Data & Analytics

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Turning Big Data Into Smart Data

Current thinking has big data and analytics turning companies into data-driven powerhouses. But if companies don’t know how to use data well, it can actually prevent companies from making the transition to data-driven operations. Jeanne Ross, 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.

NVP
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How Big Data is Influencing Big Companies

A recent data and analytics survey sheds light on what large organizations are actually doing with big data initiatives. The survey of nearly 100 senior executives from Fortune 1000 companies found that executives are reporting anincreasing commitment to big data projects. As well, most executives, 70%, are looking to improve their “time to answer” with big data.

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Three Paradoxes of Big Data

The 1997 sci-fi film Gattaca presents a society where DNA determines social class. A registry identifies and creates genetically superior individuals — termed “valids” — while winnowing out their naturally conceived “in-valid” counterparts. The “valids” have a predetermined career (and life!) path, unalterable by desire, capability, circumstance or happenstance.

But how close are fact and fiction? Can genetics, biometrics and, essentially, predictive analytics be utilized to determine an individual’s path?

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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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Smart Cities and Economic Development: What to Consider

Smart cities are popping up around the globe, from China where 193 smart cities are being piloted, to Europe, the U.K. and the U.S. Their development involves a wide scope of technology, everything from renewable energy, green buildings and smart grids to traffic management, urban security and medical technology. The goal: urban sustainable development and economic growth. Opportunities abound to be part of this global urban revitalization effort. The question is, at what cost to participants?

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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.

Image courtesy of Flickr user LunaWeb.
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Is Digital Advertising a New Form of Market Manipulation?

Social networking and digital advertising are colliding at a dizzying rate. Facebook, which has over 1 billion users, is launching video ads. Twitter, with more than 200 million users, just bought MoPub, a digital advertising platform that essentially creates an ad space that is sold and delivered every time a user views a page. What does this all mean for the relationship between businesses and consumers? The short answer: Market manipulation.

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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.

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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, Yu Jeffrey Hu and Mohammad Rahman 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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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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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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The Pitfalls of Using Online and Social Data in Big Data Analysis

Is Twitter a litmus test for how a segment of society is acting — or thinking — at any given moment? Not quite. Striking new research out of Princeton University and the University of North at Carolina Chapel Hill suggests that inferences based on how people use social media platforms like Twitter and Facebook should be reconsidered because these platforms represent skewed samples from which it is difficult to draw accurate conclusions.

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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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When Competition Shifts From the Known to the Unknown

In a research paper, Masters of Big Data: Concentration of Power Over Digital Information, Alessandro Mantelero posits that because not everyone has access to all sources of information — or the ability and infrastructure to exploit data — there is a concentration of a new kind of power: the power of information.

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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.

Showing 41-60 of 137