Analytics Strategy

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Seizing Opportunity in Data Quality

Bad data is the norm. Every day, businesses send packages to customers, managers decide which candidate to hire, and executives make long-term plans based on data provided by others. When that data is incomplete, poorly defined, or wrong, there are immediate consequences: angry customers, wasted time, and added difficulties in the execution of strategy. Getting in front on data quality is crucial, and presents a terrific opportunity to improve business performance.

Leading Analytics Teams in Changing Times

Analytics teams are often underfunded, misunderstood, and starved for talent. Extracting business value from data depends on nurturing the development and effectiveness of these teams — not just in terms of finding talent, but also in terms of getting leaders up to speed on how to use the insights analytics teams produce.

How Big Data Is Empowering AI and Machine Learning at Scale

Big Data is moving to a new stage of maturity — one that promises even greater business impact and industry disruption over the course of the coming decade. Organizations are now combining the agility of Big Data processes with the scale of AI capabilities to accelerate the delivery of business value.

Participant Questions From the Recent Data and Analytics Webinar: Round 2

On March 15, 2017, MIT SMR held a webinar to share insights from our report, “Analytics as a Source of Business Innovation.” Many participants asked questions during the webinar that we didn’t have time for, so we decided to answer them in blog format instead. This post is the second set of responses.

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Questions and Answers About Analytics as a Source of Business Innovation

On March 15, 2017, MIT SMR held a webinar to share insights from our report, “Analytics as a Source of Business Innovation,” which summarizes our findings about the increased ability to innovate with analytics and its benefits across industries. Many participants asked questions during the webinar that we didn’t have time for, so we’ll answer some of them in blog format instead.

Analytics as a Source of Business Innovation

The 2017 Data & Analytics Report by MIT Sloan Management Review finds that the percentage of companies deriving competitive advantage from analytics increased for the first time in four years. Incorporating survey results and interviews with practitioners and scholars, the report finds that companies’ increasing ability to innovate with analytics is driving a resurgence of strategic benefits from analytics across industries. The report is based, in part, on MIT SMR’s seventh annual data and analytics global survey, which includes responses from 2,602 business executives, managers, and analytics professionals from organizations located around the world.

The Flood of Data From IoT Is Powering New Opportunities — for Some

IoT promised, and delivered, a data deluge. But is the data any good? Survey results from MIT SMR’s recent internet of things research suggest that it is — but the most value goes to those who got into IoT early and have years of experience under their belt. The message to those considering IoT projects: Don’t wait.

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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.

A Bank On the Edge of a Deep River

South African finance leader Nedbank is using data and analytics as a way to help the bank’s clients better understand their business. And the more data-oriented the bank becomes, the better able it will be to turn its developing prowess on itself. As the bank dives deeper into analytics, the same data it’s using for clients can help Nedbank better understand its own organization, employees, suppliers, and more.

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.

Customer Relationships Get the Data Treatment

A 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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Improving Analytics Capabilities Through Crowdsourcing

Analytics capabilities can greatly expand a company’s ability to innovate — but what do you do when the talent you need just isn’t available? Agribusiness giant Syngenta, faced with an insurmountable analytics talent bottleneck, turned to crowdsourcing. Using a series of contests, it outsourced the development of a set of award-winning analytics tools to improve its decision making — and learned, in the process, some key factors supporting successful crowdsourcing.

Better Data Brings a Renewal at the Bank of England

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.

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.

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.

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.

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