Centralize every product attribute, hierarchy, supplier relationship, and lifecycle state into one governed Data Vault. Clean, structured product data is the foundation that makes AI forecasting and planning accurate.
This feature is part of the ForecastWorx connected planning platform — an AI-native system where demand forecasting, inventory optimization, replenishment automation, and supply planning share the same data layer and work together in real time. Every capability described below is designed to reduce manual effort, improve decision quality, and deliver measurable business outcomes for planning teams across retail, wholesale, CPG, and manufacturing.
Perspectives
When item data is clean and structured, forecasts are explainable and exceptions are meaningful.
One authoritative record per product — SKUs, UPCs, descriptions, dimensions, weights, units of measure, and pack configurations — synced from your ERP, ecommerce, and WMS systems.
Model your business the way you plan it: department, class, subclass, style, color, size — with support for multiple parallel hierarchies for merchandising, financial, and supply views.
Define custom attributes — seasonality flags, lifecycle stage, brand, vendor, country of origin — and enrich items in bulk with validation rules that keep data clean.
Track supplier relationships, lead times, MOQs, cost tiers, and landed cost components per item — the inputs your replenishment engine depends on.
Govern items through new, active, seasonal, declining, and discontinued states. Lifecycle transitions automatically inform forecasting model selection and replenishment behavior.
Every item receives a completeness and quality score. Exceptions surface missing attributes, conflicting values, and stale records before they distort forecasts.
Link new products to predecessor or comparable items so demand history transfers cleanly — critical for accurate new-item forecasting.
Map one master item to channel-specific identifiers across Shopify, marketplaces, wholesale, and retail — so demand aggregates correctly at the item-location level.
Every attribute change is versioned with who, what, and when. Role-based permissions control who can edit which attribute groups.
Step 01
ForecastWorx connects to your ERP, ecommerce platform, and spreadsheets, ingesting product records from every system into the Data Vault staging layer.
Step 02
Records are matched across systems using SKUs, UPCs, and fuzzy matching. Duplicates are merged into a single golden record per product.
Step 03
Validation rules flag missing or conflicting attributes. Bulk enrichment tools and AI-assisted suggestions fill gaps quickly.
Step 04
Items are placed into planning hierarchies, assigned lifecycle states, linked to suppliers and costs, and mapped to locations and channels.
Step 05
Clean, governed product data flows directly into demand forecasting, inventory optimization, and replenishment — no exports, no sync jobs, no drift.
PIM is the Data Vault layer of ForecastWorx — a centralized, governed repository for all product data: attributes, hierarchies, suppliers, costs, lifecycle states, and channel mappings. It ensures the planning engine works from clean, consistent, complete product data.
Standalone PIM tools focus on marketing content syndication. ForecastWorx PIM is planning-native: it structures product data specifically to power demand forecasting, inventory optimization, and replenishment — lifecycle states, like-item links, lead times, and hierarchies that planning actually uses.
ForecastWorx ingests product data from ERPs (NetSuite, Acumatica, Sage, Odoo), ecommerce platforms (Shopify), warehouse systems (ShipHero), spreadsheets, and custom sources via the REST API.
Forecasting is only as good as its inputs. Clean hierarchies enable correct aggregation, lifecycle states select the right models, like-item links give new products usable history, and validated attributes prevent garbage-in-garbage-out errors.
Yes. ForecastWorx supports parallel hierarchies — merchandising, financial, and supply views — so each team plans in the structure that matches their workflow while sharing one item master.
Every item is scored on completeness, consistency, and freshness. Items below threshold surface as exceptions with specific missing or conflicting attributes flagged, so teams fix the highest-impact gaps first.
Book a demo and see how the ForecastWorx Data Vault centralizes, validates, and structures your product information for AI-powered planning.
"In supply chain, the companies that see demand before it arrives will be the ones that survive."— MIT Sloan Management Review