# Market-Oriented Procurement Planning Leading to a Higher Service Level and Cost Optimization
## 1 Introduction  
Man has dealt with inventory issues since we first began to utilize the resources of the planet [1]. The first mathematical approach for inventory planning was the economic lot size or economic order quantity (EOQ) model, performed by [PERSON] in the 1910s [2]. Although the EOQ model was developed, it was not until the 1950s and 1960s when other major advances were realized to satisfy the needs of logistics, such as the consideration of surplus, shortage, and ordering costs, to determine inventory parameters [1]. Computerized forecasting and inventory control were initiated in the 1960s and 1970s [3]. Since the 1980s, a great effort has been made to develop inventory planning software solutions with the goals of reducing operating costs and working capital. However, in the daily business of most manufacturers in process industries, inventory planning is still driven by \"manual\"spreadsheet databases [4]. In addition, the EOQ model after one century is still analyzed and extended by researchers as well as used in practice [1]. Multiple models have already been developed by several authors on EOQ and economic production quantity (EPQ) for time-dependent demand, as well as models for stock-dependent demand [5]. Most of the developed models consider the demand of an item as an infinite parameter with product specifications that do not change over time [5]. In contrast, as markets became more complex, inventory management also became more complex [6], and market conditions began to change more quickly than researchers could respond [1]. Technology has led to rapid changes in product specifications leading to a high product demand volatility in a finite lifecycle [1]. As product lifecycles become shorter, the randomness of the demand increases [7]. As a result, most managers decide on inventory planning with a certain level of demand uncertainty. In this context, many models have been developed to deal with uncertainty and to determine the optimal inventory policy [8]. However, most inventory models are related to the classical cost analysis approach with uncertain input data accuracy [1]. The cause of uncertainty can be the environment, such as demand uncertainty [8] or disasters, such as replenishment times or information delay on inventory levels. Storage holding costs in metropolitan areas are steadily increasing [5], leading to high pressure for stock optimization and to an increased risk for stockouts in normally well-populated areas of suppliers. Therefore, how to balance the stock-holding strategy versus the optimization of costs is a key decision for managers. The need to respond to demand uncertainty is clear. Epidemic crises, product changes, and deviations in replenishment time can lead to stockouts and a high level of stocks required to provide a given service level. People affected by the potential lack of supplies are at great risk [9] as occurred with the COVID-19 global crisis when companies speculated with the demand offer, reducing it to increase margins due to the customer demand. By doing so, the purpose of a company to provide goods or services to society is not given. It is likely that further theoretical developments will be required and that there may be a need to develop methods that will determine inventory levels based on measures other than cost. Additionally, using cost minimization as a performance measure is unlikely to provide enough importance to meet users' and society's requirements. Generalizing to consider models in terms of the utility may be intellectually satisfying but leads to equally difficult problems of measurement [1]. COVID-19 had significant economic consequences globally [9]. This situation demonstrated the future risks and the current fragility of global healthcare infrastructure, such as a lack of medical resources and equipment [10]. The consequences have included production stops due to the lack of raw materials, while other producers had to decrease or shut off production because the finished products could not be shipped abroad.