25%
in warehouse operation costs
SHAiPE: the LTPlabs framework
Set the Decision
Define the flow objective
throughput, service, waiting time, productivity
Clarify the decision level
site, area, queue, service point, route, shift
Set the redesign scope
layout, routing, staffing, capacity, service-point configuration
Highlight what matters
Align on strategic metrics
throughput, wait time, congestion, utilization, labor productivity
Map the current operation and flow
people, materials, queues, bottlenecks, decoupling points
Define business and operational constraints
space, labor, equipment, safety, service rules, workload patterns
Augment with AI
Combine flow, demand, and operational data to build a digital twin and simulate and optimize the best layout, routing, and resource configuration
Prescribe the setup that delivers the best trade-off across throughput, service, productivity, and operational feasibility
- DataHistorical demandHistorical workloadWorkforce availabilityOperational constraintsAI ModelSimulationDigital TwinOptimizationResultsBest configurationsCapacity / staffing levelsExpected impact
Prototype your solution
Deliver a digital twin and optimization engine to compare scenarios and test alternatives
Run a practical pilot to evaluate recommendations in a real operating setting
Expand to scale
Plan the implementation of the proposed solution, that can vary from short-term micro-layout adjustments to a strategic transformational operational roadmap
Establish governance and monitoring metrics to follow up on the success of the recommendations, triggering eventual needs for an adjustment of the initial proposal (due to conditions update)
Nutshell
What this means for your business
6x
faster to generate and evaluate layout and flow scenarios
Higher throughput through flow decisions adapted to physical constrains
Lower congestion, waiting times, and movement waste across operations
Better productivity and resource utilization by layout and staffing optimization
Scalable decisions that adapt to sites, markets, and operating contexts
InsightsConteúdo
Conteúdo
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