Consumer Packaged Goods (CPG)

Consumer Packaged Goods Optimization & Decision Intelligence

The Consumer Packaged Goods industry operates on thin margins, large SKU portfolios, and constant time pressure. Demand shifts quickly. Promotions collide with capacity. Retailer penalties, service-level agreements, shelf-life limits, and supply disruptions compound risk. Decisions are interdependent and high-consequence.

These are not reporting problems. They are constrained decision problems. Modaai builds optimization-driven decision systems that explicitly model commercial, operational, financial, and physical constraints. The goal is not insight. The goal is defensible decisions that hold under pressure.

Modaai does not deliver dashboards, generic AI, or black-box predictions. We design mathematical decision systems that evaluate trade-offs across revenue, cost, service, and risk—then select the best feasible outcome.


Explicit Definition

Consumer Packaged Goods optimization is the use of mathematical optimization and decision intelligence to select revenue, production, inventory, and supply-chain decisions under real commercial, operational, and regulatory constraints.


Revenue Management & Pricing Optimization

Optimize margin under retailer and promotion constraints.

Applications

  • SKU-level pricing across channels and regions
  • Trade promotion planning (TPR, BOGO, multi-buy)
  • Promotion lift vs. margin trade-off analysis
  • Assortment and pack-size decisions
  • Channel conflict and retailer constraint management

Outcomes

  • Higher realized margin, not modeled margin
  • Reduced promotion leakage
  • Explicit, auditable pricing trade-offs

Sales & Operations Planning (S&OP / IBP)

Align demand, supply, and finance in one decision model.

Applications

  • End-to-end S&OP and IBP optimization
  • Supply allocation under demand surges and promotions
  • Financially constrained planning (revenue, margin, working capital)
  • Disruption and contingency scenario evaluation
  • Feasible what-if analysis across functions

Outcomes

  • Shorter planning cycles
  • Fewer manual overrides and fire drills
  • Executable plans aligned with financial targets

Production Planning & Scheduling

Increase throughput without adding assets.

Applications

  • Multi-plant production planning
  • Line sequencing and changeover minimization
  • Batch sizing and campaign planning
  • Co-packing and make-vs-buy decisions
  • Labor, sanitation, and regulatory constraint modeling

Outcomes

  • Higher asset utilization
  • Lower waste and scrap
  • Improved service with existing capacity

Demand Uncertainty & Forecast Consumption

Plan for variability instead of assuming certainty.

Applications

  • Forecast consumption with uncertainty bounds
  • Promotion-aware demand modeling
  • New product introduction planning
  • Short- vs. long-term forecast reconciliation
  • Inventory positioning under volatility

Outcomes

  • Fewer stockouts and overstocks
  • Lower inventory with equal or better service
  • Plans that hold under demand shocks

Inventory & Network Optimization

Balance replenishment, inventory, and shortfall costs. Place inventory where it provides the most value. 

Applications

  • Multi-echelon inventory optimization
  • Safety stock setting under service targets
  • Distribution network design and flow decisions
  • DC replenishment and deployment rules
  • Obsolete and slow-moving inventory reduction

Outcomes

  • Reduced working capital
  • Higher on-shelf availability
  • Lower write-offs and markdowns

Risk, Resilience & Scenario Planning

Stress-test decisions before the market does.

Applications

  • Supply disruption and capacity loss scenarios
  • Retailer penalty and service-level risk modeling
  • Promotion overlap and demand spike analysis
  • Cost inflation and margin erosion scenarios

Outcomes

  • Fewer surprises during execution
  • Quantified downside risk
  • Clear decision boundaries under stress

Why Modaai

CPG decisions are nonlinear, tightly coupled, and constrained. Modaai builds decision systems that model those constraints explicitly—commercial, operational, physical, and regulatory.

We reject:

  • Black-box prediction without accountability
  • Heuristic-only planning that breaks at scale
  • Dashboard-first systems that explain problems but do not solve them

We deliver optimized decisions with clear economic justification and auditable logic.


Who We Work With


Start with a Focused Pilot

  • Promotion Optimization Pilot: Optimize a defined promotion window across selected SKUs and retailers. Measure margin lift, leakage reduction, and service impact.
  • Constrained S&OP Pilot: Integrate demand, supply, and financial constraints for one business unit. Compare optimized plans against historical overrides.
  • Inventory Positioning Pilot: Optimize safety stock and deployment for a subset of the network. Track working capital reduction and service improvement.