Gemini Query: Imagine a milp model of the income state with MMM data, response functions, embedded to relax the model’s assumption of a fixed forecast. Further, these response functions have been linearized with steps of fixed and variable costs. Finally, quarter’s actual results were compared with the forecast as a variance analysis. Finally, those response functions involved with important variations were updated by recomputing them. Confirm the result is a new income statement including the most profit possible.
Yes, confirmed. The result of re-optimizing this setup is a revised, actionable income statement that yields the maximum mathematically achievable net profit given the updated real-world response curves and constraints.
Here is a breakdown of why this exact architecture succeeds:
How the Architecture Delivers Maximum Profit
- Relaxing Fixed Assumptions
Traditional financial planning relies on static revenue forecasts. By embedding Media Mix Modeling (MMM) response functions directly into the optimization engine, revenue becomes a dynamic variable driven by marketing investments and operational leverage rather than a fixed assumption.
- Mixed-Integer Linear Programming (MILP) Precision
Marketing response curves (like ad spend saturation) and cost structures are non-linear. By linearizing these into piecewise functions and step-fixed/variable cost steps using binary (0-1) decision variables in a MILP model:
- Diminishing returns are respected (avoiding over-spending where ad channels saturate).
- Threshold costs (such as fixed platform fees, campaign setup costs, or production shifts) are only triggered when economic benefit justifies them.
- Closed-Loop Variance Learning
When actual quarter results depart from projections, updating the underlying response functions acts as a feedback loop. Re-running the MILP model with updated response curves ensures the next period’s budget allocation and income statement reflect true market elasticity, re-optimizing resource allocation to capture the highest possible profit margin.
The Key Distinction: The MILP guarantees the global optimal solution for the mathematical model provided. The closer your recalibrated MMM response functions match true market dynamics, the closer your income statement comes to maximum actual profit in practice.
An additional benefit for discontinuing the budget.
Budgets generically have a variety of objectives. So, developing an OIS-based plan in Phase II to address them is an essential part of preparing for Phase III’s implementation. As a perspective, AccountingTools cites seven. Here is a generic mapping of OIS’s functionality to address the seven. Importantly, it enhances them all.
Finally, for other financial opportunities of possible interest to the CFO/CEO during Phase II: See”Additional OIS advantages for client’s CFO/CEO.”