Minimising inventory costs by properly choosing the level of safety stock

<p><em>Markets are everyday becoming ever more demanding and companies are adjusting in different ways. The objective of forecasting in a demand-driven supply network is to identify the probable range of expected demand so that supply can cover demand anywhere within the statistical range. Supply can cover the range either through having the capacity to replenish within lead times or by carrying excess inventory (safety stock). Nowadays, many companies put a lot of their energy and finance into setting the right level of safety stock and reducing related expenses. In this paper, we improve an existing method for calculating the safety stock for a particular Slovenian company. We present the existing and proposed methods for calculating safety stock and derive a cost model. Finally, we prove that the proposed method not only reduces average costs but also helps to meet the target customer service level – making it also applicable to other Slovenian companies encountering situations where demand is seasonal.</em></p&gt

Joint optimisation of demand forecasting and stock control parameters

Exponential smoothing methods are very commonly used for forecasting demand in a supply chain context. When estimating the parameters used in these methods, a common practice is to optimise only the smoothing constants and not the initial parameter values. In this paper we show that if we treat initial values as well as smoothing constants as decision variables, a considerable reduction in forecast error can be achieved. Additionally, the optimisation of the forecasting method should not be treated separately from the production or inventory model in which forecasts are used. The case of a centralised supply chain with an order-up-to inventory policy shows that calculated forecasts of demand, determined by minimising mean absolute error (MAE) or mean squared error (MSE), are not optimal. Finally, a method for simultaneous optimisation of demand forecasting and a stock control policy is described. Initial and smoothing parameters in the forecasting methods can be determined to minimise the total costs.Demand forecasting Holt-Winter's method Inventory control Optimisation