Data-driven decision making

Causal ML helps managers improve decision-making by enabling them to explore different options’ potential outcomes.

Leaders must tackle both cultural and technology issues to gain a more comprehensive view of risk organization wide.

Having someone take on a critical reviewer role can enhance a meeting’s effectiveness and lead to better decisions.

Agentic AI adopters must proactively address decision rights allocations, power dynamics, and decision-making practices.

AI-powered SPM can help businesses address their sales strategy and process problems through precision forecasting.

Research shows that better decision-making can be achieved through the strategic use of artificial intelligence systems.

Many marketing teams struggle to identify metrics that will support business strategy. A change in approach can help.

Organizations can develop effective digital twins despite limited training data by combining AI and human knowledge.

The natural language capabilities of LLMs can augment the predictive powers of advanced analytics.

Checking assumptions and mapping out work processes can help ensure that ML solutions fit the job to be done.

Lufthansa launched an effective program to turn all its leaders into data leaders and propel its digital transformation.

Business leaders can identify and avoid flawed AI models by employing statistical methods and statistics experts.

When deciding whether to deploy a machine learning model, focus on business metrics, not technical ones.

What’s this year’s average marketing budget? Bad question: That figure misleads marketers who want to benchmark spending.

Executing strategy requires understanding your critical roles and putting your best people in them.

Researchers are seeing stronger business benefits when KPIs are adjusted with or created by AI tools.

A research-based framework can help companies select philanthropic projects that align with their business strategies.

Hype around generative AI tools like ChatGPT impede business leaders’ ability to make well-informed technology choices.

Many finance offices aren’t benefiting from advanced analytics. A new framework can help CFOs assess their data skills.

Understanding how AI algorithms are trained and validated can help decision makers pick the right tools and avoid risk.