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Secrets are a casualty of analytical prowess, and companies have new incentives to act honorably.
Big Data approaches developed by new economy firms are being adopted by mainstream corporations.
Leading companies are using an array of detection and response techniques to become more resilient.
Data & Analytics
Support for the Data & Analytics topic provided in part by:
KNOWLEDGE PARTNERMIT Sloan Management Review is collaborating with SAS on the development of research materials connected with analytics and management innovation.
GLOBAL INSIGHTS CASE STUDY SPONSORBecoming an analytics-driven organization means embedding analytics into your day-to-day business processes to drive real innovation.
- RESOURCES FROM EY ON DATA & ANALYTICS
- Making Decisions Faster
- Scientific Retailing and Advance Analytics
- Re-engineering the Supply Chain for the Omni-channel of Tomorrow
August 21, 2015 | Deborah Gallagher
An interactive infographic from MIT SMR’s content collaborator, SAS, and its partner site, AllAnalytics.com, highlights findings from the 2015 data and analytics research report, The Talent Dividend. The animated infographic illustrates several key stats from the report, including findings on finding, acquiring and managing analytics talent, and on changes to how companies are leveraging analytics for competitive advantage.
Sam Ransbotham et al.
The 2015 Data & Analytics Report by MIT Sloan Management Review and SAS finds that talent management is critical to realizing analytics benefits.
David Kiron et al.
The 2014 Data & Analytics Report by MIT Sloan Management Review and SAS finds that an analytics culture offers better outcomes.
David Kiron et al.
The 2013 Data & Analytics Report by MIT Sloan Management Review and SAS details the emergence of Analytical Innovators.
June 25, 2015 | Michael Fitzgerald
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.
| Christopher Mazzei
An organization can have the best technology and the best analytics but still fail to deliver. As Intermountain Healthcare demonstrates, a commitment to the human dimension can drive return on analytics investment. Its leadership commitment to analytics and organizational processes promotes a culture where every question is welcome and data delivers insights. And its training and incentives for doctors and other analytics ‘consumers’ encourage behaviors that deliver better outcomes.
Finding and keeping analytics talent is a top priority for companies, and one of their biggest challenges. These articles present insight from MIT Sloan's Roger M. Stein and from Jeanne G. Harris (managing director of information technology research at the Accenture Institute for High Performance) and Vijay Mehrotra (University of San Francisco).
Roger M. Stein
Here’s what it takes to lead a high-performing data science team in which team members (and their managers) are excited by what their teammates can do.
Roger M. Stein
The process of managing a data science research effort can seem quite messy, in contrast to data's aura of reason.
Jeanne G. Harris and Vijay Mehrotra
To create real business value, top management must learn how to manage data scientists effectively.
Sam Ransbotham et al.
Should an international organization be required to take control of uniting the Internet of Things (IoT) into one system?
Sam Ransbotham (Boston College) et al.
An authors’ briefing and Q&A on the findings from the MIT SMR/SAS 2015 global study on data and analytics.
Denis Arnaud (Amadeus Travel Intelligence), Tuck Rickards (Russell Reynolds Associates), Sam Ransbotham (Boston College), interviewed by Michael Fitzgerald (MIT SMR)
A panel of experts discusses how to attract and manage analytics talent for best results.
We answer three questions about the findings in our recent Big Idea Initiative research report, “The Talent Dividend.”
Our interviews with data practitioners from Cathay Pacific airlines, General Mills, Coca Cola and more explore how organizations are utilizing data for better decision making in the real world.
Greg Jones (Equifax), interviewed by Sam Ransbotham
Equifax credit reporting agency is beginning to incorporate unstructured data from sources such as social media.
Wayde Fleener (General Mills), interviewed by Michael Fitzgerald
Companies adding analytics professionals must navigate cultural tradition and turf tensions.
Joe Locandro (Cathay Pacific), interviewed by David Kiron
Airline Cathay Pacific incorporates data into all its operations to make decision making more efficient. But experience counts, too.
Joseph D. Bruhin (Constellation Brands), interviewed by Sam Ransbotham
Graphic presentations of data are making it easier for sales people to see how they’re performing.
Remco Brouwer and Mathew Chacko (Coca-Cola), interviewed by Sam Ransbotham
Coca-Cola uses forward-looking analytics to understand its customer base and international distribution network.
Lori Baas and Traci Stanley (Christopher House), interviewed by Sam Ransbotham
Chicago nonprofit Christopher House uses data to drive outcomes in providing education services to low-income families.
With the explosion of new technologies comes a new universe of data — and Epsilon is helping businesses navigate it.
What do you do when you’ve got an unending stream of quality data, and processes in place for analytics… but you’re not sure what to do with it all?
By 2020, most new data will be generated not by people but by sensors and embedded, intelligent devices.
As sensors and computer-mediated transactions become universal, Google’s Hal Varian warns that organizations need to prepare for a flood of data.
Companies are having a tough time finding the data scientists they need — but that doesn’t mean those projects need to halt altogether.
Big data analysis can help geographically distributed companies monitor customer satisfaction.
The Echo Nest, a “music intelligence” company, uses machine-learning technology to connect people with new music.
When it comes to big data, GE avoids warehousing and instead turns to the data lake approach.
As business moves to a real-time, data-driven focus, the search for talent has undergone a quantum shift.
If there are quality problems with your data, there are ways to clean it up — but it’s often more efficient to refactor your processes to prevent “smelly” data.
Intermountain Healthcare uses data and analytics to improve its health services, including lowering its infection rates.
Huge, complex datasets are becoming universal. The skills needed to work with them? Not so much.
March 23, 2011 | Thomas H. Davenport and Jim Hagemann Snabe
Almost all executives want more and faster information, and almost all companies are racing to provide it. What many of them overlook, though, is that the real aim should be not faster information but faster decision making — and those aren’t the same things. "Few organizations have reached an optimum with regard to how fast important information reaches in boxes, desks and brains," write the authors. "Decision makers can digest only so much information, and only so fast."