MIT Sloan Management Review

MIT Sloan Management Review

Book and Periodical Publishing

Cambridge, MA 124,686 followers

Transforming how people lead and innovate

Über uns

At MIT Sloan Management Review (MIT SMR), we explore how leadership and management are transforming in a disruptive world. We help thoughtful leaders capture the exciting opportunities—and face down the challenges—created as technological, societal, and environmental forces reshape how organizations operate, compete, and create value. We encourage comments, questions, and suggestions. We respect and appreciate our audience's point of view; however, we reserve the right to remove or turn off comments at our moderator’s discretion. Comments that violate our guidelines (see below) or use language that MIT SMR staff regard as abusive, attacking, offensive, vulgar, or of a bullying nature will be immediately removed. Repeat offenders may be blocked indefinitely. MIT Sloan Management Review’s LinkedIn Commenting Guidelines: 1. Respect. Debates are great, but attacks are not. Any comment that creates a hostile environment will be removed. 2. Hate speech. Comments containing bullying, racism, homophobia, sexism, or any other form of hate speech will be removed. 3. Language. Vulgar posts may offend other readers and will be removed. 4. Personal information. Any comment with personal information (address, phone number, etc.) will be removed.

Website
http://sloanreview.mit.edu/
Industrie
Book and Periodical Publishing
Größe des Unternehmens
11-50 Mitarbeiter
Hauptsitz
Cambridge, MA
Typ
Nonprofit
Gegründet
1959

Standorte

Employees at MIT Sloan Management Review

Aktualisierungen

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    124,686 followers

    “OK, Houston, we’ve had a problem here,” said astronaut John Swigert in 1970, after an explosion disabled the Apollo 13 spacecraft on its way to the moon, 200,000 miles from Earth. Those iconic words triggered a heroic effort that eventually brought the astronauts home safely. To do so, NASA scientists and engineers needed to develop and test innovative solutions on the fly. A critical tool they used was an Earth-based “twin” of the spacecraft — then, mostly physical — upon which they could experiment swiftly and safely without endangering the astronauts. Half a century later, this concept has evolved into the digital twin (DT) — a digital replica of a complex real-world entity. DTs comprise two key elements: a high-fidelity model of the entity and a dynamic mechanism to keep the model true in real time, even as the entity changes. In industrial settings, internet-of-things (IoT) sensors typically provide the data for dynamic updates. DTs are potent tools for mission-critical applications, where experimenting with the physical system isn’t feasible or is expensive, time-consuming, and hazardous. Learn more: https://mitsmr.com/3T8SjZU

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    In today’s business environment, firms must navigate labor shortages, market shifts, geopolitical tensions that strain supply chains and manufacturing, and mandates to adopt sustainable practices. Meeting these demands will require innovation rooted in breakthrough science and engineering. Even companies in less R&D-intensive sectors will need to look to science-based innovators — so-called deep-tech startups — as they seek solutions to their key challenges. Deep tech describes a category of solutions rooted in atoms rather than bits — such as new materials, synthetic biology, fusion energy, and quantum computing — and grounded in cutting-edge research. Deep-tech ventures are startups dedicated to taking ideas from the lab bench to scaled global impact. And although these companies have great promise, adopting their breakthrough developments requires patience, a tolerance for risk, and capital. Learn more: https://mitsmr.com/3YZPdv1

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    A typical approach to DEI includes diversity training, pre-employment testing, performance reviews, and grievance systems, all of which aim to limit bias in recruiting and promotion. While better than nothing, these processes and policies are primarily designed to prevent litigation and to change (or train) people. Unfortunately, they don't change the heart and soul of the organization or the way it operates.1 Senior leaders might set up a committee or appoint a person to take charge of DEI to demonstrate that they are taking action. However, making DEI the responsibility of a czar or steering committee rather than engaging the community as a whole sidesteps the work of transforming the organization into one that thrives because it embraces diversity. A steering committee will rarely have the clout to rigorously question or change business processes — including personnel practices, reward systems, and how meetings are run — that may exclude diverse voices. These approaches are derived from an industrial view of the workforce as a set of interchangeable parts and employment as a transaction. Companies pay employees to perform a set of predefined tasks; it doesn’t matter what else they know, how they think, or what their talents might be. In this view, DEI is transactional, too. The organization follows the law by hiring people of differing identities and holding a “diversity day” to publicize them, without changing how it operates. For leaders seeking to transform their organizations through DEI, the VPM provides ways to both articulate and measure where an organization stands in its journey and where it needs to go. It also provides a way to engage the entire organization, by giving everyone — senior leaders, middle managers, and rank-and-file employees — a role in the measurement, achievement, and stewardship of DEI. It is focused on changing organizations, not individuals. https://mitsmr.com/3MkgMoR

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    Creating and implementing effective AI models requires substantial effort. However, when organizations focus too heavily on the technology and algorithms, they may ignore other critical factors, endangering their initiatives. Business leaders can improve the chances of their AI programs' success by taking on a more significant role. They should begin by identifying the appropriate data to train and operate their AI models, understanding the necessary questions to ask, and the answers to seek. It's also crucial to involve a variety of individuals, not just technologists and data scientists, but people from diverse roles with different perspectives. In this webinar, you will learn about: 💡 What we mean by “the right data” — and why it is essential for success with AI. 💡The questions managers must ask as models are developed and deployed. 💡How statisticians can fill critical gaps on your AI team. 💡How managers can build their own — and their organization’s — capabilities. Register for the webinar now: https://mitsmr.com/3Ak9hOd

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