Data & Analytics

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Six Lessons From Amsterdam’s Smart City Initiative

The city of Amsterdam is becoming a model for “smart cities” through its innovation efforts to improve the lives of its employees and inhabitants. This case offers insights into what it takes to achieve these goals, including: taking the crucial step of doing an initial inventory of data available; using and integrating data from the private sector; and experimenting and learning from pilot projects.

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Internet of Things in Motion: Analytics and Transportation

  • Research Highlight
  • Read Time: 6 min 

Vast amounts of data are being analyzed to literally help trains run on time. With digitization capturing data on everything from the weight of connected rail cars to the quality of tracks to the terrain trains are traveling through, railway companies are now able to predict when breakdowns might occur and fix those trains proactively. The results are breathtaking: nearly 100% availability of operational trains.

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Monitor, Measure, Incentivize: Is Management as Simple as That?

Nicholas Bloom, William Eberle Professor of Economics at Stanford University, conducted an extensive study of 30,000 US factories, and found that two practices, underpinned by innovative software and IT systems, stand out in highly effectively managed operations: monitoring and incentives.

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Data-Driven City Management

Many major cities recognize the opportunity to improve urban life with data analytics, and are exploring how to use information technologies to develop smarter services and a more sustainable footprint. Amsterdam, which has been working toward becoming a “smart city” for almost 7 years, offers insights into the complexities facing city managers who see the opportunity with data, but must collaborate with a diverse group of stakeholders to achieve their goals. The city’s chief technology officer, Ger Baron, makes it clear that their efforts are still early days: “I can give you the nice stories that we’re doing great stuff with data and information, but we’re very much at a starting point,” he says.

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Sales Gets a Machine-Learning Makeover

New advances in machine learning are allowing sales teams to manage huge amounts of data to become more effective and efficient. Our research suggests three main ways machine learning is being successfully integrated into sales processes. First, it allows for a scientific approach that clarifies opaque parts of the sales process. Second, it enables more-effective data-driven experimentation. Third, it automates administrative duties that take time away from higher-value tasks.

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Investing For a Sustainable Future

Investors see a strong link between corporate sustainability performance and financial performance — so they’re using sustainability-related data as a rationale for investment decisions like never before.

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General Motors Relies on IoT to Anticipate Customers' Needs

Steve Schwinke, a member of the original design team for General Motors’ OnStar service and director of its Global Connected Customer Experience unit, says that GM is leveraging the Internet of Things to deliver products and services that consistently ensure the safety of its customers. “I always talk to my team about the Wayne Gretzky quote — skate to where the puck is going,” he says. “How good are we at really anticipating? What are the things that our customers need but don’t know they need?”

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Remapping the Last Mile of the Urban Supply Chain

  • Blog
  • Read Time: 6 min 

There are many reasons to believe we are on the crest of substantial progress with even the most challenging of last mile deliveries. Innovative models such as smart locker systems, the use of electric vehicles, and on-demand fleet services such as UberRUSH are being explored. The MIT Megacity Lab is helping identify customer-specific insights about how supply chains deliver products to urban customers and finds that autonomous delivery vehicles, while still years from wide-scale implementation, hold game-changing promise.

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MIT for Managers: Goodbye Traffic Lights?

  • Blog
  • Read Time: 4 min 

The next time you’re sitting at a red light, savor the moment. If researchers from MIT’s SENSEable City Lab and the Ambient Mobility Lab have their way, your hours of waiting at traffic lights could be numbered. In an article published in PLoS One, a team led by MIT’s Carlo Ratti and Paoli Santi describe a system in which automobiles and transportation infrastructure would interact though an algorithm that would manage the safe flow of cars through busy intersections.

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Blockchain Data Storage May (Soon) Change Your Business Model

Blockchain is a data storage technology with implications for business that extend well beyond its most popular application to date — the virtual currency, Bitcoin. Managers need to build their organization’s absorptive capacity around this topic for at least three reasons: (1) the potential effects on organizational value chains, (2) communication within and between organizations, and (3) benefits from cooperation.

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Complexity’s Competitive Edge

IHG is gaining a competitive advantage from applying advanced analytics to pricing and marketing. “Addressing complexity, if you can address complexity in modern marketing, gives companies a competitive advantage that can take time for competitors to replicate,” say IHG executives Larry Seligman, Jim Sprigg, Angela Galeziowski, and Dev Koushik, in a group interview.

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On Demand: Free Webinar, IoT in Motion

  • Blog
  • Read Time: 1 min 

Siemens’ Gerhard Kress, director of the company’s Mobility Division, has extensive experience in using IoT data and analytics to predict and manage service challenges in the railway industry. He joins MIT SMR senior editor Bruce Posner to discuss how companies that move people and products can capitalize on the opportunity that IoT data offers. Kress will show how the age of Big Data lets transportation companies improve how they manage the multiple challenges affecting their operations.

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Foundations of Analytics Strategy

Competitive advantage from analytics is declining, according to the 2016 annual report about data and analytics by MIT Sloan Management Review. In this on-demand webinar, the authors of the report — Sam Ransbotham, an associate professor in information systems at Boston College and guest editor at MIT SMR; David Kiron, the executive editor of MIT SMR’s Big Ideas Initiative; and Pamela Kirk Prentice, the chief research officer at SAS Institute Inc. — discuss how analytically-sophisticated companies are managing to cultivate both innovation and competitive advantage with analytics.

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Leveraging Smart Data and Internet of Things to Realize Mass Customization

  • Research Highlight
  • Read Time: 1 min 

In an on-demand webinar, Wolfgang Gruel and Frank Piller detail new experiments in personal transportation. Gruel and Piller say that transportation customers are on the cusp of having seamless travel experiences that synchronize all transit options: schedules, traffic conditions, and personal preferences. But making this vision a reality requires knitting together previously independent systems — in part through smart data and the Internet of Things.

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In Analytics, Resolution Must Be Accompanied by Resolve

For organizations, there is no shortage of hype about the potential for data and analytics. But the reality is that creating competitive advantage from data is elusive for many organizations. Our 2016 report on data and analytics, “Beyond the Hype: The Hard Work Behind Analytics Success,” outlines just how much resolve companies need to make an analytics strategy work.

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Building a Better Car Company With Analytics

Using data and analytics to understand the complexities of modern business has become not only common, but essential. Gahl Berkooz joined Ford Motor Co. in 2004, eventually becoming head of data and governance and a member of the company’s global data insights and analytics skill team. Berkooz became acutely aware of how important analytics is to the company’s ability to thrive in the global marketplace. “What it boils down to,” he told MIT SMR’s Michael Fitzgerald, “is that we know how to make decisions. It’s about finding the opportunities to bring data and analytics to make better decisions.”

Showing 1-20 of 223