Salesforce ERP Combined BI and Analytics Strategy
CRM data tells you what might happen (pipeline, forecast, engagement). ERP data tells you what did happen (orders shipped, revenue recognized, costs incurred). Combining these datasets into unified analytics gives leadership end-to-end visibility from lead generation through cash collection. This guide covers the data architecture and tooling needed to build combined CRM-ERP analytics.
Data Architecture for Combined Analytics
Unified CRM-ERP analytics requires a shared data layer that reconciles Salesforce objects with ERP tables. This is typically a cloud data warehouse such as Snowflake, BigQuery, or Azure Synapse that ingests data from both systems. The warehouse provides a single schema where Account joins to Customer, Opportunity joins to Sales Order, and Campaign joins to Revenue by product line.
- Salesforce data extracted via Salesforce Connect, Heroku Connect, or ETL tools like Fivetran into the cloud warehouse
- ERP data loaded via database replication, API extraction, or native connectors depending on the ERP platform
- Canonical data model in the warehouse maps Salesforce IDs to ERP keys with a cross-reference dimension table
- Incremental extraction using Salesforce SystemModstamp and ERP audit timestamps reduces warehouse refresh time
- Data lineage tracking ensures analysts understand which system sourced each metric and when it was last refreshed
Key Cross-System Metrics and KPIs
The value of combined analytics comes from metrics that neither system can produce alone. Lead-to-cash conversion rate, quote-to-shipment cycle time, and customer lifetime value including service costs all require joining CRM and ERP data. These cross-system KPIs reveal process bottlenecks invisible to teams working in a single system.
- Lead-to-cash conversion rate: percentage of Salesforce Leads that ultimately generate ERP-recognized revenue
- Quote-to-ship cycle time: days from Salesforce Opportunity creation to ERP shipment confirmation
- Customer profitability: Salesforce revenue attribution combined with ERP cost of goods sold and service costs
- Forecast accuracy: Salesforce pipeline forecast compared against actual ERP booked orders by period
- Sales rep productivity: Salesforce activity volume correlated with ERP order volume and revenue per rep
Visualization and Self-Service Tooling
Once the combined data model exists, the visualization layer makes it accessible to business users. Tableau CRM (CRM Analytics) embeds directly in Salesforce for rep-facing dashboards. Tableau Desktop or Power BI serves broader audiences including finance, operations, and executive teams who need ERP-heavy views with CRM context overlays.
- CRM Analytics (Tableau CRM) dashboards embedded in Salesforce Account and Opportunity pages for in-context ERP data
- Tableau Desktop workbooks connect to the cloud warehouse for cross-functional dashboards spanning CRM and ERP
- Power BI reports with DirectQuery or Import mode against the shared warehouse serve Microsoft-centric organizations
- Self-service exploration layers with governed data models prevent analysts from misjoining CRM and ERP datasets
- Scheduled snapshot reports deliver weekly pipeline-to-fulfillment summaries to executive stakeholders via email
Want unified visibility across your Salesforce pipeline and ERP operations? Let us design your combined analytics architecture.
Related Resources
Salesforce ERP Integration Architecture Patterns
Design scalable Salesforce-to-ERP integration architectures covering API patterns, middleware selection, and data flow strategies for enterprise CRM-ERP alignment.
ERPSalesforce Order-to-Cash ERP Integration Flow
Streamline order-to-cash processes by integrating Salesforce CPQ and Orders with ERP fulfillment, invoicing, and payment collection workflows.
ERPSalesforce ERP Master Data Synchronization
Synchronize customer, item, and pricing master data between Salesforce CRM and ERP systems with conflict resolution, governance, and real-time sync patterns.