Data, AI, & Machine Learning

Plummeting data acquisition costs have been a big part of the surge in business analytics. We have much richer samples of data to use for insight. But more data doesn’t inherently remove sampling bias; in fact, it may make it worse.

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

Changing consumer expectations, new regulations, and an influx of patient data has created a perfect storm for health care organizations like Schumacher Clinical Partners to rethink how they leverage digital tools to better serve their patients and providers.

Even when faced with evidence that an algorithm will deliver better results than human judgment, we consistently choose to follow our own minds. Why? MIT Sloan Management Review editor in chief Paul Michelman sat down with the University of Chicago’s Berkeley Dietvorst to find out.

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.

A new global study finds several new categories of human jobs emerging. These roles are not replacing old ones. They are brand-new positions that complement the tasks performed by AI machines and will require skills and training that have never before been needed.

The 2017 Data & Analytics Report by MIT Sloan Management Review finds that companies that embraced analytics have begun to find new ways to derive strategic benefit from analytics.

To grasp how artificial intelligence will change organizations, understand how it delivers value.

The ability to monetize data — not hoard it — can offer competitive advantage in the digital economy.