Accounts receivable analytics is a data-driven approach to managing and optimizing the accounts receivable process. It involves collecting, analyzing, and interpreting data related to customer invoices, payments, and outstanding balances.
Accounts receivable analytics is one such solution that can revolutionize the way organizations manage and improve their cash flow. Let’s discuss the ins and outs of data analytics and dynamic reporting.
Data visibility is a concern among finance leaders that stems from the widespread adoption of multiple data sources. This brings the problem of constantly monitoring huge amounts of data for insights. Advanced data analytics help unify disparate data into a single data source which speeds up reporting and eliminate manual inaccuracies. CFOs get faster closing times, strong auditability, minimized risks, and accurate decision-making with real-time data visibility.
Dynamic reporting or real-time reporting allows access to updated, interactive reports from anywhere and any device. Dynamic dashboards allow CFOs to generate customized financial reports with multiple KPIs to get critical insights. These reports are updated automatically from ERP data.
Global strategy development demands innovative and deliberative executives to set goals, make smart decisions, and gain an edge over competitors. Let’s take a look at two of the major global growth strategies and understand the role of data analytics:
This chapter will compare traditional and advanced analytics and discuss their impact on a business. Let’s start with understanding accounts receivable data analytics.
Accounts receivable data analytics is the analysis of raw data to determine business specific insights that allow finance leaders to get real-time visibility across different AR processes.
In 2022, businesses easily recognize red flags in the O2C process within seconds because of interactive analytics and dynamic reporting. But it was not always like this; traditional methods of reporting and analytics before the introduction of SaaS were:
Let’s take a look at some factors that make traditional methods of reporting inefficient:
Advanced analytics uses sophisticated techniques such as predictive modeling, machine learning, and process automation to analyze large data sets. It offers a broader set of capabilities to address challenges that traditional methods cannot, allowing more effective strategic decision-making.
In this fluctuating economy, CFOs need to monitor crucial KPIs to maintain the business’s financial health. This chapter will discuss the key metrics and their impact on business processes.
All AR processes are distinct and require their own set of reporting and analytics to track valuable insights. This chapter will discuss the reporting and analytics for five crucial AR processes.
Cash application is the process of matching incoming payments from customers with their respective open invoices.
Top three reports:
Collections is the process of recovering outstanding payments from customers.
Top three reports:
Invoicing is the process of issuing invoices, account statements and delivering them to customers.
Top three reports:
Credit management is the process of assessing credit, granting credit, and setting the limits and terms on which it is granted.
Top three reports:
Deductions are the amount that customers do not pay in full for specific goods or services for various reasons, and deductions management is the process of resolving such deductions.
Top three reports:
Cash flow challenges are ubiquitous in the B2B world. Adequate cash availability is one of the most significant components in the growth trajectory of any business. Yet, many CFOs do not have control over their cash flow. So in this dynamic economy, CFOs have started relying on cash flow forecasting to emerge as strategic leaders.
Cash flow forecasting is a vital tool that lets you see if and when you’ll run out of money to plan ahead of time. Some of the most significant benefits it offers are listed below:
Artificial Intelligence (AI) can process, analyze, and detect patterns from vast amounts of historical data to forecast future flows within seconds. Implementing AI in your processes has several advantages over traditional forecasting methods:
The key to understanding your business is advanced AR analytics. It paves the way for optimizing your strategies for business growth. Let’s have a look at the benefits it delivers:
As we have gained a clear understanding of the value of advanced AR analytics, let’s dive deep into a real-world example and see how it is revolutionizing the mid-market:
Ivanti is a Utah-based mid-market company that automates IT and security operations.
Limited Visibility into AR Processes: Ivanti did not use a centralized repository to track reminders, emails, or notes. All kinds of reports had to be generated manually. They had no real visibility into their business operations, especially regarding payments. It resulted in a lack of ownership among teams. Also, there was no visibility for CFOs to analyze the performance of their business functions.
Ivanti adopted HighRadius’s solution, which enabled them to implement reporting frameworks at employee and CXO levels. It helped them gain visibility by tracking performance in real-time and provided a fair idea of ownership of accounts. With intuitive dashboards, the company monitored and analyzed essential metrics. The primary benefit Ivanti gained from the dashboards was cash flow forecasting. Ivanti could get accurate predictions of accounts payable based on consumer payment behavior patterns. It also helped them accurately assess high-risk customers and prioritize accounts.
After implementing advanced AR analytics, they experienced around 20% year-over-year business growth.
Data-driven organizations are increasingly taking advantage of automation to understand customers, track processes, and streamline operations. While the world is progressing, adhering to outdated technology could cost your business more than it saves. Outdated systems make it difficult to compete with other businesses in this digital world. The potential of advanced analytics and dynamic reporting is too powerful to ignore, and being the CFO, you should choose the right technology to help your company grow.
Chapter 07RadiusOne AR Suite is a complete accounts receivables solution designed for mid-sized businesses to put their order-to-cash on auto-pilot. It has three AR modules — eInvoicing & Collections, Cash Reconciliation, and Credit Risk Management to improve productivity and enable faster cash conversion. It provides out-of-the-box reporting and advanced AR analytics to help businesses capture actionable insights and enables end-to-end visibility across AR functions. Some of the highlights of AR data analytics in RadiusOne AR Suite:
Affordable, quick to deploy, and functionality-rich, the solution is pre-loaded with industry-specific best practices to take your business to new heights.
Across the globe, the rise of SaaS-based analytics and reporting has accelerated digital transformation, especially for mid-size businesses and large enterprises. The evolution of analytics from spreadsheet-based reporting to AI-driven advanced analytics is obvious. A big reason for this shift is the need to gain complete visibility over critical processes across departments and globally.
For ages, CFOs have struggled to follow the massive amount of data to uncover trends and insights to support data-driven business planning and strategizing. Today, with advanced analytics and dynamic reporting, CFOs can overcome this roadblock. Now, CFOs can gain rich insights instantly and expand their influence beyond core financial functions.
This ebook is a complete guide for mid-market CFOs to understand advanced analytics in accounts receivables (AR). It unveils the problems and solutions of limited visibility in AR management. In the following chapters, we will draw a comparison between traditional analytics and advanced analytics to understand their real value and discuss how Artificial Intelligence is leveraged in this process to enhance workflows. This ebook also covers the essential metrics that CFOs need to focus on from business and process-specific levels and the impact of adopting advanced analytics to optimize receivables.
Chapter 01Accounts receivable analytics is a data-driven approach to managing and optimizing the accounts receivable process. It involves collecting, analyzing, and interpreting data related to customer invoices, payments, and outstanding balances.
Accounts receivable analytics is one such solution that can revolutionize the way organizations manage and improve their cash flow. Let’s discuss the ins and outs of data analytics and dynamic reporting.
Data visibility is a concern among finance leaders that stems from the widespread adoption of multiple data sources. This brings the problem of constantly monitoring huge amounts of data for insights. Advanced data analytics help unify disparate data into a single data source which speeds up reporting and eliminate manual inaccuracies. CFOs get faster closing times, strong auditability, minimized risks, and accurate decision-making with real-time data visibility.
Dynamic reporting or real-time reporting allows access to updated, interactive reports from anywhere and any device. Dynamic dashboards allow CFOs to generate customized financial reports with multiple KPIs to get critical insights. These reports are updated automatically from ERP data.
Global strategy development demands innovative and deliberative executives to set goals, make smart decisions, and gain an edge over competitors. Let’s take a look at two of the major global growth strategies and understand the role of data analytics:
