Analytics & Strategy

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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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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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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.

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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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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Crafting Health Care’s Future at Kaiser Permanente

Dr. Yan Chow is a director in the Innovation and Advanced Technology group at Kaiser Permanente. While a physician with over two decades of primary care clinical practice experience, Dr. Chow also has a keen interest in technology (he’s founded several technology startups). His areas of expertise: health care IT innovation, telehealth, big data and analytics. Here, he talks about innovation and the future of health care.

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The Digital C-Suite

A new study finds that executives at large companies are unhappy with their digital strategies and ability to make decisions on technology. The problem? Lack of cohesion and coordination among departments. Having all C-level executives engage with technology and digital business strategy might be the answer.

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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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Elevating Data, Analytics to the C-Suite

The former senior vice president of vendor analytics at Bank of America is now chief analytics officer at Bank of America Merchant Services. While Merchant Services is technically a separate business, Douglas Hague’s ascension to the C-suite is notable in that it’s one of the first analytics roles to report directly to the CEO at Bank of America Merchant Services. That has some implications for strategy and for long-term planning.

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Rent The Runway: Organizing Around Analytics

Treating analytics as a strategic asset at the senior level has enabled a fashion-focused startup to innovate. Rent The Runway, an online service that rents occasion dresses, caters to its fashion-forward clientele through unique services such as on-call stylist advice and customer’s “style moment” photos. These services, driven by data and analytics, are what set Rent The Runway apart from its small pool of competitors.

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Better Decisions with Smarter Data

Part of that gap between the pressure to be more data-driven in decision making, and a lack of useful data, says Grenoble University researcher Ali Fouladkar, can be explained by the fact that while data analysis has led to competitive advantage for some organizations, decision makers are often presented with noise-filled big data. What they need instead is smart data, but the problem in getting to smart data in an era of big data is part technological and part training.

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Luminar Insights

Facing headwinds from a shifting media industry, executives at Spanish-language broadcasting company Entravision recognized the need to innovate their business model. To get there, they created Luminar, a big data insights division that utilizes about 2,000 external data points to deliver customized, transaction-based insights to marketers about Entravision’s Latino audience. The fastest-growing U.S. demographic, Latinos have amassed buying power worth more than a trillion dollars annually.

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Video: Leveraging Analytics to Transform a Traditional Broadcast Business

Using big data technology, Luminar is helping to transform its parent company, Entravision, beyond its broadcasting roots. With a data store of 50 million Latino adults with transactional records from 2,000 sources, Luminar has insights on 65% of the US Latino adult population. Luminar is able to provide new, relevant insights to advertisers and marketers interested in reaching the Latino consumer, and in the process change Entravision from a broadcast company to an insights company.

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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.

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Are Predictive Analytics Transforming Your Supply Chain?

While some industries like health care and retail are starting to see the transformational potential of big data and predictive analytics, these strategies haven’t quite panned out for supply chain managers. Why? Two big barriers: The cost of hiring skilled employees and the complexity of connecting nodes across an extended supply chain network. New research suggests that the convergence of data science, predictive analytics and big data have the potential to transform the way in which supply chains leaders lead, and supply chains operate.

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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.

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