Forecasting models are becoming increasingly sophisticated, yet many organizations still struggle to turn predictive analytics into trusted business decisions. The challenge is rarely the model itself—it's building confidence in the forecasts and ensuring stakeholders understand, trust, and act on the insights.

This session explores the principles behind developing forecasting solutions that business leaders can confidently use for planning, budgeting, and strategic decision-making. Drawing on real-world experience delivering enterprise forecasting initiatives, we'll examine the common reasons predictive models fail to gain adoption and discuss practical techniques for improving transparency, governance, and stakeholder confidence.

Using realistic business scenarios, we'll cover how to communicate uncertainty, balance model accuracy with explainability, select meaningful business drivers, and integrate forecasts into executive reporting. We'll also discuss how modern analytics platforms and AI capabilities are enabling organizations to move from static forecasting to continuous, decision-ready planning.

Attendees will leave with practical approaches for designing forecasting solutions that are technically sound, business-focused, and trusted by stakeholders across the organization.

The TRUST Forecasting Framework
Transparency
Reliability
Understandability
Stakeholder Alignment
Timely Decisions