Insight into what customers really care about often is hampered by the quality of the information being collected. Big data can support smart market research, but only if researchers embrace psychometric best practices and the basics of understanding what it is they want to measure and how. That means asking the right questions, asking enough questions, understanding how to weigh questions, and taking into consideration how people felt about the brand to begin with.

Even a highly skilled, knowledge-based industry like management consulting — one worth $250 billion and filled with some of the smartest people on the planet — is vulnerable to the same market forces that are disrupting services everywhere, including AI.

Data is recognized as a business asset, but we lack efficient ways to price it, says MIT professor Munther Dahleh. In this Q&A, he proposes a marketplace that bases the cost of data on the financial value it generates.

MIT Sloan Management Review and Google’s new cross-industry survey about key performance indicators (KPIs) asked senior executives to explain how they and their organizations are using KPIs in the digital era. The results shed light on the challenges and emerging opportunities companies face when using KPIs, demonstrate the many ways advanced use of KPIs can benefit organizations, and offer steps executives can take to make the most of KPIs going forward.

A new MIT SMR study measured the role of KPIs in aligning an organization toward its objectives. Three categories emerged: Measurement Leaders, Measurement Capable, and Measurement Challenged. Take this self-assessment to uncover challenges and opportunities based on your score — and find out what group you are in.

Retail customers may accept different prices on different channels — but retailers need to manage new complexities to make it work. These include understanding what customers value in each channel and how that affects what they will pay, giving store employees the right language for talking about price differences, and working out operational challenges. Getting it right has a real payoff: Retailers that effectively price differently across all channels see bottom-line growth of 2 to 5%.

Research from MIT Sloan Management Review and Google shows executives increasingly rely on key performance indicators (KPIs) to manage and lead their organizations. But what sets leading companies apart is not so much the number of metrics they track but how they use them to better engage customers — and thereby grow their businesses.

Join the co-authors of “Using Analytics to Improve Customer Engagement” and special guest Teddy Bekele as they show how analytical innovators are gathering and sharing data to build loyalty and keep customers.

Sports analytics first proved its case on the field and in the front office, but as the practice spreads into business operations, the industry is addressing adoption challenges found in many sectors. At the MIT Sloan Sports Analytics Conference, speakers from teams and leagues discussed how they are using analytics to boost revenue, and how they’re managing transitions in culture and strategy.

In Part 1 of our eight-part video series, we explore the real power of the digital thread, which lies not just in a “cradle-to-grave” virtual rendering of the manufacturing process, but also in the possibility of taking the lessons learned from analyzing product performance and applying them to future generations of the manufacturing process and product design.

David Harcourt of Yum! Brands Inc. shares his research and experimentation with HR analytics and shows how to align strategic talent management goals with HR analytics projects and activities.

MIT SMR’s 2018 report “Using Analytics to Improve Customer Engagement” surveyed more than 1,800 managers and interviewed executives at global companies and found that better customer engagement is linked to superior use of data and analytics.

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.

An infographic based on the 2018 Data & Analytics Report by MIT Sloan Management Review illustrates how companies can better engage with customers using analytics.

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.

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.

Until companies start to invest seriously in security, internet-enabled devices will offer far better ROI for thieves than for the companies seeking to build IoT capacity. But the benefits ultimately will make the effort worthwhile.

Identifying the optimal prices for products was once a time-consuming process. That’s changing as businesses start to take advantage of advances in machine learning, increases in computing speed, and greater availability of data.

Companies handling large volumes of data face a greater chance of erroneous linkages creeping into their analytics. Three key habits of data managers can reduce the risk of missed data connections.

To gain competitive advantage from supply chain analytics, companies need to reduce the time it takes to act on the insights those analytics generate.