Convincing The CPO To Advance Toward Analytics

Artificial intelligence’s penetration into the enterprise back office can be seen in nearly all areas of operation, but the procure-to-pay process is among the most popular targets for AI disruption.

According to McKinsey analysis, troves of data stemming from purchase orders, invoicing and payments – and the fact that procurement touches multiple areas of the enterprise, from strategic supplier relationships and compliance to spend and cash flow management – presents an opportunity for AI to greatly enhance the efficiency of multiple points in the procure-to-pay function.

Chief procurement officers (CPOs) surveyed by McKinsey expect AI to drive annual savings and reduce time spent on sourcing.

As the procurement function explores artificial intelligence, processionals are receiving greater pressure to not only manage procurement, but to reduce spend, enhance strategic business relationships and drive an organization’s overall objectives. Separate analysis from Deloitte highlights how chief procurement officers are struggling with this role.

A survey released earlier this year found that CPOs are most concerned about cost reduction in 2018, though most agree that new products and market development, as well as risk mitigation, are also critical focuses. Yet most (51 percent) believe their existing procurement teams don’t have the capacity or skills to actually deliver on these strategies.

“It’s very hard for businesses to figure out, in real time, what business transactions need,” explained Dilip Dubey, CEO of procurement technology company Xeeva, in a recent interview with PYMNTS. “It leads to pressure everywhere in the procurement process. Because there is so much complexity and so much data that all come together in procurement, it creates friction in the ability for a business to understand, at a granular level, what’s happening.”

This can lead to challenges in strategic decision-making or misalignment among stakeholders, Dubey said.

The overwhelming volume of data and information associated with procurement is an opportunity for artificial intelligence to address these hurdles, however. As Dubey told PYMNTS, this technology goes beyond standard data analytics to not only offer procurement processionals insight into how much a business is spending, but also to solve problems and guide decision makers as they progress toward their overall objectives.

“Data analytics tools definitely have a place in the procurement world, and they can share with you what’s happening,” he said. “Some of them try to go beyond that and be a bit predictive. But they are not able to actually solve problems.”

CPOs and their procurement teams still have to manually assess the next action to take, which takes up a lot of manual hours, said Dubey.

Artificial intelligence, he continued, is able to offer predictions and problem-solving for CPOs in near-real time. Procurement professionals are aware of this opportunity, too: According to Deloitte, CPOs believe that analytics technologies will have the greatest impact on their industry in the next two years. But as corporates continue with their digital transformations, separate analysis suggests the journey to AI adoption, particularly in eProcurement, is not necessarily an easy one.

Just one-third of procurement leaders surveyed by Deloitte are already using cutting-edge technologies like predictive analytics, the report noted. Only 3 percent have predictive/advanced analytics solutions in place, and only 2 percent have artificial intelligence fully deployed within the procurement function. At most, these technologies are largely “being considered,” or don’t have a presence within the procurement function at all, despite the fact that CPOs agree AI could help them achieve increasingly lofty goals.

Procurement teams are dealing with added pressures within their organizations, but their number-one priority remains cost savings. Dubey explained that artificial intelligence can have a direct impact on this area in managing payment structures and controls, as well as indirect impacts via compliance and strategic sourcing.

“Analytics that give you enough insight can give you savings of a dollar or two,” said Dubey. “Artificial intelligence, in real time, can give you savings that are three to five times what a human being can do with data analytics.

“There is great opportunity in this space for artificial intelligence – not just for simple use cases, but to drive massive savings,” he added.

Deloitte’s report suggests that, while adoption of technologies like AI remains low in the world of procurement, the organizations that do deploy these solutions are focusing on advanced analytics to optimize costs and improve efficiencies. Concerning, however, is Deloitte’s warning that the percentage of organizations using analytics technologies for these reasons has actually declined in the last year.

Organizations like Xeeva are pressing for their business customers to make the digitization leap and embrace artificial intelligence in procurement. Investors have confidence in the company, too: The firm revealed a $40 million funding round earlier this month led by PeakEquity Partners.

But for businesses to make that leap, they’ll have to overcome significant barriers. Deloitte found that nearly half of procurement professionals cite a lack of data integration and data quality as their top barriers to integrating technology in procurement, though executives highlighted several additional challenges as well, including limited understanding of data technology and limited skills necessary to embrace analytics tools.

Dubey told PYMNTS that in addition to artificial intelligence, blockchain, machine learning and even virtual reality are also seeping into the procurement function. Collaboration could be key to encouraging procurement leaders to implement these tools. As Xeeva partners with third parties to facilitate payments in its source-to-pay solution, procurement executives could fund success in working with eProcurement service providers for seamless, painless adoption of sophisticated analytics tools.