Data & Analytics

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Data Analytics Makes the Transition From Novelty to Commodity

Business is nearing a tipping point in which the use of data analytics is becoming routinely adopted. While widespread adoption of analytics will mean that it offers less competitive advantage to companies, it also means that the business environment overall will change. Information systems expert Sam Ransbotham identifies four key changes that businesses need to consider now.

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How Facebook is Delivering Personalization on a Whole New Scale

As Facebook becomes more mobile-centric, it’s also becoming adept at laying its customer data over brand data and third-party data to create uniquely customized experiences for its users. In a Q&A, Blake Chandlee, vice president of global partnerships at Facebook, details the power that comes from being able to overlay all that customer information. “Historically, we’ve never had the ability to have the scale of a mass media along with the personalization that digital provides,” says Chandlee.

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Does Your Company Collect Data — Or Hoard It?

As it has become clearer that data offers value to companies, some organizations are tempted to take a “more is better” approach. But there’s a fine line between collecting data that offers value and hoarding data, which ultimately proves counterproductive. Ransbotham’s Three Laws of Data Collection offer guidance.

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Revisiting Complexity in the Digital Age

As businesses grow and diversify, they almost inevitably make their range of offerings more complex. Until now, managing that complexity usually involved a trade-off between creating value from complexity and benefiting from the efficiencies of simplicity. But smart use of today’s digital technologies can help companies finesse those trade-offs between costs and benefits. Digitization can help companies, for instance, increase product variety and integration while maintaining process simplicity.

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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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A New, Analytics-Based Era of Banking Dawns at State Street

Change does not come easy to established institutions, particularly when they count their longevity in centuries rather than decades. Yet in the wake of the global financial crisis, State Street Bank has elected to revamp 200+ years (and counting) of banking practices in favor of a data-driven, analytics-based business model. In doing so, it created a new business, SSGX — and initiated significant cultural changes.

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In Sports, It’s Quants Versus Managers

There have been a number of stunning sports upsets that make it clear that the lines are fading between intuition and experience on the one hand, and data and analytics on the other. Where the “gut” instinct of managers and owners once ruled, analytic insights are fast becoming a standard part of the playbook. What’s at stake? Seemingly everything: trophies, revenues, funding and fans, not to mention the sheer thrill of victory. That’s particularly the case in elite professional sports.

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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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Rent The Runway: Organizing Around Analytics

For the fashionista who lacks the budget to buy fabulous designer dresses, there’s a solution: Rent one.

Rent The Runway rents occasion dresses. The company caters to its fashion forward clientele through unique services, including on-call stylist advice and customer’s “style moment” photos, parsed by measurements.

These services are, in no small measure, what sets Rent The Runway apart from its small pool of competitors. They’re are also driven by data and analytics.

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From the Editor: Decision Making in the Digital Age

Business executives today have access to far more data than any previous generation, and that transforms the way business decisions are made. The Winter 2014 issue of MIT Sloan Management Review features a special report investigating how, even with plenty of data, making wise decisions about topics like strategy can be challenging. No matter how much data we collect and analyze, our perspectives are still colored by human foibles.

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Raising the Bar With Analytics

More than half of managers surveyed strongly agree that their organizations need to step up analytics use, according to a 2013 global survey by MIT SMR and SAS Institute. In addition, survey data suggests that in companies where analytics has improved the ability to innovate, managers are more likely to share data with partners and suppliers.

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What’s Your Information Footprint?

Wealth once was measured by the amount of land, employees or equipment you had. Today we are on the cusp of a period in which another factor is an indicator of potential wealth: how much information you have. Information has the potential to be a valuable asset, and a new framework, dubbed “the information footprint,” presents a way for companies to assess their information assets and the opportunities it gives them for new value creation.

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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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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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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.

Image courtesy of AT&T.

Making Data Visible So You Can Act On It

At AT&T, John Schulz, a director of sustainability operations, had to make the company’s energy and water use data visible before the company could formulate a plan to reduce those numbers. The company’s definition has now broadened and evolved to include the social perspective on sustainability.

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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.

Image courtesy of Flickr user kk+.

Location Analytics: Bringing Geography Back

Remember geography lessons in school, painstakingly memorizing the longest rivers, cultures of various regions, the state capitals? For most of us, those lessons are in the past. But in the world of big data analytics, geography is making a comeback.

The relatively new market of location analytics is expanding the uses of more traditional geographic information system (GIS) technology to include social, geographic, physical and emotional indicators that help organizations better predict trends

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