Since I’ve released my dialer framework demo about 2 months ago, I’ve been swamped with many requests from various contact centers around the world – to utilize my dialer framework for the development of a custom made predictive dialer.
For those of you who are not in the know, a predictive dialer is a tool that is capable of analyzing the performance of each agent in a contact center, accurately predicting when his current call will be completed, and thus, start calling outbound to ensure that the agent is utilized as much as possible.
Most contact center managers believe that if an agent is utilized 100% of the day (or at least a close enough number), they will maximize their profits and work will be done faster. This is not always the case, and there are some cases where predictive dialers will be nothing more than a “White Elephant”, sitting in your call center, doing nothing.
Considering the following scenario: We have a contact center selling computer insurance plans by phone. Each agent is trained to make a sale, that is: “Don’t get off the bloody phone without a credit card!”. One of the issues with such a contact center is that there is no-way of predicting how long a sale will take. Lets imagine that one call a sale happens in 15 minutes, while in the next, we start with the kid in the house, move to the older brother, move to the mother, move to the father, ending up making a sale after 35 minutes. In other words, we have no way of profiling an agent, as there is no proper profile to the customers.
So you can argue that by utilizing statistical models and proper targeting of potential customers, we can go about and perform more accurate predictions. However, these predictions will all go up in flames, the minute a deviation from the norm of the statistic happens. We then immediately create a form of ripple effect, that is then carried across the entire contact center.
In the book “The Goal“, by Eliyahu M. Goldratt, the author tells us a story about a group of boys walking in the woods. The group of boys constantly are unable to walk the path at the designated speed, due to various timing and synchronization issues. In theory, a predictive dialer is used to better synchronize the contact center intake (numbers to be dialed), with the contact center’s ability to perform (the ability to make a sale). However, this model fails when the sale constraint is unknown, thus, making the entire model fail.
In most cases, contact centers are better off using “Preview Dialers” and not “Predictive Dialers”, unless, the contact center is highly targeted with its campaigns and sale strategy. A “sell or die” contact center strategy immediately negates the possibility of accurately measuring the contact center performance and bottle necks, thus, having an automatic pace creator in such a scenario will become redundant and will most probably just cost funds.