Big Data

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Why Big Data Isn’t Enough

  • Research Feature
  • Read Time: 13 min 

There is a growing belief that sophisticated algorithms paired with big data will find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and potentially risky, as spurious correlations and “noise” may lead analysts astray.

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Free Video Panel: Creating a Data-Driven Enterprise: Real-Life Cases

In a video panel and Q&A, MIT SMR editors discuss key insights from a recently completed series of in-depth case studies on how prominent organizations are using data and analytics to transform their operations. They review Intermountain Healthcare, GE, Nedbank, and the City of Amsterdam’s efforts to become more data driven. This set of diverse organizations offers a unique perspective on the challenges and opportunities associated with becoming a data-driven organization.

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Lessons from Becoming a Data-Driven Organization

Organizations across the business spectrum are awakening to the transformative power of data and analytics. They are also coming to grips with the daunting difficulty of the task that lies before them. It’s tough enough for many organizations to catalog and categorize the data at their disposal and devise the rules and processes for using it. It’s even tougher to translate that data into tangible value. But it’s not impossible, and many organizations, in both the private and public sectors, are learning how.

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Customer Relationships Get the Data Treatment

A new case study by MIT Sloan Management Review, “A Data-Driven Approach to Customer Relationships,” details how the South African bank Nedbank is using its rich access to a trove of transactional data from credit card use — from the time of transactions and size of purchases to retailer locations, and even specific details like the age, gender, race, marital status, and income bracket of some users — to help merchants make strategic decisions to better serve those customers.

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Achieving Trust Through Data Ethics

Eight out of 10 executives surveyed say that as the business value of data grows, the risks their companies face from improper handling of data increase exponentially. While digital advancements enable new opportunities for businesses to compete and thrive, they also create increased exposure to systemic risks. Success in the digital age will require a new kind of ethical review around how companies gather and use data.

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Digital Today, Cognitive Tomorrow

Digital transformation is happening all around us, but it’s the foundation for a much more profound transformation still to come. With huge challenges facing humanity on many fronts — climate, disease, population, food and water — we need cognitive technologies to augment human problem-solving capabilities. And those technologies are almost here.

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Want to Improve Your Portfolio? Call a Scientist

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.

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Image courtesy of Flickr user Keith Allison

Stephen Curry, the Golden State Warriors, and the Power of Analytics at Work

Organizations across an increasing number of sports and levels of competition are capitalizing on data to gain a competitive edge. Indeed, few industries have implemented data-driven decision making as successfully as sports. And learnings from the sports analytics revolution are applicable to a broad range of other industries.

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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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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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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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Variety, Not Volume, Is Driving Big Data Initiatives

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.

Showing 1-20 of 67