Bridging the Spend Management Visibility/Data Gap

It’s hard for businesses to hold teams accountable for their spend if they don’t have the data. Without knowing the numbers, they can’t ask the right questions to ensure that the teams are driving return on investment.

Aiming to solve that problem, Glean AI developed an accounts payable (AP) platform that uses machine learning to analyze deal terms, line-item purchases, redundant opportunities and negotiation opportunities.

The company has found that when companies do so, they can reduce their vendor spend by 10%.

“How we help achieve that is by giving them visibility they don’t have into their spend,” Howard Katzenberg, founder and CEO of Glean AI, told PYMNTS.

Shining a Light on Specific Line Items

On Tuesday (March 8), Glean AI announced that it raised $10.8 million in seed financing. The company said the funding will enable it to accelerate its growth and technology.

Today, for businesses using the platform, Glean AI compares last month’s spend to this month’s, shows which lines items have changed, tells them if Glean AI’s other customers are paying less for the item and points out items for which the customer might be able to drive a harder bargain.

With machine learning, the platform also spots and highlights things like overage costs. It also sums up the number of overages in a specific invoice and shows the number of overages the company paid in the last four months.

“This is a problem for a lot of companies and it kind of goes under the radar today,” Katzenberg said. “We help shine a light on it so that companies can take action.”

Providing a Single Platform for Quick Control

For too many businesses, there’s not one platform where they’re managing all their spend. They might have one program for AP, another for corporate cards and yet another for expense reimbursements.

“So, there’s not a platform where you can get quick control over everything going on,” Katzenberg said.

Another common problem is a lack of good analytics. Too often, companies find that something has gone wrong only after the accounting close, which can be two or three weeks after the end of the month.

“There’s a lot of things that get missed because you’re looking at things at a category level and, if the variance is below a certain threshold, you’re not going to pick it up,” Katzenberg said.

Inculcating a Culture of Spend Accountability

Integrations are much easier than they were five years ago, creating a greater opportunity for spend management solutions. In the same vein, the machine learning needed to extract line-item data has also come a long way.

Customers’ expectations have changed too, Katzenberg added. They now expect enterprise technology to be as easy to set up and use as some of the consumer technology they are accustomed to using.

There’s a heightened need for spend management in today’s economic environment.

“I think most founders right now are really thinking about, ‘How do I extend my runway given the current market volatility conditions?’” Katzenberg said. “I think a big part of that would just be getting much greater visibility over what we spend and trying to inculcate a culture of spend accountability.”