7 Key Strategies on How to Optimize Data within the Supply Chain


Tue Mar 29 13:00:26 CDT 2016

As one of the most data-driven departments within a healthcare organization, the supply chain is playing an increasingly important role in reducing costs and improving patient outcomes.


This fall, Modern Healthcare Custom Media, in partnership with Covidien, invited three prominent supply chain executives to participate in an exclusive roundtable discussion about this topic.


The roundtable event was moderated by Fawn Lopez, Vice President and Publisher of Modern Healthcare, and our panelists included Joe Dudas, Vice Chair of Category Management at Mayo Clinic, Vance Moore, Senior Vice President of Operations at Sisters of Mercy Health System and Nancy LeMaster, Vice President of Supply Chain Transformation at BJC HealthCare.


What was discussed? Here are 7 key takeaways. Watch the full webcast.


1. Standardization and automation are key to success. Many supply chain executives, like Joe Dudas, are working with suppliers to convert product identification numbers to GS1 standards. Other industries, such as retail and manufacturing, long ago perfected standardization and automation to lower costs while accurately meeting demand. Standardization will help clean up supply chain data in healthcare, while automation is important in reducing human error and waste, with potential savings in the millions.


2. Get an outsider’s opinion. Independent analysts can help clean and analyze your data in fresh and innovative ways. They’ll also be able to devote the time and attention needed to adequately understand your data so your organization can channel it to drive decision-making. Vance Moore from Mercy Health, for instance, mentioned third-party vendors helped value his organization’s data between $20-40 million.


3. Don’t wait for perfection. Data transparency is the best (and quickest) way to clean your data to make it more effective. Your data will never be perfect, said Nancy LeMaster from BJC HealthCare, so there’s no use in waiting to release it into the hands of your employees. Working with data in real-world instances will reveal its practical applications, as well as the areas where it may not be so practical.


4. Know what you’re looking for when it comes to analytics. Data mining is a project by itself, which is why it is important to understand what you’re looking for before diving into the analytics. Joe Dudas from Mayo Clinic suggested first dissecting the questions you’d like answers to and identifying the problems you are trying to solve. Then, create a data infrastructure to get answers to those questions in a peer-led forum and a platform to bring transparency within the entire organization.


5. Find the right talent – not necessarily from healthcare. The right people are critical to transforming data into an organizational asset. And healthcare experience is not necessarily important in a resume – in fact, data and analytics experience from other industries can bring your organization fresh perspectives to shine new light on your data.


6. Urge partners to rely on data when talking up products. To invest in accountable care initiatives, providers need to be purchasing tools and technology that is worth the expense. Encourage vendors to reference data when discussing how and why their new or upgraded product will improve patient outcomes.


7. Share, share, share. Start a dialogue with your trading partners about transparency. Ask about their costs and ask for suggestions about how to be more efficient. Not all will be receptive, but those who are may turn into one of your more cost-effective partnerships.