Ask yourself,‘ What data do I need to tackle this problem?’ That instantly narrows your scope.”
Ask yourself,‘ What data do I need to tackle this problem?’ That instantly narrows your scope.”
For organizations not yet ready for advanced analytics, looking for ways to standardize how you use common tools like Microsoft Excel and business intelligence dashboards can significantly streamline data processing.
“ We often recommend that teams start with familiar platforms like Excel,” says Wells.“ Once they’ re comfortable, they can gradually introduce more sophisticated analytics.”
Leveraging AI Artificial intelligence offers revolutionary potential for healthcare. Lancaster highlights AI ' s unique ability to process vast datasets swiftly:“ AI can rapidly analyze millions of data points and extract a handful of actionable insights. This dramatically reduces manual labor and allows teams to focus on strategic actions.”
Solutions like Medline’ s Mpower™ can provide real-time visibility into supply chain data and automate formerly manual processes, as well.
Overcoming resistance to change Even beneficial change can meet resistance. Wells compares adopting new data practices to moving homes:“ People naturally resist change because they fear losing familiar systems. Ease the transition by using familiar tools first and build trust by demonstrating immediate value.”
Iterative improvement as a long-term strategy Lancaster advocates strongly for iterative improvements.“ Solve small issues first, prove value quickly, and then expand your data strategy incrementally. This ensures sustain- able progress and prevents teams from becoming overwhelmed.”
Looking ahead: The future of data management The next generation of data management tools promises even greater efficiency:
• Advanced AI-driven analytics that proactively identify and solve emerging supply issues
• Enhanced interoperability across all healthcare systems, ensuring seamless real-time data exchange
Organizations that strategically navigate today’ s data overload will gain substantial operational advantages tomorrow. As Lancaster succinctly puts it:“ Mastering your data isn ' t about quantity— it’ s about quality and actionability.”
Healthcare organizations cannot afford to drown in their data. By clearly aligning data efforts with strategic goals, systematically cleansing and prioritizing information, leveraging emerging technologies, and adopting an iterative, manageable approach, they can transform overwhelming data into a powerful tool for enhancing patient care and operational excellence.
“ Ultimately,” concludes Wells,“ effective data management is the difference between being reactive and proactive— between scrambling to resolve crises and confidently managing future challenges.” ◼
Getting in early
The healthcare market is constantly being reshaped by mergers and acquisitions. And while consolidation may be a well-understood trend by now, deals have grown no less complex. That’ s why it’ s so important for supply chain leaders to join discussions early on.
In fact, organizations that bring their supply chain leaders to the table early are better positioned to capture value through contract alignment, SKU standardization, inventory right-sizing, etc. According to research from Ernst & Young, health systems with established cross-functional analytics teams are 36 % more likely to achieve their stated M & A objectives compared with those using traditional siloed approaches. 2 That’ s why supply chain executives must have a seat at the table from day one. Their operational expertise and data insights are vital to hitting goals and timelines.
Data as the strategic differentiator Healthcare organizations have to plan sooner for data integration in the due diligence phases, emphasizing the critical role of supply chain data in M & A success. Modern healthcare supply chains generate vast amounts of operational data— from procurement patterns and inventory levels to vendor performance metrics and compliance records.
Solid data analytics enables precise demand forecasting, optimizes inventory management and enhances operational efficiency. When properly leveraged during M & A discussions, this data provides invaluable insights into true operational costs and hidden inefficiencies.
What to measure before Day 1
• SKU and vendor overlap
• Total cost to serve
• Contract portability
• Distribution network fit
By bringing supply chain experts into early discussions and leveraging their data-driven insights, healthcare systems can lower risk, increase efficiencies, and move toward delivering the promised value to patients and stakeholders alike.
2 Ernst & Young.( 2022). Cross-functional Analytics in Healthcare Transactions. EY Global Healthcare Practice.