Analytics & Performance

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What Businesses Can Learn From Sports Analytics

In professional sports, some teams are becoming sophisticated in using data to measure team and player performance, sports business and health and injury prevention. Sports teams’ use of analytics has much to teach other managers about alignment, performance improvement and business ecosystems. For instance, teams are beginning to assess performance in context, seeing how teams do with or without a particular player. This “plus/minus” analysis could be a valuable technique for many businesses as well.

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Collecting Business Value from Energy Data

On the website of energy analytics startup Pilio, CEO and cofounder Catherine Bottrill says that it is a combination of technology, economics and politics that are instrumental in environmental problem solving. However, there is another ingredient necessary, says Bottrill: People. Bottrill is combining behavioral science with energy analytics to help organizations better understand — and manage — their energy use.

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How Analytics is Giving Fashion a Makeover

Recommendation engine StyleSeek is relying on data and analytics to drive business and fashion decisions — every single one of them. With about 50,000 actively registered users — impressive considering the company recently came out of private beta — and close to 200 retailers on board including the likes of Nordstrom, Macy’s and Anthropologie, StyleSeek may have tapped a new approach to a longstanding industry.

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Analyzing Performance in Service Organizations

We can’t always trust our intuition about how employees will perform. Intuition can be misleading, or just plain wrong. So a growing number of savvy service businesses have investigated the use of a sophisticated linear programming technique called DEA, or data envelopment analysis. Authors H. David Sherman and Joe Zhu, who call DEA “balanced benchmarking,” write that the technique helps companies locate best practices not visible through other management methodologies.

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Free Article

Predicting the Performance of Analytics Talent

The surprising finding that 55% of big data analytics projects are abandoned comes from a recent survey of 300 IT professionals. The most significant challenge with analytics projects, according to the survey? Finding talent. Most (80%) of the respondents said that the top two reasons analytics projects fail is that managers lack the right expertise in house to “connect the dots” around data to form appropriate insights, and projects lack of business context around data.

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Image courtesy of Flickr user MegMoggington.

Team GB: Using Analytics (and Intuition) To Improve Performance

Becoming an elite athlete — or coaching a team of this rarified breed — has as much to do with talent and skill as it does with experience and intuition (not to mention some serious hard work). And data is increasingly part of that mix at the highest echelon of sports: the Olympic Games. At Team GB analytics are used to both monitor the performance of athletes and to predict how well a team will perform. But what could the future hold? Evidence-based coaching — and training.

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From Value to Vision: Reimagining the Possible with Data Analytics

Based on a global executive survey with 2,500+ respondents and interviews with more than two dozen executives and academics, MIT Sloan Management Review and SAS Institute Inc. report on the distinctive characteristics and habits of companies that are very effective at using analytics to compete and innovate. This report offers an in-depth analysis of Analytical Innovators, the early leaders in the analytics revolution that is changing how many companies are managed.

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Sensing the Future Before It Occurs

GE believes companies will boost productivity and profits by using intelligent sensors and analytics to predict when parts and manufacturing lines will fail. This will smooth operations and accelerate product development. GE is investing in its operational use of intelligent sensors and hiring software developers to create better algorithms for analyzing huge amounts of data. William Ruh, head of GE’s global software development center, discusses the reasons behind GE’s investment in new technologies and why it thinks these will transform the global economy.

Image courtesy of Flickr user prayitno.
Free Article

Can Sensors Fuel Productivity Growth?

The Internet Revolution has so far not produced the kind of long-term productivity growth seen during the Industrial Revolution. Digital technology drove U.S. productivity growth above three percent annually only between 1996 and 2004. Since then, productivity has fallen to about 1.6 percent a year. General Electric argues that productivity growth will jump again as the industrial Internet emerges, connecting machines like turbines and jet engines to factories, and using analytics to make better decisions about maintenance and production.

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Video: Big Data and Analytics Right Now

Erik Brynjolfsson, director of the MIT Center for Digital Business, talks about the big data revolution with Tom Davenport, who helped get that revolution started with his seminal article “Competing on Analytics.” Their discussion illuminates what’s different about big data and how big data is changing management and the way businesses run.

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Business Quandary? Use a Competition to Crowdsource Best Answers

Top data scientists often share three characteristics: they are creative, they are curious and they are competitive. Anthony Goldbloom, CEO of Kaggle, a company that hosts data prediction competitions, has figured out how to tap all three of these characteristics to help companies crowdsource their analytics problems.

Veronika Belokhvostova, head of Global Business Analytics at PayPal.

Mining Data at PayPal to Guide Business Strategy

“The kind of people we hire want to know that their work is not gathering dust on some shelf, but has a real impact on the company,” says Veronika Belokhvostova, head of Global Business Analytics at PayPal. And indeed, business analysts there are collaborating with business leaders to answer the “what should we do next?” question.

Image courtesy of Match.com.

Innovating With Analytics

A data and analytics survey conducted by MIT Sloan Management Review in partnership with SAS Institute Inc. found a strong correlation between the value companies say they generate using analytics and the amount of data they use. The creators of the survey identified five levels of analytics sophistication, with those at Level 5 being most sophisticated and innovative. These analytical innovators in Level 5 had several defining traits. This article explores those traits.

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Image courtesy of IBM.

Winning the Race With Ever-Smarter Machines

The capabilities of computers are now improving so quickly that concepts can move from the realm of science fiction into everyday life in just a few years, rather than a lifetime. Rapid advances in information technology — computer hardware, software and networks — are yielding applications that can do anything from answering game show questions to driving cars. But to gain true leverage from these ever-improving technologies, companies need new processes and business models.

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Analytics: The Widening Divide

In this second joint MIT Sloan Management Review and IBM Institute for Business Value study, we see a growing divide between those companies that, on one side, see the value of business analytics and are transforming themselves to take advantage of these newfound opportunities, and those, on the other, that have yet to embrace them.

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