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Nine Factors That Influence Inventory Planning and Optimization

Inventory Optimization & Management

Inventory planning is hard to do. As supply chain complexity continues to expand, it’s getting more and more difficult to reach and sustain optimal inventory levels. Regardless of the level of difficulty, however, inventory must be managed, and the rewards go to those who do it well. Finding ways to cost-effectively serve customers can be the difference between growth and decline, between profit and loss for a business. It’s a constant balancing act: having enough inventory, not too little or too much. If you are responsible for striking that delicate balance, here are nine factors that you need to consider when planning your inventory:

1. Forecast Quality: An inventory forecast can be basic or complex. In some operations, it is a straightforward calculation using sales and current inventory value over a year to predict turns. Other calculations such as economic order quantity (EOQ) include an estimate of annual demand, holding costs, ordering costs, and carrying costs to predict optimal inventory levels. Regardless of the method of calculation, the quality of the forecast has a big impact on business operations. Inaccurate sales calculations and seasonal surges or drops can mean missed deliveries and disruptions in production.

2. Lead Time and Cumulative Lead Time: As the global economy has grown, supply chains have become more complex. This complexity is in part due to the far-flung nature of sourcing and purchasing raw materials and components. Some companies must source inventory locally, regionally, and globally to secure the lowest cost. Lead time on distant products may include latency in logistics at ports or airports on the shipping end as well as on the receiving end, adding time to the process. Long lead times for individual components often also increase the cumulative lead time for finished products. Item lead times exceeding replenishment time expectations require deployment of various inventory and capacity strategies to achieve satisfactory results.  

3. Variability of Demand and Supply: Demand variability is the difference between a forecast’s projected sales and what actually ships. It is measured as the standard deviation of demand divided by the mean. If the ratio is low, demand is consistent. If it is high, demand is sporadic or volatile. If a product has a stable mean but wide variations above and below the mean, you need to decide when and how to cover shortages that will inevitably occur when demand is high. While decision-making will always be a part of planning, demand variability relies on accurate statistics to allow you to make those decisions with confidence.

From time to time, disruptions or variability in vendor supply will occur. These disruptions may be related to weather, shipping and logistics issues, or other factors. As disruptions occur, quick communication is necessary to inform customers of their order status. In complex global supply chains with manual systems and inadequate tracking and monitoring of goods movement, delays can multiply and significantly impact the reliability of supply.

4. Service Level: Service level is the expected probability of not stocking out during the next replenishment cycle. It is a balance between safety stock required to cover lead times and customer demand versus carrying costs. It is a trade-off between opportunity and operations costs. Manual approaches to applying service levels to safety stock calculations tend to be “one size fits all” across all items. Such approaches result in the right level of inventory for some items, too much for others, and too little for the rest. The most accurate method of calculation is a statistical approach requiring several data elements for each item. This method can be challenging without a planning system. 

5. Customer Order Visibility: The farther in advance from a requested ship date that customers communicate their needs, the less you need to rely on forecasting and the corresponding risk of forecast inaccuracy. Firm commitments replace uncertainty, which reduces the need for safety stocks. Additionally, predictive information related to customer ordering behavior can supplement statistical forecasts to improve accuracy. 

6. Customer Response Time: Response time refers to the speed at which the customer expects delivery of an order.  Shorter response times compared to cumulative lead times require greater investments in inventory, capacity, and flexibility to comply.

7. BOM Complexity: Whether from a discrete manufacturer with complex recipes or assembly companies, multi-level bill of materials (BOMs) can be difficult to navigate. In some cases, there may be different versions of BOMs for the same product within different departments. In other cases, there may be differences in units of measure adding complexity when the numbers must be netted up or down formulaically to reach a value understood by planners. Situations where the BOM and planning system are not linked and instead rely upon manual calculations can be especially complicated. The process is also impacted when there is inadequate or unautomated change management for BOM updates, which can result in incorrect ordering or stocking of components—leading to stockouts or obsolescence.

8. Capacities: In conjunction with sales and demand forecasting, capacity planning can drive inventory forecasts. Capacity miscalculations coupled with inaccurate demand estimates can have a major impact on supply, resulting in inventory shortages or overstock. Because many operations still use a silo approach between capacity, inventory, and lead time, the trade-offs may never be fully understood, and the system will continuously incur inventory shortages or overages.

9. Supply Network: Modern supply chains are vast, diverse, and loosely connected systems that stretch across the entire globe. Weather, labor disputes, customs issues, regional conflict, and a host of other factors can impact one or more parts of the supply network at any given time. If communication and monitoring are not in place, each disruption adds time or creates the condition for inventory risk.

You need to take all of these factors—from the simple to the complex—into account when planning inventory. The problem is that for so many companies, planning processes are still manual, or they consist of spreadsheet-based systems that can’t easily consider all inputs or else miscalculate the input. With inadequate systems, replenishment planning—establishing and monitoring stocking levels and then triggering replenishment actions at the correct lead time—is extremely difficult.  

An automated inventory planning system that includes material requirement planning (MRP), distribution requirements planning (DRP), rough cut capacity requirement planning (RCCP), and order planning can help alleviate these issues. The system can automate the generation of statistical forecasts to supplement actual customer orders, and it can automatically calculate safety stocks using statistical methods. Consumption policies can guide staff on stocking requirements. Inventory levels can be automatically adjusted as demand changes. And items can be segmented based on business importance, accuracy, forecastability, and order frequency.

Each of the factors outlined in this blog can be better managed with an inventory planning system. Such a system will enable you to accurately control and monitor inventory in real time to ensure optimization.  Additionally, the move to an automated system will mitigate factors related to manual tasks, lack of monitoring, inadequate communication, and human error.

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