Prescriptive Optimization for FP&A and Manufacturing Planning — deFacto Global

How dF-Prescribe Mix works

A manufacturing finance team stages their plan — products, capacity constraints, labor limits, and objectives — in the deFacto model. dF-Prescribe Mix optimizes the product mix under those constraints, evaluating the trade-off between labor utilization, contribution margin, and bottleneck resources. The result is reviewed against P&L impact and key production KPIs. When the result meets the review criteria, it writes a new deFacto scenario that the finance and operations teams can evaluate side by side against the existing plan.

The solver behind this loop is swappable via a proprietary universal solver interface. The open-source path uses PuLP with CBC, which has been tested on standard product-mix problems and returns results in fractions of a second at that scale. For larger or more complex problems, the adapter connects to commercial solvers. The planning system of record — deFacto — is the constant; the solver is the interchangeable engine.

This is appropriate for manufacturing finance teams that want to explore constrained product-mix planning before committing to a commercial solver license.

The optimization loop: stage, optimize, review, write back

dF-Prescribe Mix runs four steps: Optimize (product mix under capacity), Review (P&L impact, labor KPIs, bottleneck analysis, plan shape), Prescribe (confirm the result is acceptable and suggest as a solution in a new scenario), Writeback (write the optimized mix as a new deFacto scenario, consumed by Excel and Power BI). The review step is manual — finance approves the result before it becomes a scenario. This keeps the planner in control of what enters the plan.

The solver is swappable — pick the cheapest engine that fits

The solver adapter decouples the solver from the planning system. Open-source PuLP with CBC is proven on standard product-mix scale at no license cost. HiGHS and OR-Tools are additional open-source options. Commercial solver licenses are available through partnerships: Gurobi is often cited at $10,000–$50,000+ per year; IBM CPLEX from approximately $3,400 per year for a single-user license; D-Wave Hybrid Quantum for specialty and complex problems. The correct choice is the cheapest solver that returns a feasible and better answer inside the decision window (effectively real-time) — not the most powerful one available.

From manual what-if to automated scenario generation

Most FP&A teams build scenarios by hand — adjust one variable, test the outcome, save the version, start again. That works for three or four variations. It does not work when the decision space is large.

dF-Prescribe Mix changes the approach. Given defined objectives (maximize contribution margin, minimize cost, balance utilization) and a set of constraints (labor capacity, raw material availability, production line limits), the solver generates a large number of feasible product mixes and surfaces the one that best satisfies the objectives. The result is not a spreadsheet to hand to a supply chain analyst — it is a new deFacto scenario, grounded in the same actuals and budget the rest of the finance team works from, ready to compare and present.

Manufacturing finance teams evaluating questions like “what production mix maximizes revenue given current capacity?” or “what happens to margin if we prioritize Product A over Product B through the bottleneck?” no longer need to build each variant by hand. The solver explores the space; the planner picks the scenario that fits the business context; deFacto writes it back as the plan. The Planning System of Record is the constant; the solver is the analytical engine that extends it.

What is in scope: constrained product mix and RCCP

The current capability handles constrained product mix and rough-cut capacity planning (RCCP) — given available labor (hard and soft constraints), objectives (minimize cost, maximize contribution, balance utilization), and a set of products, find the feasible mix. Inventory network optimization, detailed production scheduling, and multi-echelon supply chain planning are outside the current scope. This page answers FP&A-qualified optimization questions, not supply chain network design.

Operational planning scores: Vena leads this axis

In the mid-market peer table, deFacto scores 4.60 on operational planning, compared to Vena at 4.70 and Planful at 4.45. (Source: BPM Partners Vendor Landscape Matrix, July 2025.) This is an honest disclosure: Vena leads on operational planning in the peer table. The prescriptive optimization capability described on this page is targeted at manufacturing finance teams with product-mix planning needs — a narrower problem than general operational planning breadth.

Where prescriptive optimization fits in the deFacto model

Prescriptive optimization sits at the top of the scenario planning stack. Scenario planning covers Class A what-if — Goal Seek and Solver write-back — which is available in general production use today. dF-Prescribe Mix extends that into constrained product-mix optimization for manufacturing finance teams. dF Foresight handles statistical time-series forecasting separately.

See also: AI planning software hub · Compare optimization platforms · Compare to Anaplan · Compare to Pigment