PCA Product Cost Analytics
Data classification: GM_Confidential
Domain: Finance Data Engineering — Product Cost Analytics
Application / data product context: Finance360 Product Cost Analytics (workflow family 42124)
Primary business capability: Product cost, material performance, mix variance, build volume, and VIN-level cost analytics
Catalog schema: finance_prod.gold_product_cost
Overview
PCA (Product Cost Analytics) is GM Finance's product cost intelligence foundation for understanding how vehicle and powertrain costs vary by organization, market, brand, model, material, supplier context, and time period. It harmonizes planning, actual, and analytical cost sources into curated gold tables and dashboard-ready materialized views so Finance, FPA, GPSC, product cost, and engineering cost teams can compare reported costs, investigate material drivers, and support sourcing and forecasting decisions.
PCA is designed to answer practical product-cost questions such as:
- How do total reported product costs compare period over period by organization, country of sales, brand, and model?
- How do GL, CPURAM, and EGPPS views of material cost align, and where are the largest reconciliation gaps?
- Which materials or part families drive the biggest changes in product cost or material performance?
- How do mix, volume, and variance effects explain movement in product cost summaries?
- What do build volume, sold-vehicle, and VIN bill-of-material detail show for a given cost period or product configuration?
- How can analysts move from an executive dashboard view to part-level or VIN-level investigation without rebuilding logic?
At a business level, PCA supports the Finance360 Product Cost Analytics dashboard suite, including total reported product cost comparison, material cost comparison, material performance, mix analysis, and detailed VPPS-level cost views. Phase 2 work extends the footprint toward a unified PCA Superset that brings CPURAM, PIM, and purchasing analytics into common vehicle and powertrain views.
Key benefits
Product cost is a primary driver of vehicle profitability and sourcing decisions. Cost signals are spread across Hyperion planning extracts, CPURAM material views, general-ledger and FinCore detail, build-volume sources, and bill-of-material structures. PCA reduces that fragmentation by publishing repeatable gold summaries and pca_-prefixed materialized views for dashboard consumption.
For business users, PCA makes product cost easier to compare across systems, regions, and product hierarchies. For data engineers, it provides a governed Finance360 pipeline family with DAVE data-quality checks, incremental gold loads, and clear separation between foundational materialized views and business aggregate tables.
The most common business themes are:
| Theme | Typical questions |
|---|---|
| Reported product cost | How do total reported product costs compare by period, organization, and product? |
| Source alignment | How do EGPPS, CPURAM, and GL/FinCore material costs compare for the same scope? |
| Material performance | Which materials or components explain the largest cost movement or price performance? |
| Mix and variance | How do volume, mix, and variance drive changes in product cost? |
| Build and sold volume | How many vehicles were built or sold in scope, and how does that affect cost analysis? |
| VIN and BOM detail | What parts and costs attach to a VIN or vehicle configuration for deep dives? |
Who uses it
| Team / persona | How they use PCA |
|---|---|
| FPA and product cost analytics | Executive dashboards, period-over-period comparisons, and cost-bridge analysis |
| GPSC and sourcing / material teams | Material performance, supplier/part context, and contract-change analysis |
| Manufacturing and engineering cost teams | Build volume, BOM, powertrain, and vehicle-part investigations |
| Finance leadership | High-level reported cost and mix views in Finance360 review cycles |
Core business scope
PCA organizes product cost analytics around cost reporting subjects rather than raw source exports.
| Subject | What it captures |
|---|---|
| Product and organization | Marketing division, brand, model, product hierarchy, sales location, and organization rollups |
| Reported product cost | Summary-level reported costs from planning and reporting sources used in Dashboard 1-style comparisons |
| Material cost comparison | Cross-system material cost alignment across EGPPS, CPURAM, and GL/FinCore contexts |
| Material performance | Material and part-level performance summaries and detail for price/cost driver analysis |
| Mix and variance | Mix, volume, and variance explanations at summary and analytical grains |
| Build and sold vehicles | Build volume and sold-vehicle facts that anchor volume-driven cost analysis |
| VIN and BOM | VIN bill-of-material and vehicle-part detail for configuration-level investigations |
| Powertrain and profitability extensions | Powertrain component detail and product profitability summaries where published |
| Standard cost and VPPS detail | Material standard cost and VPPS-level cost breakdowns for detailed cost walks |
PCA supports global and regional analysis, but many dashboard filters assume explicit organization, sales location, brand, and period context. Keep those filters visible when comparing dashboard totals to ad-hoc SQL results.
