MM Foundation, Enterprise Structure and Master Data

MM / P2Pintermediate

MM Foundation Part 2: Master Data Quality — Material, Supplier, Info Record and Source Data

Key takeaway

Keep procurement master data reliable: common data defects and their process impact, mandatory fields and field control, duplicate checks, governance with owners and workflows (e. g. MDG), data quality monitoring, and cleansing before migrations.

Explanation

📌 KEY POINTS
✅ Typical defects: duplicate suppliers, missing views, outdated info record prices, wrong units, missing source lists.
✅ Field control (material type/industry sector, BP groupings) and mandatory fields prevent incomplete data.
✅ Governance: data owners, request/approval workflows (e.g. MDG), change logs.
✅ Monitor quality with KPIs and fix at source.
⚠️ Migrating dirty data into S/4HANA multiplies problems — cleanse first.

━━━━━━━━━━━━━━━━━━━━
▶ WHERE WE ARE
Part 1 gave the overview. Now quality and governance.

━━━━━━━━━━━━━━━━━━━━
▶ 1. DEFECTS AND IMPACT

Duplicate suppliers → split spend, duplicate payments risk.
Missing views → POs/GRs fail.
Wrong prices/units → invoice variances.

━━━━━━━━━━━━━━━━━━━━
▶ 2. PREVENTION

Field selection by material type; BP groupings and number ranges.
Mandatory fields, duplicate checks.

━━━━━━━━━━━━━━━━━━━━
▶ 3. GOVERNANCE

Owners per domain (material, supplier, pricing).
Request/approval workflows; MDG for central governance.

━━━━━━━━━━━━━━━━━━━━
▶ 4. MONITORING

KPIs: duplicates, incomplete records, outdated info records, blocked suppliers used.

━━━━━━━━━━━━━━━━━━━━
▶ 5. CLEANSING

Before migration: deduplicate, archive unused, validate.

━━━━━━━━━━━━━━━━━━━━
▶ STEP BY STEP

Run a duplicate supplier check.
List materials missing plant views for active plants.
Review info records with outdated prices.
Define owners and KPIs.

✅ CHECKPOINT: a monthly data quality report exists and each issue has an owner.

Code example

ABAP Code

===== STEP 1: checks =====Duplicate suppliers: tax number / bank / name+city comparisonMissing views: materials without purchasing/MRP views for active plantsOutdated info records: price validity expired, last PO price deviates strongly ===== STEP 2: controls =====Material type field selection | BP grouping + number range | mandatory fields | duplicate checkGovernance: MDG change requests with approval ===== STEP 3: KPIs =====% incomplete materials | duplicate supplier rate | invoice price variance rate | manual PO price overrides

Real project scenario

A global template program found 18% duplicate suppliers across legacy systems. Spend by supplier was understated and duplicate invoices were paid twice. Cleansing before migration, MDG with duplicate checks for new suppliers and a monthly quality dashboard reduced duplicates below 1%.

Common mistakes

No data owners.
Migrating without cleansing.
No duplicate checks.
Ignoring outdated info records.
Measuring nothing.

Best practices

Assign owners per domain.
Cleanse before migration.
Enforce field control and duplicate checks.
Use approval workflows.
Report KPIs monthly.

Interview angle

Questions: "How do you ensure master data quality in MM?", "What problems do duplicate suppliers cause?", "What would you cleanse before migration?"
Strong answer: defects and impacts, field control and duplicate checks, governance with owners and MDG workflows, KPIs, cleansing before migration.

Practice this lesson

Quick check

1. When is the best time to cleanse procurement master data in an S/4HANA program?

2. Duplicate suppliers exist across legacy systems. What is the main business risk?

3. Which control prevents incomplete material masters for a specific material type?

Interview questions

1. After a purchasing organization restructuring, buyers report that certain fields (e.g., incoterms, payment terms) are unexpectedly becoming mandatory or hidden in specific purchasing document types, but only for one purchasing organization. How would you diagnose and resolve this?

Answer it in your own words first, then compare.

2. Why is master data quality (material master, vendor master, purchasing info records) considered a foundational control point in a Procure-to-Pay implementation, rather than just a data-entry concern?