Stock Optimization

Description: Predict stock levels to optimize inventory management, anticipate demand for finished products and reduce costs.

Problem

The pharmaceutical industry is characterized by high complexity and dynamism. Pharmaceutical products have a limited shelf life and are subject to strict regulations. Their demand can be affected by factors such as market trends, competition, marketing campaigns, and changes in public policies. In this context, efficient inventory management becomes a fundamental pillar for the profitability and success of pharmaceutical companies. It is estimated that poor stock management can imply additional costs of up to 20% of the inventory value (1).

Accurate prediction of stock levels is critical to optimizing inventory management in the pharmaceutical industry. It allows companies to anticipate demand for finished products, ensuring the availability of raw materials and avoiding excessive costs associated with storage, obsolescence, and immobilized working capital. Additionally, proper stock management minimizes the risk of production interruptions, resulting in greater operational efficiency, better customer service, and a solid reputation in the market (2).

Size of the Problem‍

• 20% additional cost: Poor inventory management can add up to 20% of the inventory value in additional costs (3).

• Median Days of Inventory Outstanding (DIO): 180 days, indicating a 6-month average inventory holding (1).

• Operational efficiency: Minimizing stock-outs and overstocks can lower inventory costs by 10% (2).

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Problem Size

Precisely predicting stock levels is an urgent necessity for the pharmaceutical industry, which operates in a complex and dynamic environment characterized by products with limited shelf life and strict regulations. In this context, efficient inventory management ensures profitability and business success. The consequences of poor prediction are considerable, with additional costs of up to 25% on the inventory value, production interruptions, negative impact on customer satisfaction, and damage to the company's reputation. Conversely, accurate prediction of actions brings tangible benefits, such as optimizing efficiency, reducing costs, improving customer service, and strengthening reputation (4).

Solution

1. Market Demand Predictive Analysis: Using artificial intelligence models to analyze historical sales data, market trends, and public policy changes to predict future product demand. This analysis helps pharmaceutical companies proactively adjust their stock levels, ensuring product availability without incurring excessive costs due to overstocking.
2. Supply Chain Optimization with AI: Using advanced algorithms to assess and optimize the flow of materials and finished products through the supply chain. This includes managing lead times, production capacity, and inventory levels in real-time, allowing for a more agile response to market fluctuations and minimizing the risk of production interruptions.
3. Predictive Model for Stock Level Adjustment: We have developed an artificial intelligence model that uses a balanced dataset with variables such as historical sales volume, production capacity, average inventory, and market demand forecast. The target variable, 'Stock Level Adjustment Needed', indicates whether it is necessary to adjust stock levels, allowing pharmaceutical companies to implement changes based on accurate predictions to maintain operational efficiency and reduce costs.

Data Sources

• Sales and Production Historical Database: Contains information on past sales and production, which is helpful in identifying demand patterns and seasonality.

• Suppliers and Raw Material Prices Database: Provides details on suppliers, prices, and contractual terms, helping evaluate the availability and costs of raw materials.

• Industry Regulations and Policies Database: Offers information on government regulations and policy changes, which are vital for compliance requirements and anticipating impacts on the supply chain.

• Market and Competition Database: Contains data on market trends, competitor products, and changes in consumer demand, aiding in adjusting inventory strategies.

• Inventory and Stock Tracking Database: Records information on inventory levels, movements, and obsolescence, allowing for effective monitoring and precise inventory management.

Citations

1. The power of predictive analysis in cost forecasting - FasterCapital. (n.d.). FasterCapital. https://fastercapital.com/es/contenido/El-poder-del-analisis-predictivo-en-la-prevision-de-costes.html

1. The pharmaceutical industry facing artificial intelligence: an inexorable transformation | Online Articles. (n.d.). https://www.farmaindustrial.com/articulos-online/la-industria-farmaceutica-ante-la-inteligencia-artificial-una-transformacion-inexorab-ZlWfV

1. Ribeiro, R. (2021, October 7). Artificial intelligence in companies: we reveal the secrets behind some successful examples. Rock Content - ES. https://rockcontent.com/es/blog/inteligencia-artificial-en-las-empresas/

1. Melena. (2023, December 18). Warehouse stock management: what it is and how to do it correctly. ARBENTIA. https://www.arbentia.com/blog/gestion-stock-almacen-que-es-como-realizarla/

1. Perri, M. B. (2023, October 17). AI Pharma: the role of artificial intelligence in the medicines of the future | Globant Blog | Globant Blog. Globant Blog. https://stayrelevant.globant.com/es/technology/data-ai/ia-pharma-papel-inteligencia-artificial-medicamentos-futuro/