Most of us don’t shell out hundreds of dollars on personal items or products without being 100% sure that everything fits, meets our standards, and delivers exactly what we need. Organizations make huge investments in technology, but often don’t spend the time upfront to figure out whether the platform or solution fits.
Although technology and automation are supposed to make things simpler, don’t underestimate the “sizing” process. Sizing a new technology involves understanding how processes, manual effort, and volumes that will be impacted by functionality, and what change management is required to successfully implement a new system, automation or platform.
There are plenty of cases of great technology not being properly implemented, thus creating more work or extending cycle times, instead of delivering better results. All too often, organizations end up with problematic outcomes because they didn’t analyze the impact of the tool’s functionality on their environment.
Automate your collections strategy
Collections platforms are a good example of technology that can be both a blessing and curse if you don’t analyze the impact of strategy configuration or work assignment. There are a lot of great collections platforms in the market.
Here at Capgemini, we leverage intelligent automation and our own credit-to-cash (C2C) platform to deliver best-in-class results in our clients’ collections processes, and we’ve implemented a great deal of collections and order-to-cash (O2C) technology for our clients. Ideally, your collections platform should automate more actions than it creates manual tasks – but therein lies the challenge! We reply on our Insights and Data teams to help get it right.
The challenge of excessive or the wrong tasks
Problems occur when organizations fail to analyze data properly. Not all collections systems include enough cognitive components to recognize when collections strategy rules create too many unnecessary tasks and actions vs. the ability to support or resource these actions in a timely manner.
For example, if you’ve implemented collections software within a high-volume collections environment, you’re probably no stranger to task backlogs – resulting from setting up too many steps in the collections strategy, or other rules that result in a manual action. There are lots of examples of teams or clients ditching their strategy and working through Excel-based aging because they were overwhelmed with system requested actions. Using data insights and analytics to model the impact of the collections strategy and collections actions prior to go live gives you time to correct any bad assumptions and optimize design.
Leverage analytics to understand where to automate
The right insights and analytics solution can significantly reduce your manual effort and double the outcome if used to evaluate the volume and effectiveness of tasks before you implement a collections platform or other technology. If you analyze how your customers pay, group your customers by payment habits, know when to email or call, and understand how to properly approach your customer base, you will get solid outcomes with less effort. Analytics can jump start working capital improvements, and make collections strategies fit your people, processes, and technology design.
Read other blogs in this series:
- Leverage insights to understand how to collect from customers
- Adopt an automation-first approach to make your collections strategy more dynamic
Learn more about how Capgemini’s Finance Powered by Intelligent Automation offering helps you navigate the myriad of products, tools and services, enabling your business to benefit from an intelligent solution that combines automation, digital platforms, know-how and insight.
Caroline Schneider has been delivering and designing O2C solutions for clients for over 18 years. She is passionate about delivering solutions to clients to maximize their working capital through technology, automation, and industrialized process design.
Chandrasekhar Nukala has been delivering strategy, consulting, corporate finance, and business & finance analytics projects for over 15 years. His primary focus is solving client business challenges and delivering value using advanced analytics, including predictive and AI, and strategic frameworks.