Once the inventory planning numbers have been calculated, the planner can engage in a detailed review of the results. The analysis of the results of the inventory optimization algorithms can be performed by leveraging alerts. Alerts and Excel planning views allow you to measure the quality of the new plan. The baseline way in which the quality or impact of a new inventory optimization run can be measured is by comparing it to the previous iteration. This can be done by taking a snapshot (a copy) of the previous inventory components and comparing it to the newly calculated results.
If the relative change is dramatic, it’s worth spending time to analyze it. The relative change typically has two angles; on the one hand, you could look at the percentage difference—for example, if the inventory rises 20% for a particular product, that might be a cause for analysis. On the other hand, it’s typically important to overlay this with a dollar-change amount. Especially in cases where the inventory numbers are low, a change from 1 to 2, for example, in safety stock might represent a 100% change, but if the value of the product is one dollar while other products have a value of thousands of dollars, this plays an important role in prioritizing which products to spend time on.
You can complement this approach of using Excel planning views by adding custom alerts, which can provide additional charts to immediately assess some of the key drivers. For example, you could add a chart with the demand pattern for this product, which would immediately tell you if there was an uptick in demand in the previous cycle that triggered the increase in safety stock.
Analyzing the inventory plan
Beyond alerts and evaluations of specific product-related increases, you can leverage dashboards, which provide a comprehensive overview of all key performance indicators for the newly calculated inventory plan. It’s good practice to create multiple scenarios that allow planners to compare results and pick a scenario that aligns closest to the business imperative of the product group, region, or organization.
Planners can create multiple scenarios to simulate the impact of increasing service levels. The system can calculate the corresponding expedite costs and add them to the safety stock to find the minimum.
The analysis in this phase isn’t necessarily limited to only evaluating parameters that are under the direct control of the inventory planner. The analyses are aimed at reducing the total cost of inventory while maintaining the desired level of customer service. Analyses can be performed to determine the cost of the variance in customers’ ordering patterns. A higher coefficient of variance in the demand will lead to a higher safety stock, so if there is little knowledge about the ordering pattern the customer will exhibit, you need to buffer your supply network with extra inventory to account for this. In industries in which customers are connected to the company for a long duration, there can be room to engage with customers in collaborative planning, which allows you to reduce the uncertainty.
For example, if a customer was to provide a customer forecast and adhere to it closely, you could reduce safety stock while maintaining the same customer service. The same can be said of the supplier side: if you can build a better supplier collaboration capability, this will reduce the inventory cost in the network. Inventory simulations allow you to provide quantitative and value-based information to support such initiatives.
Concluding this step includes selecting which scenario will form the baseline of the inventory plan moving forward, making adjustments to inputs where root-cause analyses call for it, and confirming that the overall metrics of the newly optimized inventory plan look good.
