Finance and Accounting
How order-to-cash automation transforms financial management?
The order-to-cash (O2C) process, which includes a company’s order processing, order management, and credit management, is a critical aspect that affects the bottom line. It may face bottlenecks and operational inefficiencies if done manually. It is an interconnected series of activities that can make or break a business’s improvements for financial management transformation.
Research has shown that inefficiencies in O2C processes can lead to a significant decrease in pre-tax income, up to 5%. These inefficiencies can manifest as billing errors, miscommunication between departments, disputes, delays, and chargebacks. The financial impact of these inefficiencies is substantial, highlighting the need for a solution. However, financial management automation has the potential to not only eliminate these issues but also increase revenue by 10-15%.
This article focuses on the current financial management challenges that CFOs face and the role of AI-powered order-to-cash automation in addressing these issues. By leveraging advanced technologies, such as AI, CFOs can streamline their operations and drive significant improvements in their financial management processes.
Current financial management challenges for CFOs
In the absence of AI, RPA, and analytics-driven order-to-cash automation, CFOs can be bogged down with heavily manual processes, human errors, and overstaffing. Common challenges they face are:
Pressure to drive innovation
With increasing competition and technology adoption, CFOs are under pressure to drive innovation within O2C processes. Without adopting modern technologies, O2C processes are prone to delays, costly errors, and conflicts, all of which can directly impact the bottom line.
Improve the working capital
Cash flow and liquidity are two critical factors which businesses have traditionally managed by increasing their days payable outstanding (DPO). However, this is no longer an option due to increasing government regulations and the number of options suppliers have. Most suppliers now insist on elaborate contracts with clear terms of payment. Repeated defaults can cause mistrust, and the supplier could withdraw their business, uncovering the need to improve financial management.
Overstaffing and manual tasks
Even after adopting ERP, the O2C process has seen little to no reduction in the number of staff and hours it takes to do a job. Time-consuming manual efforts continue to dominate many areas within finance and directly impact customer order processing, invoicing, chasing for and receiving payments, handling reconciliations, and managing cash. With stringent credit controls and the need to reduce bad debt, the person-hours have increased.
AI-enabled O2C management
Dynamic and forward-looking CFOs must adapt and grow in changing financial markets. To manage large volumes of data within a limited time and with accuracy, they must leverage AI-enabled O2C automation.
Real-time analytics and reporting
With AI-enabled analytics and reporting, CFOs can perform predictive analysis and make informed decisions based on real-time data. For example, the system can flag a consistent revenue leakage that went unnoticed due to manual processes. The finance team can immediately fix it to increase revenue.
CFOs can meet their KPIs, increase profitability, reduce expenses, and deliver solutions based on the client’s needs. Technology also brings transparency to financial management transformation.
O2C process automation
By replacing legacy systems with AI and RPA-based processes, businesses can remove data silos and efficiency blocks across all touchpoints. Centralised data management and real-time access-controlled sharing bring greater visibility and insights across the organisation.
RPA works with AI to extract real-time analytics to simplify manual processes and ensure compliance.
Greater efficiency and accuracy
AI-driven O2C automation handles time-consuming, repetitive tasks and eliminates the need for manual work. For example, AI and optical character readers (OCRs) can extract relevant data from vendor bills, match them with purchase orders, validate them against pre-defined rules, and process payments with appropriate approvals. This increases the accuracy and speed of the O2C process while processing payments within time, thus increasing trust with the vendor.
Collections streamlining
AI uses predictive analysis to identify customers who might be at risk of defaulting payments. This helps businesses optimise their collections process and allocate resources efficiently. AI can suggest personalised collection strategies, increasing the chances of successful debt recovery.
Lower risk of fraud
Traditional fraud detection and correction methods were reactive and often led to revenue loss. Frauds remained undetected for an extended period, making any chances of recovery bleak.
AI algorithms detect patterns and anomalies that indicate a potential fraud before the perpetrators get away with it. It continuously analyses vast amounts of data to search for suspicious transactions, duplications, and unauthorised discounts and saves the business from financial losses.
How can Infosys BPM help in improving financial management?
The end-to-end order-to-cash solutions improve the day’s sales outstanding, recognise revenue early, and elevate the end-user experience. Key niche activities include revenue assurance, pricing analytics, fraud management, plugging revenue leakage, cashflow analytics, and industry analysis.
Read more about order-to-cash automation at Infosys BPM.
