Inventory Simulation


While Inventory Optimization selects the mathematically optimal inventory levels, Inventory Simulation demonstrates “How” the inventory levels and policies will perform in the “real world” given real demand and supply variability.

Business Problem

Are you experiencing these business challenges?  Do these questions sound familiar?

Common Business Challenges

Optimized inventory levels not generating expected service performance
Demand or supply distribution not reflective of real variability
Highly volatile demand or seasonality
Extended and variable supplier lead times
Erratic fluctuations in inventory levels
Inconsistent or low fill rates and increasing stock-outs

Key Questions for Consideration

Do the projected service levels resulting from an inventory optimization appear overly optimistic?  Are you achieving the desired service levels?
How does the simulation compare when I model actual historic demand (order history) compared to calculated demand variability?
What impact does fulfillment or transportation lead time variability have on my fill rate or service level?
What are my peaks and troughs in inventory levels?  When do they occur?

Service Solution

Supply Chain Acuity’s Inventory Simulation service helps our clients validate existing or proposed inventory policies and predict fulfillment and customer service performance.  We use a sophisticated supply chain simulation tool to build and run discrete event simulation models.  We examine how key replenishment policies and large demand fluctuations impact actual customer service metrics such as fill rate or on-time performance, inventory levels over time, and detailed financial results.  Demand can be modeled either using actual order history or a demand pattern with a variability distribution.   

Delivered Benefits and Desired Outcomes

The power to holistically understand the impact of inventory policies and variability on inventory levels across a multi-echelon supply chain network and identify improvement opportunities
Ability to model and quickly run “What-If” scenarios to understand key inventory drivers and evaluate trade-offs between
                customer service level and inventory investment to plan for changing business requirements
Validate optimized inventory levels
Validate demand distribution assumptions
Validate and predict expected customer service levels and location fill rates
Understand peaks and troughs in inventory levels overtime