Industries as complex as healthcare - where multiple stakeholders impact strategy, day-to-day decision making and management - require technology to implement effective collaboration and drive operations in a cost-effective way. Spend savings is of paramount importance across most industries, especially healthcare, as many health systems are facing shrinking margins. Finance teams and supply chains are continuously working together to identify the most lucrative savings opportunities as a result. One often-overlooked avenue for savings is third-party service contracts. On average, U.S. hospitals overspend $39 billion each year on purchased services, or third-party services. Such a significant amount of spend can easily be redistributed to other areas of need or into an organization’s bottom line.

Today, organizations are seeking efficient ways to not just understand their purchasing data – but to draw actionable conclusions from it. With the emergence of tabulating platforms and proprietary analytic systems in the past two decades, supply chains are getting caught in an overwhelming tsunami of “big data” – whereby data volume becomes a challenge in and of itself. Yet, service agreements pose unique challenges, as every contract is customized to an organization’s respective needs. For indirect spend with your third-party partners, a deeper level of sourcing expertise is required to understand where your opportunities lie.

That’s where we differentiate.

Conductiv, with a 15-year track record of successfully leading third-party services optimization, has modeled its analytics engine around a database that captures more than $300 Billion sourced across 615+ service categories. Our platform, engineered with AI and machine learning, also relies on analysts to continuously review and update models in a dynamic marketplace.

Through this expertise, our analysts have identified 10 significant features for successful purchased services analytics.

1) Auto-classify spend files

Utilizing AI and machine learning technology removes the manual effort of classifying spend by category. Your analytics should utilize AI to automatically classify your spend files. Relying

on a manual process takes time and leaves space for human error, which leads to confusing data. Auto-classifying files allows for spend transparency that allows supply chain leaders

to understand spend trends and consolidation opportunities.

2) Identify average category savings using historical data

Having a rich data pool is key to understanding where your organization sits in comparison to your peers. By looking at their average category savings in historical data sets, customers can

anticipate a savings range with a high-degree of confidence in specific categories. This intelligence alerts teams to rising costs to drive negotiation talks in addition to revealing categorical spend averages for future strategic planning.

3) Build a top 15 roadmap

Identifying low-hanging fruit can be key to seeing quick savings and help you understand the best place to get started. Your analytics technology should help you map out a savings plan to address high ROI categories quickly. This will help you forecast your savings roadmap.

4) Identify off-contract spend and consolidation opportunities

Analytics technology should clearly identify and flag off-contract spend for you, enabling you to spot and correct any rogue spending. Making off-contract spend clearly visible is also key to helping you to identify any consolidation opportunities that may help improve your contracts value.

5) Split responsibilities across teams, filter by facility group

Customers should be able to filter analytics by facility group or service line to gain visibility into how spend is being managed across entire departments. These insights enable teams to shift work or provide support to teams across an organization’s ecosystem as needed. Streamlining responsibilities and needs in this way enables teams to quickly align savings targets with their contracts, understand contract value across stakeholders and unite cross-department stakeholders with processes to move contracts through the evaluation and negotiation pipelines more efficiently.

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