Source systems by business subject
PCA combines planning, profitability, vehicle, and ledger-aligned sources into Finance360 gold tables and materialized views.
| Subject area | Key source patterns |
|---|---|
| EGPPS / planning extracts | Hyperion EGPPS-style planning data for reported product cost summaries and forecast/actual version filtering |
| CPURAM | Material performance, supplement cost, and CPURAM-aligned analytical feeds |
| GL / FinCore | Ledger-aligned product cost detail for GL and FinCore comparison dashboards |
| Vehicle identity and options | Vehicle360 and VOIC-style vehicle configuration inputs for build volume and BOM context |
| Sold vehicles and revenue cost | Sold-vehicle and vehicle revenue/cost detail used in downstream gold facts |
| Currency and reporting reference | Currency conversion and reporting-zone reference data for USD reporting views |
| BOM and part master | Bill-of-material and vehicle/part structures supporting VIN- and part-level analysis |
Phase 2 roadmap work extends PCA with a Superset layer that unifies CPURAM, PIM, and purchasing analytics into shared vehicle and powertrain views for additional dashboards and future agent-assisted analysis.
Business measures and rules
PCA reporting spans summary, comparison, and detail grains. Users should confirm which grain and source family applies before comparing totals.
| Measure / rule | Business meaning |
|---|---|
| Reported product cost | Planning/reporting-aligned product cost totals used in executive comparison dashboards |
| Material cost (CPURAM / EGPPS / GL) | Different source families answer alignment questions; do not assume they reconcile without filters |
| Mix / variance amounts | Volume, mix, and variance style measures in mix analysis summaries |
| Build volume | Vehicle build counts used to contextualize cost and mix movement |
| Sold vehicle detail | Sold-vehicle facts used for period, location, and product-scoped cost analysis |
| VIN BOM detail | Part-level bill-of-material amounts tied to VIN or configuration investigations |
| Forecast vs actual version | EGPPS-style dashboards often filter to latest archived or approved planning versions |
Many PCA pipelines apply effective-date, vehicle-category, currency, and version filters in materialized-view logic. Confirm dashboard period, currency, organization, and version context before comparing totals across dashboards or SQL extracts.
Reporting and analytics interfaces
PCA is exposed through Finance360 dashboard experiences backed by gold tables and materialized views.
| Interface | View of the data | Primary use cases |
|---|---|---|
| Dashboard 1 — Total Reported Product Costs Comparison | Aggregated reported cost comparison | Executive period-over-period product cost review |
| Dashboard 2 — Material Cost Comparison | EGPPS vs CPURAM vs GL/FinCore alignment | Source reconciliation and material cost bridges |
| Dashboard 3 — Material Performance | Material performance summaries and detail | Material driver and price performance analysis |
| Dashboard 4 — Detailed Product Costs (VPPS L1–L3) | VPPS-level cost breakdown | Detailed cost walk by VPPS hierarchy |
| Dashboard 5+ / Phase 2 views | Mix, build volume, profitability, and Superset experiences | Deeper analytical and unified product-cost views |
Databricks materialized views (pca_*) | Dashboard-ready aggregates over curated base MVs | Repeatable semantic consumption and refresh orchestration |
| Databricks gold tables | Persisted detail and summary tables for engineering and controlled exploration | Reconciliation, DQ review, and advanced analysis |
| Finance360 / Genie (roadmap) | Conversational analytics over integrated PCA assets | Future self-service and agent-assisted cost analysis |
Common published gold objects include product_cost_summary, mix_variance_cost_summary, material_performance_summary, material_performance_detail, material_cost_comparison_summary, vin_bill_of_material_detail, sold_vehicle_detail, and vehicle_build_volume_detail.
Finance360 relationship
PCA is a first-class Finance360 application within the Future of Finance and product cost analytics portfolio. It is not only a technical schema; it is an governed analytics product with executive dashboards, materialized-view orchestration, and an active Phase 2 roadmap.
