Three principles show how successful retailers are responding to digital disruption and using insights to improve customer experience — not just in the end-of-year rush, but year-round.

Innovation is transforming the health care industry, with unlikely collaborators teaming up to provide higher-quality, lower-cost services. In this interview with MIT SMR, Harvard Business School professor Regina Herzlinger, an expert in health care delivery and innovation, discusses recent collaborations between retailers and insurers, such as CVS’s partnership with Aetna and Walmart’s with Humana, and explains why hospitals and other providers must be more innovative, too.

A 2018 research survey found that companies see competitors gearing up for big data and AI success — and that’s fueling their investment in similar capabilities.

Working with Lean Startup author Eric Ries inspired General Electric to test a new way of working. FastWorks is an agile process, complementing the Six Sigma process already in place at GE.

The senior director of the Cisco Digitization Office shares context on specific initiatives underway to keep Cisco relevant in a digital area.

John Glaser, vice president of population health at Cerner Corporation, discusses the opportunities and challenges presented by health care data.

The impact of artificial intelligence on the future of work and organizations was an especially popular topic on MIT Sloan Management Review’s website in 2017. But AI wasn’t the only subject on readers’ minds. Other widely read pieces of new content addressed timely issues like digital transformation and design thinking — as well as perennially important topics such as innovation, strategy execution, problem formulation, and negative emotions in the workplace.

Sam Ransbotham and David Kiron, co-authors of the 2017 MIT SMR Data & Analytics Research Report, “Analytics as a Source of Business Innovation,” shared the findings and insights from their research into the changing landscape for companies looking to embed data and analytics into their strategies, processes, and operations.

Two questions for AI managers; the DAO of blockchain business; standing up a successful innovation lab.

How blockchain could transform management; the Internet’s effect on innovation hubs; putting data to work with knowledge graphs.

Fast, iterative “virtual research centers,” where hypotheses are tested and improved before they are scaled into new products, are edging out traditional R&D approaches.

Bringing high-tech inventions built on patented technologies to market can be complicated and risky. The threat of added costs from patent infringement lawsuits has led technology companies to pool their talents — and patents — in technology consortia. Joining a tech consortium requires managers to weigh intellectual property value against the value of future collaborations and assess the consortium’s pros and cons for innovation, competition, and market creation.

Unlike agriculture, where cutting-edge technologies are being aggressively adopted, forestry and its related industries are something of a technology laggard. But the prospect of the industry using sensors in the field, both in sawmills and even embedded within trees themselves, is emerging. Eric Hansen and Scott Leavengood, both professors at Oregon State University’s Wood Science and Engineering department, discuss how the Internet of Things could help drive efficiency and improve quality in the forestry sector.

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.

At its roots, life-cycle assessment (LCA) is a method to quantify total sustainability impacts — like resource use and environmental damage — over the entire life of a product, from “cradle to grave.” While there is informational value in the basic exercise, the real utility of LCA is comparison — that is, comparing one product’s sustainability impacts with another’s. Given the effort and cost involved, what are the strategic benefits of LCA? And should you be employing such a process?

Chinese companies are opening up a new front in global competition. It centers on what the authors call accelerated innovation — that is, reengineering research and development and innovation processes to make new product development dramatically faster and less costly. The new emphasis is unlikely to generate stunning technological breakthroughs, but it allows Chinese competitors to reduce the time it takes to bring innovative products and services to mainstream markets. It also represents a different way of deploying Chinese cost and volume advantages in global competition.

During a recent Exec Ed course, Big Data: Making Complex Things Simpler, MIT Sloan offered its first-ever virtual 4Dx course. Through the AvayaLive Engage platform, online students were transported, as avatars, to a virtual auditorium. That was the classroom setting for the two-day program.

Despite the considerable amount of attention paid to social media by business, the press, and academia, managers still don’t have a clear understanding of what social media actually is. Managers need to understand the nature of social media so that they can understand its strengths and weaknesses for their own business. If they don’t — in a market environment increasingly influenced by social media — they may find themselves at a competitive disadvantage.

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.

A data and analytics survey conducted by MIT Sloan Management Review in partnership with SAS Institute Inc. found a strong correlation between the value companies say they generate using analytics and the amount of data they use. The creators of the survey identified five levels of analytics sophistication, with those at Level 5 being most sophisticated and innovative. These analytical innovators in Level 5 had several defining traits. This article explores those traits.