1. Data analysis can improve business processes by identifying gaps and inefficiencies. Analyzing a company's purchase order and accounts payable data revealed $322 million of open purchase orders that had actually been paid, reducing liability. 2. Fuel card usage analysis found fuel costs increased 15% from 2013 to 2014 despite only a 3% rise in miles driven, suggesting non-compliant fuel card usage. Data on fuel purchases, miles driven, and assigned vehicles was analyzed to identify the cause. 3. Effective data analysis requires understanding the purpose, assessing the relevant data, using the right tools, identifying issues, and improving processes based on insights. This allows risks to be mitigated and more informed management decisions.

1. Can Data Analysis Improve
Process?
Sam Carr

2. Content
• What is data? What is big data?
• The importance of data analysis.
• Risk of poor business processes.
• How data analysis improves business
processes.
• Business processes impact your
operations.

3. What is Data?
• Data is a set of valuable information.
• Data can be measured, collected, reported
and analyzed.

4. What is Big Data?
• Big Data = HUGE Volume

5. What is Big Data?

6. Big Data Characteristics
• Volume
• Variety
• Velocity
• Veracity

7. Who Uses Big Data?

8. The Importance of Data
Analysis
• Understand your business.
• Know your business risks.
• Provide valuable information for
management decisions.

9. Risks of Poor Processes
• Misstatement of financial reporting
• Fraud
• Sales decrease
• Cost inefficiencies

10. How data analysis improves
business processes
1. Understand your purpose.

11. How data analysis improves
business processes
2. Understand your data.

12. How Data Analysis Improves
Business Processes
3. Choose the right analytic tool. (i.e. IDEA)
and perform data analytics

13. How Data Analysis Improves
Business Processes
4. Identify gaps based on the analysis
results

14. How Data Analysis Improves
Business Processes
5. Improve your business processes

15. How Data Analysis Improves
Business Processes
6. Practical examples

16. AP Data Cleaning
Background
• PBC had items paid or otherwise resolved that remained
in the Company’s Purchase Order System (PO System)
and the Company’s home grown three-way-match portal
databases.
• PBC was going to convert to Oracle and Management
wanted to have clean date before conversion.
• The total of accumulated liability was $325 million but
Management estimated the total was around $5 to $6
million.

17. AP Data Cleaning
1. Understand the purpose
To identify purchase order line items that have
been paid or have otherwise been resolved, but
remain in the PO system

18. AP Data Cleaning
2. Understand the data
Data Received
• Purchase Order (PO) file - the Open PO
detail by line item was extracted from the
PO system/ three-way match system
• Accounts Payable (AP) file - the vendor
history file of payments from AP system

19. AP Data Cleaning
2. Understand the data (Cont.)
• 10-year range: May 2002 – April 2012
• 21,434 PO’s and 80,372 line items totaling
$325M
• 292,901 AP payments totaling $1.8B

20. AP Data Cleaning
3. Choose the right tool and perform data
analytics (we chose IDEA)
• Quickly processing large data files
• Smart queries
• Drawing the process flow for the analysis
to create the audit trail for re-performance

21. AP Data Cleaning
Data Analysis Procedure in IDEA

22. AP Data Cleaning
Data Analysis Procedure in IDEA (Cont.)
PO file
Join file
PO
Summarization
file
C1
AP file
AP
Summarization
file
C2 C3 C4 C5 C6 C7
C1 w PO
lines
C2 w PO
lines
C3 w PO
lines
C4 w PO
lines
C5 w PO
lines
C6 w PO
lines
C7 w PO
lines

23. AP Data Cleaning
Data Analysis flowchart per IDEA

24. AP Data Cleaning
Data Analysis Result:
Beginning Balance $325,015,000
Cleaned PO’s $323,152,000
Ending Balance $1,863,000

25. AP Data Cleaning
4. Identify the gaps based on the analysis
results
Why did
this
happen?

26. AP Data Cleaning
Let’s see the process.

27. AP Data Cleaning
5. Improve your business process
• Fix the process
• Routine testing of three-way match

28. AP Data Cleaning
Let’s see what should be improved
Close paid PO’s in
PO system and
3‐way match portal
Three‐way match
process
Pay invoices in AP
system
3‐way match in
AP system?
YesNo

29. Fuel Card Compliance
Background
• NPI issued fuel cards to employees who
were assigned trucks
• Fuel cost increased around 15% from
2013 to 2014 but miles driven increased
only 3%
• Why did fuel costs increase so much?

30. Fuel Card Compliance
1. Understand the purpose
To identify the cause for the increase of fuel
cost .

31. Fuel Card Compliance
2. Understand the data
Data Received
• 2013 fuel card activities
• 2014 fuel card activities
• Detail of employees assigned trucks and
issued Fuel Cards – both years

32. Fuel Card Compliance
2. Understand the data (Cont.)
• In 2013, the miles driven was 6.3 million;
the fuel gallon purchased was 577,000
and the cost was $2.1 million
• In 2014, the miles driven was 6.6 million;
the fuel gallon purchased was 623,000
and the cost was $2.4 million

33. Fuel Card Compliance
3. Choose the right tool (IDEA or Excel) and
perform data analytics

34. Fuel Card Compliance
Consideration:
The average gas price per gallon in Texas
in 2013 and 2014 were $3.338 and $3.225
respectively (3.5% decrease!)

35. Fuel Card Compliance
Procedures taken:
Employee
List
2013&2014
Join file
2013 Join
File
2014
Activities
2014 Join
File
Employee
List
2013
Activities
C1 C2 C3