Why Your Procurement Data is So Bad

Spend visibility is one of the most basic requirements for any procurement team. But despite that fact, procurement data is often unreliable or incomplete. How can procurement identify savings opportunities without spend visibility? Put simply – they can’t.

With so much work going into data collection, no one wants to hear that their procurement data is bad, but lack of data hygiene can cause significant issues. Much of what procurement does impacts the larger business so procurement needs to be confident in what they are reporting—and that impact is only growing as new challenges arise. According to a recent study by Ardent Partners, 87% of procurement teams believe their impact grew during the pandemic, making it even more essential to have accurate data to make informed decisions.

You can’t solve the problem if you don’t know what is causing it. And if, as the Ardent Partners study asserts, “critical business strategies at many enterprises will focus on matters that play to the strengths of procurement teams,” procurement needs to have reliable data.

So, why exactly is your procurement data just so bad?

Poor Data Discipline Leads to Bad Procurement Data

Poor data hygiene results in business decisions built on an unstable foundation. In the business world, there’s a common fallacy that revolves around implementations of expensive and sophisticated systems, such as ERP or P2P solutions. It’s often believed that costly, complex tools lead to clean data, but when unsupported by robust data discipline, these systems are only being fed by unreliable data. This is a classic example of more isn’t always better—especially when it’s more bad data.

Processes that lead to bad procurement data include

  • Data input errors
  • Data omissions
  • Miscoding
  • Lack of proper controls
  • Assumptions about data

Bad processes and procurement practices continue to affect downstream data quality and CPOs need to be armed with good data. A recent DeLoitte survey shows that leading CPOs “prioritize data to…make fact-based decisions.”

General Ledger Codes are Designed for Finance, Not Procurement

When it comes to analysis of business spend, finance looks to the GL. GL codes are designed to resonate with the priorities of the finance team, making them largely inapplicable to procurement. Procurement seeks to drive cost savings, which appeals to Finance, but they also strive to identify quality suppliers, enhance the value provided by tools and services, find innovative solutions to business problems, and make purchases that support other business goals, such as reduced environmental impact or improved social responsibility. These benefits are not reflected on the GL code ─ and therefore don’t really reflect the value provided by procurement teams.

In fact, developing a useful category taxonomy for procurement is among the top ways a procurement organization can succeed with a spend visibility initiative. You can’t accurately identify why money is being spent when you can’t map it to a purpose. Procurement needs a “taxonomy that roughly maps on to the way in which categories are organized and managed within the function itself.”

Too Many Systems Lead to Bad Procurement Data

The executive suite loves to see numbers. It’s how they make informed decisions. However, what if the numbers were only based on data from a single system while your data is actually spread across several? That doesn’t exactly make for a truly “informed decision.”

It’s common for procurement to use disparate tools without a single unifying source of truth. From a visibility standpoint, pulling disparate data from multiple systems is the stuff made of nightmares. Reliable data has to come from one source or it will forever remain incomplete.

What Can You Do About Bad Procurement Data?

Bad procurement data is not an ideal operating state, especially in today’s business climate. The DeLoitte survey states that leading CPOs utilize “end-to-end integrated processes and solutions, while the Ardent Partners study reveals that big data “has the potential to become the next major force and catalyst for the profession.” With expectations such as those, you need to make the move from bad to good procurement data.

You do that by starting to:

  • Implement standard processes for collecting data. Implement common operating procedures for inputting data and train your team according to those practices.
  • Define a taxonomy for procurement. Identify which categories you intend to measure and how those will be quantified according to a shared lexicon between finance and procurement.
  • Implement a single source of truth and take measures to ensure 100% adoption. Consolidate all procurement data in one place. That way, everyone is operating on the same source of data and implement practices that encourage large-scale adoption.

The first step for many procurement teams is to identify how they want to begin their roadmap to a system with accurate spend data.  Whether you build versus buy a spend analysis solution, everything starts with your data.

Learn more about the decision to build versus buy and how to identify the right spend analytics solution to inform your procurement strategy.

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