Inventories form buffers for logistics within and among organizations. Inventory management is thus another important instrument for planning & control. Categorizing and typing storage and warehouses facilitates detailed inventory management. A physical inventory count of stored and in-process inventory verifies the accuracy of book inventories as a prerequisite of accurate inventory valuation.
An important basis for various calculations in demand forecasting and in materials management is provided by statistics that analyze particular events such as inventory transactions, sales, and bid activities. These statistics contain information on quantities and values as well as on the number of transactions.
The ABC classification according to various measures of value, such as turnover, determines the importance of items in a product line. For this, the item range is first divided into different ABC categories. The XYZ classification distinguishes items with regular or even continuous demand from those with lumpy/erratic or discontinuous or unique demand. Additional statistics sort out items that are exceptions according to some criterion.
Stochastic materials management aims to produce production or procurement proposals prior to actual demand resulting from customer orders. In most cases, a demand forecast is the sole basis for both the proposed quantity (the batch) and the proposed time of receipt.
The most familiar technique for stochastic materials management — particularly for continuous demand — is the order point technique. The order point is the expected value of demand during the lead time. Safety stock is carried to absorb deviations from the expected value, and safety lead time, which is also translated into a safety quantity, is used to absorb deviations from the lead time. If forecast parameters change, both order point and safety stock must be recalculated.
In the simplest case, materials management determines the batch size that will yield a minimum of setup and ordering costs and carrying cost. However, in the stochastic case, there is as yet no concrete customer demand, so that the optimum batch size can only be derived (the economic order quantity EOQ) from a long-term forecast of total demand. In the final reckoning, however, this calculated quantity merely indicates the order of magnitude, and thus it can be rounded up or down generously. The order of magnitude is robust in the face of errors in quantity or cost forecasts. However, the formula does not take into account the effects of shorter lead times with smaller batches. In practice, other constraints exert an important influence on the final selection of minimum or maximum batch size. These include storage space requirements, storability, minimum order volumes, speculation, and so forth. Extensions to the simple batch size formula arise when taking into account lead time, quantity discounts, and kit or collective management.
Course sections and their intended learning outcomes
Intended learning outcomes: Describe usage statistics, analyses, and classifications. Explain in detail the order point technique. Disclose how to calculate safety stock. Differentiate various batch or lot sizing techniques.
Intended learning outcomes: Present characteristic features of stores management. Produce an overview on inventory transactions. Describe physical inventory and inventory valuation.
Intended learning outcomes: Present statistics on inventory transactions, sales, and bid activities. Explain the ABC Classification and the Pareto Chart. Describe the XYZ Classification and Other Analyses and Statistics.
Intended learning outcomes: Explain the order point technique and variants thereof. Describe the safety stock calculation with continuous demand. Disclose the determination of the service level and the relation of service level to fill rate.
Intended learning outcomes: Produce an overview on production or procurement costs, batch-size-dependent unit costs, setup and ordering costs, and carrying cost. Explain optimum batch size, optimum length of order cycle, the classic economic order quantity formally and in practical application. Disclose extensions of the batch size formula.
Intended learning outcomes: Calculate examples for the ABC Classification and for the combined ABC-XYZ classification. Differentiate between Safety Stock Variation and Demand Variation. Determine batch size depending on stockout costs. Assess the effectiveness of the order point technique.