For PCA, Finance360 is relevant in four ways:
- It provides the business entry point for product cost dashboards and Finance360 access workflows.
- It hosts the
gold_product_costcatalog assets andpca_materialized views used by dashboard refresh jobs. - It aligns product cost modernization with CPURAM, planning, and purchasing initiatives through the PCA Superset program.
- It shares engineering, DQ, and release standards with other Finance360 applications in the
360Fin_230337_fin360ecosystem.
Downstream consumers
| Consumer | How PCA contributes |
|---|---|
| Product Cost Analytics dashboards | Primary business consumption of pca_* materialized views and summary gold tables |
| FPA / GPSC analytics | Material performance, comparison, and mix analysis for cost management |
| CPURAM-aligned analytics | Shared material and profitability context through CPURAM-source MVs |
| Finance Data Engineering operations | Incremental loads, DAVE checks, ETL control, and Phase 2 Superset delivery |
| Future PCA agent / Genie experiences | Integrated cost context for conversational analytics over governed gold assets |
Security and access model
PCA uses Finance360 and Databricks governance patterns aligned to finance cost data. Access should follow least privilege by dashboard role and environment.
| Access pattern | Intended audience | Typical capability |
|---|---|---|
| PCA dashboard consumer | FPA, GPSC, and finance cost reviewers | View approved Product Cost Analytics dashboards |
| PCA power user | Experienced cost analysts | Broader dashboard and controlled semantic exploration |
| Engineering / DQ user | Finance Data Engineering and support teams | Pipeline monitoring, DAVE results review, and table validation |
| Direct query access | Approved technical users | Controlled query access to finance_prod.gold_product_cost in approved environments |
Getting access
Report access starts from the Finance360 access page.
- Open
https://gmone.gm.com/programs/finance/global/en/gm/home/finance360-get-access.html. - For What Do You Need Access To?, select Product Cost Analytics or the relevant PCA dashboard experience.
- Select the dashboard or report of interest.
- Follow the displayed steps to continue to the required myGMAccess request.
- Provide a business justification that explains the product cost analysis or reporting work being performed.
- After approval, validate access in the target dashboard or approved Databricks workspace.
For current business, Finance IT, and Finance Data Engineering support contacts, use the PCA Collaboration Folder on the FoF Program Integration SharePoint site, Product Cost Analytics architecture materials, and current operating pages in the 360Fin_230337_fin360 repository.
Where the data lives
The primary Databricks gold serving layer is:
finance_prod.gold_product_cost
BOM- and vehicle-configuration-oriented analysis may also use:
finance_prod.gold_product_cost_bom_gbl
Business users should usually start with the approved Product Cost Analytics dashboards or governed materialized views before moving to direct-query or lower-level delta tables.
For technical users, finance_prod.gold_product_cost is the best production starting point for curated PCA analysis. Use pca_* materialized views for dashboard-aligned questions and gold detail tables for reconciliation or pipeline investigations.
Popular tables and views
These objects are useful to recognize when getting started. They are listed for orientation, not as a complete schema guide.
| Object | What it is used for |
|---|---|
pca_product_cost_summary_mv | Dashboard-ready reported product cost comparison aggregates |
pca_material_cost_egpps_cpuram_comparison_mv | Cross-source material cost comparison for alignment dashboards |
pca_material_performance_analysis_mv | Material performance analysis feeding performance dashboards |
pca_mix_analysis_mv | Mix and variance style aggregates for analytical dashboards |
pca_vehicle_build_volume_mv | Build volume base materialized view for volume-context analysis |
pca_vin_bom_mv | VIN bill-of-material base materialized view for BOM investigations |
pca_gl_sold_vehicles_mv | Sold-vehicle base materialized view for sold-unit analysis |
product_cost_summary | Persisted product cost summary gold table |
mix_variance_cost_summary | Mix and variance summary analysis |
material_performance_summary | Material performance summary reporting |
material_performance_detail | Detailed material performance investigations |
material_performance_part_level_cost_summary | Part-level material performance cost summaries |
material_cost_comparison_summary | Persisted material cost comparison summaries |
material_standard_cost_detail | Standard cost detail for VPPS and cost walks |
vin_bill_of_material_detail | VIN-level BOM detail for configuration analysis |
sold_vehicle_detail | Sold-vehicle detail for period and location scoped analysis |
vehicle_build_volume_detail | Build volume detail supporting volume-based cost views |
vehicle_part_detail | Vehicle part detail for part-level investigations |
powertrain_component_detail | Powertrain component cost detail |
product_profitability_summary | Product profitability summary where published for Phase 2 views |
Practical guidance for engineers
- Start with the dashboard or
pca_*materialized view that matches the business question before querying base gold tables. - Use
pca_product_cost_summary_mvorproduct_cost_summaryfor reported product cost comparison questions. - Use
pca_material_cost_egpps_cpuram_comparison_mvormaterial_cost_comparison_summarywhen the question spans EGPPS, CPURAM, and GL/FinCore alignment. - Use
material_performance_summaryormaterial_performance_detailfor material driver analysis. - Use
mix_variance_cost_summaryorpca_mix_analysis_mvfor mix and variance investigations. - Use
vin_bill_of_material_detailorpca_vin_bom_mvwhen the question requires VIN/part configuration detail. - Use
vehicle_build_volume_detailandsold_vehicle_detailto anchor volume and sold-unit context. - Confirm period, currency, organization, and version filters before comparing dashboard totals to SQL results.
