AdaptiveHierarchy™: Custom hierarchical forecasting for real-world demand planning
Define your own demand dimensions at setup, manage master attributes, and pivot forecasts across any combination — then apply top-down, bottom-up, or middle-out adjustments with automatic allocation to the lowest level.
See a demoThe fixed hierarchy problem
Traditional demand planning tools lock teams into a rigid hierarchy (for example: Region → Customer → SKU). When the business needs a different view — like SKU by channel, or demand by plant, or demand by transportation mode — teams export spreadsheets and rebuild logic by hand.
That creates:
- Version conflicts and manual effort (spreadsheet sprawl)
- Inconsistent numbers across teams
- Slow consensus in S&OP/SIOP cycles
AdaptiveHierarchy™ exists to eliminate fixed-hierarchy constraints and let teams plan in the views that match their decisions.
Dimensions, hierarchies, levels, attributes — the language of real demand planning
Most demand planning systems structure data using these core concepts:
Dimensions
The "axes" you plan by (product, customer, location, time)
Hierarchies
How you roll up within a dimension (SKU → family → category)
Levels
The specific tiers within a hierarchy (store, city, region, total)
Attributes
Descriptive fields like brand, lifecycle, facility type, contract tier
Measures
The values you track: sales history, consensus forecast, accuracy
Many solutions rely on planning hierarchies at product, location, and customer levels — useful, but often not enough for how businesses actually operate.
Custom demand dimensions — model sales history the way you sell
DemandPlan lets you define custom demand dimensions at setup, based on what exists in your sales history — not what a legacy tool forces you into.
What did we sell?
SKUs, product groups, product type
Who did we sell it to?
Customer, customer group/family, region
Where did we sell/ship it from?
Plant, DC, terminal, warehouse
How did we deliver it?
Truck, rail, parcel, pickup
How did we sell it?
DTC, wholesale, retail, ecommerce
Who sold it?
Salesperson, sales team, partner
When did we sell it?
Transaction date, fiscal period
Because this is setup-driven, you can also support dimensions unique to your business — like mode of transportation, fulfillment type, incoterms, route, program, or any other sales-history field your planners actually use.
Custom attributes — build the masters you need (and plan with them)
Beyond dimensions, real planning depends on attributes: the fields that help you group, filter, and analyze quickly.
Product master attributes
Brand, category, pack size, lifecycle stage, margin tier
Customer attributes
Segment, contract type, tier, geography
Plant/facility attributes
Site type, capacity band, region, make/buy
Channel attributes
Channel group, program, pricing strategy
Attributes are what make forecasting usable at scale: they let you pivot without building new spreadsheets, and they help teams answer planning questions fast.
Pivot anywhere — plan at the level your decision actually happens
AdaptiveHierarchy™ gives planners the flexibility to view and adjust forecasts across all demand dimensions — at any level, and in any combination.
Instead of forcing a single tree, you can pivot views to match decisions like:
- Product family × region × plant
- Customer group × channel × SKU
- Mode of transportation × DC × category
- Sales team × customer × product line
This is especially important when the same business needs multiple "truths" at once: commercial rollups for finance, customer rollups for sales, and operational rollups for supply chain execution.
Adjust top-down, bottom-up, or middle-out
Hierarchical forecasting exists because businesses need forecasts that make sense at every level (e.g., SKU → category → region → total), not just at the bottom. AdaptiveHierarchy™ supports planning flexibility described as bottom-up, top-down, and middle-out.
Automatic disaggregation (allocation) with pro-rata logic
When you adjust a forecast above the lowest level (for example, increasing a region or product family), DemandPlan uses pro-rata disaggregation — allocating changes proportionally across lower-level demand dimensions based on existing ratios.
Example:
If you increase "North America" demand by 10%, the system distributes that change across SKUs/plants/customers according to their share of the current forecast — keeping your plan consistent everywhere without manual Excel allocation.
Where AdaptiveHierarchy™ helps most
S&OP / SIOP alignment
Reconcile sales inputs, finance targets, and operational constraints faster with shared, coherent views.
Multi-site operations
Plan by plant/DC/warehouse and pivot when constraints change — without rebuilding spreadsheets.
Customer-specific planning
Manage key-account changes without breaking the global plan. Drill into customer × product instantly.
Scenario planning
Compare baselines, ML scenarios, and consensus versions in one platform with full traceability.
Adaptive vs fixed hierarchy
| Capability | Fixed hierarchy tools | AdaptiveHierarchy™ |
|---|---|---|
| Custom dimensions at setup | Limited / template-driven | Yes — align to sales history fields |
| Pivot across multiple dimensions | Often spreadsheet export | Pivot and plan dynamically |
| Adjust at any level | Possible, but painful | Designed for top/middle/bottom workflows |
| Allocation/disaggregation | Manual or rigid rules | Pro-rata disaggregation for coherent plans |
| Collaboration + auditability | Bolted on | Built-in collaboration + audit trail |
Frequently asked questions
Ready to plan without rigid hierarchies?
See AdaptiveHierarchy™ in action and build a demand plan that matches your business — not a vendor's template.
Schedule a demo