310 Flashcards
(33 cards)
IMPACT Model
Steps in using data analytics in an audit
I = Identify the questions
M = Master the data
P = Perform the Test Plan
A = Address and refine results
C = Communicate Insights
T = Track outcomes
Types of Data
- Qualitative Data
- Nominal Data
- Ordinal Data
- Proportion
- Quantitative Data
- Ratio Data
- Interval Data
- Discrete Data
- Continuous Data
- Distributions
Qualitative Data
Categorical Data (e.g. Count, group, rank)
Nominal Data
Simple Categories (e.g. Hair color)
Ordinal Data
Ranked Categories (e.g. Gold, silver, bronze)
Proportion
Shows the makeup of each category (e.g. 55% cats, 45% dogs)
Quantitative Data
Numerical Data (e.g. Age, height, dollar amount)
Ratio Data
Defines 0 as ‘absence of’ something (e.g. cash)
Interval Data
0 is just another number (e.g. temperature)
Discrete Data
Whole numbers only (e.g. points in a basketball game)
Continuous Data
Numbers with decimals (e.g. Height)
Distributions
Describe the mean, median, and standard deviation of the data
Analytics Testing
- Descriptive
- Diagnostic
- Predictive
- Prescriptive
- Example Audit Procedure
Descriptive Analytics
- What Happened? What is Happening?
1) Summary Statistics
2) Cross Tabulations of Performance (Pivot Tables)
3) KPI Tracking
4) Costing and/or Process Costing
5) Clustering Suppliers, customers, processes, locations
Diagnostic Analytics
- Why did it happen? Can we explain why it happened?
1) Comparison of KPIs to expectations
2) Price, Rate, Usage, quantity, and overhead variance analysis
3) Conditional Formating
4) Regression Analysis estimating cost behavior
5) Correlations
Predictive Analytics
- Will it happen in the future? Is it foreseeable? What is the Probability something will happen?
1) Sales Forecasting
a) Time Series
b) Competitor and Industry
performance
c) Macroeconomic Forecasts
d) Regression
e) Classification of Indirect Costs
i) What is the Appropriate cost-
driver to allocated overhead
Prescriptive Analytics
- What should we do based on what we expect to happen? How do we optimize our performance based on potential constraints?
1) What-if Analysis
2) Goal Seek Analysis
3) Cash Flow (Capital Budgeting) Analysis
4) Sensitivity Analysis
Example Audit Procedure
Analysis of new accounts and sales employee bonuses
Predictive and Prescriptive Analytics
Both provide probabilistic models
The Big V’s of Big Data
- Volume
- Velocity
- Variety
Volume
Refers to size
Velocity
Refers to frequency
Variety
Refers to different types
The Balanced Scorecard
- Identifies the most important metrics to measure and target goals for comparison
- Consists of:
1) Financial
2) Customer
3) Internal Process
4) Organizational Capacity