DMS — Data Management System
Turn messy ERP and CRM data into living rules that compound over time. For retail and service companies managing inventory, clients, invoicing, and sales.
Three Modules, One Loop
Concrete capabilities that turn messy operations into living rules
Analytics (Volume)
Quantify data quality issues by financial impact
- Surface bottlenecks and error patterns
- Rank issues by error volume and manual touch time
- Track KPI baselines for continuous improvement
Rule Regime
Codify data policies as executable, enforceable rules
- Turn implicit policies into explicit constraints
- AI-generated process maps + human refinement
- Deterministic enforcement with automatic alerts
Process Map
AI-generated operational flows with validation breakpoints
- AI discovers flows, you refine and approve
- Interactive maps prevent operational drift
- Queued reprocessing for errors (Q1 2026)
Platform access available after pilot kickoff
Break the consultant cycle
Stop repeating the same data quality projects. Build institutional memory instead.
Consultant Cycle
- Ad-hoc projects; drift returns
- Knowledge walks out; re-learn later
- Repeat spend every few years
- No system of record for rules
DMS Loop
- Rules live over company data
- Process map prevents drift
- Alerts now, queued reprocessing Q1 2026
- Institutional memory builds over time
How it works
Watch data flow through the loop. Each cycle improves quality and reduces problems.
Your company’s data improves every cycle.
From ingestion to transformation, Alteridad closes the loop.
Operational focus areas
ERP and CRM data quality metrics for retail and service companies
Inventory Management
- •Completeness: % required product fields filled
- •Uniqueness: % SKUs without duplicates
- •Accuracy: % inventory counts matching physical stock
- •Consistency: % products with no cross-system conflicts
Client Data (CRM)
- •Validity: % contacts with proper email/phone format
- •Uniqueness: % customer records without duplicates
- •Completeness: % accounts with required fields
- •Referential integrity: orphan contacts per 1k records
Invoicing & Billing
- •Rule pass rate: % invoices passing validation
- •Conformance rate: % invoices matching billing flow
- •MTTR: mean time to resolve invoice errors
- •Accuracy: % line items matching contracts
Sales Operations
- •Completeness: % orders with required fields
- •Case throughput time: quote-to-cash duration
- •Straight-through processing: % orders with no manual touch
- •Consistency: % sales data across ERP/CRM systems
Pilots focus on 1-2 high-impact metrics from your ERP or CRM system. We establish baselines, implement rules, and track improvement over 4-6 weeks.
For retail and service companies with operational data in inventory, client management, invoicing, and sales systems.
What DMS measures
Industry-standard metrics across data quality, governance, process mining, and observability
Data Quality
- •Completeness: % required fields filled
- •Validity: % values matching type/format
- •Uniqueness: % records without duplicates
- •Consistency: % records with no conflicts
- •Accuracy: % values matching reference
- •Conformity: % values using standard codes
- •Referential integrity: orphan keys per 1k rows
Rule Engine & Governance
- •Rule coverage: % critical fields with rules
- •Rule pass rate: % rows passing validation
- •Issue backlog: open violations count
- •Fix throughput: violations resolved per week
- •Auto-fix rate: % violations auto-remediated
- •MTTD: mean time to detect violation
- •MTTR: mean time to resolve violation
- •Review SLA adherence: % on-time reviews
Process Mining
- •Case throughput time: start to finish
- •Waiting time: idle between steps
- •Variant count: unique process paths
- •Conformance rate: % cases matching model
- •Rework rate: % cases repeating steps
- •Straight-through processing: % no manual touch
- •SLA breach rate: % cases exceeding SLA
Observability & Pipelines
- •Freshness lag: source event to warehouse
- •Volume anomaly rate: unexpected row counts
- •Schema drift incidents: changes per month
- •Lineage coverage: % datasets tracked
- •Pipeline success rate: % successful runs
Adoption & Coverage
- •Monitored fields: count under active rules
- •Table coverage: % tables onboarded
- •Rule execution volume: evals per day
- •Issues resolved: fixes closed per week
- •Data doc completeness: % documented
Integrations
Connect to your critical data sources. We meet your data where it lives.
Databases
- • PostgreSQL / Supabase
- • CSV/Excel imports
- • Custom connectors available
APIs & Feeds
- • REST API endpoints
- • Event notifications
- • Custom data pipelines
SDKs & Docs
- • API documentation
- • Integration guides
- • Implementation support
Need a specific integration? We build custom connectors during pilot engagements.
Discuss your integration needs →Security & Compliance
Enterprise-grade security built in from day one
Encryption
- • In transit (TLS 1.3)
- • At rest (AES-256)
- • Key management controls
Access Control
- • Row-level security (RLS)
- • Role-based access (RBAC)
- • Audit logs for all actions
Regions
- • Primary: US-East (Virginia)
- • EU hosting (Supabase Frankfurt)
- • HQ in Paris, France 🇫🇷
Compliance
- • Controls aligned; audit planned
- • EU hosting available (Frankfurt)
- • Security review process
Start with a pilot
4-6 week engagements focused on one high-impact operational metric. Transparent pricing, measurable outcomes.
Pilots are customized to your specific operational challenges and data landscape.