Big Data

Showing 1-7 of 7

Ransbotham-Analytics-Myopia-1200x1200
Free Article

Avoiding Analytical Myopia

Analytics offers managers a great way to fine-tune processes, but too many executives focus on metrics at the expense of the bigger picture. The blinders and focus that work well to optimize the details of a problem may prevent managers from seeing other options, and intense focus on a narrow measure can address only the well-specified puzzle — resulting in a myopic view of the problem. Executives who desire bigger breakthroughs need to encourage exploration.

Gloor-Email-Organization-1200

What Email Reveals About Your Organization

By studying data from email archives and other sources, managers can gain surprising insights about how groups should be organized and about which communications patterns are most successful. Anonymized analysis of internal information communication found that creative people, for instance, work more productively on projects with strong leaders than on collaborations without a clear leader. In addition, in many situations, groups of leaders taking turns worked better at sparking creativity.

Highly-detailed-planet-Earth-at-night-1200

Sharing Supply Chain Data in the Digital Era

Effectively managing and coordinating supply chains will increasingly require new approaches to data transparency and collaboration. Supply chains in coming years will become even more “networked” than they are today — with significant portions of strategic assets and core capabilities externally sourced and coordinated. Already, progressive companies are developing novel solutions to the dilemma of data transparency by using data “cleanrooms” and digital marketplaces.

Fleener-1200

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.

luchese-1200-3

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.

advertisement

BeanIoT-1200
Free Article

If You Think Big Data’s Challenges Are Tough Now

Although workers and consumers generate two-thirds of all new data, that’s about to change. Sensors and smart devices — from traffic lights and grocery store scanners to hospital equipment and industrial sensors — are beginning to generate an enormous wave of data that will increase the digital universe ten-fold by 2020. Guest blogger Randy Bean, CEO of NewVantage Partners, explains what this means for executives trying to adapt to a rapidly changing, data-centered business environment.

Campisi-1200

Gone Fishing — For Data

When you’re dealing with data on the massive scale that a company like GE uses, a data warehouse just isn’t big enough to house it all. And organizing it ahead of analysis is more of a burden than a help. GE’s CIO Vince Campisi explains to MIT Sloan Management Review why his company is now storing data in a data lake — and how that approach changes the kind of human resources his company is looking for.

Showing 1-7 of 7