Analytics & Business Intelligence

Business leaders must rethink data management to succeed with machine learning.

How companies assign responsibility for analytics is a crucial factor in exceeding business goals.

IBM’s Mark Foster discusses what makes digital transformations succeed — and why it takes humanity.

Our experts reveal where leaders should focus their efforts in 2020 and beyond.

Companies implementing AI must protect customers’ autonomy, privacy, and individuality.

Leadership behaviors that build trust, purpose, and energy bolster collaboration and engagement.

MIT SMR authors David Bray and R “Ray” Wang discuss how people-centered design principles can serve as a framework in AI implementation.

Companies already use data to make marketing decisions. Will deep learning enable a leap forward?

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.