Data & Analytics

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Marketing In Five Dimensions

Computers, scanners, mobile and wearable technology have made it both easier and harder for companies to find their customers. Easier, because there’s so much more data about consumer behavior; harder, because analyzing that data is a significant challenge (never mind deciding how to act on the analytics). Companies like Epsilon are stepping up to help businesses to figure out what the data tell them about their customers — and what to do with that knowledge. In a Q&A, Epsilon’s CEO Andy Frawley describes some of the challenges his company works through on a daily basis.

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Better Decision Making with Objective Data is Impossible

“Our world is awash in data, and data is not the same thing as facts,” writes Boston College's Sam Ransbotham. “While data seems to promise objectivity, instead it requires analysis — which is replete with subjective interpretation.” Ransbotham argues that while having data is a necessary step towards making objective decisions, it’s a myth that data is objective. Moreover, findings that counter current thinking provide organizations with opportunity for distinction, differentiation and advantage.

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Using Big Data for Better Health Outcomes

Intermountain Healthcare is leading the way in data driven healthcare. In an example from Intermountain’s own operating rooms, the use of data to measure the impact of standardized surgeon attire on infection rates resulted in a significant drop in those rates. The infection control scenario is just one result from decades of work at Intermountain to build a data culture. Over the years, clinicians have learned to work together on a concerted effort to bring data based insights to clinicians and managers.

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The New Data Republic: Not Quite a Democracy

There are clear signs that the movement to democratize data is making real progress. Barriers such as infrastructure, culture, tools, and governance that once kept data access limited are quickly eroding. But access to data isn’t enough: Data democratization also requires knowing how to work with data and understand data analysis tools and techniques. Without these capabilities, the data democracy is only an illusion — and most people are still unable to participate fully.

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At This Education Nonprofit, A Is for Analytics

In an interview with MIT Sloan Management Review, Christopher House CEO Lori Baas and director of quality assurance Traci Stanley explain how they're using data throughout their educational organization to track student outcomes and look for improvements. "We now can show, based on the assessments, not only how our kids are improving in their cognitive development, or social-emotional development, but also how we compare to similar organizations," says Bass.

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Innovating with Airborne Analytics

Hong Kong’s premier airline is using a blend of data and know-how to guide its daily operations. In an interview with MIT Sloan Management Review, Cathay Pacific CIO Joe Locandro describes how the airline uses analytics to make decisions that balance data with what it knows from the field. “Analytics will give you statistical spreads, give you training, but you still need to have this thing called experience and insight,” he says.

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When Health Care Gets a Healthy Dose of Data

American health care is undergoing a data-driven transformation — and Intermountain Healthcare is leading the way. This MIT Sloan Management Review case study examines the data and analytics culture at Intermountain, a Utah-based company that runs 22 hospitals and 185 clinics. Data-driven decision making has improved patient outcomes in Intermountain's cardiovascular medicine, endocrinology, surgery, obstetrics and care processes — while saving millions of dollars in procurement and in its the supply chain. The case study includes video clips of interviews and a downloadable PDF version.

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The Analytics Talent Dividend

In May 2015, co-authors Sam Ransbotham, David Kiron and Pamela Kirk Prentice presented the findings from the recent global sustainability study, “The Talent Dividend.” The study found that the integration of analytics talent into the organization is key to analytics success. The webinar speakers discuss the components of a human resources plan for analytics talent, and give guidance on how to implement that plan in your organization.

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On the Care and Feeding of Your Analytics Talent

A panel of experts discusses the challenges of finding, engaging and organizing data scientists for best results. They talk about how to support your data scientists and keep them engaged in the right kinds of tasks and how to integrate new talent into your existing data and analytics team. They also talk about the skills and traits to look for when recruiting and selecting your data/analytics team, and how to assess existing internal talent for data roles.

