Spend Analytics’ Real-Time Visibility Problem

They say money talks, and if the procurement function is to show its strategic value to the enterprise, savings have to reach the bottom line. Research suggests only a fraction of the savings procurement generates actually do so, however.

The digital transformation of procurement processes promises to land more of those savings on bottom lines, but technological disruption is no easy change to endure. While an end-to-end procurement overhaul may ultimately benefit the balance sheets, ProcurePort Director of New Client Acquisitions and Strategic Partnerships Jemin Patel says APIs have made it easier than ever for companies to take a step-by-step approach to digitally overhauling their procurement processes.

Why that’s important, he recently told PYMNTS, is because a less painful upgrade to procurement systems can deliver easier, quicker access to quality data, and an elevated ability to analyze spend.

“It’s making it easy for companies to implement procurement processes and digitize them faster than they could a few years ago, when they had to pony-up a large amount of money,” he said.

Recent analysis from Deloitte highlighted how high procurement digitization has climbed on executives’ priority lists. As procurement teams explore new technologies, their highest goal is to reduce costs (cited by 78 percent of survey respondents). Accelerating adoption of eProcurement technologies has now armed executives with the quality data they need to assess how they’re spending corporate money. However, according to Patel, spend analysis strategies have largely become retroactive, spaced-out activities that provide limited value to the enterprise.

“Now that data is digitized, it’s easy to do spend analysis and look at historic trends, to look at what decisions to make going forward,” he said. “But what we see is that there is all of this data, there are these strategies being implemented and new data is coming in, but there is no connectivity.”

Procurement leaders may analyze historical spend and implement strategies with suppliers or spend categories as a reaction to that information. Unfortunately, Patel noted, these leaders rarely continue to analyze data in real-time to assess whether or not those strategies are actually working, or whether they should adjust their approach.

“There is a big gap in monitoring what’s happening once a strategy is implemented and comparing it in real-time with data,” he said.

This is the point of friction that ProcurePort aimed to address through the rollout of its newest tool, Spend Trend, a spend analysis software that aggregates data from an array of sources and enables procurement managers to monitor analysis of that data in real-time.

In pursuit of access to real-time spend data, there is an array of strategies the enterprise can deploy, rather than undertaking an entire, end-to-end transformation process of the procurement function. Rising adoption of ePayments, electronic banking and digital finance systems “makes a huge impact on tracking spend in real time,” Patel said, adding that he’s seen an influx in the use of these tools in only the last three years.

Though a gradual approach to digitizing procurement is, perhaps, a more palatable strategy for many organizations, there are technologies that threaten to deliver a more drastic disruption of the function, yet yield greater volumes and quality of spend data.

For ProcurePort, that means artificial intelligence (AI), a technology that Deloitte’s report found to have significant potential in the area of real-time spend analysis by predicting demand, costs and supply sources. However, researchers found adoption of tools like predictive analytics to be low in the procurement space, and procurement leaders “remain hesitant about investigating new digital tools and technologies, such as artificial intelligence, robotics and blockchain.”

Indeed, Patel said, blockchain and AI are some of the largest buzzwords in the procurement space today, but when it comes to distributed ledgers, the technology is not yet viable for easy implementation in the market.

“There is less barrier to entry to push out an AI solution than it is to push out a blockchain tool,” he said. Patel added that AI may have greater potential to offer an immediate impact, not only on the ability to access data, but to automate the cleansing and categorization of that information.

As procurement explores which technologies to embrace, the goal is becoming clearer: digitize data for real-time spend analysis. The benefits of doing so go beyond being able to assess whether past strategies have been effective, Patel said, and have the potential to impact strategic sourcing, cash flow management and a slew of other areas of corporate spend and finance.

“The goal is to give visibility into data so you can create new strategies,” he explained. “One strategy is cash flow management. If you’re spending a lot of money with one supplier, you can put new payment terms in place, for example. We’re trying to close the loop. So, as data comes in, we not only want to show a comparison between original data — which built the strategy for a spend category — and compare. We want to show the procurement team trends so they can have a real pulse on how the numbers are moving as strategies are implemented.”