Pharmaceutical Company Optimizes Inventory Management with Salesforce Forecasting
Highlights
Time Savings
Cost Savings
Reduction in Stockouts
Optimized Inventory
Business challenges
One of our client, a renowned global pharmaceutical company with a vast product portfolio. They were facing challenges with their inventory management system, which resulted in frequent stock-outs, excess inventory, and increased operational costs. In an effort to streamline their supply chain operations, decided to implement Salesforce to improve their forecasting capabilities
issues faced:
- Stock-outs and Delays: The company often ran out of crucial medications, leading to delays in fulfilling customer orders. This not only affected their reputation but also resulted in lost revenue.
- Excess Inventory: In contrast, they also had excess inventory of some products, which tied up capital and warehouse space.
- High Operational Costs: The fluctuating demand and supply variations led to high operational costs. The lack of a systematic forecasting system was a primary contributor.
- Inefficient Resource Allocation: The company struggled with allocating resources effectively, causing bottlenecks in manufacturing and distribution.
Data Points: To address these issues, collected various data points:
- Historical Sales Data: Tracked the sales of each product over the past several years, noting seasonality and trends.
- Demand Fluctuations: Data on unexpected spikes or drops in demand were collected and analyzed.
- Supplier Performance Data: Information on the reliability and lead times of their suppliers.
- Inventory Turnover Rates: Data on how quickly products were selling and how long they were sitting in the warehouse.
- Economic Indicators: Information on economic factors that might affect pharmaceutical demand.
Salesforce Implementation
We implemented Salesforce to address inventory management issues. We utilized the forecasting module of Salesforce, which encompassed the following steps:
- Data Integration: We integrated our past sales figures, variations in demand, supplier performance statistics, and economic indicators into Salesforce.
- Machine Learning Algorithms: The forecasting module of Salesforce employed machine learning algorithms to examine our historical data and project future demand for each product.
- Collaboration: Salesforce facilitated collaboration across our different departments, like sales, production, and procurement, enabling us to coordinate based on the forecasts. Automated
- Reordering: Based on these forecasts, Salesforce automatically created purchase orders to ensure we maintained ideal inventory levels.
Tech-stacks Used
- Salesforce CRM Platform
- Oracle Database
- Salesforce APIs
- Visualforce
Business Results
The implementation of Salesforce for forecasting had a significant impact on the company:
- Reduction in Stockouts: Stockouts were reduced by 70%, improving customer satisfaction and revenue.
- Optimized Inventory: Excess inventory was reduced by 50%, freeing up capital for other investments.
- Operational Cost Savings: Operational costs decreased by 15% due to more efficient resource allocation.
- Improved Supplier Relations: Better forecasting allowed for more accurate orders with suppliers, which improved reliability and lead times.
- Time Savings: The automated forecasting system saved approximately 20 hours of manual work each week.
- Cost Savings: The company estimated an annual cost savings of $2 million due to reduced stockouts and operational efficiency.