This article previously appeared on Ontario Systems' blog and is republished here with permission.

Your organization’s workflows are likely automated to the point that your agents may not be making many decisions about account treatment – But those they do make have a big impact.

Most agencies determine workflow before accounts are placed and set up in a software platform. And those decisions are often based on successful practices discovered in other lines of business.

For example:

  • Is sending a third letter after the first and second effective? Is it never effective? What are the conditions affecting results?
  • With what account segments does that extra work become meaningful?
  • Are different kinds of work more effective? Do letters get better results than phone calls to a certain group of accounts?

In other words: Which treatments are the right ones to apply to a given set of accounts? How do you find out?

Identifying proper tactics for more efficient operations first relies on analytical skills, and your use of reports, dashboards, and other tools to discover what’s working well and what isn’t. And if you’ve used many different account workflows, and automated them, chances are you have a lot of data to work with.

By treating your data like a trusted advisor and asking it questions, you will very likely discover there is not a single “best practice” when it comes to treating accounts. Some portions of your portfolio will answer your questions differently. For example, you might find a third letter might be twice as effective with one client’s accounts as it is with your average portfolio. Or for accounts over 180 days old, a renewed phone calling campaign might be more effective than a third letter. Perhaps accounts of a certain balance warrant a late stage score and skiptrace effort.

But if you’ve only used a single workflow in the past, this data might be hard to come by. In that case, it may be more effective to ask what little data you have to point you toward your most effective agents within each segment of your portfolio.

If you are not sure where to start, try these 3 tactics:

  1. A/B Testing. Find two batches of accounts that look particularly similar – in lines of business, demographics, score, age, etc. – and separate them, so they can be logged and analyzed apart from one another. If you haven’t done so already, create these batches with an alpha sort on a client assignment. Then, discuss possible treatment among your managers and agents for these kinds of accounts, design workflows for each, and test them. Try sending a letter both before a phone call, or on contact. Try more frequent phone calls with one group than the other. Try changes in caller ID for those calls. Try setting a schedule on one group that calls for three weeks, then stops for three weeks, then comes back for three weeks. When the trial is over, compare the results. How is each batch performing and liquidating? Are the results different than expected? Why?
  2. Give ownership to your best agents. Take one of these segments, and distribute the accounts among your agents. Set automation to ensure compliance and minimum SLAs are met. Establish workflow ceiling and floor rules, and let your agents work within these guidelines, determining the best course of action. Then, review their tactics, and tie them to results. Your best agents will be able to identify weaknesses in the workflow you’ve designed, and inform its refinement. The most effective tactics uncovered can then be set in workflow automation for all agents to follow.
  3. Focus on segmentation. Many agencies fail to place a special focus on clearly delineating treatment for particular groups of accounts, doing so broadly, or not at all. Different account segments very likely deserve different account treatment, perhaps even by different agents. One group of agents might be particularly adept at handling 365 day and older medical accounts, for example, while another might be better on student loans. Segmenting your account inventory makes this process far more efficient. Segmentation can be applied on a much more granular scale than simple business class – retail, medical, student loan, auto deficiency etc. There are very likely unique account segments within each of these lines of business, and they may overlap between each. Scoring is one way to segment across business class. Your own analytics will show you other criteria as well, including previous payers, consumers with a higher than normal number of accounts, geographic regions, age of accounts, and more.

Your system and your agents can tell you a lot. Become acquainted with both, learn how to better apply the skills with which your people are adept, and identify accounts that pay. Becoming close with all these important criteria can lead to big gains for any receivables operation. Enlisting your agents not only provides operational insight, but staffing know-how. That knowledge will ultimately allow you to marry your account analytics to your staff analytics and get the best accounts to each agent.

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Disclaimer: Ontario Systems is a technology company and provides this blog article solely for general informational and marketing purposes. You should not rely on the content of this material for any other purpose or as specific guidance for your company. Ontario Systems’ advice, services, tools and products described herein do not guarantee compliance with any law or industry standard. You are ultimately responsible for your own company’s actions and compliance efforts. Because everyone’s situation is different, you must consult your own attorneys, accountants, and/or other advisors to obtain specific advice on your company’s compliance, legal, tax, regulatory and/or other business needs. Despite Ontario Systems’ efforts to provide current and up-to-date information, you need to recognize that the information contained herein may become outdated quickly and may contain errors and/or other inaccuracies.

© 2017 Ontario Systems, LLC. All rights reserved. Information contained in this document is subject to change. Reproduction of this publication is not permitted without the express permission of Ontario Systems, LLC.


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