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Many organizations are finding success with IoT projects by starting small, considering the short- and long-term value of initiatives, and looking at alternative ways to investigate issues for the information they need.
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What’s happening this week at the intersection of management and technology: Smart earbuds at work; adding cybersecurity to the executive job description; diving into data lakes
An infographic provides highlights of MIT SMR‘s 2016 Internet of Things report and illustrates the three key areas business leaders need to address in order to realize the IoT value proposition.
More tasks are being done by cognitive technologies, cutting costs, improving efficiencies, and displacing humans. This may lead to less differentiation between organizations, and a shifting composition of activities within the organization.
Despite improvements in cognitive technologies, the “Jetson” dream managerial scenario of sitting back and letting machines do all the work is still far from reality. Decisions that executives face don’t necessarily fit into defined problems well suited for automation. Cognitive technologies will increasingly absorb the easiest aspects of executive jobs, but at least for the time being, countless decisions still require human engagement.
In a conversation with MIT SMR’s David Kiron and Sam Ransbotham, associate professor of information systems at the Carroll School of Management at Boston College and guest editor for the Data and Analytics Big Idea Initiative for the MIT Sloan Management Review, Jeffrey Bohn, chief science officer at State Street Global Exchange discusses how he is developing better trading and risk strategies for clients using State Street’s proprietary data and analytics.
In a free webinar, James Heppelmann, president and chief executive officer of PTC, discusses how IoT is transforming companies’ organizational structures. He’ll illustrate the new need for companies to coordinate across product design, cloud operation, service improvement, and customer engagement, and some of the models for making the transition to a new structure, including centers of excellence and steering committees. The presentation is followed by a Q&A session with the presenter.
The Bank of England, one of the world’s oldest and most influential central banks, has made analytics excellence a key pillar of its mission to promote economic stability within the United Kingdom. Like other central banks, the Bank has relied on data and analytics to formulate policy recommendations. But, since 2008 when it regained its status as a regulator, the Bank has begun using its access to new forms of data to increase its insights and forecasting abilities about the British economy.
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.
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.
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?”
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.
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.
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.
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.
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.”
The past several years have been period of exploration, experimentation, and trial and error in Big Data among Fortune 1,000 companies, and the result has been a different story. For these firms, it is not the ability to process and manage large data volumes that is driving successful Big Data outcomes. Rather, it is the ability to integrate more sources of data than ever before — new data, old data, big data, small data, structured data, unstructured data, social media data, behavioral data, and legacy data. Guest blogger Randy Bean, CEO of NewVantage Partners, explains why the “variety challenge” has emerged as the top data priority.
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