From the March 2020 issue of HealthCare Business News magazine
With these elements in place, supply chain is better able to make decisions based on facts. “Fact-based decision making involves using clean data to drive action, rather than gut-feel or a mentality of this is how it’s always been done, so this is how it should continue to be done,” he said. “Accountability and visibility are key for us so we take every step we can to ensure that stakeholders and project team members consistently understand how data fits in and how we use it to make informed decisions.”
Developing a real-time, dynamic dashboard was key to their success. For example, when manufacturers experience shortages, the dashboard enables the team to make sound decisions. “Our dashboard enabled us to have weekly calls to identify day’s supply, pending stockouts, partner on subs, and get ahead of the problem to determine options and solutions,” Bissette said. “We went from having four hours to solve a critical problem — finding a sub on Friday afternoon to get through the weekend — to having five days or greater to work with our value analysis teams to determine best sub, implement communication and training plans, and time to stage the sub for roll out. Another perk with the visibility is the buyers reduced their overstock. Instead of reacting to gut and buying six months of supply when they only needed two weeks, they had real-time data to make best decisions.”
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Implementing these components doesn’t have to include a heavy investment in new technology either. “We leverage existing technologies to create forecast models and dynamic dashboards that end-users can utilize without having to be trained on new software or tech,” he explained. “Prior to our dashboards we would spend several hours trying to figure out the impact of a single back order and drive action around that one item. We had no idea that there was a problem across a product line and that orders were stacking for a particular manufacturer or distributor. With the dashboards we were able to look across product lines, vendors and manufacturers to see problems in real time. We were able to have a vendor change what product went into production first based on our critical low. Because of this partnership and visibility into real-time data, we went from a projection of weeks of no critical stock to a couple of hours or a day.