Invoice Processing Can Be Cheaper: The TCO of Invoice Data Capture (Part 1)
In this series, we focus on everyone’s favorite subject: the cost. Because one way or another, the more business a company does, the more invoices its Accounts Payable will eventually deal with. We unwrap the real Total Cost of Ownership of three basic approaches to data entry – a manual process, a template-based OCR solution, and AI-based cognitive data capture. But it’s not just about a particular pricetag. We are going to unravel an analytical framework that you can take and apply on your business next.
None of us enjoys the routine aspect of AP (Accounts Payable) operations. Pushing invoices around, entering data to internal systems, gathering approvals and getting payments done. It creates little value, but is essential nevertheless. It is “just a cost center”, but the costs can be cut. Its operation is a fixed process, but the process can be optimized.
With modern technology like Artificial Intelligence and Robotic Process Automation, the AP department can be completely transformed. New approaches can turn around all activities, process by process. This improves nebulous qualities like flexibility and transparency, but also very down-to-earth ones – a bill’s time-to-process, staffing issues, and of course the cost.
In this post, we are going to focus on the manual data entry aspect of the AP process. This is the least productive cog in the wheel, ripe for automation, that can, however, absorb some of the biggest costs in the department.
The Actual TCO for OCR
Spoiler alert! We are going to start by comparing the three approaches head to head and throw in some actual numbers. The numbers are based on a fairly typical model scenario. No worries, we will dive into all the details below – and also explain how all the numbers came to be. After all, our real goal is to give you a blueprint to think about data entry TCO in your organization. So let’s measure the efficiency of invoice data capture!
As you can see, the TCO in our eyes is not just the cost itself. We think about the technology – is your company going to be as efficient as your competitors? We think about the implementation time – long implementation creates risks, delays, and just more effort to amortize. We think about the upfront part of the cost – because that makes the risk and uncertainty so much bigger. We think about the total cost – on a per-invoice basis because that makes it easiest to reason about in the whole context of Accounts Payable; a company receiving more invoices is simply going to pay more for that process. And finally, we think about how happy your team is – which would seem to be a separate topic, but our clients actually report staff motivation (and thus retention) as one of their key issues when operating back-office business processes!
You simply need to have the staff to do this work for the organization to function, and how much you spend only comes second.
But now, let’s delve into the meat of the matter for the rest of the series: the technical analysis of the total cost.
How did we get our data?
At Rossum, we strongly believe in data, searching for the actual truth and transparency. Quite honestly, third-party data in this domain isn’t great and published estimates routinely vary by an order of magnitude. Many parties have an ax to grind, or rather sell; so do we, admittedly, but our estimates still come out at the very low end of what’s commonly published. We would simply rather err towards the conservative side rather than draw pies in the sky.
We still quote some of the better sources in the rest of the series, but for the most part, we just go by the data that we have gathered and that represent our typical clients. When a new client comes to Rossum with an interest to improve their data capture process, our automation experts take a deep look at their metrics and experience and measure the efficiency of their invoice data capture. This helps the client to receive the best options for them, but it also gives us quite a good insight into the market and the zoo of all the data entry processes in the world. And the insight on cognitive data capture then, of course, comes from our long-term production clients.
Meet our model company
For the purposes of the TCO calculation in this series, we picked some particulars and calculated costs for a model example of an imaginary company. To give basic context to the numbers above, it feels fair to conclude the first post with the details. So dream with us:
The Corp, Inc. is based in Central Europe, operates in a retail segment and is processing 360,000 invoices per year or 30,000 invoices monthly…
––stop right there, the number of invoices per year is the only number we need to know, no more details necessary, you may think. Well, in order to approximate the costs we need to know much more information about the invoices themselves, who issues them and what is their life cycle within the organization. You are going to see that those specifics will be mentioned as part of the costs for some data extraction methods. So let’s continue!
Their invoices come in as digital PDF and scanned images (we are excluding EDI, supplier portals or P2P platforms) from 2,000 different suppliers, with natural supplier rotation of around 20% per year. Invoices are, on average, 1.8 pages in length, but line item data is not necessary. This makes it just 15 data fields to be captured. The fields are mostly numerical (ranging from amounts to dates and VAT identifiers), averaging 6 digits per field.
Invoice processing may involve up to three other departments that need to be contacted to validate/approve information (procurement in particular). For the Head of AP and managers, we estimate yearly wages of $48,000; for the operators transcribing the data, we will go with $24,000. In this comparison, we are going to use fully loaded costs, meaning all direct and indirect costs of human operators included — from the hiring and training costs, to computer and office overhead to managerial costs stemming from the company structure. Fully loaded costs are therefore $96,000 and $48,000, respectively.
One-time costs of new technology can be quite significant – to be fair, we dissolve them over a period of three years. That would be the typical amortization horizon with the rapid pace of new technology in our model company.
If you are reading carefully, you surely noticed – we stacked this process very heavily towards ease of manual processing! If there is any organization where manual data capture would be viable, it is going to be our model company. Just 15 fields, no line items or even address lines, and comparatively cheap workforce – each of these would make a big dent in the TCO otherwise. We are simply giving the low-tech processes every advantage we can. We will be glad if you share your TCO experience in the comments!
The scene is set, and it’s time to start processing some invoices. How much is that going to cost? We will discuss how to figure out the total process cost in the next post in the series, along with outlining exactly how we arrived to the cost of $2 per invoice in a manual setting.
If you want to analyze your own use-case, book a call with our automation expert here.