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General Mills Builds Up Big Data to Answer Big Questions

General Mills brought a data scientist into its Consumer Insights group because it wanted to use its existing data more effectively. The company thought it was making decisions based too much on outside data at the expense of what it knew. But figuring out what the company actually knew about its consumers was the challenge facing Wayde Fleener as he came on board. In an interview with MIT SMR’s Michael Fitzgerald, Fleener talks about how he got started in building a Big Data practice within his division.

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Participant Questions from the Recent Data & Analytics Webinar

On May 7, 2015, we held a free, live webinar to share the findings and insights from the latest MIT Sloan Management Review Data and Analytics Big Idea Initiative research report, “The Talent Dividend.” The report presents our findings on the role of analytics talent in creating competitive advantage. At the end of the webinar, many participants asked questions. Unfortunately, we didn’t have time to answer them all during the webinar itself. So instead, we’ll answer some of the questions this month, and some next month.

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Coca-Cola’s Unique Challenge: Turning 250 Datasets Into One

At The Coca-Cola Company, one of the big challenges is how to understand customers who are a long pipeline away in the inherently intermediated world of hundreds of Coke bottlers. That means moving toward newer technologies to do more forward-looking analytics versus backward-looking analytics, says the company’s Remco Brouwer and Mathew Chacko.

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The Talent Dividend

The 2015 Data & Analytics Report by MIT Sloan Management Review and SAS finds that talent management is critical to realizing analytics benefits. This fifth annual survey of business executives, managers and analytics professionals from organizations located around the world captured insights from 2,719 respondents. It finds that organizations achieving the greatest benefits from analytics are also much more likely to have a plan for building their talent bench.

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Once You Align the Analytical Stars, What’s Next?

You’ve figured out how to get the data, and how to make sure it’s good quality. You’ve hired the right people to put your data through the analytics wringer. Now you’ve got the results in your hands &mdash and you may not be sure what to do next. Consuming analytics effectively — and getting business value out of your analytics — is a challenge for many companies, and executives must get creative to increase their comfort level.

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Minding the Analytics Gap

While analytical skills are improving among managers, the increasing sophistication of analyses is outpacing the development of those skills. The resulting gap creates a need for managers to become comfortable applying analytical results they do not fully understand. A 2014 survey by MIT Sloan Management Review, in partnership with SAS Institute Inc., highlights the ways that companies can address this problem by focusing on both the production and consumption sides of analytics.

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The New World of Work

Advanced digital technologies are swiftly changing the kinds of skills that jobs require. Researchers Frank MacCrory, George Westerman and Erik Brynjolfsson from the MIT Sloan School of Management and Yousef Alhammadi of the Masdar Institute studied the changes in skill requirements over the 2006-2014 time period. While demand has clearly grown for computer skills, it has grown for interpersonal skills, too. The authors advise people in all lines of work to be flexible about acquiring new talents.

Image courtesy of Wal-Mart.

Sustaining an Analytics Advantage

Many companies have maintained a competitive advantage through analytics for many years — even decades. Those companies include Wal-Mart, ABB Electric, Procter & Gamble, American Airlines, and Amazon. Peter C. Bell (Ivey Business School) writes that "research over a 30-year period suggests that there have been five basic ways in which companies have sustained an advantage generated through analytics." Tactics include keeping your company's analytics secret and applying analytics to the right problems.

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Analytics in E Major

The Echo Nest, a self-described “music intelligence” company recently acquired by Spotify, uses machine-learning technology to connect people with music. “At our core,” says CEO Jim Lucchese, “what we’re trying to do is what a great deejay does, or the friend that you rely on musically: to better understand who you are as a fan.” In a Q&A, Lucchese describes how the company merges machine learning and cultural analytics to describe music in an analytics-friendly way and help users find new music they’ll enjoy.

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Are Data Scientists Really a Breed Apart?

What differentiates data scientists from other quantitative analysts? It's partly their skill set and partly their mind set. “The recent emergence of the digital enterprise has created a seemingly insatiable management appetite to amass and analyze data,” write Jeanne G. Harris and Vijay Mehrotra. Data scientists are particularly able to make sense of so much information. For instance, 85% said their projects often or always address new problems, compared to 58% of analysts who made that claim.

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