Analytics Strategy

In an era of constant change, data and analytics teams must change rapidly to enable businesses to survive, never mind compete.

Companies can use an array of tactics to make sure that their data products inspire action — and create value.

Companies need to evolve and shift thinking around what it means to have a data-driven culture.

A Q&A with AWS’s Rahul Pathak on the advantages of transitioning your company to a data-driven enterprise.

Companies today are swimming in data — but how do we build a data strategy that creates value?

Preparing for AI’s next phase means prioritizing your talent pipeline and technology infrastructure.

Companies are beginning to reboot their machine learning and analytics, disrupted by the global pandemic.

A pharmaceutical giant enlists a consultant to help create an industry-leading global compliance system.

There has been a huge demand for data scientists in the past decade. Is that about to change?

The true underperformers in this digital disruption era are not measures but their managers.

Five essential management practices illustrated through the lens of sports analytics.

Organizations need algorithmic smarts to excel in the future of work.

A recent study connects the fear of disruption with technology investment at large companies.

Brands must focus on what their customers have in common — not what makes them different.

Organizations that make use of data from a variety of sources excel at customer engagement, as explained in the 2018 Data & Analytics Report.

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

Given the growing importance of data to companies, how should managers measure its value?

The cost of bad data is an astonishing 15% to 25% of revenue for most companies.

Getting business value from data depends on developing effective analytics teams — leaders included.

Large amounts of data don’t inherently remove sampling bias; in fact, they may make it worse.