cost to serve
SHAiPE: the LTPlabs framework
Set the Decision
Define commercial priorities
which products, channels, and customer segments to differentiate
Align on strategic priorities amongst commercial, supply chain and finance teams
service level vs. cost to serve
Highlight what matters
Map current baseline and performance gaps
Service level/OTIF, OEE, inventory
Establish ideal cost-to-serve vs. margin by segment
product, segment, market segment
Define constraints
capacity, lead times, MOQs, safety stock rules
Align success metrics
service level, inventory rotation, OEE, cost-to-serve
Augment with AI
Simulate service costs trade-offs across MTS, MTO, and hybrid strategies to prescribe the optimal supply mode per SKU × segment
- DataHistorical demandThroughputs and setupsMarket strategyCurrent inventoryAI ModelResultsExpected OTIF service levelProduction resources usageInventory evolution
Prototype your solution
Run digital-twin tests against historical performance to calibrate
Build a scenario generation interface allowing supply chain leadership to test and validate service/cost trade-offs
Pilot with a subset of segments / channels to real life validation
Expand to scale
Define the implementation plan, with tight control of
Link ERP-like systems to upstream & downstream integration
Train supply chain and commercial teams on the new process
Establish review cadence aligned with S&OP cycles
Monitor KPIs continuously and refine segmentation as market dynamics evolve
What this means for your business
Higher service level (OTIF / fill rate) where it matters most, without increasing the cost to serve
Reduction in working capital by eliminating MTS overstock on low-demand, low-margin SKUs
Supply strategy aligned with commercial segmentation; every service level decision anchored on company strategy
Conteúdo
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