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FleetPride had a recent surge of customers due to multiple business acquisitions. Managing the large number of accounts became problematic for the small team handling collections. The responsibilities of the collectors included lots of low value manual work. The process was time consuming and needed swift automation to deal with the large number of customers.
Since 2011, FleetPride has added 100 locations and 30,000+ customers due to acquisitions. This increased the pressure on managing such a large base of customers with a relatively small staff of collectors (Customer Service Reps), thus necessitating technology to improve productivity to meet the growth in operations.
The collections department had to perform various low value manual operations for dunning and reconciliation, which was time consuming. With the increase in customers, they needed an optimized way of doing such work.
FleetPride suffered from an excessive number of overdue balances and their speed to collect was less than optimal. High volumes of long collection lead times adversely impacted their cash flow and raised write off risk. After reviewing their situation, the conclusion reached was that they needed immediate advancements in technological, organizational, and process capabilities to effectively process the existing workload. The major operational issues which needed immediate attention were:
FleetPride, Inc. is the America’s largest retailer of heavy duty truck and trailer replacement parts with over 260 branches in 45 states.
Manufacturing & Distribution
America
$1 billion
Collections Cloud
Collections at FleetPride was largely manual. A limited Collections team had to manage a large number of customers. This made things unmanageable and they needed technology to optimize their existing process. Moving forward with automation, the expectations of FleetPride were:
Previously, analysts had to manually aggregate information from ERP such as Past Due invoices and Customer Contacts and reconcile it in huge spreadsheets. This was a time-consuming process and was difficult to track for every customer.
The HighRadius Collections Cloud generates a prioritized worklist that intelligently gathers data and does task prioritization. With this feature, the analysts can directly focus on the dunning process rather than aggregating information.
In their existing process, the analysts had to manually track Reminder Calls, Reminder Mails, and Blocked Orders. This method is prone to errors, and monitoring them regularly is taxing.
The Rules-based Automation allows automated low touch dunning and enables strategic collection activities. The strategic rules used for dunning include prioritizing customers into various buckets based on their payment history and risk class and applies recommended actions for speedy collection. The solution is able to monitor payment commitments, reminder calls, reminder mails, and blocked orders.
The analysts have their own self-generated worklists which allows them to focus on the accounts which need immediate dunning. The accounts have been prioritized based on information from their payment history such as past due duration, past due amount, and risk class. The worklist also suggests actions to speed up the dunning. Rather than collecting customer information from various sources, the solution is able to display all the information in a consolidated worklist. This results in a faster and low-touch dunning process.
The solution sends automated correspondence such as emails in bulk. The solution consists of in-built templates according to the dunning stage of the customer, for example, first past due, second past due, and demand notice. It can be customized at will and has the provision of attaching purchase details of the customer such as invoice copies and payment portal link. It also tracks the communication history with the customer.
The reporting feature provides complete managerial visibility in the collections processes. Its interactive drill down functionality enables a thorough root cause analysis and provides key operational insights. It can be used to isolate areas of growth and identify keys areas for improvement. It allows monitoring metrics and tracking KPIs. It provides a graphical representation of the performance of the analysts