Audit workflow automation

PROJECTS / AUTOMATION

Engineering Workflow Automation: Audit Data Processing

Automating high-volume SAP and transaction data processing for an audit workflow. An automation workflow designed to reduce repetitive data-processing activities, combining SAP report extraction, sheet-of-transactions consolidation and structured Excel processing into a faster and more reliable workflow.

253

REPORTS PROCESSED

SHEETS OF TRANSACTIONS

~5.5M

ROWS ANALYZED

6→3

MONTHS ESTIMATED

The Challenge

The audit required the analysis of 253 individual reports containing accounting and transaction information related to an operational asset. For each report, the workflow required identifying the relevant lines and extracting the associated document number. These document numbers then had to be located across 22 sheets of transactions, each containing approximately 250,000 rows. The main challenge was not the complexity of any individual step, but the cumulative time required to repeat the same operations hundreds of times across millions of rows.

The Solution

The automation was developed progressively as recurring bottlenecks became clear. The first step was the consolidation of the sheets of transactions, transforming multiple large files into a more structured and searchable dataset. The next step automated the extraction and preparation of SAP report information, reducing the amount of manual filtering and repetitive data handling required before the transaction search.

Automation developed in stages

Week 1 08/06 – 12/06

Automation: None

Week 2 15/06 – 19/06

Automation: None

Week 3 22/06 – 26/06

Automation: Sheet Consolidation

Week 4 29/06 – 03/07

Automation: Sheet Consolidation

Week 5 05/07 – 10/07

Automation: Sheet Consolidation

Week 6 13/07 – 17/07

Automation: Sheet Consolidation + SAP Report Extraction

Week 7 20/07 – 24/07

Automation: Sheet Consolidation + SAP Report Extraction

Week 8 27/07 – 31/07

Automation: Sheet Consolidation + SAP Report Extraction

112

253 processes completed across 8 weeks.

6 → 112 weekly throughput as the automation workflow evolved.

The Result

~50%

REDUCTION TIME

253

PROCESS COMPLETE - 8 WEEKS

18,7x

WEEKLY THROUGHPUT INCREASE

ENGINEERING VALUE

Why it matters

TIME

Less time spent on repetitive data manipulation.

SCALE

Ability to process hundreds of reports against millions of transaction rows.

CONSISTENCY

A standardized workflow reduces variability in repetitive processing steps.

FOCUS

More time available for the actual audit analysis instead of manual data preparation.

IMPLEMENTATION

Technical approach

Python

Data manipulation and workflow automation.

Excel

Structured output and working files.

SAP Reports

Source data extraction.

Sheets of Transactions

High-volume transaction datasets.

Data Filtering

Identification of relevant records.

Document Matching

Connecting report information with transaction data.

Python · Excel · Data Processing · Workflow Automation

COMPARISON

From manual workflow to structured automation

BEFORE

Manual report generation

Manual filtering

Manual document identification

Repeated searches across large sheets of transactions

Copy and paste

Manual Excel consolidation

High repetitive workload

→

AFTER

Structured report extraction

Automated filtering

Automated document preparation

Consolidated transaction data

Structured matching workflow

Automated data organization

More time for analytical work

REFLECTION

Engineering impact beyond code

The value of the project was not the automation itself, but the time and analytical capacity it created.

By restructuring a repetitive, high-volume workflow, automation reduced the amount of manual data manipulation required and allowed the team to focus more of its effort on the actual audit analysis.

”Automation is most valuable when it removes repetitive work from engineering processes and gives people more time to solve the problems that actually require engineering judgment.”