--- title: Supplier 360 url: https://documentation.cluedin.net/solutions/use-cases/supplier360 content_type: concept section: Solutions & integrations > Use cases --- # Supplier 360 > concept: Explains how something works. # Supplier 360 in CluedIn — Step-by-Step Implementation Guide Supplier 360 delivers a single, trusted, and actionable view of each supplier across ERP, procurement, finance/AP, risk, and contract systems. This guide walks you through the end-to-end build in CluedIn: ingest → standardize → match/link → golden record → enrich → govern → publish. --- ## Outcomes - A **golden supplier record** per supplier (and per site) with complete, standardized attributes. - **Linked entities**: supplier ↔ sites ↔ contacts ↔ contracts ↔ POs ↔ invoices ↔ risk events. - **Quality, lineage, and auditability** for compliance and operations. - **Publish/Sync** to downstream systems (ERP, procurement, analytics). --- ## Prerequisites - Access to source systems (e.g., SAP/Oracle ERP, Ariba/Coupa, AP platform, spreadsheets). - RACI: Ensure you have **Accountable** access for the objects you’ll import/export. - A dedicated environment (or VM) for heavy jobs (ingestion, matching, toolkit operations). --- ## Reference Data Model **Core entities** - `Supplier` (legal entity level) - `SupplierSite` (site/plant/branch) - `Contact` (people) - `Contract` - `PurchaseOrder` - `Invoice` - `RiskEvent` (e.g., sanctions hit, delivery failure, ESG breach) **Common attributes (examples)** - Supplier: LegalName, TradingName, TaxID (VAT/ABN/EIN), DUNS, RegistrationNo, Country, Address, BankAccount (IBAN/BIC), EmailDomain, Category, Status. - SupplierSite: SiteName, Address, Country, GLN, ParentSupplierId. **Relationships** - Supplier **has** many SupplierSites, Contacts, Contracts, POs, Invoices, RiskEvents. --- ## Step 1 — Connect & Ingest Sources **Portal**: *Data Sources → Add Source* 1. Add ERP master data (Vendors/Suppliers + bank data). 2. Add procurement networks (catalog, onboarding). 3. Add AP/Finance (invoices, payments). 4. Add risk/enrichment sources (sanctions, credit, ESG), optional. 5. Add ad-hoc files (CSV/XLS) for legacy/one-off data. **Tips** - Use **sampling** first to inspect field sparsity and formats. - Define **source metadata** (system name, extraction time, primary keys). --- ## Step 2 — Define Entities & Mappings **Portal**: *Entity Explorer → + Create Entity Type* 1. Create `Supplier` and `SupplierSite` entity types. 2. Map source fields → target attributes (normalize names like `VendorName` → `LegalName`). 3. Track **provenance** (SourceSystem, SourceRecordID). **Tip**: Keep site-level data **separate** from the parent supplier; many duplicates stem from conflating these. --- ## Step 3 — Standardization & Normalization Rules **Portal**: *Governance → Rules (Data Part Rules)* Create rules to standardize inputs **before** matching: - **Names**: strip punctuation/stopwords; uppercase/lowercase consistency. - **Addresses**: split house/street/city/postcode; normalize country codes (ISO-2). - **Phones**: E.164 standardization. - **Tax IDs**: remove separators; validate checksum per country. - **Bank**: IBAN/BIC validation. - **Email domains**: extract domain from contact emails. **Recommended tags** - `Standardized`, `NeedsValidation`, `InvalidTaxID`, `InvalidBank`, `LegacySource`. --- ## Step 4 — Configure Identity Resolution (Matching) **Portal**: *Entity Matching → Supplier* 1. **Blocking keys** (to reduce comparisons): - `(Country + CleanedLegalNameSoundex)` - `(TaxID)` when present - `(EmailDomain)` (fallback) 2. **Match rules** (examples): - **High-confidence**: exact `TaxID` OR exact `DUNS`. - **Medium**: `CleanedLegalName` fuzzy ≥ 0.92 AND same `Country`. - **Supplemental**: phone OR email domain OR address similarity ≥ 0.9. 3. Set **thresholds** (e.g., Auto-merge ≥ 0.97; Steward review 0.90–0.97). 4. Run a **matching job** and review candidates in **Data Stewardship**. **Pitfall to avoid**: Over-aggressive fuzzy name matching across different countries. Always include **Country** as a condition unless you have multi-national evidence. --- ## Step 5 — Stewardship: Review & Merge **Portal**: *Data Stewardship → Match Review* 1. Inspect candidate pairs; verify with TaxID, DUNS, or contracts. 2. Approve merges; reject false positives; tag edge cases (`AmbiguousMatch`). 3. Use **Unmerge** if a mistake is found (audit captured in History). **Tip**: Triage by **confidence** and **impact** (number of downstream links). --- ## Step 6 — Golden Record Survivorship **Portal**: *Governance → Rules (Golden Record Rules)* Define attribute precedence and tie-breakers: | Attribute | Precedence (highest → lowest) | Tie-breaker | |----------------|------------------------------------------------------------|-----------------------------| | LegalName | ERP > Procurement > AP > CSV | Most recent update | | TaxID/DUNS | ERP only | N/A | | Address | Site-specific registry > ERP > Procurement | Highest quality score | | BankAccount | ERP (verified) > AP | Verified flag = true | | Category | Procurement taxonomy > ERP | Most frequent value | | Status | Risk compliant > Pending > On hold | Most recent risk check | Add **Actions**: - Tag `VerifiedSupplier` when TaxID valid & sanctions clear. - Compute **completeness score** and tag `LowCompleteness` < 0.8. --- ## Step 7 — Enrichment & Risk **Portal**: *Data Sources → Add Source* (enrichment), *Governance → Rules* - Pull official registry details (legal address, directors where available). - Run **sanctions/PEP** checks; tag `SanctionsHit` with evidence fields. - Append credit/ESG risk ratings; store dates and providers. **Tip**: Separate **enrichment freshness** (LastCheckedAt) and set a rule to re-check periodically. --- ## Step 8 — Quality Scoring & Dashboards **Portal**: *Data Quality → Profiling / Dashboards* - Define KPIs: completeness %, duplicates, invalid TaxID, invalid bank, address parse rate. - Track Golden Record creation rate and match precision (steward overrides vs auto-merge). --- ## Step 9 — Governance, Security & Lifecycle **Portal**: *Governance → Policies / Retention / Permissions* - Apply **RACI**: Accountable access for stewards; Restricted for sensitive fields (bank). - **Retention**: e.g., archive inactive suppliers after N years; delete after audit closure. - **Audit**: Ensure changes (merges, overrides) are captured in History; enable rollback. --- ## Step 10 — Publish / Integrate **Portal**: *Exports* - **ERP sync**: push Supplier + Site golden attributes. - **Procurement**: push status/category/compliance flags. - **Analytics**: export wide table to warehouse/BI. - **Eventing/APIs**: expose CRUD/read APIs for master data consumers. **Tip**: Start with a **read-only** feed to validate mapping, then switch to authoritative sync. --- ## Step 11 — Scheduling & Operations - Schedule ingestion, matching, and golden updates (off-peak where possible). - Monitor job runtimes; alert on spikes (likely due to source anomalies). - For large batches, run heavy jobs on a **dedicated server/VM** to avoid timeouts. --- ## Step 12 — Validate & UAT - Sample checks: 50–100 suppliers across regions and sources. - Verify tax/bank/address survivorship; confirm no cross-supplier conflation. - Have AP/Procurement/Compliance sign off on a **go-live checklist** (below). --- ## Step 13 — Package & Promote **Portal/CLI**: *Product Toolkit* - Export entities, rules, policies, dashboards. - Promote to staging → production. - Ensure you have **Accountable RACI** and run large toolkit jobs on a **dedicated box**. --- ## Go-Live Checklist - [ ] Ingestion schedules configured and ran successfully. - [ ] Matching thresholds tuned; low false-positive rate verified. - [ ] Golden survivorship rules approved by data owners. - [ ] Sanctions/credit enrichment configured and refreshed. - [ ] Exports mapped and validated in target systems. - [ ] Retention & access policies applied. - [ ] Runbooks for **rollback/unmerge** documented. --- ## Common Pitfalls & How to Avoid Them - **Conflating sites with legal entities** → Model `SupplierSite` separately; match on site identifiers. - **Over-reliance on name similarity** → Require TaxID/DUNS or multi-evidence for auto-merge. - **Dirty TaxID formats** → Normalize and validate before matching. - **Bank detail risk** → Use verified source precedence; never crowdsource survivorship. - **Timeouts on big runs** → Stagger jobs; use dedicated compute; batch by country or source. - **Re-polluting golden records** → Disable or adjust problematic Rules *before* rollback/re-runs. --- ## Example Rules (Patterns) **Data Part Rule — Normalize TaxID** - Condition: `TaxID` present - Action: strip non-alphanumerics; upper; set `TaxID_Normalized`; validate checksum; tag `InvalidTaxID` if fail. **Matching — Auto-merge** - If `TaxID_Normalized` exact OR `DUNS` exact → Confidence = 1.0 (auto). - Else if `CleanedLegalName` fuzzy ≥ 0.92 AND `Country` equal AND (`EmailDomain` OR `AddressSim` ≥ 0.9) → Confidence = 0.96 (steward). **Golden Record — Survivorship** - `LegalName`: ERP > Registry > Procurement (most recent tie-break). - `Status`: if `SanctionsHit` then `OnHold` else `Active`. - Tag `VerifiedSupplier` when (`TaxIDValid` AND `SanctionsClear` AND completeness ≥ 0.85). --- ## Troubleshooting - **Too many duplicates**: Lower auto-merge threshold; add blocking by Country; require TaxID/DUNS. - **Missed matches**: Add alternative keys (RegistrationNo, GLN, EmailDomain); tune fuzzy threshold upward/downward. - **Wrong golden values**: Review precedence order; check source quality; re-run with corrected rules. - **Slow processing**: See performance article; run heavy jobs on dedicated compute; schedule off-peak. --- ## Success Metrics - Duplicate rate ↓, auto-merge precision ≥ 98%. - Golden record completeness ≥ 85–95% (target by region). - Time to onboard new supplier ↓ (days → hours). - Sanctions/risk check freshness ≤ N days. - Downstream exception rate (ERP/procurement) ↓. --- ## Summary Supplier 360 in CluedIn combines **standardization**, **robust matching**, **clear survivorship**, and **governed publishing** to deliver one trusted view of every supplier. Follow the steps above, validate with real samples, and iterate your rules until precision and completeness meet your business targets. . Up: [Use cases](https://documentation.cluedin.net/solutions/use-cases.md)