I’d wager that the majority of Spend Matters PRO members have grown up approaching analytics from a “procurement” and “spend” perspective, rather than diving deep on payables datasets. I’m certainly guilty of this, going back to when I first got into procurement 15 years ago – going back to some early work at FreeMarkets on creating some very basic spend datasets with colleagues in Microsoft Access. Yet payment analytics, especially when looked at together with supplier (and invoice-based) data, presents a potential treasure trove of savings and working capital (and even revenue, potentially) insight, that precious few companies today are effectively mining as well as they could.
The reason for this, of course, is that the origins of spend analysis go back to driving and measuring sourcing strategy and procurement compliance – not looking at how one pays suppliers as a potential source of creating value. In other words, we focused on “Buy” rather than “Pay.”
There’s Truth in Them Thar Invoice Data Hills
In Them Thar Hills, a short comedy flick from the 1930s starring Laurel and Hardy, the two funny men travel to the great outdoors in hopes of healing one of the duo from gout. This is the era of Prohibition and they arrive outside a cabin that was recently used by those making illegal alcohol. To hide their tracks from the authorities before Laurel and Hardy arrive, the moonshiners dump their alcohol into a well, which then the comic pair drink from, thinking it will be healing mountain water. Of course they note the off taste, but they chalk it up to minerals in the water (good for healing, clearly). Following this, comedic chaos ensues, as one can imagine.
There are great lessons in this for procurement when it comes to looking at data. For one, we’re all looking for a “cure-all” – but we also know deep down that such a remedy does not exist and, in fact, the pursuit of such a panacea can lead us down a dangerous path. Yet many of us are willing to try anything except truly looking ourselves in the mirror and remaking ourselves based on tangible metrics (i.e., data).
In the case of P2P data, the equivalent of the quick fix is running basic queries that consider such basic areas as purchase price variance (PPV) for like or similar items, SKUs or services. Other basic queries – again, using datasets focused on supplier and spend data or high-level payables information – include looking at spend that is on-contract vs. off-contract, trending patterns based on both demand and price changes and potentially going deeper on the reasons for variance (e.g., expediting vs. non-expediting).
In short, as a colleague summarized it the other day, traditional approaches to spend analytics go deep by focusing on cost and price (based on what suppliers have charged and other related datasets such as contract information). Yet by going so deep – especially with more advanced queries – procurement might be missing out on a potentially bigger, easier and more consistent prize that is easier to obtain and keeps “paying back” versus simply driving one-time savings opportunities.
Might there be potentially better (or at least supplementary) information sets to start with that focus more on the AP and treasury side of the P2P house rather than procurement alone? And that help avoid the one-off “cures” that we all know do not work in practice (such as identifying savings but never implementing them – and getting caught up on your own perceived successes without realizing that they’re actually dragging you down rather than getting the organization ahead)?
The answer is absolutely and unequivocally “YES!”
How to Find Gold Downstream Before Mining
The reason that we’re spending so much time on teasing out the value of analyzing AP spend data and supplier master data in our “50 Shades of Pay” series is so that you can find a lot of gold in the river without even having to go upstream to the purchase order (PO) mine. And you don’t need too much fancy equipment to find it. You only need to consider a number of fields to start, which should be relatively easy to obtain from ERP and related transactional procurement systems. Some of the fields to consider starting with PO and related data: PO data, retrospective purchase orders (a small scale endemic in many companies designed to make up for a lack of upfront procurement efforts), PO change orders and non-PO spending information. Add to this a few other AP-centric fields and you’re off to the races. These additional fields include:
- Total number of suppliers
- Total number of payments/value
- Payment term(s) and adherence to terms
- Invoice cycle time (receipt/acknowledgement date to actual payment)
- Invoice exception rates
- Invoice rejection rates
- Time for exception to approval
- Value of exceptions and credit notes
- Straight through processing rates
The combination of these dozen or so data fields can yield a far greater number of actual savings and working capital strategies. Even before getting to specific trade financing strategies (which we’ll explore in the second installment of this series), let’s consider some of the basic strategies and tactics that can come out of such an analysis: [Note: some of these may seem incredibly fundamental, but our experience suggests that a great majority of organizations are still leaving many of these opportunities on the table.]
- Double or Duplicate Payments. Even with organizations that have deployed P2P systems, we often observe that some duplicate payments remain which fall outside of the eProcurement, e-invoicing and invoice automation cracks. Of course, moving to proactively stop duplicate payments before they happen should be a primary goal, and (eventually) payment data analysis can help us identify 100% of such activity and take action to reclaim dollars or obtain credits with suppliers.
- Understanding Invoice Posting and Receipt Data. This involves understanding not the day it was received from a supplier, but the day it was actually posted to ERP. The latency in this process – which remains all too common – is representative of AP-process inefficiencies (foundationally) and can also make it impossible to fully capitalize on more advanced financing strategies.
- Payment Performance. Payment performance data – understanding how and when suppliers are paid based on invoice receipt data, payment/contract terms and actual payment dates – holds the key to creating working capital programs such as standardizing or extending payment terms with the promise of paying as promised (potentially in tandem with trade financing programs). Moreover, shifting terms – having the clock tick for invoices based on receipt of invoice vs. invoice date, for example – based on visibility into this and related payment performance information can also unlock working capital and/or drive financing opportunities.
As our analysis continues, we will consider how insight into this type of data can enable more advanced AP, treasury and supply risk management strategies that can complement procurement-centric spend analytics and visibility efforts. Also please continue reading our “50 Shades of Pay” series that is methodically sweeping through not just payment analytics, but PO-centric spend analytics, supply base analytics, and then finally a broader set of richer supply analytics. Spend analytics is the gateway out to them thar hills, and it’s important to remember that using payment analytics downstream in the river is an easy place to find the gold before moving upstream into the hills to really start mining.