# Market-Oriented Procurement Planning Leading to a Higher Service Level and Cost Optimization
## 5 Conclusions  
After completion of the research work, the following points can be successfully concluded:  
* Due to a new conceptual model developed for inventory management, managers can use the model as conceptual guidance or as a tool for improving operations and decision-making by gathering real-time data within the fourth industrial revolution. * The case study was created and simulated with different simulation models to test their performances with the same KPIs. * The simulation of the market-oriented simulation model presented better overall results for the relevant key parameters for all five scenarios, particularly in demand scenarios and product lifecycles with high variability, demand pattern changes, and uncertainty. As a result, the simulation can evolve as a decision-making support tool for managers to analyze what-if-scenarios, to generate digital twin models, and to develop new IT platforms. The final goal is to transfer this research method to real organizations, applying it in some cases as a guide for inventory management and in scenarios with volatility, such as product launches and new supply chain flow designs. In detail, the theoretical, managerial, and empirical conclusions, as well as the limitations of the research performed and the potential research work derived, are described as follows:  
Theoretical conclusions and contributions--the research paper pursued the following objectives: the development of a model for higher OTD and service levels while optimizing the inventory costs. To achieve these goals, a cybernetic model was applied with the following characteristics:  
* Forecasting techniques and their application for different planning horizons. Selection according to the maximization of the forecasting accuracy under demand uncertainty. * Selection of the safety factor depending on the target service level. * Use of the different procurement policies and their change based on the system conditions as demand variability. * Investment decisions are based on product lifecycle. Therefore, the main theoretical contribution and novelty of the approach is the integrated conceptual model developed with a methodological combination of:  
* Decision-making within the model for the planning areas based on real-time data. * Criteria for changing between forecasting methods. * Criteria for changing procurement policies. * Criteria for adapting organizational planning dynamically. * Consideration of different lifecycle patterns and their consideration of planning and investment decisions. * Conceptual model based on cybernetics and simulated based on system dynamics. Figure 7: Discussion framework: scenarios for managers (own elaboration). Managerial conclusions and contributions:
* The current challenges of manufacturing companies were described, and those influencing the inventory management as well as the common methods were applied in the models. * Dynamic inventory management with adaptability was proved to be necessary, particularly when uncertainty is high. * The importance of synchronized demand planning, inventory planning, procurement planning, as well as personal planning together with investment planning, considering the overall lifecycle, was concluded as key for organizations to secure long-term viability. * The methodological combination provides managers with a framework to be prepared for future scenarios, to generate digital twins, and to develop IT software based on market-oriented procurement planning. Therefore, the model is the basis for a conceptual model to generate value-added solutions based on Industry 4.0 technologies, such as the Internet of things and real data monitoring. Empirical conclusions and contributions: To prove the utility of the new concept, a simulation for a supply chain of an OEM and a Tier 1 manufacturer was created by including the necessary instruments and developed control systems as well as validation by means of simulation. All models were implemented in Vensim software and simulated to compare the performance in different demand scenarios.