According to a recent study by Gartner, by 2024, CIOs and finance teams will spend $3 billion annually on Invoice to Cash (I2C) applications. The pandemic has accelerated the demand for integrated I2C applications as companies look to urgently optimise internal processes and drive faster cash collections.
McKinsey also states that 11% of 1,140 business executives surveyed believe their current business models will be economically viable through 2023. It’s easy to understand why 64% of those execs say their companies must build new digital businesses to succeed.
So, what are the current roadblocks faced by finance teams and how can automation help you get ahead of the competition?
Many organisations rely solely on their Enterprise Resource Planning (ERP) solution for accounting and managing finance. Whilst most ERPs can automate basic finance functions, critical processes such as order-to-cash require specialised automation solutions to optimise processes and positively impact the customer experience.
Organisations expect their ERP solution to optimise resources for stock and sales, but few focus on the important asset of how much money they might be owed through the accounts receivables function.
This places significant risk on cash flow, forecasting, and the ability to deliver a positive customer experience.
Here are our top 3 reasons why you might be falling short when relying solely on your ERP to manage the Order-to-Cash process.
A typical I2C process features many manual touchpoints. This causes errors, makes it difficult to close month and period end financials, and creates a lot of unnecessary risks.
Multiple ERP instances mean staff can find themselves searching in several places; email, spreadsheets, and CRM tools to locate the most up-to-date customer account information.
Team members feel frustrated as they are unable to resolve disputes or follow up on outstanding accounts, impacting customer and employee satisfaction.
An automated accounts receivables platform can provide 95% straight-through cash posting and automated deduction coding. Payments are auto-matched to invoices and AI can be leveraged to apply cash accurately even with an incomplete or inaccurate invoice number.
Ongoing customer communication for payments is an essential part of accounts receivables. How do you know if an invoice has been received? Do you have any early indicators that there is a dispute which will hold up payment? Or are there easy mechanisms for questions to be raised so that any queries can be answered before a payment is made?
Your ERP can work with an automated A/R solution to make this process more transparent. Online invoice tracking will demonstrate when the invoice was delivered, who opened it, and show any questions or disputes as a result.
If a customer has a dispute, they can post this online, automatically notifying the A/R team so they can resolve the issues more quickly without having to go back and forth via post, phone, or email.
These self-service capabilities are now demanded by customers and those who are unable to meet this expectation will likely lose market share as customers will be forced to defect to other brands.
Within an integrated framework, AI capabilities will also process payment history to predict customer disputes and payment dates which impact cash flow forecasting and decision making.
“Vendors are introducing more advanced and predictive analytics enabled by AI. These trends can include early identification of customer at risk, smarter prioritisation of collection activities or better cash application rates through predictive and prescriptive insights for users to improve decision making.”
Many companies are still struggling to get their act together when it comes to data. ERPs provide some basic data analysis but in the area of I2C, many of the issues lie with the large amounts of unstructured data that need to be evaluated every day.
Leveraging AI from an integrated platform allows you to quickly identify any invoices that are past their due date, the amounts outstanding, and which accounts are likely to miss their payment dates. Armed with this information, finance teams can focus on predicting delays for larger payments well before payment is even expected.
As the data pool increases over time, AI can identify patterns and predict the validity of future deduction claims.
“While demand for first-time I2C application purchase is anchored on enabling automation and improving efficiencies, the shift toward an integrated application to manage end-to-end I2C processes has become a key requirement for most finance organisations.”
There is no doubt your ERP is an integral engine, a necessity that drives your business. However, to significantly improve cash flow, leverage data for strategic decision making, and exceed client expectations, you need to optimise your O2C process by leveraging an end-to-end accounts receivable cloud platform.
The two can work together seamlessly to improve working capital, improve customer and employee collaboration and help you demonstrate the true value of your team to stakeholders.
HighRadius were recently positioned as a leader in the first ever Gartner Magic Quadrant for Integrated Invoice-to-Cash Applications.
HighRadius Integrated Receivables Software Platform is the world’s only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway – covering the entire gamut of credit-to-cash.