Self-Study: 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.