In a supply chain, keeping your inventory costs as low as possible while maintaining your target customer service is a challenge. It is also necessary to consider contingencies for increased demand or discrepancies in supply. anyLogistix inventory optimization software helps you find solutions for cutting costs, without sacrificing your service level, by providing a computer model of your supply chain for experimentation — a supply chain digital twin. This inventory planning and optimization tool is used for testing inventory policies and calculating balanced policy combinations.
ALX enables you to conduct single-echelon or multi-echelon supply chain inventory optimization. You can:
In our white paper, Simulation-Based Inventory Planning for the Digital Supply Chain Era, we investigate the advantages inventory simulation provides, and how it can help analysts define the right inventory strategies. Read the white paper and learn how to take a supply chain inventory management to a new level of efficiency!
read the white paperInventory simulation provides insight where analytical methods cannot. A supply chain simulation model shows system behavior over time and can be used when complexity prevents mathematical-analytical examination. This means supply chain simulation is good for:
Simulation models can consider randomly varying parameters, including transportation and production lead times, demand per product, changes in order quantities, and more. Using real stochastic values in all these metrics, instead of averages, allows you to catch complex interdependencies between them. This provides you with a deeper insight into which factors are driving up your costs, and what policy changes are needed for a lean and low-risk inventory plan.
Optimization that takes place in isolation, within single facilities or at a single level, can interact badly with other areas of a supply chain. For example, uncoordinated inventory policies can create disruptive feedback and contribute to the bullwhip effect. To avoid this, the whole supply chain must be considered. In this case, the development complexity for analytical methods may be considered too great.
A supply chain digital twin, based on simulation modeling, can handle the complexity of multi-echelon inventory optimization. The characteristics of supply chain digital twins means they replicate how supply chains work, representing their behavior and operational logic. This enables the multi-echelon inventory optimization model to capture activities without compromise. Policies at each echelon can then be developed and tested in harmony with those at other levels, so that the supply chain is optimized from end to end.
ALX’s unique simulation modeling capability allows you to capture the supply chain design as is: models are extendable and can include all tiers of your network at the level of detail required to achieve your aims. For example, high inventory costs for raw materials can be driven by production stage processes that are difficult to discover. With ALX, you can model your manufacturing site at the level of workstations, shifts, and equipment, to see exactly where a bottleneck is or what is inflating your stock.
The same goes for disturbances in transportation lead times and sourcing plans. Finding inventory drivers may be especially difficult for products with complex BOMs and multiple links between production sites. This is where detailed simulation modeling can help determine the sources of anomalies and provide a basis for inventory optimization.
All of this cannot be achieved with traditional analytical inventory optimization solutions that do not use simulation modeling.
With ALX, you can test any emergency scenario and quantify its impact on your inventory. For example, you can simulate the bankruptcy of a major supplier, a leap in transportation costs, or an unexpected increase in demand. You are able to see how your network would be affected by an event and adjust your inventory plans accordingly.
Summarizing the above, inventory management optimization is a prime example for the use of simulation in supply chain. To learn more, you should watch our Simulation-Based Inventory Optimization Webinar. During this webinar we investigate what advantages inventory simulation provides, and how it can help analysts define the right inventory policies.
watch the webinarIf you are operating a network with multiple tiers, you may choose to manage and optimize inventory levels from top to bottom, across your whole supply chain. This helps avoid localized optimization plans that may work against each other.
ALX can be used for:
For example, an ALX simulation model can help you better understand interdependencies between your customer service level and stock-outs of packing material at factories. Or, it can assist you in finding the influence of end-customer demand fluctuations on order placements across multiple tiers of the supply chain. ALX helps you identify the consequences of the bullwhip effect on your network and helps you overcome them.
For a deeper dive into inventory optimization and planning with anyLogistix software, you can watch the following how-to video.
Supply Chain Inventory Management: Safety Stock Estimation
Keeping inventory levels low while satisfying demand and optimizing risk is a major challenge for supply chain managers. Simulation modeling is a key supply chain tool that helps by providing insight into the connections and dynamics of your supply chain — enabling robust optimization and improving profitability.
See how inventory optimization with ALX software is used by Deloitte.