- Use lower-level delta tables and source-aligned views only when investigating pipeline logic, DQ failures, or reconciliation.
Product cost glossary
| Term | Meaning |
|---|---|
| PCA | Product Cost Analytics — Finance360 product cost reporting and analysis program |
| EGPPS | Planning and profitability extract family used in reported product cost views |
| CPURAM | Cost/profitability analytics source used for material performance and comparisons |
| VPPS | Vehicle Product Profitability Structure — hierarchical cost breakdown used in detailed dashboards |
| VOIC | Vehicle of interest configuration context used in BOM and vehicle views |
| Mix / variance | Combined volume, mix, and variance explanation of product cost movement |
| PCA Superset | Phase 2 unified dataset combining CPURAM, PIM, and purchasing analytics |
pca_ prefix | Domain naming standard for PCA materialized views in gold_product_cost |
Data refresh cadence
PCA dashboard materialized views and gold tables refresh on orchestrated Databricks schedules tied to upstream source readiness. Dashboard families do not all refresh at identical times; material-cost comparison and product-cost summary chains may depend on earlier base MVs completing successfully.
Before using PCA totals for a formal business review, confirm the latest successful job run for the relevant 42124-edw-*-fin-pca-* workflow and review DAVE results when available. This is especially important during migrations from legacy catalog names to finance_prod.gold_product_cost.
Getting started path
Work through these steps to become productive with PCA:
- Read the business overview, core scope, measures, interfaces, and access sections in this document.
- Review Product Cost Analytics architecture and dashboard materials in the PCA Collaboration Folder.
- Confirm the needed interface: executive comparison, material comparison, material performance, mix analysis, or detail/BOM views.
- Request access through myGMAccess using the appropriate Finance360 Product Cost Analytics role.
- Start with Dashboard 1 or the matching
pca_*materialized view before writing custom SQL. - Validate period, currency, organization, and version filters when comparing periods or systems.
- Move into lower-level gold tables or source-aligned views only when investigating reconciliation, DQ results, or pipeline behavior.
Architecture diagrams (Lucid)
| Diagram | Purpose | Link |
|---|---|---|
| Finance360 — MOR and PCA Overview | How MOR and PCA fit under Finance360 and shared sources | Edit in Lucid · View |
| PCA — Product Cost Analytics Data Flow | Dashboard → MVs → gold tables → sources (incl. Phase 2 Superset) | Edit in Lucid · View |
Reference links
| Resource | URL |
|---|---|
| Finance360 | https://finance360.gm.com |
| Finance360 access | https://gmone.gm.com/programs/finance/global/en/gm/home/finance360-get-access.html |
| PCA Collaboration Folder (SharePoint) | FoF Program Integration — PCA Collaboration Folder |
| Databricks gold schema | finance_prod.gold_product_cost |
| BOM gold schema | finance_prod.gold_product_cost_bom_gbl |
| Finance360 GitHub repo | GeneralMotors-IT/360Fin_230337_fin360 |
| Product Cost Analytics architecture (internal) | GM_FIN_360 Logical Architecture — Product Cost Analytics materials |