Change Management

A framework to help leaders understand how they weathered COVID-19 and to keep leveraging their new innovation skills.

In this webinar, Jeffrey D. Camm and Thomas H. Davenport explain how the COVID-19 pandemic has impacted the practice of data analytics.

In this webinar, MIT SMR author Eric J. McNulty shares practical tips for leaders leading through the global COVID-19 pandemic.

AI is a powerful tool for innovation when leaders communicate its benefits.

To operate their companies effectively worldwide, leaders need to rethink how work gets done, and where.

To drive major change, companies must link data quality and data science within the organization.

The winner of the 2020 Beckhard Prize is “Improving the Rhythm of Your Collaboration,” by Ethan Bernstein, Jesse Shore, and David Lazer.

Developing truly innovative strategy requires workshopping your own company’s disruption.

Strategizing for change, leading with agility, and developing AI strategy.

A fundamental source of confusion about change is the use of that single term — change — to refer to three distinct strategies.

The most effective response to disruption is a long-view focus on employee development.

AI strategy will only get big results if companies focus on what AI can do at scale.

MIT SMR Winter 2020 examines workers’ emotions and education, tech dilemmas, and how best to transform.

To plan for change that will stick, leaders must first understand how employees adopt digital tools.

Times of rapid change call for a new leadership model.

If companies want to compete with blockchain, they must first cooperate to develop standards.

MIT SMR‘s Summer 2019 issue takes a closer look at the cultural changes adopting AI may require.

A new leadership model advocates organizations built on close relationships, openness, and trust.

Here’s a pragmatic framework for blending the best of the past with your ambitions for the future.

Technology changes quickly, but organizations change much more slowly.