Analytics & Business Intelligence

A webinar summarizing lessons learned in AI implementation from the 2019 Winning With AI Report.

No matter how compelling it seems, data alone won’t win people over unless infused with a story.

Just because a company can build an AI-infused product doesn’t mean it should.

Tom Davenport, Alex Breshears, and Abbie Lundberg discuss the specific challenges enterprises face in machine learning, and how they can create an end-to-end, factory-like capability.

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

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?