Keeping inventories at optimal levels is extremely difficult when a company produces more than 10,000 pharmaceutical products, and each has a different demand pattern.

A major European pharmaceutical distributor and retailer found that they had excess inventory of some products and not enough of others, couldn’t consistently fulfill immediate availability for their drugstores, were spending too much on storage costs, and spending too much time on manual stock forecasting.

Optimizing stock levels was a continuous challenge.

The company’s warehouse stores about 10,00 products from 200 suppliers and ships inventory every day to their 36 drugstores. “Optimizing the quantities and types of products always in stock was a continuous challenge,” said the company’s CEO. The company sought a demand-forecasting tool that would allow it to more accurately determine required stock quantities and replenishment frequencies.

One of the key requirements for the application was the ability to calculate an optimal stock level for each pharmaceutical product and to indicate the service quality associated with a given stock level. This service level is key: For instance, it calculates what the chances are for a retail customer to be helped directly, given a certain inventory level. The higher the immediate availability of a pharmaceutical item, the lower the forecasting risk that the retail customer will go to another drugstore. The goal is to provide continuous high service levels while reducing warehousing costs.

SAS DDPO handles the entire forecasting process accurately

A SAS DDPO solution was developed to handle the entire forecasting process, from data collection to reporting. It aggregates information from historical sales figures, stock levels, product prices, and other sources and forecasts demand on a weekly basis. It also suggests optimal stock levels, taking into account frequencies for product orders and corresponding service quality for every stock level.

With the SAS solution, inventory managers can analyze the system’s suggestions in detail and decide whether to modify them. They can also run simulations like checking the effect of less inventory on service levels. This helps establish optimal inventory levels for the entire network, taking into account central stocks as well as local stocks at drugstores. This was not possible with the previous forecasting system. The new SAS DDPO solution also features a monitoring and alert system in case inventories fall below a specified level.

Great precision in forecasts and flexibility in reporting

Advanced statistical methods are now used for both fast- and slow-moving items, which allows for great precision in forecasted data. It also provides the flexibility to adapt statistical parameters to market realities and changes in demand patterns.

The system also features extensive reporting capabilities. Purchasing managers at the warehouse have easy access to standard performance reports which contain data on the service levels for each product, the differences in local stock levels between drugstores, and much more.

Top managers can also access reports to follow up on the correlation between service-level evolution and inventory cost evolution. They can also check that the monetary value of the total inventory remains within pre-defined limits. SAS DDPO can also compare the company’s performance figures to industry benchmarks and legal requirements regarding product availability.

“The reporting feature is proving to be of great assistance in making more appropriate decisions, and in verifying where we stand in comparison with the rest of the sector,” observes the CEO.

SAS solution provides immediate returns on investment

The SAS DDPO solution yielded immediate quantifiable returns. Product availability rates reached 99%; inventory costs decreased 10%; inventory turns increased 5X; and the company’s service-level increased by 3 percent, to 97 percent of its target. As a result of these improvements, earnings increased as stock-outs declined. Armed with accurate demand forecasts and a clear picture of its inventory, the company now has more working capital, which was previously tied to inventory, and a better picture of when, where and how often each product needs restocking.

“Our return on investment was actually reached within one year.” said the CEO. “Overall product availability has improved while inventory costs have gone down. Stock rotation has increased, which means the working capital has diminished. Staff efficiency has also improved, and our forecasting has gained in precision. Both our drugstores and our retail customers now enjoy improved service quality,” concluded the happy CEO.


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