The shortage of products, or stockout, is identified as a critical business issue, leading to disruptions inproduct flow and subsequent economic damage. In particular in the healthcare context, stockouts can pose risks topatients due to the inability to administer essential medications. The study presents an in-depth analysis of a set ofpharmaceutical products based on a five-year database containing information on demand, stock, and orders placed.In particular the aim is to assess the performance of various demand forecasting techniques on this product set andsubsequently find the most cost-effective dynamic reordering policy’s parameters. The efficacy of the forecastingtechniques is selected based on minimizing the Root Mean Square Error (RMSE). Subsequently, a periodic dynamicreview policy is applied to determine the number of orders and resulting backorders, evaluating the total managementcost for the item. This approach allows for the evaluation of the effectiveness of ad hoc forecasting methods for eachproduct compared to using a uniform approach. The results of the analysis provide a detailed overview of theforecasting techniques' performance related to dynamic reordering policy parameters and demonstrate the benefitsearnable with respect to the company classical management.

Pharmaceutical Inventory Management: A Comparative Analysis of Forecasting Techniques and Dynamic Reordering Policies / Coruzzolo, Antonio Maria; Lolli, Francesco; Balugani, Elia; Tronto, Benedetta; Forgione, Chiara; Rimini, Bianca. - In: ...SUMMER SCHOOL FRANCESCO TURCO. PROCEEDINGS. - ISSN 2283-8996. - (2024). (Intervento presentato al convegno XXIX Summer School “Francesco Turco” – «Sustainability and resilience in industrial systems across the era of digitalization» tenutosi a Otranto, Italia nel 11/09/2024 - 13/09/2024).

Pharmaceutical Inventory Management: A Comparative Analysis of Forecasting Techniques and Dynamic Reordering Policies.

Coruzzolo Antonio Maria;Lolli Francesco;Balugani Elia;Forgione Chiara;Rimini Bianca
2024

Abstract

The shortage of products, or stockout, is identified as a critical business issue, leading to disruptions inproduct flow and subsequent economic damage. In particular in the healthcare context, stockouts can pose risks topatients due to the inability to administer essential medications. The study presents an in-depth analysis of a set ofpharmaceutical products based on a five-year database containing information on demand, stock, and orders placed.In particular the aim is to assess the performance of various demand forecasting techniques on this product set andsubsequently find the most cost-effective dynamic reordering policy’s parameters. The efficacy of the forecastingtechniques is selected based on minimizing the Root Mean Square Error (RMSE). Subsequently, a periodic dynamicreview policy is applied to determine the number of orders and resulting backorders, evaluating the total managementcost for the item. This approach allows for the evaluation of the effectiveness of ad hoc forecasting methods for eachproduct compared to using a uniform approach. The results of the analysis provide a detailed overview of theforecasting techniques' performance related to dynamic reordering policy parameters and demonstrate the benefitsearnable with respect to the company classical management.
2024
XXIX Summer School “Francesco Turco” – «Sustainability and resilience in industrial systems across the era of digitalization»
Otranto, Italia
11/09/2024 - 13/09/2024
Coruzzolo, Antonio Maria; Lolli, Francesco; Balugani, Elia; Tronto, Benedetta; Forgione, Chiara; Rimini, Bianca
Pharmaceutical Inventory Management: A Comparative Analysis of Forecasting Techniques and Dynamic Reordering Policies / Coruzzolo, Antonio Maria; Lolli, Francesco; Balugani, Elia; Tronto, Benedetta; Forgione, Chiara; Rimini, Bianca. - In: ...SUMMER SCHOOL FRANCESCO TURCO. PROCEEDINGS. - ISSN 2283-8996. - (2024). (Intervento presentato al convegno XXIX Summer School “Francesco Turco” – «Sustainability and resilience in industrial systems across the era of digitalization» tenutosi a Otranto, Italia nel 11/09/2024 - 13/09/2024).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1385889
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