For senior business leaders, implementing SAPSuccessFactors Payroll is a strategic investment. But beneath the platform’s promise lies a delivery risk that’s easy to miss and costly to ignore:

Dirty payroll data.

While configuration and integrations get much of the attention, data quality is what determines compliance, accuracy, and trust. And if poor data goes undetected, the consequences stretch far beyond project timelines—they affect employee pay, audit results, and organisational reputation.

Where Dirty Data Becomes a Compliance Liability

SAP SuccessFactors Payroll relies on upstream data from Employee Central. When that data is flawed, compliance obligations are put at risk.

Real examples include:

• Incorrect tax file numbers or PAYG codes leading to over- or under-withholding
• Misaligned job structures and pay group mappings, breaching classification or award entitlements
• Unreconciled absence balances, causing errors in long service leave or personal leave entitlements
• Incorrect termination pay logic impacting redundancy or final pay compliance
• Superannuation misallocation, breaching legal contribution requirements
• Data gaps across jurisdictions, failing local compliance in multi-country payroll environments

In each case, the cost of correction post go-live can be significant: manual overrides, payroll reruns, audit flags, and reputational damage.

Compliance Starts With Data Ownership

Successful programs treat payroll data quality not as a technical stream—but as a core compliance activity.

That means:

1. Identifying high-risk fields early: Focus on pay, tax, super, leave, and cost allocations
2. Embedding payroll compliance leads into design workshops: Avoid rework by aligning config with legislation
3. Running mock data loads and audit reconciliations: Validate outputs before testing begins
4. Using local compliance checklists: Align SuccessFactors setup with legal and enterprise agreement obligations

When data ownership is clear, compliance risk reduces. When it’s left to the end, exposure grows.

A large organisation implemented SuccessFactors Payroll with over 3000 employees across multiple Australian states. Early mock loads revealed:

• 5% of records missing accurate TFNs
• Mismatched superannuation fund IDs
• Leave balances that didn’t reflect EBA clauses and obligations

The leadership team paused delivery to embed a payroll compliance stream, assign accountability, and correct high-risk data before UAT. The result: a clean audit path, accurate go-live, and restored trust across HR and Payroll teams.

SuccessFactors Payroll doesn’t just run your pays—it proves your compliance.

If you’re leading or sponsoring a program:

> ✅ Have we identified which payroll data fields carry compliance risk?

> ✅ Are payroll leads empowered to drive data accuracy—early?

> ✅ Will our data stand up to audit scrutiny on day one?

If the answers are unclear, the time to act is now—not during testing.