If there’s one part of business where mistakes are unacceptable, it’s the order-to-cash (O2C) cycle. O2C is a huge, multi-departmental process, and every part of it must be as accurate and efficient as possible to minimize the risk of profit loss. Digital automation keeps everything running smoothly. How should your company approach O2C digitization?
The first step in any venture is information gathering, and O2C operations are no exception. It’s incredibly time-consuming to collect and evaluate information manually. Data analytics is essential for O2C processes, such as gathering credit histories and evaluating the creditworthiness of potential commercial clients.
Data analytics programs simplify the process by collecting, organizing, and analyzing relevant data. Automated data collection is faster, more precise, and more complete than manual research. And analytics features do much of the requisite evaluation work for you. When reviewing options for data analytics applications, narrow your search to programs that include data points specific to commercial credit.
Cognitive tasks, such as creative problem-solving, require human attention, but it can be difficult to focus on high-level activities when hundreds of smaller jobs also demand attention. Automation frees up human resources for more complex undertakings requiring their intervention. Robotic process automation (RPA) is a valuable tool for the accurate and inexpensive completion of some O2C tasks. The hard part is deciding which functions are appropriate for automation. The more creativity a task demands, the more human participation is necessary.
Automate simple O2C tasks, such as:
- Automated payments can be completed with minimal human intervention, and alert systems are in place to signal when intervention is required.
- Credit management. Collect and analyze external data to evaluate creditworthiness and detect potential fraud and/or security risk.
- Automate invoicing to eliminate the risk of human error.
RPA is extraordinary technology, but there are some tasks too complicated for it. To automate more complex processes, you’ll need to look to a more sophisticated approach.
Artificial Intelligence (AI)
AI, specifically machine learning, can be combined with automation tools to increase functionality. Human brains are optimized for pattern recognition. Computers are designed for calculation and data storage. Machine learning allows for basic pattern recognition in computers — which can process much larger samples of data — meaning O2C tasks can be automated to a previously unheard-of extent.
Automate O2C processes with AI, including:
- AI can take data from analytics and leverage it to identify the best commercial credit customers.
- AI can analyze effective collection methods on a case-by-case basis and implement solutions accordingly.
- AI is capable of dispute management — up to a point. It can collect accurate data on specific cases and recommend a course of action.
Despite its reputation, AI is not capable of creative thinking. Most business processes remain beyond AI’s ability to govern without human intervention. Bots aren’t equipped with a human’s creative perspective. Without the human element, bots are ineffective at marketing and creative problem-solving. They can collect demographics and analyze data to target certain markets, but they can’t implement the creative processes necessary to engage a human response. For proof, look no further than AI attempts at creative writing. While entertaining, AI compositions remain incomprehensible. Any task that demands outside-the-box thinking is better left to human ingenuity.
The O2C cycle is a set of complex, sensitive processes that must be handled with minimal error. Combining digital analytics, automation, and AI simplifies processing, minimizes errors, and boosts O2C efficiency.