead to good decisions (sometimes) — Roger M. Stein

MIT Sloan Senior Lecturer Roger Stein

MIT Sloan Senior Lecturer Roger Stein

From Computerworld

Before companies can profit from big data, they often must deal with bad data. There may indeed be gold in the mountains of information that firms collect today, but there also are stores of contaminated or “noisy” data. In large organizations, especially financial institutions, data often suffer from mislabeling, omissions, and other inaccuracies. In firms that have undergone mergers or acquisitions, the problem is usually worse.

Contaminated data is a fact of life in statistics and econometrics. It is tempting to ignore or throw out bad data, or to assume that it can be “fixed” (or even identified) somehow. In general, this is not the case.

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Unlocking the value of data – Allison O’Hair

MIT Sloan Lecturer Allison O'Hair

MIT Sloan Lecturer Allison O’Hair

Compared to five years ago, the amount of data we now generate is huge. Some companies collect that data, but more often than not they don’t do anything with it. Business analytics is an important tool to help organizations harness the power of that data. By unlocking its value, you can do things like improve profits, predict consumer behavior, better understand markets, and make more informed decisions. Most importantly, it can give you a competitive edge.

For those of us in the field of operations research, data analytics is a huge and exciting area. It’s a critical tool for businesses moving forward. As a result, we’re offering MIT Sloan’s popular Analytics Edge course on the MITx online, interactive learning platform this spring. We want to share the cutting-edge knowledge generated at MIT on this important topic with people around the world. Read More »

Say “yes” to speak with a representative — service automation frustrating customers — Peter Weill

MIT Sloan Sr. Researcher Peter Weill

Have you tried to apply for a mortgage lately? If so, you might have some rather unpleasant memories of filling out endless forms and – if you had a question — trying to navigate through a voice recognition telephone system that didn’t understand you. If you were able to actually reach a real person, that employee might have been more focused on the procedure than actually listening to you. What is the result of this automation of processes? Not surprisingly, it’s disconnected and frustrated customers. Read More »