Will Black Friday deals flood your SAP system? Time for a data privacy reset.

Will you have that sinking feeling after Black Friday? The chaos of the shopping madness around Black Friday deals will be over; but the data hangover lingers.

In his previous blog, my colleague Paul Hammersley explained this problem: every 'guest checkout' order, every temporary address, and every 'dummy' customer record entered for one-time transactions leaves behind a scatter of unnecessary Personally Identifiable Information (PII) deep within your SAP Production system.

This isn't just data; it's a growing backlog of data privacy debt.

Let’s be honest: the transaction data itself isn’t the issue. The real compliance and performance headaches come from treating that data like it’s permanent.

For too long, the approach to cleaning up this scattered PII has been reactive: massive, costly archiving projects, or waiting until a stressful Data Subject Access Request (DSAR) forces you to go hunting for a one-off customer record from five years ago.

It's time to retire the data debt firefighting approach.

The most successful IT and compliance teams aren't focused on curing the hangover; they’re focused on preventing it from recurring. Your Q1 mandate isn't just to clean up last year's mess: it's to implement a seamless, automated routine for data minimisation that future-proofs your SAP landscape.

This is when you need to be proactive.

Manual cleanup: Can you solve it with archiving?

For IT and SAP Basis teams, the immediate, reactive fix to massive data is often archiving. It’s a familiar process; a technical comfort blanket. But here’s the harsh truth about the Black Friday PII hangover: it’s not an archiving problem.

Archiving works brilliantly for clearing out large, closed, and static datasets – think old financial documents or massive log files that have reached their legal retention limit. The guest checkout PII debt, however, is a different beast entirely. It’s often small, scattered, and stubbornly interconnected.

Your one-time shoppers and temporary 'dummy' customer records don't sit neatly in one place waiting to be boxed up. They leave fingerprints across address tables (ADRC), Sales Order logs, and sometimes even marketing interaction records.

The wholesale scenario: PII hidden in plain sight

Consider your wholesale distribution channels – the thousands of Black Friday deals completed through partners like Amazon or Costco. In these scenarios, you often have no core Customer Master record for the final buyer. Instead, the final customer’s PII is tucked away in customised Sales Order and billing documents. The wholesaler is the ‘Ship-to’ customer, but the actual delivery address – the real PII – is linked to the Sales Order via tables like the VBPA.

The technical reality is painful: you’re forced to hunt down a needle of PII within a data haystack that is constantly being added to. This manual, custom-query approach is slow, consumes valuable time, and dangerously prone to human error.

The volume of transactions guarantees that your data debt will always grow faster than your team can possibly clean it up manually. If your process isn't proactive and part of your standard routine, your system is already non-compliant.

When does your data landfill become a governance crisis?

While the IT/Basis team grapples with the technical pain of cleaning up scattered PII (the data landfill), the Data Privacy Compliance Manager is dealing with the resulting governance crisis. The problem shifts from "Can we delete this?" to "Can we prove we are compliant?"

The sheer volume of the data debt undermines your ability to meet two core regulatory challenges. The moment a customer submits a DSAR or a Right to Erasure request, the clock starts ticking. If your SAP system is a ‘data landfill’, that simple request becomes a frantic, high-risk audit. You are forced to search for stray PII records associated with a temporary shopper across multiple, potentially non-standard tables.

The global and contractual retention nightmare

A single Black Friday purchase can involve PII subject to dramatically different retention periods. Financial data may need to be retained for seven years, but the PII attached to the guest record may need to be removed immediately in compliance with local data privacy laws, such as GDPR, CCPA or POPIA.

The risk is compounded by the contractual mandates of wholesale agreements. We have recently seen clients facing 30-to-60-day retention periods enforced on sales made through these channels. After shipping times, return policies, and basic processing have expired, your clock has started ticking. Assuming a successful Black Friday with hundreds of thousands of sales, can your manual process successfully manage the removal of complex PII (like that linked via VBPA) within a 30-day window? The answer is almost certainly no.

The mandate is clear: move beyond manual cleanup and adopt a strategy where data minimisation is an automated, continuous SAP routine.

Your 3-step playbook for SAP data health

Shifting from reactive data debt to proactive data health requires specialised tools designed specifically for the unique challenge of SAP data. This is about implementing routine, targeted data minimisation.

How can you be proactive to cure the hangover and preventing the landfill from growing?

Step 1: Discover and understand your debt

You can't clean what you can't find. The first step is automatically identifying where all that scattered PII from one-time shoppers resides – even in non-standard or custom tables, and complex linked records like those arising from wholesale orders.

• Proactive move: Implement a solution like EPI-USE Labs’ Data Disclose that can scan your Production data and map PII to specific legal entities and retention periods. This ensures you apply the correct rule – whether it’s a seven-year financial mandate, or a 30-day contractual deadline.

Step 2: Minimise and mask

Not all data debt needs to be destroyed immediately. Some financial data must be retained for audit, but the PII attached to it can often be anonymised or redacted.

• Proactive move: Use a rules-based system that separates the sensitive PII (the high-risk data) from the legitimate business data (the data your auditors need). By redacting or masking PII, you drastically reduce your attack surface without impacting business continuity. EPI-USE Labs’ Data Redact allows you to remove the PII data from your SAP system.

Step 3: Automate and audit as routine

A playbook is only really effective if it's executed routinely, safely, and without human intervention. This is the difference between an annual panic attack and a seamless compliance routine.

• Proactive move: Operationalise minimisation. Set up automated, scheduled processes that safely delete or redact PII based on your pre-defined rules. EPI-USE Labs’ Data Retain makes this possible. It creates an audit trail for every action, giving the Compliance Manager the verifiable proof they need to demonstrate adherence to global regulations.

Black Friday: a call to data health

The rush around Black Friday exposes the weakness in traditional data management: scattered PII and short contractual deadlines are a threat to compliance, and a drain on performance. So stop treating your SAP system like a data landfill that requires an annual deep clean, and adopt the proactive playbook. Shift from fighting data debt to ensuring continuous data health with an automated, auditable routine that keeps your systems clean, compliant, and ready for the Black Friday rush.

Ready to introduce a proactive routine?

Don't wait for the next DSAR or 30-day deadline to force your hand. Find out how the EPI-USE Labs’ Data Privacy Suite for SAP solutions enables you to operationalise data minimisation, quickly, safely, and with the auditability your organisation needs.