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Allocations spread a pool of values (typically cost, but it works for any aggregate) across consumers based on a measurable driver. They answer the question: if we incur this cost, how should it be assigned to the things that consume it?

You know your total marketing spend for a quarter. You want to attribute it to specific products based on something measurable — campaign hours, leads generated, qualified opportunities. An allocation spreads the marketing pool across products using your chosen driver, giving each product a fully-loaded cost.

You spend $X running shared infrastructure (compute, storage, licensing). Each business unit consumes a different amount. An allocation spreads the IT cost across units based on usage metrics — VM hours, storage GB, license seats — so each unit’s P&L reflects what it actually consumed.

Finance, HR, legal, facilities — central functions that serve the whole company. Allocations distribute their cost across the divisions they serve, typically by headcount, revenue, or a weighted blend.

For multi-entity organizations, allocations model how internal services are priced between entities. The output drives intercompany journal entries.

You have revenue at the product or customer level. You have costs at various pools (sales, support, infrastructure, COGS). Allocations bring everything together at the product/customer grain so you can see actual margin.

Cost flows down a hierarchy of components. Each step in the BoM is an allocation: subassembly costs spread to assemblies, assemblies to finished goods, finished goods to SKUs.

Without an allocation engine, you’d build these models in spreadsheets — fragile, hard to audit, hard to repeat with updated data. PlaidCloud allocations give you:

  • Reproducible models that re-run automatically as source data refreshes
  • Audit trail showing which source rows contributed to which target rows
  • Layered allocations where outputs feed further allocations
  • Dimensional integration so allocations respect your existing hierarchies