Pricing & revenue under capacity and trust constraints.
The problem.
Pricing decisions are made under four simultaneous pressures — projected demand, contribution margin, inventory position, and the price commitments customers already saw last week. Move any of the four in isolation and one of the others breaks.
Most pricing systems chase the first signal and recover from the third. The plan that arrives on Monday solves yesterday's demand under last quarter's margin guidance, with the inventory adjustment bolted on by hand.
The shape of the decision.
Variables: prices per SKU per channel per period. Constraints: margin floors · inventory caps · price-change frequency rules · promotional commitments. Objectives: contribution · sell-through · trust signal.
How Alpha Z helps.
We frame the pricing question as one optimization program — demand, margin, inventory, and trust are all in the same formulation, not in four spreadsheets. The algorithm returns the surface that is provably optimal under the rules the team set.
Each price change comes with the binding constraint and the marginal value of relaxing it. The team learns where the rules are actually costing them — the formulation becomes the conversation.