ERP Master Data Quality Agent
Version v1.4 · Production · Deployed at 12 organisations — continuously scans ERP master data for completeness gaps, behavioural anomalies and duplicate entities, and routes every finding to an accountable owner with a full audit trail. Read-only against your ERP.
What this pack does
Enterprise ERP master data decays quietly. Vendors are created twice under slightly different legal names, statutory fields are left blank during month-end pressure, and dealer classifications drift from the way the business actually operates. None of it breaks a system — it just quietly distorts spend analytics, tax reconciliation and channel reporting.
This accelerator deploys a scoped Master Data Quality workspace that scans customer, vendor and material master data on a schedule, produces findings from three independent detection methods, and routes each one to a named owner with a validation workflow. Findings close only when the correction is confirmed in the source system's change log — not when someone clicks "done".
Typical first-scan outcome at a mid-size ERP estate: 200–400 rule failures, 15–30 behavioural anomalies and 5–15 duplicate clusters, with 60–70% of findings owned by three or fewer people.
How it works — six agents, three detection methods
What this pack deliberately does not do
- It does not write to, correct or delete anything in your ERP. Corrections are made by your team in the system of record.
- It does not auto-merge duplicate records. Clusters are recommendations that a steward confirms or rejects.
- It does not replace your MDM tool. It tells you what is wrong, who owns it, and whether it was fixed.
- It does not act on anomalies without human validation. Every ML finding carries a confidence score and a validation step.
Ownership routing template
The pack ships with a routing template. During deployment it is mapped to your own owners and governance forums; it stays editable in Settings → Ownership routing.
| Domain | Finding type | Accountable owner | Review forum |
|---|---|---|---|
| Customer | Completeness gap (RULE) | Kavita Iyer | Weekly dealer data huddle — Thursday |
| Customer | Behavioural anomaly (ML) | Sandeep Krishnan | Monthly master data governance forum — second Tuesday |
| Customer | Duplicate cluster (ENTITY) | Kavita Iyer | Monthly master data governance forum — second Tuesday |
| Vendor | Tax / statutory field gap (RULE) | Anjali Desai | Payables control review — fortnightly |
| Vendor | Duplicate cluster (ENTITY) | Ramesh Pillai | Monthly master data governance forum — second Tuesday |
| Material | Classification / UoM gap (RULE) | Vinod Rathi | Materials governance council — monthly |
Prerequisites
- A lake copy of ERP master data, or a read-only ERP OData / RFC service account.
- Extract of the last 24 months of transactional behaviour per entity (for anomaly baselines).
- A named accountable owner per master data domain.
- One governance forum where findings are reviewed on a cadence.
Deployment configuration
Agents installed
All six register in AI Context → Fleet Governance with budget caps and kill-switches.