Understanding the Collections Maturity Model


This e-book, with research on more than 500 receivables projects, concludes that credit and A/R leaders are more likely to positively impact A/R KPIs if they start with an assessment of their collections operation maturity on 5 key parameters -people, processes, data, collaboration, and technology. The Collections Operations Maturity Model has been devised to help finance decision-makers perform an in-depth evaluation of their current operations and identify clear next steps to advance up the maturity pyramid.

Contents

Chapter 01

Executive Summary: Why Care?

Chapter 02

Why do companies need to re-engineer credit and collections processes?

Chapter 03

The 5 Pillars for Improving DSO

Chapter 04

Understanding the Collections Maturity Model

Chapter 05

Success Story: Dr. Pepper Snapple Group

Chapter 06

Conclusion

Chapter 07

About HighRadius
Chapter 04

Understanding the Collections Maturity Model


Introduction

The collections process is no mean feat. Growth in businesses, through organic and inorganic expansion, has only meant more demand. This has led directly to more transactions with an ever-rising number of customers. The collections challenge is clearly not going away. A great deal of insight into the future of collections management could be gained by looking at how the collection process has matured over the years based on the key success factors. The rest of this section discusses how the top 5 success factors affect processes in the collections maturity model.

  • People: How to make sure that people work as assets and do not inhibit the ability to scale?
  • Process: Is the process the most optimized? How much time is being lost in low-value work?
  • Data: Are the collectors reaching out to the right customers in the right order of priority? Do they have real-time information?
  • Collaboration: Is it easy for collectors to fetch and update data from different teams as well as the customers? Are phone-calls the only way to interact with a customer for an open invoice?
  • Technology: Should collections process start after the invoice is due? In the presence of automation, how much work is left to be done manually?

Evolution of Collections Maturity Model

The collections maturity model consists of the evolution of the collections process from an ad-hoc process to a reactive process into a preventive process and finally into a proactive process. The rest of this section explores these individual process level details.

Ad-hoc Process

Ad-hoc processes focus on the people part of the operation. The most obvious solution to increase the collection output for teams following this process is to increase the number of resources deployed in the collection process. There is little emphasis on improving the actual collection process, improving collaboration or leveraging technology to eliminate the dependence on human resources. Every aspect of collections right from preparing a worklist, contacting customers to reconciling cash is manual. The analyst is the one who is in charge of deciding who to contact and how to contact and the entire collections process is dependent on the skill, expertise, and decisions made by the collector. The process overview is given below: Guide to a proactive collections team The following explores how the ad-hoc process defines the 5 key success factors:

  • People: This process is dependent on human skill and speed to deliver output. They follow the simple equation of leveraging additional resources to handle a larger volume of work.
  • Process: There is no process flow defined across the collectors and each collector works individually on his/her accounts.
  • Collaboration: The analysts collaborate with different departments and customers manually via email or phone calls.
  • Data: Data on invoices statuses is manually obtained from the credit, cash application and deductions teams by the collectors and manually entered into the system. There are no means to log communication details in a centralized manner in this process.
  • Technology: There is zero or very minimal use of technology in day to day work of the collectors since this is a very manual process.

Reactive Process

In this process, some ground-level standardization is adopted into the system. It focuses on the process itself. This helps the collectors to design and define the process flow, however, it is limited to ensuring that the collectors have a ?basic? outlook on the statuses of different customer invoices. This process is the root level standardized and in the absence of a system, organizations depend on individuals to implement credit and collection policies. The process overview is given below: Guide to a proactive collections team The following explores how the reactive process defines the 5 key success factors:

  • People: This process is dependent on human skill and speed to deliver output. There is no visibility into individual collector?s performance.
  • Process: Process flow and collection strategies are defined to some extent. The generation of prioritized worklist is manual and driven subjectively based on the collector?s understanding and level of expertise.
  • Collaboration: The analysts still collaborate with different departments and customers manually via email or phone calls.
  • Data: The aging lists and customer master data are captured from the ERP. However, the collectors need to manually store payment commitments and customer notes.
  • Technology: There is a basic technological support available. The ERP system drives consolidation of the process to some extent.

