Technology Trifecta Can Move AR to New Era
State-of-the-art intelligent technology is transforming AR management and collections automation in the order-to-cash (O2C) process. Finance is process-intensive, but the goal is information. Recording and reporting financials is the first necessary objective, but the information contained therein is critical to understanding and forward decision-making.
The problem has been that gathering and processing all the necessary data is a complicated, difficult, and labor-intensive process. Even with ERP and accounting systems, software applied to discrete functions, and the considerable power of spreadsheets, there has been insufficient interoperability. Important data resides in disparate formats and systems, and it has required much human and manual effort to overcome the gaps. Given the time that takes, the information is always behind the current situation.
Organizations struggle with limited transparency into transactional data and enterprise performance. They typically have multiple systems, manual sourcing of data and errors in data capture, fragmented tools, and poor integration.
It is very laborious to produce one global report on what is happening. Unanswered questions include where is the cash, which customers are paying, where are there healthy patterns, and what are the unhealthy habits of customer payment? It is not easy to bring this information together.
Digital Transformation through Robotic Process Automation, AI and Analytics
Much is being said and written about digital transformation, also called digital business maturity. It will look different for every company. For some, it will involve a complete reinvention of the company. But, for many more, it is about process transformation to strengthen an organization’s competitive position and open new business opportunities and directions.
The critical point is that digital transformation is underway. New technologies harnessed together solve formerly intractable problems like those identified above. These technologies include robotic process automation (RPA), artificial intelligence (AI) and analytics, creating and acting on a collective pool of structured and unstructured data.
Bots take over repetitive manual tasks, from information gathering to dunning letters. Analytics describe, predict and prescribe actions. AI brings machine learning to improve automated processes automatically. AI also provides digital assistance, which enhances the customers’ experience.
Emagia’s Receivables/O2C Automation Platform, recognized by Gartner, IDC, Forrester and others, brings together data from disparate systems, countries, languages and currencies to provide a unified global view of the receivables portfolio. It turns operations from 20 percent automated/80 percent manual to 80 percent automated, with people handling an escalated 20 percent.
Having a global view of your accounts receivable portfolio is paramount. Emagia’s digital O2C platform has prebuilt interface adaptors to pull information from multiple ERP systems to provide a complete statement. For example, a company can now access global total balance, current and aging, risk, customer payment patterns.
The CFO or finance director has dashboard visualizations of the information at their fingertips. At the same time, AR and collection managers and collectors can view the detail by region, business unit, or customer.
Where most organizations find it nearly impossible to get real-time information, digital AR makes it available at any time. This digital AR portfolio is the foundation for digital collections.
Emagia focuses sharply on collections productivity. It starts with the availability of all relevant information in one place, including every document and extensive notes, including promises to pay and dispute records. Emagia’s Collections Workbench automatically sets daily color-coded tasks, driven by strategy and priorities. Collectors can access needed documents in seconds and get quickly to work. The system offers customizable reminder and dunning letters, which the system can send en masse or individually.
With automated process tools in place, the role of the manager shifts to monitoring the data displayed in dashboards and reports. The manager can analyze to see what has happened and what will happen, including cash forecasting.
Cash forecasting is an exceptional part of a fully automated system. Short-term liquidity forecasting is a vital aspect of digital receivables. With all the data available in one place, AI can understand patterns to provide a forecast. To set strategy, the AR or collections manager can see what it would look like if every customer were to pay on time and what cash likely will be collected based on historic customer payment patterns.
In a “black swan” situation, as with the pandemic in 2020, you can look at implications. The system can make forecasts for the entire organization, by region or division. Having this information at their fingertips, AR and collection managers understand what’s happening and can advise the business.
Collections Then and Now
These capabilities long looked for in the past are available today. For example, one of Emagia’s customers, a global $3 billion IT firm, has already transformed collections. Today it has achieved 90 percent automated collections, over 90 percent automated cash application, and 90 percent current accounts receivable, with a customer-accounts touch rate of 100 percent.
Digital AR and collections, part of Emagia’s digital order to cash platform and system, can produce a global report on what is happening. It can answer where the cash is and facilitate its timely collection. State-of-the-art technologies shift the processing burden to machines. The shift reduces error, dramatically increases speed, and, through machine learning, steadily increases accuracy.
Analytics provide up-to-the-minute history as well as predictions and prescriptions. Customer access to information supported by an intelligent digital assistant improves their experience. That is just one part of what digital transformation can accomplish.