Tom Davenport speaks at the 2017 MIT CIO Symposium, sharing the three ways businesses use artificial intelligence.
Most of us view our jobs as specialized or somehow differentiated, but the world of business and management increasingly feels otherwise. For many organizations today, the next big driver of job commoditization is automation driven by smart machines. Simply put, if a job is viewed as a commodity, it won’t be long before it’s automated. The key for workers whose jobs have traditionally seemed safe: Highlight the tasks that require a human touch.
- Read Time: 13 min
Anindya Ghose, Heinz Riehl Chair Professor of Business at New York University’s Stern School of Business, is one of the pioneering explorers of the intersection of mobile and marketing. In his new book, Tap, he collects his findings and weaves them together into a set of nine forces that marketers can wield to drive sales via mobile technologies.
Andrew McAfee and Erik Brynjolfsson discuss the future of work and the global economy at the 2017 MIT CIO Symposium.
Many managers are excited about smart machines but are struggling to apply machines’ limited intelligence. Indeed, computers can process data just fine, but to generate competitive advantage from machine learning applications, organizations must upgrade their employees’ skills. Companies will also need to redesign employee accountabilities to empower and motivate them to deploy smart machines when doing so will enhance outcomes.
Even when faced with evidence that an algorithm will deliver better results than human judgment, we consistently choose to follow our own minds. Why? MIT Sloan Management Review editor in chief Paul Michelman sat down with the University of Chicago’s Berkeley Dietvorst to find out.
At the MIT Sloan School of Management’s 14th annual CIO Symposium, “The CIO Adventure: Now, Next and… Beyond,” senior IT executives came together to discuss key technologies, including how AI will transform the workplace. The goal: to help prepare these tech leaders for challenges they face, including shepherding ongoing digital transformations, building a digital organization, and managing IT talent.
- Read Time: 8 min
As analytics and big data continue to be integrated into organizational ways and means from the C-suite to the front lines, authors Josh Sullivan and Angela Zutavern believe that a new kind of company will emerge. They call it the “mathematical corporation” — a mashup of technology and human ingenuity in which machines delve into every aspect of a business in previously impossible ways.
Zhang Ruimin, the CEO and chairman of the Qingdao, China, white goods giant Haier Group Corp., has done what most chief executives dare not even dream about. He blew up nearly the entire administrative structure of a global manufacturing enterprise, eliminating the 10,000 management jobs that once held it together, and reshaped the organization into a network of entrepreneurial ventures run by employees.
The MIT Sloan School of Management 14th annual CIO Symposium discusses the impact artificial intelligence will have on the jobs of the future.
Digital technologies are making work increasingly thought-driven, not muscle-powered. In this environment, planning and execution are merely table stakes for leadership. Real leaders must inspire and reward employee ingenuity, and must be bold enough to move creativity from the organization’s periphery to its center. To do that, leaders need to adopt five personal behavior changes, including resisting the temptation to tell people what to do and embracing distributed leadership.
Thanks to emerging technologies like 3-D printing, manufacturers can offer consumers customized products and do so with unprecedented speed. Intrigued by a new product you saw in a YouTube video? Well, someday soon you may be able to personalize it, order it via the company’s website, and have it in your hands in a matter of days. But to enable this phenomenon at scale, an entirely new model of supply chain is required.
Plummeting data acquisition costs have been a big part of the surge in business analytics. We have much richer samples of data to use for insight. But more data doesn’t inherently remove sampling bias; in fact, it may make it worse.
Many executives believe they are good at identifying leadership talent. However, when asked how they make their decisions, they often cite intuition or “gut” instincts. Social science research, on the other hand, suggests that individuals are often prone to cognitive biases in such decisions. Rather than just relying on the subjective opinions of executives, some companies are using assessment tools to identify high-potential talent.
New research finds that stories about consumers’ positive experiences with a brand significantly increase users’ engagement with brand websites, and stories originating from consumers are especially powerful in shaping brand attitudes in social media. Indeed, companies that aren’t offering experiences that leverage consumer input in brand-related narratives are missing out on important opportunities to connect in a meaningful way with potential buyers.
- Read Time: 17 min
There’s a great deal of enthusiasm about platform strategies these days. Entrepreneurs pitch their startups as the next Uber, the next Facebook, or the next Airbnb, while executives in established companies are retooling their strategies around platforms to drive growth and compete digitally. But creating a successful platform business is not easy — as economists Richard Schmalensee and David S. Evans explain in this MIT Sloan Management Review interview.
Companies today work with an incredibly diverse array of people. To thrive, these organizations need culturally neutral, globally coherent leadership standards. These standards should promote needed outcomes without prescribing behaviors, since some behaviors are outside of the cultural norms in some countries. Inevitably, significant advantage will accrue to companies that ready their people for truly global leadership.
We are evolving toward the age of networked enterprise, in which the traditional hierarchies of the corporation will be supplanted by self-organizing systems collaborating on digital platforms. In this environment, strong cultures may turn from assets to liabilities.
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