Preventive Process

A preventive process starts focusing on data to drive decision making in the collections process. This includes generating prioritized worklists for the collectors. This process also leverages information from other creditto-cash processes and includes that information to drive collector activity. It also uses technology for automating clerical tasks such as dunning correspondence. The system uses credit policies and other factors to generate worklists and suggests actions for collectors about customer correspondence. While the collections process is largely standardized, the process is still mildly dependent on collectors and the collections team chases only past-due A/R. Collaboration with buyer A/P teams is still manual. The following defines the process: Guide to a proactive collections team The following explores how the preventive process defines the 5 key success factors:

  • People: There is comparatively a low dependency on human resources as the process is largely automated.
  • Process: Process is streamlined to a large extent and analysts follow predefined collection strategies (derived from multiple parameters) that are able to provide basic recommendations for customer dunning and correspondence activities.
  • Collaboration: Repetitive and templatized dunning correspondence with customers is automated through pre-defined emails and reminder letters. However, a large part of the inter-departmental communication occurs manually via email or phone calls.
  • Data: A comprehensive pool of data is available to drive collector activity. While standardization of data is achieved to a large degree, collectors still need to manually store payment commitments and customer notes.
  • Technology: A stable framework is provided by technology to carry out repetitive, manually intensive tasks in an automated fashion. However, the extent of support required to leverage the collections process as a strategic business operation is limited.

Proactive Process

Proactive Process focuses on leveraging people, process automation through technology and data, for decision making and easy collaboration with other credit-to-cash teams. The collection teams extend the collaboration to their customers by enabling them with a single interface for all receivable related issues, including invoicing and payments to enable seamless customer correspondence. These teams are also able to automate the capture of promises-to-pay from low-risk customers, thereby freeing up bandwidth to focus on the most critical and important accounts. The collection teams stay significantly ahead as they start advancing the axis of the collections process far earlier by leveraging advanced machine learning algorithms to predict the possible date on which a customer could make a payment and therefore chase customers proactively. This considerably optimizes the collection activity and ensures a square focus on accounts that are most likely to be delinquent. These teams are able to achieve the maximum collection output while deploying the least resources and ensuring high levels of customer satisfaction at the same time. The cash is posted automatically once payment is done with no touch. The process overview is given below: Guide to a proactive collections team The following explores how the proactive process defines the 5 key success factors:

  • People: The analyst intervention limited to only calling the most critical customers.
  • Process: Process is streamlined across the entire organization and analysts strictly follow predefined collection strategies based on a variety of factors like account status and history, credit score and risk category. Advanced level of support is available for recommended actions and strategies to drive high impact collection activities.
  • Collaboration: The collectors contact only the most critical customers through the phone while rest are contacted through automated email. Buyer AP teams can now collaborate with A/R team on a common portal.
  • Data: The A/R teams can access all receivables information like invoice status, claim status, customer-related history, promise to pays and call notes under a single roof. The customers can access all account-related information on a single portal and make payments.
  • Technology: The process automates the low-level, time-consuming clerical tasks like manual data extraction from ERP, manual worklist creation and correspondence with non-critical customers. The important aspects of account prioritization using numerous static and dynamic factors, and correspondence with customers through emails are automated. Moreover, technology is able to augment collections efforts by analyzing and predicting customer payment behavior with the goal of driving highly targeted, nuanced and proactive collections activities.

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HighRadius Integrated Receivables Software Platform is the world's only end-to-end accounts receivable software platform to lower DSO and bad-debt, automate cash posting, speed-up collections, and dispute resolution, and improve team productivity. It leverages RivanaTM Artificial Intelligence for Accounts Receivable to convert receivables faster and more effectively by using machine learning for accurate decision making across both credit and receivable processes and also enables suppliers to digitally connect with buyers via the radiusOneTM network, closing the loop from the supplier accounts receivable process to the buyer accounts payable process. Integrated Receivables have been divided into 6 distinct applications: Credit Software, EIPP Software, Cash Application Software, Deductions Software, Collections Software, and ERP Payment Gateway - covering the entire gamut of credit-to-cash.