The Company

This company, which is part of the pharmaceutical industry, stands out as a fundamental element in the supply chain of one of the world’s largest consumer health companies. As a strategic production partner, it produces a range of globally recognized personal care products. Additionally, it has a vast portfolio of global brands, including skin care, oral hygiene, and over-the-counter medications.

The Challenge

The company faced several supply chain challenges threatening operational efficiency and market demand responsiveness. One major issue was the long lead time in acquiring raw materials. Due to the dependence on purchase orders to initiate the procurement process, the company experienced a lead time ranging from 60 to 270 days. This delay was directly linked to the complexity of managing a global supply chain with multiple international suppliers.

In addition to lead time problems, the company struggled with highly inefficient stock management. It was forced to maintain high levels of stock for high-volume finished products, a costly and risky method.

Furthermore, inefficiencies in the company’s forecasting processes also proved to be a challenge. Previous tools and methods were often inadequate to keep up with rapid market demand changes, resulting in static forecasts that did not reflect market reality, leading to both excess inventories and shortage issues. The inability to accurately predict future needs complicated inventory management and limited the company’s ability to respond agilely to market changes, resulting in financial losses and missed sales opportunities.

The approach

The company adopted a multifaceted strategy involving innovations in processes, technology, and management to overcome challenges related to long lead times, inefficient stock management, and forecasting inefficiencies. Each element of the approach was designed to address the identified problems directly. Below are some of the initiatives:

Implementation of the Procurement to Forecast (PTF) Model

Addressing long lead times for raw materials

The PTF model was adopted to align raw material procurement with future demand forecasts. This allowed the company to initiate orders proactively, drastically reducing production lead time by minimizing dependence on receiving a purchase order first.

Implementing PTF involved sharing dynamic forecasts with suppliers, ensuring that raw materials were ordered and delivered according to the schedule necessary to meet production demands.

Impact on stock management

By better synchronizing raw material procurement with demand forecasts, it was possible to maintain lower levels of finished product stock, reducing costs.

Development of advanced forecasting and simulation tools

Addressing forecasting inefficiencies

Advanced forecasting tools and simulation models were developed to make forecasts more accurate and responsive to market changes. These tools helped the company adjust production and stock levels based on updated consumption data.

Simulating different demand scenarios enabled the company to anticipate fluctuations and act before impacting operations negatively.

Stock risk mitigation

Simulating different safety stock levels allowed the company to determine the ideal balance between maintaining responsiveness and minimizing storage costs.

Process optimization and standardization

Continuous Improvement and Scalability

Process optimization involved mapping and redesigning all production and logistics steps to support the PTF model efficiently. This effort ensured that new standards could be replicated in other units and with other external manufacturers.

An operational playbook was also developed to standardize PTF implementation, ensuring that all teams followed the same procedures and guidelines. This facilitated the scalability of improvements and guaranteed quality across the supply chain.

Results

The strategic improvements implemented resulted in tangible benefits, such as:

• 70% reduction in lead time: A 70% decrease in the lead time for finished products, significantly improving market agility and responsiveness.
• 17% reduction in safety stock: Improved efficiency allowed for a 17% reduction in safety stock, enhancing the company’s liquidity.
• Market responsiveness: Enhanced forecasting tools enabled quicker adaptation to demand fluctuations, reducing the risk of overstock and losses from unsold products.

Issues related to long lead times for raw materials, inefficient stock management, and forecasting inefficiencies are critical and can significantly impact a company’s ability to respond effectively to market demand. However, by implementing the Procurement to Forecast model and developing advanced forecasting tools, it is evident that this operational transformation was successful and has a promising future.