Analytics & Organizational Culture

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How to Hire Data-Driven Leaders

For recruiters, the technological developments of the past 3 years have been transformational, says Tuck Rickards of Russell Reynolds. With the transformation of business to a more real-time, connected, data-driven focus, the type of talent companies seek — even the type of organizational structure they’re building — has undergone a quantum shift. But the changes aren’t yet done: “The next five years are huge for companies to reorient themselves from a leadership and team perspective,” warns Rickards.

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Sports Analytics: The NFL Connects with Fans

In a conversation with MIT Sloan Management Review, Michelle McKenna-Doyle, the NFL's senior vice president and first-ever CIO, discusses the organization’s customer-focused approach to big data and analytics. She explains how the NFL works to make its employees comfortable with their own data sets.

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Is Your Organization Ready for the Impending Flood of Data?

Hal Varian, chief economist at Google and emeritus professor at UC Berkeley, has been with Google for more than a decade and has unique insight into the past and future of data analytics. In a conversation with MIT Sloan Management Review guest editor Sam Ransbotham, Varian says that companies need to beef up their systems to function within an overwhelming data flow — including new voice-command system data and other computer-mediated transactions.

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Catching Up with Scantily Clad Analytics Emperors

If you’re lying awake at night fretting that your competition has mastered analytics when you haven’t, take a breath — many of the stories we hear about analytics success are likely skewed. The transition to analytics-focused business is still far, far from universal, and that, says information systems expert Sam Ransbotham, means you have a chance to catch up.

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Short on Analytics Talent? Seven Tips to Help Your Company Thrive

Companies are having a tough time finding the data scientists they need — they just aren’t being trained fast enough to meet market demand. While it may be challenging to keep ambitious analytics projects in development without employees with the necessary skill sets, that doesn’t mean those projects need to halt altogether. Sam Ransbotham offers seven tips for making progress when you don’t have enough analytics talent on board.

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At Amadeus, Finding Data Science Talent Is Just the Beginning

Everyone wants to hire skilled data scientists — especially Spain’s Amadeus, a travel sector technology company. Amadeus has brought more than forty new hires into this post since 2013. But locating talent is just the beginning. In an interview with MIT Sloan Management Review, Amadeus’s Denis Arnaud describes the steps he takes to not only identify data science talent, but to make sure they integrate well into the company, too.

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Training the Next Generation of Business Analytics Professionals

When Michael Rappa proposed to his employer, North Carolina State University, that they create a degree program for business analytics in 1999, they dismissed the idea. But 14 years later, the Institute for Advanced Analytics is a pioneering and successful program that trains analytics professionals for businesses hungry for analytics skills. Rappa sat down with MIT Sloan Management Review’s Michael Fitzgerald to explain how the Institute came about — and where it’s headed.

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Getting Value From Your Data Scientists

Data scientists differ from other types of analysts in significant respects. To create real business value, top management must learn how to manage these “numbers people” effectively. To help executives avoid repeating some of the mistakes that have undermined the success of previous generations of analytical talent, the authors offer up seven recommendations for providing useful leadership and direction.

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Capitalizing on Data by Building Organizational Capabilities

The idea is simple: develop a methodology that ties patient outcomes to provider fees so that clinicians are rewarded when patients’ health improves. Making it happen is a lot more complicated. When WellPoint undertook this task, it discovered that there was more to it than simply the challenge of applying data analytics technology — the company’s innovation processes had to be reinvented.

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Technology Solutions for Health Care Need a Continuous Process

It’s no secret that the fee-for-service model in U.S. health care is a driving factor in spiraling costs. WellPoint’s innovative plan to shift to a value-based payment plan may prove to be a key innovation that keeps a lid on those costs. But as commentator Sam Ransbotham points out, their effort to change the payment system also highlights a need for process changes at WellPoint itself.

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The Analytics Mandate

Based on a global executive survey with 2,000+ respondents and interviews with more than thirty executives, MIT Sloan Management Review and SAS Institute Inc. report that analytics has become a common path to business value. Organizations are now being challenged to step up their use of analytics, whether they are just getting started or are seasoned practitioners. The implications for industry competition are coming into focus—companies that incorporate analytics into their culture are finding success in the new digital era.

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Harnessing Quant Power

A new book by Thomas H. Davenport and Jinho Kim says that if companies can’t turn all the data they’re swimming in into better decision making through quantitative analytics, they’re “probably creating suboptimal performance.” The book, Keeping Up with the Quants: Your Guide to Understanding and Using Analytics, is geared toward executives who are not analytics experts but whose jobs require them to deal with those who have such expertise, both inside and outside their organizations.

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Why Predictive Analytics Needs Due Process

Researchers are proposing a new method to limit privacy harms from predictive analytics: Apply due process that would determine, legally, the fairness of an algorithm. While a new framework may be a step forward for individual privacy, what does it mean for organizations that collect and utilize big data through a predictive analytics lens? A couple of things — should data-oriented due process pass policy and legislative muster.

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Are Algorithms Influencing Your Business?

The growing importance of algorithms to business and society is a little discussed feature of our increasingly digital world. These algorithms are the underpinnings of NSA surveillance, online search engines, corporate security, modern matchmaking and other activities in both the private and public sector. They can be a source of competitive advantage (think Google), play an operational role or drive marketing. Just what are algorithms, how are they used, and what happens when influential algorithms go wrong?

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The Relevance of Data: Going Behind The Scenes at LinkedIn

It is an understatement to say LinkedIn is growing like a weed. With 238 million members in over 200 countries, 2.8 million active company profiles, and 1 million professionally oriented groups, LinkedIn has become the world’s largest professional networking site. Deepak Agarwal, LinkedIn’s director of relevance science, explains how his company uses data and analytics to sustain this growth.

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Transparency as a Competitive Advantage: Think Very Carefully About Communicating Your Data Sharing Initiatives

In the weeks following revelations that the U.S. National Security Agency's domestic spying network taps the electronic and telephone communiqués of so many Americans, consumers have intensified their concerns about corporate complicity in government data snooping. That leads to the question: Are we at the beginning of a consumer backlash that will stymie data-sharing? Or is it inevitable that we're moving into a new era of diminished privacy?

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How eBay Uses Data and Analytics to Get Closer to Its (Massive) Customer Base

You can find just about anything on eBay: A vintage BMW, a Lear jet, a half-million-dollar yacht. From all that activity stems a lot of data and, eventually, information. In conversation with MIT Sloan Management Review contributing editor Renee Boucher Ferguson, Neel Sundaresan, senior director of research at eBay, discusses how eBay uses data and analytics at every level of the company to continuously evolve eBay’s numerous sites and services for buyers and sellers.

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How Analytics Can Transform Business Models

There are 52 million Latinos in the United States, with $1.5 trillion of purchasing power. Entravision Communications Corporation, a Spanish-language media company, reaches about 96% of that U.S. Latino audience through its television and radio stations and digital platforms. And it's using that extraordinary reach to provide media solutions to marketers interested in tapping into the Latino consumer market.

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Lessons From Analytical Innovators

In a webinar recorded in March 2013, the speakers present findings from the recent global study they co-authored, “From Value to Vision: Reimagining the Possible with Data Analytics.” In their study, they identified leaders of the analytics revolution they call “Analytical Innovators.” These companies share three key characteristics: a widely shared belief that data is a core asset; more effective use of more data for faster results; and support for analytics by senior managers shift power and resources to those who make data-driven decisions.

Showing 1-20 of 35