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Are your spend classification efforts relevant and truly moving the needle?

This sponsored Viewpoint article has been provided by Xeeva
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Last month, we examined the current constraints on procurement today and discovered that data spend quality is an issue that’s holding organizations back. Digging in further, we found that spend classification is a big factor affecting organizations’ abilities to get high-quality data. The reality is you don’t know what you’re actually spending in each category. For many procurement teams, getting the insights they need is challenging because classification is painful and time-consuming, and they don’t know how to make things better.

Let’s take a deeper dive into some of the problems with spend classification today:

1. The data isn’t detailed

Low-quality spend data is imperfect due to poor, ill-formed, incomplete or conflicting information. There’s potential for error from manual inputs or sheer indifference on following set guidelines. The lack of definition also has a major effect on data quality, whether it’s part data, service data or any other type. Not only that, but the information that’s there is often just summary data that doesn’t include any details for you to understand and analyze it. When this happens, you have no concept of what was purchased, used or even the costs spent. To address this, organizations end up doing extensive post-analysis RFIs to fill in the blanks and create some understanding, but that doesn’t necessarily allow you to add in all of the missing information.

2. Descriptions lack standards

Without proper standards set in place, there’s a tendency to describe the same thing in multiple ways, based on who or where the data comes from. For example, “glove, rubber, large” is not intuitively the same as “rubber gloves large” or even “guante de hule grande.” Likewise, the same item may be represented by several product codes, depending on where it is used. You’ll also often find that the same descriptions are actually referring to different parts. While other times there are different descriptions for the same part. For instance, a 1/4” hex drive could be just about anything, or in another case, one operation might consider a pneumatic torque wrench an assembly tool, another a power tool, and another a hand tool. All of these distinctions can be highly confusing when trying to understand what your organization is buying.

3. No consistency in the taxonomies used

Most of the industry classifies based on UNSPSC or eClass codes, but the benefits of doing so are limited. While UNSPSC and eClass provide a common industry language with suppliers, they certainly do not help you perform sourcing because the taxonomy is product-based and unable to capture the view that category managers need to actually engage the market. Others do classification based on GL codes or organized around internal commodities or categories, but these usually don’t align with external taxonomy. To make things more complicated, every organization utilizes different taxonomies — and many have a rigid structure that you need to follow. When you have data that is not structured correctly and isn’t consistent across the board, it leads to major challenges.

Organizations often don’t address these issues because dealing with them is time-consuming and can be relatively difficult if you don’t have the right tools or regulations in place.

If you don’t know what you’re spending in each category, you can’t identify or differentiate items appropriately, and you don’t have consistency or standards, what does that mean for your organization?

It’s simple: Your spend classification is not useful! Your organization will never be able to gain control of your spend if your data doesn’t empower you. And if you don’t have a handle on your spend data, you’ll never be able to make insightful decisions or find ways to cut costs properly.

Enhancing your spend classification from tedious to painless

Spend classification doesn’t have to be painful. There are software solutions out there that can make your classification useful, so you can execute smart business decisions. Here are three ways that you can get more from your classification:

1. Align your classification to supply markets

The challenge with universal schemas tends not to be at the commodity level, but in the way the commodities are rolled up. As a purchasing professional, you are dealing with supply markets or a set of competitors supplying the same sets of commodities. So, a taxonomy that recognizes that and allows you to naturally understand the scope and leverage of your purchase in those supply markets empowers the buyer to both shape strategies and maximize outcomes.

2. Supercharge your supply market taxonomy with domain expertise

Utilize a technology that’s flexible enough to incorporate the resident know-how in an organization, but also constrains the flexibility to be useful within supply markets. It will take advantage of everything that your organization knows, while directing that expertise into a supply market-based structure. A solution with flexible taxonomy capabilities lets you use whatever structure you want, be it your own, UNSPSC, GL codes, your accounting system’s, or even a consultant’s, and it will adapt to these different structures for classification. For example, it can understand and be adaptable if in one system gloves are in the category “safety,” while in another they’re under “safety equipment.” Xeeva’s source-to-pay solution goes beyond with its classification capabilities using flexible taxonomy by being able to do so on the fly, powered by AI, in real time — quickly and accurately.

3. Take advantage of advanced AI to granularly classify your data

When you classify your spend data with AI, the classification gets done faster. Like we mentioned earlier, many organizations struggle with classification because it takes too long. If you have an AI-driven solution, like Xeeva’s, that has sophisticated natural-language processing capabilities, it can rapidly classify data records to improve data quality and consistency. State of the art AI is able to process at both a term- and line-item level. It does so by taking unstructured and fragmented data across various systems and performs the heavy lifting of looking at every line item and making sense of it to quickly classify and categorize it based on the taxonomy of your choice — providing you with a complete view of your spend data. Additionally, classification becomes more accurate because the AI is more reliable than humans. Best of all, it frees up (often limited) resources to be more strategic in procurement and sourcing.

By utilizing these approaches, you will get better visibility into your spend data so you can actually see how much you’re spending in each category and get detailed insights into performance.

Xeeva has helped numerous clients improve their classification with our patented AI — allowing them to get real results. With the flexibility to use our pre-defined taxonomy or your own, our software will classify and categorize spend data holistically, looking at every individual line item to deliver improved insights and intelligent recommendations. When organizations have multiple ERP systems and experience challenges in getting an overall view of total categorized spend, our advanced AI can aggregate the data, classify it across all systems, and group it together for an overall view.

Once the spend data is classified, you’re able to use the data to identify trends and outliers, performance, and opportunities. You will gain the ability to track spend by category, thereby leveraging volumes for better pricing with suppliers. You can eliminate tail spend with supplier consolidation. You’ll also be able to identify spend leakage with the intelligence to pinpoint and address it logically based on category. All in all, your spend classification will no longer be painful and time-consuming.

Learn how to take your spend a step further and stop spend leakage by signing up for our webinar, co-hosted with Spend Matters, “Can’t stop the bleeding? Ways to identify & prevent spend leakage in procurement.” Sign up today!

Koushik Kumaraswamy is Xeeva’s vice president of artificial intelligence.

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