Competing With Data & Analytics

How are organizations leveraging data and analytics to increase operational efficiency, engage key stakeholders, and report on business successes? Since 2006, the Data and Analytics initiative has investigated how technology enables competitiveness.

MIT SMR’s research employs global qualitative and quantitative methods to investigate how data is influencing business processes, offerings, and engagement with customers. It looks at trends in the use of analytics, the evolution of analytics strategy, optimal team composition, and new opportunities for data-driven innovation.

Why APIs Should Be Regulated

Digital titans with access to large quantities of data are a challenge to competition. To maintain a competitive business environment, regulation focusing on both market and data dominance needs to be developed. Among the best tools for limiting companies’ influence: data audits.

Using Analytics to Improve Customer Engagement

The 2018 Data & Analytics Global Executive Study and Research Report by MIT Sloan Management Review finds that innovative, analytically mature organizations make use of data from multiple sources: customers, vendors, regulators, and even competitors. The report, based on MIT SMR’s eighth annual data and analytics global survey of over 1,900 business executives, managers, and analytics professionals, explores companies leading the way with analytics and customer engagement.

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Your Data Is Worth More Than You Think

Data has become a key input for driving growth, enabling businesses to maintain a competitive edge. Given the growing importance of data to companies, how should managers measure its value? An increasing number of institutions, academics, and business leaders have begun tackling the valuation problem to help organizations realize more value from their data.

Give Technical Experts a Role in Defining Project Success

Poor communication between managers and technical experts is an obstacle to technology innovation that literally has been present for centuries. To overcome these issues, leaders need to absorb three key lessons about how to manage the inherent tensions between defining technical requirements and achieving valuable business outcomes.

Sustaining Advantage With Transitory Technologies

Just when you have your data collection and analysis systems in place, technology changes mean that your company needs new, updated systems. This is a problem for many companies — but it can also be an opportunity. Organizations that work with data from old and new equipment can learn more about the shortcomings that modern techniques have in this context and can gain advantage in developing tools that no one else has.

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.

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Balance Efficiency With Transparency in Analytics-Driven Business

Algorithms are affecting many aspects of daily life, but most people have no clarity as to how they work — even in the companies that create and use them. But individuals and organizations need to carefully consider what this lack of transparency means when it comes to fairness and honesty in commercial interactions and decide where to draw the line on data ethics.

Romantic and Rational Approaches to Artificial Intelligence

Organizations have made rapid gains in their ability to generate big data sets, but the ability of managers and executives to develop insights from that data has lagged behind. Data processing by artificial intelligence offers the prospect of speeding things up — but it also risks expanding the gap, as managers lack understanding of how AI reaches its data-based conclusions.

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.

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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.

Research Findings: Analytics as a Source of Business Innovation

Sam Ransbotham and David Kiron, co-authors of the 2017 MIT SMR Data & Analytics Research Report, “Analytics as a Source of Business Innovation,” shared the findings and insights from their research into the changing landscape for companies looking to embed data and analytics into their strategies, processes, and operations.

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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