Effective accounts receivable management is critical to the success of any business, as it helps to improve cash flow, reduce bad debt, and increase customer satisfaction. As businesses grow, effective management of accounts receivable becomes imperative. And there comes a point where thousands of invoices are generated by the organisation, and the manual process of accounts receivable becomes counterproductive for the businesses.
According to a report by Markets and Markets, the accounts receivable automation market is expected to reach USD 3.0 billion by 2024, growing at a CAGR of 12.1% from 2019 to 2024.
The increasing adoption of cloud-based solutions, the need for cost reduction and efficiency improvement, and the growing demand for better customer relationship management are some of the factors driving the growth of this market.
The reason for such an increased adoption is since as businesses grow and the volume of accounts receivable increases, managing invoices, tracking payments, and collecting outstanding balances becomes increasingly complex. Traditionally, businesses have relied on manual processes, such as spreadsheets, to manage their accounts receivable. However, with the advent of automation tools, businesses now have the option to streamline their accounts receivable management.
While a lot of businesses have already welcomed the automation of AR management processes, may are still trying to evaluate the benefits, with costs being one of the deterrents. To invest in a new automation tool, the organisations need to understand the value that they get out of it. And many a times, it is pitted against zero additional cost of existing manpower.
The biggest fallacy is around understanding the real cost of manual AR processes. The costs associated with manual Excel-based processes not only includes the cost of labour, it also includes the cost of errors, and the cost of lost productivity. The labour cost includes the salaries and benefits of the employees responsible for managing the accounts receivable process, such as data entry, invoice creation, and collections as well as employees responsible for data analytics. The cost of errors includes the potential for mistakes in data entry, invoicing, and collections, which can result in lost revenue, chargebacks, and customer dissatisfaction. The cost of lost productivity includes the time spent on manual processes that could be better spent on other business activities.