Distribution Service Agreements (DSAs) have continued to evolve over recent years especially as they relate to how they evaluate channel performance. For the most part, manufacturers structure the agreements to ensure trade partners effectively and efficiently fulfill downstream orders, manage volatility of orders, maintain appropriate inventory level (as defined by manufacturer), and transmit data to manufacturers.

As the industry matures in how DSAs are structured, we are seeing trends of new concepts such as misses being incorporated into agreements. However, what is very interesting is how much the industry has validated the efficacy of DSAs. Even as the agreements are getting more complex, I don’t know if the industry really knows if DSAs are working to drive improved channel performance. That is why the release of Scorecard Analytics is so exciting.  Our Scorecard offering is the first fully automated and configurable end-to-end platform for distribution agreement management, improving the profitability and quality of national account relationships. With the new Scorecard Analytics enhancement, life sciences suppliers can now view and analyze their Scorecard data longitudinally by their various metrics, trade partner sets, and product sets. They can view this data one trade partner at a time or in aggregate. This allows manufacturers to run robust analyses to determine if, in fact, their DSAs are improving channel performance.

By pulling Scorecard Analytics data into our IntegriChain Builder business intelligence tool, life sciences manufacturers can create robust visualizations that make it clear how trade partner performance is linked to DSA payments. They can choose to include all of their trade partners, product sets, and metrics in the analysis. Once this data is in IntegriChain Builder, it is simple to create drill paths that allow a manufacturer to easily see how metric performance varies by trade partner, how one trade partner compares with another trade partner, how the “big three” compare with the rest of the market, and more. This information can help guide conversations with trade partners and lead to improved performance by underperformers.

To round out the analysis, manufacturers can pair up payment data with the performance data to really see how effective DSA payments are driving channel performance. Payment information can be viewed by three categories: opportunity, pre-adjusted, and final. Opportunity reflects the maximum payment a trade partner could receive for a given metric – the maximum basis point award. Pre-adjusted refers to the actual payment a trade partner would receive prior to any overrides, exclusions, or adjustments are applied. Final refers to the actual payment provided to a trade partner – net of all adjustments, exclusions, and overrides.

Paired with both performance and payment information, life sciences manufacturers can begin to see how well their trade partners are performing over time – compared with each other and in aggregate. With this intelligence, manufacturers can now really begin to take a close look, quantitatively, at how well DSAs are driving channel performance.

Join us for our next post where we discuss how Scorecard Analytics can be used to help with structuring new DSAs.

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About the Author

Sunay Shah

Sunay Shah

Vice President, Product