AstraZeneca Analytics 50 Submission
AstraZeneca is a global, science-led biopharmaceutical company that develops innovative life-changing medicines. In this highly regulated industry, it is vital to operate as efficiently as possible to maximize the availability of high-quality medicines to patients at minimal cost. This starts with having the right manufacturing capacity and plans for the future.
Until 2015, the network capacity design process, which determines investments, capacity and output across the 26 AstraZeneca facilities, had been expansive in time and effort and simplistic in output. To support the changing product portfolio of the company, capital decisions needed to be made quickly while analyzing multiple options and scenarios. So, as part of its operations strategy, an initiative was launched to address process shortcomings, optimize capacity plans and provide a potential benefit of hundreds of millions of dollars. After finalizing the decision criterion and algorithm needed, Llamasoft was selected as the solution provider for its accelerated data modeling capability and a robust supply chain optimizer module.
A dedicated team of experts collected detailed manufacturing data from the sites, which along with the 10-year demand forecast was used to develop and validate the base model. Then different scenarios were analyzed to evaluate potential changes to demand volume and geographic distribution, impacts of divestitures and acquisitions, and expansion, consolidation and rationalization of capacity. The rigorous analysis has provided reliable output and has opened up new options to evaluate, which were previously considered too hard to assess.
The solution and its implementation have been a resounding success. For the first time, this is a truly data-driven approach to long-term capacity planning. The model has been used to evaluate and recommend several network changes to best meet the long-term needs of the company and patients. The solution has not only highlighted potential financial benefit, but has been instrumental in instilling a more conscientious data-driven approach to decision making.