Re-engineering saves

Citation

(1999), "Re-engineering saves", Work Study, Vol. 48 No. 2. https://doi.org/10.1108/ws.1999.07948baf.005

Re-engineering saves

Re-engineering saves

In its quest for continual improvement, global research-based pharmaceutical corporation, Eli Lilly, commissioned a re-engineering project. It wanted to ensure its complex manufacturing supply chain was functioning to the best of its abilities, but also needed a quick, complete and cost-effective analysis of its system without affecting the physical plants or its human resources.

Eli Lilly's Applied Computational Modelling (ACM) group was charged with this task. Their first job was to build a computer model of its biosynthetic human insulin supply chain. This would allow Eli Lilly to determine whether its inventory was correctly positioned to accommodate the variability in the manufacturing cycle times, and to determine whether the inventory levels could safely be reduced, lowering the company's high cost of capital. Micrografx Optima was chosen as the modelling software that would carry this out.

To simplify the task, the model was restricted to its North American Humulin manufacturing supply chain. The data and modelling structure would be replicated later in other manufacturing plants and supply chain efforts. The supply chain was then mapped across 15 different departments, using Optima's integrated swim-lanes. Each activity symbol was assigned data, such as duration, cost, capacities and resources.

After the data were entered, ACM ran multiple simulations, from one day, to annual "snapshots". The results, available in both graphical and tabular format, validated overall cycle times, inventory, shipping, and resource utilisation levels. But what if uncontrollable circumstances shut down a bulk plant for 60-90 days? With Optima, ACM just changed the formula of the transaction generators, schedules and cycle times, and re-ran the simulation. The result: if Eli Lilly would switch to accelerated processing during emergencies, the customer service levels at the end of the chain would not be affected by any downtime at the front of the chain.

Using Micrografx Optima for modelling and simulation allowed Eli Lilly to perform analysis of its biosynthetic human insulin manufacturing supply chain quickly, completely and cost-effectively. The impact of various factors, including a major disaster, on the overall supply could now be estimated with a high degree of confidence and without affecting the physical plants or its human resources.

The process contributed to a better understanding of the supply chain and, as a result, to improved decision making. At the end, Eli Lilly was able to reduce its bulk inventories without any shortage impact on shipments, resulting in a net present value saving of over $8 million.