Six Layers. One Source of Truth.
The Guidance engine is organized into six sequential layers. Each layer takes the output of the previous one as its input. The result is a single, continuously updated number for every metric that matters — from raw ingredient cost to net margin per unit sold on Amazon after all fees, deductions, and trade spend.
Raw Data In. Clean Data Out.
Before any math can happen, the data has to be clean. Guidance ingests supplier invoices, distributor remittance files, production records, and sales data — and normalizes all of it into a unified internal format.
This includes resolving the hardest normalization problem in CPG: distributor deduction codes. UNFI, KeHE, and every other distributor uses a different taxonomy for deductions (spoils, MCB, OI, EDLC, scan-backs). Guidance maps all of them to a universal deduction taxonomy so that every deduction is categorized, tracked, and attributed to the correct SKU and promotion.
Every Ingredient. Every Overhead. One Landed Cost.
The cost foundation layer calculates the true landed cost of every ingredient and packaging component — not just the invoice price, but the full cost including freight, duty, tariffs, and any applicable Section 301 surcharges.
Costs are tracked at the lot level, which means when the same ingredient arrives at different prices across different purchase orders, Guidance knows which lot was used in which production run and applies the correct cost to each batch — not an average.
One Price Change. Instant Update Across Every SKU.
This is Guidance's core differentiator. When a supplier raises the price of an ingredient, the change propagates automatically through every BOM that uses that ingredient, recalculating the COGS for every affected SKU in real time.
No manual updates. No "I'll fix the spreadsheet later." No discovering three months after the fact that your margins were wrong because you forgot to update the BOM for the reformulated version of your top SKU.
The propagation engine also handles multi-level BOMs — if a sub-assembly uses an ingredient that changed price, the cost change flows through the sub-assembly and up to the finished good automatically.
COGS That Reflects What Actually Happened in Production.
Standard COGS calculations use standard costs — what you expected to spend. Guidance calculates actual COGS at the lot level — what you actually spent, accounting for yield variance, rework, waste, and any production deviations.
If your production yield was 94% instead of the expected 97%, Guidance knows. The COGS for that lot reflects the actual yield, not the theoretical one. Over time, the system learns your typical yield ranges and flags deviations that suggest a process problem or a supplier quality issue.
True Net Margin. Per SKU. Per Channel. After Everything.
COGS is only half the picture. What a brand actually keeps depends on which channel the product was sold through. A unit sold through UNFI has a completely different net margin than the same unit sold DTC or on Amazon — because each channel has its own deductions, fees, freight costs, and promotional allowances.
Guidance calculates true net margin for every SKU in every channel simultaneously. UNFI deductions (spoils, MCB, OI) are categorized and deducted. Amazon referral fees, FBA fees, and advertising costs are applied. DTC payment processing, shipping, and return rates are factored in. The result is a single, accurate net margin number for each channel — not an estimate.
Every Number Comes With a Grade.
Every calculation in Guidance carries a Confidence Score — a grade from 0 to 100 that tells you how much to trust the number. A COGS figure based on a confirmed supplier invoice, an actual production record, and a reconciled distributor remittance gets a high confidence score. A COGS figure based on a 90-day-old price estimate gets a low one.
This matters because in CPG, you are always making decisions with incomplete data. The Confidence Score tells you which numbers are solid and which ones need to be updated before you make a pricing or channel allocation decision.
The optimization layer uses the confidence-scored data to surface actionable insights: which SKUs have deteriorating margins, which channels are underperforming relative to their cost structure, and where a price increase or channel reallocation would have the highest impact.