# Market-Oriented Procurement Planning Leading to a Higher Service Level and Cost Optimization
## Materials and Methods
### Delimitation of the Research Work  
Among the managerial challenges, the problem of inventory management is one of the most relevant and requires efficient solutions knowing that there is no one-fits-all approach suitable to all firms [31]. Inventory management is a key issue in supply chain management. The importance of inventory management in industrial applications derives from the effect of stockouts in customer satisfaction and of stocks in the economic balance of organizations. In addition, the value of U.S. inventories was estimated to be over USD 1707 billion in December 2013. Therefore, the potential savings from efficient inventory management offer great potential. Classical models for inventory management with uncertain demand include continuous-review policies and periodic-review policies. Classical models have one main advantage in that they are easy to implement. Therefore, they are optimal for simple inventory management cases. However, the complexity of supply chains limitsthe suitability of the classical models for inventory management due to capacity constraints and the variety of sources of uncertainty [32].  
The comparison of different inventory replenishment policies can improve the level of customer service and reduce the inventory cost without requiring further resources [33]. Many inventory management studies investigated the inventory challenge as an isolated problem. However, decision-making in production, inventory, and supply chain management is essentially a problem of matching the diversity of external and internal factors of the organization [34]. Matching supply and demand is particularly challenging when the supply must be chosen before observing demand and when the demand is uncertain [34]. Inventory inaccuracy is prevalent in many industries and supply chains. Internet of things (IoT) and radio frequency identification (RFID) were identified as an effective potential solution to inventory inaccuracy by providing transparency in relation to inventory information [35].  
Modeling is an important tool for investigating complex problems, such as the interaction between stock levels and the environment. Models that use only a few variables can indicate whether those variables have a positive or negative influence, and, by doing so, may broadly show the influence that they may have in isolation and help to identify variables that require a closer analysis [1]. However, due to system complexity, models optimizing one metric will, in general, not perform well when trying to optimize another indicator, such as cost. For these reasons, it is advantageous to perform 'total' simulations and assess the performance against many different important indicators, such as cost, return on investment, service level, inventory turnover, and labor requirements [1].  
In this context, our research pursues this goal to provide a 'total' simulation with multiple options and parameters that provide a global evaluation and support tool for managers and planning employees dealing with challenges of demand, inventory, and procurement planning in all kinds of manufacturing companies. Within the software, various simulation models can be derived. For the results, three are selected, two based on literature and one developed based on the methodology exposed, named the market-oriented procurement planning model. The models are tested for a Tier 1 and an automotive manufacturer. The simulation case study assesses the performance of these three simulation models when dealing with five different demand scenarios. The patterns of the demand scenarios are extracted from the literature. By doing so, the different procurement policies can be tested in all potential lifecycle scenarios.  
As a result, the research provides a framework for managers to design models, simulations, or tools of different complexity levels for planning purposes, considering a set of integrated key indicators. This work also proves the conceptual model with the case study and the simulation results.