Data & Analytics

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Image courtesy of Walmart

Should You Outsource Analytics?

Outsourcing analytics activities can offer benefits, but it requires a carefully constructed relationship between the company and the business process organization (BPO). Customers must be careful not to lose their expertise or their core intellectual property. Research suggests that companies with superior analytics capabilities will approach outsourcing differently than companies that are analytically challenged.

David Simchi-Levi

Overheard at MIT

“Big Data in Manufacturing” was the theme of a daylong conference held in Cambridge, Massachusetts, in November 2013 and sponsored by the MIT Forum for Supply Chain Innovation and the Accenture and MIT Alliance in Business Analytics. But the speakers’ insights weren’t restricted to manufacturing.

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Turning Big Data Into Smart Data

Current thinking has big data and analytics turning companies into data-driven powerhouses. But just having data doesn’t make a company smarter; if companies don’t know how to use data well in the first place, it can actually prevent companies from making the transition to data-driven operations. Jeanne Ross, the director of MIT’s Center for Information Systems Research, says that companies can build cultures that encourage people, even low-level employees, to work well with data by using evidence-based management.

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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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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.

Image credit: LinkedIn Corporation

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.

Image courtesy of Flickr user Vermin Inc.
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Omnichannel Retailing and Data Analytics: Leveling the Playing Field

We’re in a new world of omnichannel retailing that includes physical, online and mobile channels. And those channels are blurring.

In a recent AllAnaltyics video and web chat, Analytics in the Age of Omnichannel Retailing, researchers Erik Brynjolfsson, director of the MIT Center for Digital Business, Yu Jeffrey Hu, associate professor at Georgia Institute of Technology’s Scheller College of Business, and Mohammad Rahman, associate professor at University of Calgary’s Haskayne School of Business, discussed the challenges facing retailers.

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Big Data That’s Good for the Public

Facts: 900 million. Active sources: more than 100,000. Data sets: 30,000, with 200 million time series and 1.5 billion fact values.

Link all these data sources together and what do you get? Timely, if not crucial, contextual information about markets, trends, competitors, products and consumer opinions.

This is the promise of DOPA, a project funded under the umbrella of the European Union.

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A Process of Continuous Innovation: Centralizing Analytics at Caesars

Over the past several years, Caesars has undergone a reorganization, in part to centralize its analytics functions. It has sought to build a deeper understanding not only of customers, but also of operations — everything from food and beverage analytics to labor analytics. Ruben Sigala, chief analytics officer at Caesars, talks with MIT Sloan Management Review contributing editor Renee Boucher Ferguson about that process, some valuable lessons learned, and where innovation and intuition play a role.

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Big Data’s Travails Don’t Mean It’s Derailed

Executives are growing dismissive of Big Data’s value. Even the best companies can struggle to get good results from their data. But data isn’t getting smaller, it’s getting much, much larger. Corporate executives should look at what’s emerging from universities like MIT, where researchers are beginning to get answers to longstanding big questions in healthcare, public policy and finance.

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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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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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Big Data and Big Change Management: A Path Forward

MIT Sloan School of Management recently held a two-day executive education course, Big Data: Making Complex Things Simpler, designed to provide organizations with both an overview of big data and a few techniques to harness some of the illusive power of data. But in all the discussions that surfaced around the big issues from big data, the reality that many organizations grapple with is change management.

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Educating Executives Online in Four Dimensions

I am the proud recipient of an MIT Sloan Executive Education Course certification. Or, my avatar is.

MIT Sloan’s Big Data 4Dx executive education course, held simultaneously in Cambridge and in the virtual world this April, was the first ever to use a gaming interface. Think Second Life for the professional set.

Through the AvayaLive Engage platform, we online students were transported (as avatars) to a virtual auditorium, the classroom setting for the two-day Big Data: Making Complex Things Simpler course.

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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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Reimagining the Possible with Data Analytics? Some Answers to Your Questions

During our webinar, we described those characteristics that define each group, and what your organization can do to become more like Analytical Innovators — if you’re not there already (in a poll, 13% of audience members identified themselves as Analytical Innovators).

As the hour-long webinar came to a close, we found that there were far more questions than we had time to answer. And we also found that there were far too many intriguing questions to let them go unanswered.

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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 numerous television and radio stations and digital platforms. It uses 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 21-40 of 109