Analytics & Business Intelligence

Why do workable analytics-based strategies always seem to fail when the playoffs start?

Re-skilling done right, telling a good data story, and three big points on disrupting yourself.

To solve the issue of advanced analytics talent concentration, companies need to think creatively.

This case study follows Mondelez International’s project to implement RPA as part of its AI journey.

Innovations from the front office are keeping fans engaged and disrupting the staid order in sports.

AI offers the potential to break down silos and make collaboration more effective.

Digital transformation empowers smarter KPIs.

Counterpoints takes a closer look at whether football’s running game still matters.

MIT Sloan Management Review‘s Fall 2019 issue looks at customer experience, collaboration, and cybercrime.

Through analytics, companies can reduce the costs of collaboration — and reap its rewards.

To avoid bias, people-centered design principles must be the foundation of deep-learning algorithms.

Giving customers what they want quickly is a worthy goal. Businesses can’t always afford to do it.

Automation can go far beyond cars. Self-driving company capabilities are closer than we realize.

Data and algorithms can mitigate gender bias in venture capital funding.

As sports become ever more analytical, can there be such a thing as too much data?

The time when companies could simply ask the world to trust AI-powered products is long gone.

Counterpoints looks at whether analytics can quantify team chemistry.

Defensive analytics are shaping how NBA basketball strategy is evolving.

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

Analytics can help NBA teams make better draft pick decisions.