Businesses continually focus on discovering ways to reduce costs and enhance productivity. With that approach, the primary target is automating and error-prone and labour-oriented processes such as Accounts payable (AP). As any business flourishes, there comes a time when manual hard-copy invoicing becomes too inefficient to continue. In this article, we majorly focus on explaining how much cost is vested in manual processing of accounting entries and to what extent can these costs be reduced by adopting the automation solutions.
Upgrading to an Automated Accounts Payable system or AP automation is an excellent way to reduce costs and boost productivity. But before explaining the automated system, let’s peep into the costs and pain points that businesses suffer when their accounting operations are manual.
When we studied a survey of organizations that use a fully manual AP approval process, we observed various challenges in their Accounts payable process. Major of them were:
- Manual data entry and inefficient process
- Manual routing of invoices for approvals
- Lost or missing invoices
- Majority of invoices received in paper format
- Lack of visibility into outstanding liabilities
- High number of discrepancies and exceptions
- Inability to approve invoices in time to capture discounts
- Decentralized AP processes
Implementing Invoice Processing and AP Automation:
Organizations are attempting to eliminate these pain points by automating their accounts payable processes, creating an automated invoice management. By adopting automation, they also intend to reduce the cost of administrative operations so that they can redirect those funds towards revenue-generating centres. In addition to it, they can experience the other qualitative improvements that AP automation has on the process itself. So how does the AP automation begin with?
There are two general approaches through which the automation of Accounts payable is accomplished. We will explain them in brief:
1. Template-based OCR Solution: OCR technology that converts printed text into data, is used to extract invoice details. But how does this OCR understand what data to extract? The OCR asks the user to draw zones or boxes around the area that are to be extracted, save its coordinates and return text lying inside it. Oh, wait! Save a minute. Did you just notice the pitfall here?
As the invoice design(layout) changes, the OCR might give absurd values, or worse, will return nothing at all. That means if your layout of invoices is fixed throughout, only then this solution fits your automation. But what if we have thousands of invoices all from different vendors. Doesn’t it need an intelligent tool to learn the fields? The very problem case resulted in the evolution of the next generation of automation, which used machine learning to learn how the invoice field are located relative to other fields and the correct pattern of data to read, let’s understand this now.
- Provides total confidentiality, since is gets deployed on-premise.
- Feasible if invoices come from fixed vendors, with fixed layouts.
- Drastically fails if template design changes.
- Needs retraining for every unique layout. Thus, the user needs to be well-trained.
- Involves multiple costs like costs in annual licenses, installation, training users and administrators, IT infrastructure, maintenance and support.
2. AI-powered, Intelligent Processing: The biggest advantage of AI-based processing is that AI looks at the invoice the same way a human does. Meaning, this AI does not need drawing boxes over templates, since it comes ready with high accuracy on the map. In addition, it keeps on learning as every invoice is processed. Voila, that sounds like magic!
- Training is quick and one time, just takes few hours.
- Digitization advantages inherited: Searching, Filtering, Sorting is just a click away.
- Users can work remotely since it is on-cloud
- Rarely typing required. Just 1-2 mouse clicks for every invoice.
Improvements after AP Automation:
The two greatest overall reported improvements resulting from AP automation are a reduction in paper invoice volume and faster invoice approvals. When compared to the mid-market and SMEs, enterprises disproportionately achieve lower AP processing costs through AP automation. Besides, it is observed that the cost-benefit of automation corresponds with the size of the organization; the larger the organization, the greater the savings. Other benefits that were significantly boosting efficiency were:
- Improved visibility into unpaid invoices
- Lower AP processing costs
- Increased employee productivity
- Reduction in late payment penalties and interest
- Increased capture of early discounts
- Better compliance with regulatory requirements
- Improved supplier relationships
Cost effectiveness of AP Automation
Let’s lastly look into the most crucial, i.e. the financial aspect of these two approaches in AP automation, in comparison with the manual processing of invoices. Many a time, businesses misinterpret the costs by only comparing only the direct costs involved. Unfortunately, many hidden costs show up only after the implementation making it too late for businesses to roll back. Therefore, we focus on making you aware of the comprehensive term – TCO, i.e. Total Cost of Ownership, that includes end-to-end, hidden costs, right from Installation to the support. The table summarizes the comparative TCO you should consider before adopting the right automation solution for your business.
|Parameter||Manual Processes||Template based OCR (partial automation)||AI based Full Automation (KlearStack AI)|
|Technology Stack||Paper||On-premise||Cloud & Browser|
|Installation & setup time||0||Few months||Few Hours to a week|
|Upfront Cost||0||$ 10K – 40K||0|
|Per field Keystrokes||9 keystrokes for a 9-digit field.||Often two clicks in retyping for errors||Single click for validation (even this is optional)|
|Per invoice keystrokes||105||10-20 For rework (Because of OCR errors)||0|
|Time for invoice||250-300 seconds, including validation/rework.||80 – 90 seconds including rework time.||50-60 seconds (with No rework required)|
|Per field data entry time||3.8 seconds (overhead, at avg typing speed) *||1 – 1.5 seconds (only correcting the OCR data)||0|
|Invoices needing rework||12.5 %||10 % (due to poor scans, tilted paper)||1-2 %|
|Full time employee can process per month (Max)||3840 Invoices||7000 – 8000||Nearly 30000-40000.|
|Employee Moral||Unhappy, Burdened||Content||Feel Valued & Excited|
|Time for rework (supervising)||5.5 minutes (if data entry errors are considerable)||2 – 3 minutes||Few seconds|
|Licensing and training||No licensing needed. Nut training can drain few man days||Ranging from $20000 to $40000, depending on companies.||No Licensing. Pay- as- you- use model. No training required for users.|
|TCO – average cost of invoice processing^||$ 2.03 per invoice||$1.03 to $ 4 per invoice||$ 0.25 – $0.50 per invoice|
* – Ref : IOFM time- estimations for manual processing hurdles.
Where is Industry heading?
The evolution of AI-based AP automation has not only transformed the account payable processing lightning fast but also added an entirely new dimension to the overall psychology of employees engaged in accounting operations. Its high time every business, may it be across any industry or domain, adopt this revolution and get a step ahead in the race of profitability.