Leaders and clients depend on us for our insight, analytical skills, findings, and recommendations. They need us to help make critical decisions, and sometimes we fail. Some of the common beliefs that we treat as guaranteed facts include: × More data will lead to better analytical results × The 'Bell curve' is universally applicable × Precision means accuracy × Relationships are linear × Correct data leads to better results × Correlation means causality × Fast answers are the correct and best answers × Our data is perfect, etc. Each of the previous will lead to more errors. We need to audit our own analytical tools to assess where and how we are inadvertently delivering bad findings. The focus is to re-examine our analytical processes. Our constituents depend on us; we cannot let them down.
Learning Objectives
After attending this presentation, you will be able to...
- Identify common problems embedded within many financial analyses and determine actions to take to prevent those problems.
- Analyze how assumptions directly lead to analytical errors.
- Recognize the need to audit their own work.
- Identify areas auditors need to review when evaluating analyses.
Major Topics
The major topics that will be covered in this course include:
- Certain flaws in GAAP accounting
- Confusing precision with accuracy
- Assumptions that lead to errors
- Why static analysis will fail
- How statistics mislead
- Why the ‘Bell curve’ leads to errors
- How and why speed ruins our findings
- Inherent problems within AI
- The need for proper and adequate review
