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Is the problem that services spend is complex or simply that you have bad spend data?

When it comes to services spend, many organizations find it difficult to manage. CPO Innovation reports that “services spending can range from almost 50% to 80% of what firms buy from outside vendors.”

Just like any category of spend, especially indirect, it all goes back to the data. There’s the adage, “if you can’t measure it, you can’t manage it.” We know the goal of an organization is to have as much spend under management as possible — but if you don’t have good visibility into your spend, how can you expect to manage it properly?

In this post, we review the complexity of services spend, the importance of cleansing your spend data, and how doing so can help you manage not just your services spend better but all indirect spend.

What makes services spend so complex?

Organizations are relying more on external workforces. However, services spend is often disjointed. The procurement of services is vastly different than that of purchasing goods and materials. For one, the services procurement market is highly fragmented. Services aren’t even their own category — they fall into various spend categories. Depending on your industry or business, services can range from consulting services to equipment maintenance to cleaning services to contract lawyers and more.

For buyers and services suppliers, the quotation process is often more manual and doesn’t typically occur within an ERP or P2P system. Not only that, but the definitions of services aren’t clear, and there’s no tangible outcome the way there is with a physical good. Many factors can come into play, including KPIs, requirements, the relationship, etc. Not helping the cause, even more, is that service data is often just summary data. You might have a general idea of what services you received, but you lack data regarding the elements, usages or costs of the services provided.

This is where data cleansing and enrichment come into play

Organizations of all sizes deal with large quantities of siloed spend data that’s incomplete, inaccurate and, quite frankly, just imperfect, which makes it difficult to get a clear, complete picture of spend.

By cleansing, classifying and enriching your spend data using a standardized method and a taxonomy that’s agnostic to products and services across industries, you’ll start to experience better spend management.

The taxonomy is important because it allows you to organize and manage spend by grouping it together and creating a common language between buyers and sellers. UNSPSC and NAICS are two of the most universally accepted taxonomies. UNSPSC can be used to classify groups of items or services by common characteristics. NAICS, on the other hand, uses a hierarchical structure to identify the industry, which for services, points well to categories. Although they don’t map directly to each other, utilizing these two taxonomies together helps with simplified item categorization, easier navigation and clearer consolidated spend reporting.

Spend classification isn’t easy, but proper classification can make all the difference in your spend management strategy. Using artificial intelligence (AI) technology is an advantageous way to make classification easier and faster because its machine learning algorithms can learn from the data it receives — whether it’s yours or another company’s. In the right solution, it can cleanse, categorize, deduplicate and also enrich your spend data to provide better attributions in just minutes. The more data it has, the better it can understand and the superior information and insights it’ll be able to return to you.

Good data can help you manage your services spend better

By cleansing and enriching your spend data, you can unlock hidden insights. In a time when spend reduction is a key business initiative for many, who wouldn’t want help uncovering new ways to save? With item-level granular visibility, you’ll be able to view spend by category, supplier, location, buyer and price variances among other insights.

Leveraging AI technology to maximize your classification efforts, will enable you to:

  • Experience improved classification at a supplier level for spend analytics
  • Facilitate supplier discovery for sourcing
  • Automate onboarding of suppliers for procurement and marketplace
  • Gain immediate value from item-level data classification

The lesson?

According to Gartner, “organizations believe poor data quality to be responsible for an average of $15 million per year in losses.”

Be proactive with your spend data. Don’t let poor data quality stand in your way of savings opportunities and driving strategic value, even with your services spend. When you have high quality spend data, you’ll be able to accurately understand what’s going on, establish compliance and control, manage spend appropriately and find ways to save. So, invest in an AI-powered spend management solution that will improve your spend data quality by cleansing and classifying it down the line level. Experience a smarter, faster way to achieve savings and see the difference granular insights can make across all categories of spend, especially services. Remember, better spend data enrichment leads to better sourcing outcomes.

To learn more about Xeeva’s AI-powered, data-driven spend management solutions, click here.