Dynamic Pricing Optimization in Tier-1 A&D Supply Chain
Customer:
Leading Tier-1 Aerospace & Defense organization.

Business Challenge:
The customer manages a catalog of over 2 million unique parts. To streamline inventory and improve efficiency, the organization needed to:
- Identify and replace redundant or obsolete parts
- Offer removed items for external purchase with optimized pricing
- Maintain sales volume while increasing margins
Manually pricing and planning at this scale was unsustainable, and static models failed to capture the complexity of real-world demand.
ESI LABS Objective:
Develop a system that could generate more profitable price lists without reducing overall sales volume.

Solution Delivered:
- ESI LABS deployed a rule-driven dynamic pricing engine built on:
- A proprietary optimization algorithm incorporating hundreds of operational, market, and item-specific parameters
- Business rules that mapped item relationships, substitution logic, and catalog constraints
- An adaptive pricing model that aligned profit targets with acceptable volume trade-offs
The solution integrated seamlessly into existing planning systems and could simulate various price elasticity and catalog scenarios.
Implementation Timeline:
- 6 months: System design, modeling, and rollout
- 6 months: Tuning and refining pricing models for full-scale operations
Results Achieved:
7%
Average item prices increased by 7%
2%
Sales volume decreased by just 2%
4%
Overall profit increased by 4%
Conclusion:
The dynamic pricing engine delivered a 7% price uplift with minimal volume impact, driving a 4% profit increase and transforming pricing into a scalable, data-driven advantage.
Director of Supply Chain Optimization, Tier-1 A&D Organization
Our catalog pricing was historically complex, and we lacked the tools to optimize it at scale.
ESI LABS delivered a pricing engine that didn’t just automate the process—it made it smarter.
We increased average prices by 7% while keeping volume impact to a minimum.
Profitability is up, and we now have a system that adapts to changes instead of chasing them.
Their combination of rule logic and optimization algorithms was exactly what we needed—and they delivered it in under a year.
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