Keeping Tabs on Your Spend Data: A Quick Guide

As procurement professionals, we live and breathe data. From tracking supplier performance to forecasting future spend, the numbers we collect and analyze form the backbone of our decision-making. But let’s be honest – sometimes that data can be a bit messy. Incomplete entries, duplicates, and other accuracy issues can creep in and undermine the insights we’re trying to uncover.

We know what you’re thinking – data quality isn’t the most glamorous topic. But stick with us here, because maintaining accurate spend data is crucial, and not just for informed decision-making. That’s right, your data has uses far beyond the typical procurement reports and dashboards.

The many uses of spend data

These days, spend data is the fuel that powers all sorts of digital innovations. Remember those AI and advanced analytics solutions everyone’s been raving about? Well, they’re only as good as the data they’re built on. Inaccurate or incomplete procurement information can lead to flawed algorithms and biased insights.

But the applications of clean spend data don’t stop there. Forward-thinking teams are using their data to identify process improvements, track the impact of new initiatives, and share valuable information with stakeholders across the organization. The better your data hygiene, the more you can leverage it to drive meaningful change.

So, how do you go about keeping your procurement and spend data ship-shape? Let’s dive in.

Start with a solid foundation

The first step is to get your data collection processes firing on all cylinders. That means establishing clear definitions for key metrics, implementing standardized templates for data entry, and training your team on best practices. After all, if the data going in is messy, the data coming out will be a nightmare.

Once those foundational elements are in place, it’s time to start verifying your data for accuracy. Regularly reconcile your procurement records against financial statements and other authoritative sources. Cross-checking the numbers helps you catch any glaring discrepancies. And don’t be afraid to dig deeper with sampling techniques – randomly selecting a subset of records to audit can uncover sneakier data quality issues.

Is it clean? Is it complete?

There are two key factors to consider when it comes to data quality: cleanliness and completeness.

Data cleanliness refers to the accuracy and reliability of your information. Are the numbers and fields in your procurement records free from errors, duplicates, and inconsistencies? Can you trust the data to represent the true state of your purchasing activities?

Data completeness, on the other hand, is about ensuring you have the full picture. Are all the relevant details there? Is crucial data scattered across disconnected spreadsheets, email attachments, and on paperwork? Are there gaps in your records that could lead to incomplete or skewed analysis?

Both cleanliness and completeness are crucial for deriving meaningful insights from your spend data. Without clean, complete information, your reports and dashboards will be riddled with flaws, undermining your ability to make informed decisions.

Whose job is it, anyway?

Maintaining data accuracy isn’t just the data analyst’s responsibility. It’s on all of us to keep our information clean and reliable. After all, we’re the ones inputting the data, approving the purchases, and reviewing performance.

Foster a culture of data stewardship where everyone takes ownership. This means providing clear guidance, offering ongoing training, and empowering your team to flag mistakes or errors without fear of repercussion. Data quality should be a shared priority, woven into the fabric of how we work.

Lean on technology

Of course, manual data checks can only get you so far, and can’t compare with the effectiveness and efficiency of leveraging technology to streamline your data validation efforts. Procurement software with built-in data validation features can automatically flag duplicate entries, incomplete fields, and other anomalies. And data analytics tools can surface trends and outliers that might slip under the radar.

The key is finding the right balance of tools and processes. Maybe you use your procurement platform to set mandatory fields and enforce data standards, then complement that with quarterly deep-dive audits using an analytics solution. The specifics will depend on the size and complexity of your procurement operation, but the core principles remain the same.

Address issues proactively

So, you’ve got your data collection nailed down, you’re verifying everything, and you’ve got the tech to support your efforts. But the work doesn’t stop there. Maintaining data accuracy is an ongoing battle, and you need to be prepared to tackle issues head-on.

Start by developing a comprehensive data quality improvement plan. Outline your key data sources, define acceptable error thresholds, and map out a clear roadmap for addressing problems. Then, get buy-in from stakeholders across the organization. Data quality will continue to be a struggle unless you can break down silos between procurement, finance, and other departments.

Finally, remember to continuously monitor your data processes and make refinements as needed. Procurement is a dynamic field, and your data management approach needs to evolve right alongside it. Stay vigilant, keep your finger on the pulse, and don’t be afraid to try new things.

The payoff

We know what you’re thinking – all this data wrangling sounds like a lot of work. You’re not wrong; maintaining spend data accuracy requires a concerted, cross-functional effort. But trust us, the payoff is more than worth it.

Beyond the obvious benefits of making better, more informed decisions, high-quality procurement data unlocks a world of possibilities. Imagine the insights you could uncover by feeding clean, reliable information into your AI and analytics tools. Or the efficiency gains you could drive by identifying process bottlenecks.

And then there’s the opportunity to reduce spend across major categories by an average of 18% to 22% each year (!) with a group purchasing organization.

Analyzing new GPO member data for savings

When a new organization applies for Una membership, the first thing we do is analyze their spend data to identify potential savings opportunities through the power of group purchasing.

But this analysis is only as effective as the data we’re working with.

That’s why we put such a heavy emphasis on data accuracy and completeness – the more comprehensive and correct the information, the more value we can deliver.

Learn more about maximizing the value you receive from your group purchasing organization: