Analytics & Business Intelligence

This case study describes how Honeywell and EY teamed up to build a powerful compliance scorecard.

Land O’Lakes’ CTO explains how data and artificial intelligence help the organization support agricultural production.

Watch this webinar to learn about using data insights to empower employees and enhance productivity.

Increasing productivity today requires creating cultures based on empowerment, wellness, and trust.

Learn to achieve healthy productivity while boosting employee engagement, empowerment, and wellness.

Data science project failure can often be attributed to poor problem definition, but early intervention can prevent it.

Successful digital initiatives require metrics that track business results, not technology use.

Streamlined metrics can get people moving in the same direction and improve business performance.

Data-driven leaders are using machine learning to surface new KPIs and better align behaviors with strategic objectives.

Analyzing e-commerce clickstream data can give retailers insight into which delivery options customers prioritize.

David Kiron and François Candelon discuss the latest MIT SMR-BCG AI and business strategy report at Web Summit 2021.

Nasdaq’s Douglas Hamilton explains how his AI research team supports business units for the global exchange operator.

Learn how workplace analytics can be leveraged to build trust and increase employee empowerment.

ExxonMobil’s Sarah Karthigan discusses leading AI projects that focus on self-healing strategies for IT operations.

The visibility arising from digital employee monitoring requires purpose, policies, and management.

Develop a “digital thread” that connects people, products, and processes internally and externally.

New research shows that an individual’s decision-making style informs the choices they make when using AI-based inputs.

This free webinar offers expert advice on adopting AI today and preparing for tomorrow’s challenges.

In this webinar, experts from Kaiser Permanente, Accenture, and SAS discuss business readiness for AI.

Retailers should analyze customers’ preferences before deciding how to optimize their delivery networks.