- Opinion & Analysis
- Read Time: 6 min
When you’re developing a strategy for a new business, testing assumptions in your plan in a logical order gives you the best chance to make course corrections early — and not waste time and money.
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Responding to a recently published essay, an MIT SMR reader pushed back against the view that managers must prepare for radical and rapid change in a digital world; he argued that this position may be overly alarmist. The discussion continues.
Chief information officers need to oversee all of IT — in close collaboration with marketers and the business units. Only then can companies deliver digital experiences that win, serve, and retain increasingly demanding customers.
Although traditional financial services companies now offer mass-market financial advice via “robo-advisers,” average U.S. customers seeking investment advice are still underserved — and platform-based digital powerhouses like Amazon are taking notice.
Many executives don’t understand how to craft a compelling vision for change that will gain widespread commitment within their organization. Leaders should start by asking themselves: What will people see, hear, and feel once the changes have been achieved?
“Getting performance management right is an old challenge,” according to Nik Kinley and Shlomo Ben-Hur, authors of the article “The Missing Piece in Employee Development.” The key element isn’t measuring performance but the interactions and conversations that individuals have with their managers.
In this webinar, MIT SMR authors Melissa Bowers, Adam Petrie, and Mary Holcomb discuss the phases of Analytics Insight Cycle Times, present case studies for actual success, and steps supply chain executives can take to reduce cycle times and to ultimately make supply chain analytics a transformational and competitive resource in their organizations.
MIT Sloan Management Review editor in chief Paul Michelman argues that the importance of corporate culture will dissipate as organizations become flatter and more distributed. However, several readers take a different view.
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 western multinationals have a tough time finding local talent in East Asia — a problem that global companies originating in East Asia don’t seem to face. One problem: The cultural values and expectations of those doing the hiring and those seeking the jobs are at odds.
Any approach to leadership development that tries to reduce the complexities of leadership to a series of standard boxes to be ticked or traits to be emulated will have little enduring impact.
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.
Digital technology has already upended the media and information sectors. It’s about to do the same to the manufacturing economy, and pave the way for what can be called the “pan-industrial” strategy.
A recent MIT Sloan Management Review article argued that companies need to choose whether to focus their digital strategy on customer engagement or digitized solutions. But several readers wondered why they needed to choose one option over the other.
Blockchain technology has the potential to transform how businesses are organized and managed. It allows companies to eliminate transaction costs and use outside resources as easily as internal resources. The implications for areas such as accounting, contract negotiation and enforcement, sales and marketing, and capital investment are myriad. Companies should start exploring how this technology could impact their industry and processes.
When it comes to putting data to use, communication — or rather, lack of it — between the data scientists and the executive decision makers can cause problems. The two sides often don’t speak the same language and may differ in their approach to and respect for data-based decisions. Given these challenges, organizations may need to call upon a “data translator” to improve how data is incorporated into decision making processes.
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