In this knowledge base, we focus on inventory management/optimization of finished goods. As mentioned in the examples for the 4 different types of companies (ASML, Boeing, Tesla, Coca Cola), not every company should (solely) be optimizing or plan inventory for their end products.
If you are heavily make to order or assemble to order, you don’t want to build up inventories for all different product variations, but want to keep inventories of the items that go into these variations.
However, these calculations rely on various factors, some of which companies may readily have information for, while others might require additional data collection.
Historical demand data: Provides the basis for calculating demand variability, allowing companies to establish averages and standard deviations in demand.
Determined service levels: These directly influence the safety stock calculation.
Lead time: Average lead time data for each supplier, critical to determining how long stock needs to last until the next (likely) replenishment.
Demand variability: Fluctuations in demand over time, often calculated as standard deviation, impact safety stock needs. High variability requires higher safety stock to maintain service levels.
Order frequency: Frequency of ordering or production cycles affects safety stock needs. More frequent orders allow for lower safety stock.
Order quantities or batch sizes: Minimum order quantities (MOQs) or fixed batch sizes directly influence the inventory strategy, potentially requiring higher safety stock if MOQs are large.
Supplier/lead time reliability: Measures how consistently suppliers meet lead times. If reliability data shows frequent delays, companies might hold more safety stock. However, not all companies track supplier performance in detail.
Demand forecast accuracy: The accuracy of demand forecasts influences required safety stock. If forecasts are often inaccurate, higher safety stock may be necessary. Some companies monitor forecast accuracy closely, while others don’t.
Inventory carrying or warehousing costs: These costs can indirectly impact safety stock levels if the company aims to optimize carrying costs. Many companies track total warehousing costs but may not link them directly to individual items.
Stockout costs: The financial impact of stockouts (e.g., lost sales, production downtime). Companies that can quantify this cost can make better decisions about safety stock levels, but many don’t have precise figures for stockout costs.
Customer demand sensitivity: Measures the impact of stockouts on customer satisfaction. While qualitative insights might be available, many companies lack quantifiable data on how stockouts affect customer loyalty or satisfaction.
Production lead time variability (for manufacturers): Fluctuations in internal production lead times may require extra safety stock for components. However, companies often struggle to quantify this variability in an exact manner.
Cost of overstock vs. understock: Balancing the cost of excess inventory against stockout costs can fine-tune safety stock levels but requires detailed financial analysis that isn’t always readily available.
Supplier capacity constraints: If a supplier has capacity issues, there might be risks of extended lead times during peak demand. Most companies don’t have visibility into supplier capacity limitations.
If companies are not going for this kind of automated approach, then more basic policies are available as well.
Hereunder is an overview of more basic inventory policies that take into account only a few basic factors.
For more details, we recommend that you look into Nicolas Vandeput Inventory Optimization book where he elaborates on such manual approaches related to reorder points, periodic reviews, impact of lead times, supplier variability. These inventory management courses (and blog articles by ABC supply chain) might also be good starting resources for these manual approaches.
Reorder point (ROP): An order is triggered when inventory reaches a specific level, calculated as demand during lead time plus safety stock.
Periodic review & order-up-to level: Inventory is checked at regular intervals, and orders are placed to reach a predetermined target stock level.
Economic order quantity (EOQ): Determines the ideal order size to minimize total costs by balancing ordering and holding costs.
Kanban replenishment: A visual, signal-based system where inventory is replenished based on real-time demand, commonly used in just-in-time settings.
Just-in-time (JIT): Minimizes inventory by timing stock arrivals precisely with production needs, reducing on-hand inventory.
Multi-echelon inventory optimization (MEIO) - later more on this topic: Optimizes stock levels across multiple locations in the supply chain to reduce total inventory costs.
Safety stock for lead time variability: Extra stock is held to buffer against variability in demand or lead time, ensuring availability during fluctuations. A good article by ABC supply chain on this.
Min-max: Sets minimum and maximum inventory levels; when stock falls to the minimum, it’s replenished up to the maximum threshold.
Coverage in days: Inventory is managed by maintaining a stock level that covers expected demand for a certain number of days, ensuring enough supply for a set period based on forecasted demand.