Data-Driven Decisions for Finance: Strategy, Governance and Practical Insights

Overview

Finance and accounting professionals must apply a disciplined, decision-first approach to using data under uncertainty. David Schlosser, PhD, Senior Advisor at Velocity Advisory Group, presents a practical system for making defensible, data-driven decisions—addressing cognitive biases, data quality and controls, and decision governance. He emphasizes when data is “good enough,” how to avoid analysis paralysis, and how to align measurement, accountability, and documentation to support sound judgment and audit-ready decisions.

Highlights

Prerequisites

Work experience in a corporate staff environment, or an introductory course in information technology.

Objectives

• Identify decision questions, assumptions, and measures that support timely, defensible choices in finance and accounting contexts.
• Recognize common sources of bias, data limitations, and governance challenges that can weaken professional judgment and decision quality.
• Distinguish between data that is sufficient to inform action and data that requires additional validation, controls, or documentation.
• Select appropriate roles, metrics, and review mechanisms to support accountability, learning, and audit-ready decision-making.

Preparation

None.