Live SAP’s 2027 Deadline Is Coming. Are You Ready? Register Now
The Economics of SAP Data Quality

Quantifying the Enterprise Cost of Untrusted Data

Poor data quality doesn’t show up as a line item, it shows up everywhere else

As SAP environments grow more complex, defective master and transactional data creates economic impact that extends well beyond IT, driving operational inefficiency, working capital pressure, transformation cost, and enterprise risk. This white paper introduces a practical framework that helps organizations trace data defects to their true financial impact and translate technical data-quality indicators into measurable business outcomes.

Why Download this Whitepaper?

Understand why poor data quality costs organizations 9.7% of annual revenue on average

Trace how a single data defect moves through SAP processes into measurable financial impact

Quantify the working capital and cash flow impact of defective AR, AP, and inventory data

Model your own annual data remediation cost using a simple, repeatable formula

Understand why poor data makes SAP transformation exponentially more expensive

Learn why AI and automation amplify—rather than absorb—the cost of untrusted data

Download the Economics of SAP Data Quality Whitepaper
Key Insights Covered in the Whitepaper
The four economic impact areas of poor SAP data: operational efficiency, working capital, transformation cost, and enterprise risk
The Datavapte Data Quality Cost Chain™—the five-stage model from data defect to economic impact
Where cost actually appears: a process-by-process map across procure-to-pay, order-to-cash, inventory, finance, and more
The Data Quality Economic Impact Model for converting technical KPIs into financial metrics
Why data quality becomes more expensive to fix the later a defect is caught in SAP transformation
A roadmap from episodic data cleanup to continuous economic control
Who’s this Whitepaper for?

CFOs and Finance Leaders

CIOs, CTOs, and IT Executives

SAP Program & Transformation Managers

Enterprise Architects

Master Data & Data Governance Leaders

Compliance, Risk, and Internal Audit Teams

Download the Whitepaper & Get Instant Access to:

A complete framework for quantifying the enterprise cost of poor SAP data

The Datavapte Data Quality Cost Chain™, with a worked example

A working capital and cash flow impact model for AR, AP, and inventory

An economic formula for modeling your own annual remediation cost

Research-backed benchmarks from Gartner, Aberdeen, Experian, SAPinsider, MIT Sloan, and TDWI

Actionable recommendations to move from periodic cleanup to continuous control

Turn SAP Data Quality into Measurable Business Value

Download the Economics of SAP Data Quality whitepaper and discover how structured data quality management can reduce cost, protect working capital, lower transformation risk, and build the trusted foundation SAP AI requires.

Download