The credit crisis is creating new opportunities for collection shops to play a larger role in the success of a company. It also creates an imperative for management to foster excellence.
Collecting debt is an undervalued function in the financial sector, and certainly in the eyes of consumers. It marks the end of a once-bright relationship. Now, as collection activity rises along with delinquencies and chargeoffs, financial experts predict problems will dig deeper into accounts that once looked solid. This means competition for the same dollar is greater; and more people collectors are calling are hard-pressed to pay.
In the past, agencies would have managed the problem with numbers. Want better results? Throw more agents at the problem. Dial more numbers. Talk to more debtors. Get more promises to pay.
Those strategies worked well in the old economy. But now, collection companies can’t simply add agents, even though volumes are higher. Collectors in 2010 have to do more with less. Make that: Do better with less. Collecting more debt means creating excellence in collections. Now is a perfect time to perfect four aspects of performance: agent productivity, call effectiveness, aligning customer treatment and metrics.
Boosting Agent Productivity
Why is an 80% utilization rate considered satisfactory when agents are the most expensive part of the collection apparatus? For every hour of every day for every agent, that means giving up 20% with no regrets. What if the expectations were raised just a little, perhaps up to 85% or even 90%? That’s just three minutes a day per agent. Across 100 agents, it’s 300 minutes. That’s like adding five more people - free. Downtime is sheer waste, and it’s the same for smaller centers.
True, the flipside of absolute efficiency is intolerable turnover. Agents are skilled practitioners, not automatic dialers. Setting productivity expectations too high burns out even the best, leaving behind massive training costs and only inexperienced agents.
But there are optimum ranges. Below 80%, agents are bored and missing their incentives. Above 95%, they can’t win, so they leave. But somewhere between 80% and 95%, each incremental percentage gain drives significant gains in dollars collected.
Reaching that rate doesn’t mean driving agents harder. It means using tools that eliminate the main causes of downtime, such as systems that automate and centralize campaign and policy management. Tools like these enable companies to change strategies and campaigns quickly, without interrupting agents. Nobody appreciates uptime more than agents, and their performance will show it.
Improving Call Effectiveness
This is where progressive companies are employing predictive analytics, not just to take certain actions with regard to certain accounts but to not take certain other actions that waste precious resources.
Everybody knows that to keep up the crucial measures of right-party contact and promises to pay, the best time to call is a determining factor and the best time for most people is in the morning or evening. But how does one even out the peaks and valleys, keeping staff highly utilized in the off-peak hours, and possibly remove calls from the morning and evening queues?
Here is an example, and remember, this is all about probabilities that affect the potential value of each call. Collectors might be 80% likely to reach Customer A during the day, but he owes just $100, so the potential value of that call is only $80. On the other hand, the likelihood of reaching Customer B during the day might be only 50%, but he owes $1,000. The potential value of calling him in the middle of the day is $500.
High-value calls need to be queued first. Granted, they may not all be reached then, and the call will have to go back into the evening queue. But the probability of reaching them is higher then, so the potential value of that call is high, too, so collection resources are still being optimized.
To make swift, automatic decisions like that, Collections needs predictive analytics that can specify all those probabilities and more. Which customers need a call before they will pay? Which will come up with the payment, call or no call? With which customers is the company “top of wallet” and will get paid first?
Aligning Customer Treatment
Many opportunities get squandered by the wrong interaction. After all, some customers will pay up without a call. Others prefer to self-serve rather than take a call, so they need a self-serve option. The direct call, the most expensive treatment, should be reserved for those instances where it will deliver the best results. Predictive analytics are more and more powerful in determining what that right treatment should be, customer by customer.
The wisdom of the right treatment has always been there, but it’s more important today. There is a brand new kind of customer showing up in collections these days – people with otherwise many years of spotless credit records who never expected to be in this position and may well have multiple accounts with the same institution.
When the recovery comes, they will either still be there, or they will be with a competitor. These customers are in collection queue. Their experience with the collection agent will either improve that relationship or diminish it.
The right analytics enable collections to be intentional and strategic about knowing the contact. For example: Which ones must we retain if at all possible? Which ones do we just try to collect as much as possible? Having that information allows collectors, in turn, to direct each customer to treatments designed to deliver that outcome. Not only can agencies spend precious resources more efficiently, but they can combine good customer service with good collections practices.
They say “you get what you measure” and collections has mainly measured volumes: How many calls? How many right party contacts? How many promises to pay, etc.
If the goal today is to get better decisions about agent productivity, call effectiveness and customer-centric treatments, collections needs metrics that service them: cost per call, value per call, promises made, promises kept and treatment optimization.
Once they know these things, collectors can prepare better scripts, learn where the company is “top of wallet,” target customers more accurately, reach the right ones earlier, keep from overdialing some customers and underdialing others, and so on.
Metrics are supposed to be about accountability, but traditional collection metrics have tended to be so aggregate, so averaged, as to be opaque. Averages don’t point to remedial actions. If management learns that average after-call work time is 260 seconds, that may be satisfactory but it is not much to act on. What if half of the agents are at three times the average?
Management needs to see the information by agent. They need to compare their best and their worst performers, understand what is driving each and get the worst to improve by doing what the best do.
Likewise for any other “average” metric. Why are some agents outperforming on promises made pay? Do they also outperform on promises kept? Good, specific metrics give managers a way of digging into performance and finding ways to improve. In the end, they will learn vast amounts of valuable information from these metrics, and then feed it back into the analytics for continually improved results.
Today’s economy, while showing signs of improving, remains a harsh reality. But tough times are often the best times to innovate. Now is not the time to ask for more. It’s the time to ask for excellence.
Joe Pratt is collection specialist at ALI Solutions Inc.