Inventory drivers in a pharmaceutical supply chain

In recent years, inventory reduction has been a key objective of pharmaceutical companies, especially within cost optimization initiatives. Pharmaceutical supply chains are characterized by volatile and unpredictable demands –especially in emergent markets-, high service levels, and complex, perishable finished-good portfolios, which makes keeping reasonable amounts of stock a true challenge. However, a one-way strategy towards zero-inventory is in reality inapplicable, due to the strategic nature and importance of the products being commercialised. Therefore, pharmaceutical supply chains are in need of new inventory strategies in order to remain competitive. Finished-goods inventory management in the pharmaceutical industry is closely related to the manufacturing systems and supply chain configurations that companies adopt. The factors considered in inventory management policies, however, do not always cover the full supply chain spectrum in which companies operate. This paper works under the pre-assumption that, in fact, there is a complex relationship between the inventory configurations that companies adopt and the factors behind them. The intention of this paper is to understand the factors driving high finished-goods inventory levels in pharmaceutical supply chains and assist supply chain managers in determining which of them can be influenced in order to reduce inventories to an optimal degree. Reasons for reducing inventory levels are found in high inventory holding and scrap related costs; in addition to lost sales for not being able to serve the customers with the adequate shelf life requirements. The thesis conducts a single case study research in a multi-national pharmaceutical company, which is used to examine typical inventory configurations and the factors affecting these configurations. This paper presents a framework that can assist supply chain managers in determining the most important inventory drivers in pharmaceutical supply chains. The findings in this study suggest that while external and downstream supply chain factors are recognized as being critical to pursue inventory optimization initiatives, pharmaceutical companies are oriented towards optimizing production processes and meeting regulatory requirements while still complying with high service levels, being internal factors the ones prevailing when making inventory management decisions. Furthermore, this paper investigates, through predictive modelling techniques, how various intrinsic and extrinsic factors influence the inventory configurations of the case study company. The study shows that inventory configurations are relatively unstable over time, especially in configurations that present high safety stock levels; and that production features and product characteristics are important explanatory factors behind high inventory levels. Regulatory requirements also play an important role in explaining the high strategic inventory levels that pharmaceutical companies hold

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems

Regression Monte Carlo for Microgrid Management

We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device is used to shift power from times of high renewable production to times of high demand. We introduce a methodology to solve microgrid management problem using different variants of Regression Monte Carlo algorithms and use numerical simulations to infer results about the optimal design of the grid.Comment: CEMRACS 2017 Summer project - proceedings

On two-echelon inventory systems with Poisson demand and lost sales

We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u

End-of-Life Inventory Problem with Phase-out Returns

We consider the service parts end-of-life inventory problem of a capital goods manufacturer in the final phase of its life cycle. The final phase starts as soon as the production of parts terminates and continues until the last service contract expires. Final order quantities are considered a popular tactic to sustain service fulfillment obligations and to mitigate the effect of obsolescence. In addition to the final order quantity, other sources to obtain serviceable parts are repairing returned defective items and retrieving parts from phase-out returns. Phase-out returns happen when a customer replaces an old system platform with a next generation one and returns the old product to the original equipment manufacturer (OEM). These returns can well serve the demand for service parts of other customers still using the old generation of the product. In this paper, we study the decision-making complications stemming from phase-out occurrence. We use a finite horizon Markov decision process to characterize the structure of the optimal inventory control policy. We show that the optimal policy consists of a time varying threshold level for item repair. Furthermore, we study the value of phase-out information by extending the results to cases with an uncertain phase-out quantity or an uncertain schedule. Numerical analysis sheds light on the advantages of the optimal policy compared to some heuristic policies.spare parts;end-of-life inventory management;phase-out returns