Supply Chain Management Consulting
Supply Chain Simulation
Overview
Supply Chain Simulation is a discrete event simulation that demonstrates or predicts “how” a given supply chain network or process will perform with demand and supply variability and operations constraints. On-time customer deliveries, fill rates, back-orders, transportation asset utilization, unit manufacturing times are a few of the many metrics and outputs from the simulation.
Practical applications for network simulation include:
• Evaluate the results from a Network Optimization
• Supply chain risk analysis
• Inventory analysis
• Process Improvement
• Bottleneck analysis
Business Problem
Are you experiencing these business challenges? Do these questions sound familiar?
Common Business Challenges
• Supply chain risk; disruptions in supply or rapid changes in demand
• Need to understand customer service implications of changing supply chain design
• 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
• Limited transportation fleet capacity
• Poor customer service or late transportation deliveries
Key Questions for Consideration
• What is the potential cost and service impact of an unexpected supply disruption? Demand spike?
• Can the alternative network design continue to support or improve customer 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?
• How much inventory storage space do I need this year? When will I need additional capacity?
Service Solution
Supply Chain Acuity’s Supply Chain Simulation service helps our clients validate existing or proposed network structures and processes by predicting performance and customer service levels. We use a sophisticated supply chain simulation tool to build and run discrete event simulation models to study a variety of practical applications listed in the overview section. We examine how key replenishment, transportation and manufacturing sourcing 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 supply chain policies and variability on supply chain performance across a multi-echelon supply chain network and identify improvement opportunities
• Ability to model and quickly run “What-If” scenarios to understand key supply chain processes and predict customer service levels
• Validate network optimization results
• Validate demand distribution assumptions
• Validate and predict expected customer service levels and location fill rates
• Understand peaks and troughs in inventory levels overtime
• Quantify and mitigate supply chain risk