DATA ANALYTICS & THE SMALL AUDIT DEPT: HOW TO IMPLEMENT FOR BIG GAINS

WEBINAR

PRESENTERS

Bob CuthbertsonCPA, CA, CITP, Chief Operating Officer CaseWare Analytics

Jared S. SoileauPhD, CIA, CPA, CISA, CCSA, CRMA Assistant Professor, Accounting Louisiana State University

TODAY’S ENVIRONMENT

• Use of Data Analytics

• Barriers to use

RESEARCH

• AuditNet

• IIA

• KPMG

• Deloitte

AUDITNET 2016 SURVEY

• Most IA only use basic technology- Not harnessing

full potential

• Market demands more

• IA plans to include more technology in the future

• Opportunities to improve – investment in tech,

people

IIA 2015: USE OF TECHNOLOGY

• Use of software tools for data mining has increased 14%

• Measuring from 2009 – 2015!

• 4 out of 10 CAEs think their use of technology is at least appropriate.

IIA 2016: CBOK BENCHMARKING

• 23% - reliance on manual systems and processes

• 39% - some use of electronic WP and other office technology tools

• Less than 40% actively using technology in audit methodology

KPMG 2015 SURVEY

• 60% of survey respondents

indicated not effectively

using analytics in IA

DELOITTE 2016: IA AT CROSSROADS

• Use of analytics largely at basic levels

• 86% use analytics, but only 24% at intermediate, 7%

advanced

• Use of analytics is expected to increase

• 58% - expect to use ½ of their audits

• 37% - expect to use ¾ of their audits

• Internal Audit faces barriers

• Talent gaps

• Quality data

OVERALL…

• Lots of talk, promises for the future, no real call-to-action

• Barriers – talent, data, cost

ANALYTICS: BETTER THAN GUESSING!

Jared S. Soileau

Assistant Professor of Accounting

Louisiana State University

OVERVIEW

• Getting Motivated

• Roadblocks – Excuses

• Encouragement

• Brain Storming - Questions?

• Analytic Methods

• Implementation Tips

EXCUSES ONLY GET IN THE WAY

EXCUSE REALITY

I don’t know where to start You cannot finish if you don’t start!

We have never done it that way What if you had?

I can’t do it because of limited

resources (time/money/staff)

It’s a marathon, not a sprint!

The data does not exist What data is available?

You cannot evaluate what you do

not measure!

What is our goal? If you aim at nothing, you are sure to hit it!

GETTING MOTIVATED

• It is not about where you start, but what you achieve!

• Ad hoc is better than non-existent

• Embrace the opportunities to add value

• Focus on business/management priorities

• What questions does management have about the business?

• Depends on Business/Industry

GETTING MOTIVATED

• Empower Employee(s)

• Failure can be a better lesson than success

• Better to fall/fail than not to try

• Identify someone that has:

o Extensive business knowledge

o An inquisitive mind

o A thirst for learning new skills, and

o Data skills (or attitude to learn)

ANALYTICS - NOTHING NEW...

Why does Data Analytics Seem Like Something New?

• Return on Assets

• Direct/Indirect Unit Costs/Labor Costs

• Turnover (Inventory, A/R, Employee)

• Reorder Point

• Credit Limits

• Forecast Production Planning

• Benford’s Law

WHERE DO YOU WANT TO GO?

Data Capture

Descriptive Analytics

Predictive Analytics

Prescriptive Analytics

VALUE ADD DEPENDS ON GOAL

Know where you want to go!

• + Revenue

• - Expenditures

• ~ Manage Risk

• ~ Evaluate/Improve

• Controls

• Compliance

• Safety

INVENTORY AND OPPORTUNITIES

• Outside of Internal Audit, what efforts are being

made towards Analytics?

• What is being done? By whom? For what?

• Can these efforts be leveraged?

• Is the process audited?

• What data is available?

• Internal - Who owns the data?

• External – What data sources? (e.g. twitter, yelp, Facebook…)

INVENTORY AND OPPORTUNITIES

• Brainstorming (e.g. SAS99)• What are the most burning questions?

