MIT Sloan Center for Information Systems Research (CISR)

Abstract:
Enterprises today often replatform as part of their efforts to become Future Ready because the state of their existing systems, data, and processes hinders the organization’s ability to compete in the digital economy. In replatforming, an en…

Abstract:
Enterprises today often replatform as part of their efforts to become Future Ready because the state of their existing systems, data, and processes hinders the organization’s ability to compete in the digital economy. In replatforming, an en…

Abstract:
Four characteristics of AI—unproven value, model opacity, model drift, and mindless application—make it challenging to get stakeholders to trust AI solutions. As a result, organizations that strive to become AI-powered adopt practices to pro…

Abstract:
Four characteristics of AI—unproven value, model opacity, model drift, and mindless application—make it challenging to get stakeholders to trust AI solutions. As a result, organizations that strive to become AI-powered adopt practices to pro…

Abstract:
In the digital economy, companies must partner to thrive. In this session, Ina Sebastian discusses how companies successfully digitally partner for growth and innovation with examples from different domains, including Kaiser Permanente, Maer…

Abstract:
MIT CISR research has found that organizations that innovate greater strategic value faster are taking time to test and learn to build successful digital offerings, a portfolio of initiatives that achieve strategic objectives, and shared res…

Abstract:
MIT CISR research has shown that, given the right environment, a conventional workforce can achieve unconventional results. In this session, Nick shares how digital transformations can enable or constrain employees, and how to design employe…

Abstract:
In this session, we introduce the concept of data liquidity, which is the ease of data asset reuse and combination. First, Barb moderates a classroom discussion of a case study that features Anthem Health’s data liquidity efforts. Then, Barb…

Abstract:
This session introduces the concept of AI scale, and distinguishes AI scale up (the volume of model use) and AI scale out (the volume of recontextualized models). Barb illustrates AI scale with a case study from Pega, and how AI projects can…

Abstract:
Wherever your enterprise is on its journey to transformation, it will soon be accelerating. Drawing on the latest global MIT CISR research from over one thousand companies, Peter describes (1) what it takes to be a Future-Ready enterprise—on…

Abstract:
Companies capture value in a digital transformation from customers, participating in ecosystems, and operational efficiencies. Together, the three types of digital value explain 38 percent of company growth and 24 percent of profitability. B…

Abstract:
A digital company is designed, not structured. This is an important distinction because great design involves constant tinkering. Structuring and restructuring do not provide sufficient adaptability to evolving customer needs and digital cap…