At AstraZeneca I work in global supply chain and strategy. Most of my time now is spent on our long-term capacity modeling. So looking at the 10-year horizon, looking at demand and supply, and building out a plan of are we fit for purpose for the next 10 years within the company. Getting quality data and putting it into a model or a view that you can feel comfortable with, both not just as a customer within global supply, but the senior stakeholders as well is the biggest challenge. We have a lot of data we need to filter through to get to a true purpose of what the information will give us from a supply chain answer.
For us, Data Guru has been a real positive impact in taking the information that we have, filtering it out, doing some validation steps, and then from the modeling side as well, once that data gives us a baseline, we get asked what-if we change this demand? What if we move these products and assets to these locations? What does that do to the answer that we want to achieve? So by better quality data in, we get better quality data out.
From a time savings, we’ve been 50 percent in turnaround at minimum there. From a cost perspective, we’ve taken an asset of 30 million dollars out of the equation from the capital planning that we thought we needed by running some risk-based scenarios. By running all these different what-if’s, we really could get confidence from Supply Chain Guru, from Data Guru software, to our senior stakeholders to say, “We believe that we don’t need this asset now, and so we can take it out of the capital plan.”