• Related to Operations

• Related to Risk

• Related to Control

• Who has the skills to lead an initiative?

EXAMPLE: CHURCH OFFERINGS

• How would you conduct analysis?

• Deposit

• Attendance – Service, other events (e.g. holiday, weather, football)

• Autopay

• Week of Month

BRAINSTORMING EXAMPLES

• How do I answer the question?

• Do I understand the business?

• What is the Operating Cycle?

• How do I confirm the accuracy and completeness of the data?

• Does the data represent understanding of the process?

• What causes might influence the relationship?

• What alternative data is available to capture and measure the constructs?

• What sources contain the data?

• What preparation needs to be made to the data?

BRAINSTORMING EXAMPLES

• What statistical method should I use to evaluate the relationship?

• Visualization

• Correlation

• Regression

• What tools do I need?

QUESTIONS TO ASK

Questions depend on perspective and many other factors

• Transportation Industry

• What is the cost of overbooking flights?

• Can we maintain customer loyalty while overselling flights?

• How can I reduce fuel costs?

• How can I reduce delivery time?

• How can I reduce insurance costs?

• How can I reduce accidents?

• What is the impact of Uber?

• How does weather impact operations?

QUESTIONS TO ASK

• Accounts Receivables

• What is the effect of 2/10N30 on Collections?

• What is the effect of 2/10N30 on Revenue?

• How does Apple pay impact me?

GETTING STARTED

• What are the ingredients?

• Questions

• How frequently are credit limits overridden? What is the result?

• How frequently do stock outs occur?

• Do buyers have over reliance on vendors?

• Data/Data Sources

• Where can I get…?

What do you want to

understand?

Data

Critical Thinking

GETTING STARTED

• Methods

• Descriptive Statistics

• Correlation

• Regression

• Visualization

• Technology

• What software do I need?

What do you want to

understand?

Data

Critical Thinking

WHAT DATA IS NEEDED?

Marketing /Social Media

Financial Performance

Operations

Customer Service

Competitor Performance

Economic Indicators

Relationships/Predictions

DATA ANALYTIC TECHNIQUES

Visualization A picture is worth a 1,000 words

Outliers/Anomalies Standard Deviations from the Mean

Correlation Compare Y and X - Do they move together?

Time Series What is the trend? (e.g. Y-O-Y, M-T-M)

Cluster Grouping of events/activities

Regression Evaluate association between X and Y - Control for other known relationships

Benford’s Law Pattern anomaly of 1st Digits

MATURITY CLASSIFICATION

Non-Existent

Ad hoc Analysis/

Audit Testing

Repeatable Analysis

Continuous Auditing

Continuous Monitoring

Audit Development Management Process Ownership

AUDIT THE ANALYTICS PROCESS

If Data Analytics exists outside Internal Audit

• Integrity

• How/has the accuracy of data been validated?

• Has this been audited?

• How timely is the data?

• Confidentiality

• Who has access?

• What do they have access to?

• Is the access approved/appropriate?

• Availability

• When can it be accessed?

TAKE AWAY #1

Analytics is a Tool and does not replace

• Business knowledge

• Inquisitiveness

• Professional Skepticism

• Communication

• Objectivity

TAKE AWAY #2

• Scalability is Key!

• Develop a plan

• No harm at starting small, but there is in not starting

• Don’t rush - too fast could lead to crash

• Understand the data available

• Who owns it?

• Where is it?

• What format?

• Is it currently monitored?

TAKE AWAY #2

• Build and learn; Learn and Build

• Get the training or staff necessary

• Continuously ask new questions

TAKE AWAY #3

• Big Data is a goal – not a starting point

• Do not let Big Data capabilities get in the way

• Value Added analysis = additional resources

• Maximize likelihood of success

• Start with easy wins

• Do not rush growth and maturity

• Expand to new data through maturity

• Apply new knowledge and data

• Unstructured data

DATA ANALYTICS & THE SMALL AUDIT DEPT: HOW TO IMPLEMENT FOR BIG GAINS

WEBINAR

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