Data & Analytics

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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.

Sponsor's Content | Why a Data and Analytics Strategy Today Gives Marketers an Advantage Tomorrow

  • MIT SMR Custom Studio | Content Commissioned for Google Analytics 360 Suite

Nearly 90 percent of senior marketers in a recent survey said an understanding of user journeys across devices and channels is critical to marketing success. No wonder: Leading brands are those that build a foundation of data and analytics to deliver personalized, relevant experiences throughout the customer journey. Determining and measuring the most effective customer engagements is something each organization must do through experimentation, which requires new skills, mindsets and processes.

Moving Beyond the Silicon Valley State of Mind

In his new book Sensemaking, a polemic defending the need for the liberal arts in business, Christian Madsbjerg, the founder of strategic consultancy nReD Associates, argues that leaders shouldn’t try to know everything. Instead, they should try to make sense of something.

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Sponsor's Content | Journey to AI: Building a Foundation in Big Data Analytics

  • Content Created By Google Cloud

AI is making headlines — and not just in futuristic technologies like self-driving cars. It’s transforming business processes in established industries, from retail to financial services to manufacturing. But what’s the best way to adopt AI for your organization?

The 2017 Richard Beckhard Memorial Prize

The editors of MIT Sloan Management Review are pleased to announce that the winner of this year’s Richard Beckhard Memorial Prize, awarded annually to the most outstanding MIT SMR article on planned change and organizational development, is Emilio J. Castilla’s article “Achieving Meritocracy in the Workplace.”

A Data-Driven Approach to Identifying Future Leaders

Many executives believe they are good at identifying leadership talent. However, when asked how they make their decisions, they often cite intuition or “gut” instincts. Social science research, on the other hand, suggests that individuals are often prone to cognitive biases in such decisions. Rather than just relying on the subjective opinions of executives, some companies are using assessment tools to identify high-potential talent.

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.

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Why It Pays to Be Where the IT Talent Already Is

As demand for big data technologies grows, so does the problem of finding sufficient skills. Result: Talent shortages could limit the rate of productivity growth. Research shows that labor-market factors have shaped early returns on investment in big data technologies such as Hadoop, a framework for distributed processing of large data sets. It turns out that when know-how is scarce, organizations that invest in new IT or R&D derive significant benefits from the related investments of other organizations.

Designing and Developing Analytics-Based Data Products

The combination of new analytical capabilities and burgeoning data assets are being used to form value-added “data products.” Such products have powered rapid growth in the value and success of online companies, but the expansion of analytics means the standard model for developing these products needs to evolve. An updated model needs to reflect new “time to market” expectations and input from a variety of stakeholders.

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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.

Achieving Meritocracy in the Workplace

Rewarding employees based on merit can be more difficult than it first appears. Even efforts to reduce bias can backfire; disparities in raises and bonuses by gender, racial, and other characteristics persist in today’s organizations not only despite management’s attempts to reduce them but also because of such efforts. The author describes how a simple analytics-based approach can address these concerns and produce a truly meritocratic workplace.

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.

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.”

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