Supplier Analytics Help Buyers Release the Cash in the AP Cache

Nick Chaplin
Nick Chaplin
Manager, Professional Services, Coupa Software, United Kingdom

Nick has a long history of implementing and managing support processes within Software as a Service businesses.

Read time: 5 mins
Auto-Matched Invoices Donut Chart

Every buyer knows the cost of doing business with a supplier is much more than simply the unit price of the goods or services delivered.  But how much more? There are costs for implementing the contract, training, changes to internal business processes, contingent services, support, maintenance and many other elements that add to the total cost of acquisition and ownership for anything you buy.

In many cases these costs are hidden, yet we all have the sense that they add up to something substantial.  In some cases these costs are pure administrative overhead that adds no value for anyone. Being able to systematically identify and address these could deliver huge benefits to both buyers and suppliers. The biggest obstacle is getting visibility into these transactions and knowing what steps to take to address them. Coupa supplier analytics can help you do that.

We know that invoice processing is one of the main areas where the costs of trading hide. Up until now, the only ways to understand which suppliers were more expensive to do business with were either to gather anecdotal evidence from the accounts payable team, or export data from the AP system and then try to analyze and interpret it. The latter requires a lot of manual work and the results—if ever accurate at all—are frequently out of date and irrelevant before they can be acted upon.

With Coupa Release 12, announced in October, we’re providing buyers with new analytics tools to begin to quantify these hidden costs. This new functionality grew out of a request from a customer here in the UK who’s leading in adoption of our analytics solution. Their Customer Success team here worked with the customer and the development team in California to build tools to let them drill down into invoice history and pinpoint exactly which suppliers are adding unnecessary transaction costs. We felt this capability would be valuable to any number of customers so we made it generally available in Coupa Analytics in this release. Here’s how it works.

We all know how invoicing should go in the ideal world: When you trade with a supplier, you send them an order, they deliver the goods, you receive those goods and they submit an invoice. All three of those match; the order was approved up front and the invoice is ready to pay.  There’s no mess or background work or accounts payable cleanup on the back end.  These transactions are “touchless” from an AP perspective and require far less effort to manage.

Sounds marvelous in theory, right? Many suppliers would like it to work like that too and will work with buyers to achieve it, because they want their back office administration to be easy. They want their accounts receivable process to be simple, and they want to be paid on time, without chasing invoices. The cost of doing business with these suppliers is lower because when they submit an invoice it doesn’t require a lot of handling.

Then there are suppliers that are more costly to deal with. Now customers can drill down into invoice transactions to see which suppliers are creating the most headaches and costing the most to manage.

It’s one thing to be able to see that you’ve got 2,000 invoices pending approval and 20,000 that have been approved. Our standard tool did that.  But that doesn’t tell you historically what percentage of invoices were a perfect match, how many invoices have been waiting for approval for longer than normal, or which suppliers were responsible for these match failures. In short, it did not tell users what was normal or exceptional, and what was right and what was wrong.

Now buyers can not only see the current state of their invoice processing backlog, but also track metrics and trends on the efficiency of the end to end process, and drill down to understand what is driving the metrics in one direction or another. 

req to invoice cycleInvoice processing times are a strong indicator of AP efficiency. With supplier analytics you can easily monitor this trend.

They can also see things such as, which suppliers frequently submit invoices that need a lot additional handling, such as approvals for price and quantity difference, voids, on-holds and disputed invoices. They can see if the trend is getting better or worse, and then drill down into individual transactions and start identifying problems and remedies.

Maybe it’s that the supplier hasn’t adopted electronic invoicing, and consequently there is a very loose connection between orders and invoices. Maybe by enabling them on the Coupa Supplier Network they can perform an invoice flip which ensures a perfect match and immediate confirmation of approval.

Is the supplier is receiving a high number of free form requisitions, which contain mistakes in the price or description of goods/services required? They could create catalogs or web forms which set the price and specification of the most common orders up front.

Are prices often wrong? It may be that contracted prices are variable from month to month.  For example, index-related commodities such as gas, oil or copper cable fluctuate frequently, and consequently users may place orders with out of date pricing. Working with the supplier on how pricing is maintained, for example by allowing the supplier to maintain catalogs themselves, might solve the problem.

All of this moves the conversation from, “we know there’s this big, opaque lump of inefficiency sitting there in AP,” to “let’s drill into this cache of information and see where we can tweak processes to release the cash locked away in wasted effort.”

With visibility into this big bucket of invoices in the approval process, buyers can easily identify problem suppliers, make changes and also track and quantify the impact of those changes and identify new areas for improvement.

That would be a pretty big task, and near impossible without an analytic solution to help. We think it’s a big leap forward for our platform and our customers, and we’re looking forward to collecting some real success metrics as more customers get further down the road using this capability.