By David Johnson, NICE Systems and Fred Daum, PSEG Long Island
If you manage or support a call center, you have undoubtedly heard the phrase “we need to reduce the call volume.”
More often than not, organizations task the call center staff with leading this charge. You can see why they might think this is a good idea, but it’s a fundamentally flawed approach to call volume reduction.
The call center can handle calls more efficiently, optimize their capacity to take calls, and reduce the number of call backs or escalated calls. Organizations often lose sight of the reasons for the calls in the first place, however. Customers call because they don’t understand their bill, received correspondence from the company, need to make a payment, have an outage or have not had an expectation met, all of which reside outside the the call-center staff’s purview.
The challenge to the entire organization is to identify, categorize and analyze the call volume in a manner that drives change within the departments and processes that are outside the call center. Interaction Analytics is a tool helps do that. It improves a contact center’s quality programs and operational efficiencies that can identify and address the impact of departments and processes outside the contact center’s normal control.
We’ve all been in a meeting where the topic of call volume comes up and is met with “show me the data.” This is where a tool like Interaction Analytics comes into play-it allows the organization to quantify calls being made to the call center and drive changes that improve overall operational efficiencies.
PSEG Long Island (PSEG) offers a ready example. When it launched Interaction Analytics along with Call Quality in 2014, one of the first orders of business was to create call categories and integrate them into a quality plan. PSEG developed 14 categories, including High Bill, Collections, Tree Trim, Payment, Balance Billing and Website. In addition, it established reporting protocols to track several dimensions, including call volume, caller dissatisfaction, number of repeat calls and computer telephony integration (CTI) data on a monthly basis.
This breakdown enabled PSEG to take a holistic look at which aspects of its business were creating a high volume of calls and then actively engage departments and processes outside of the call center to understand their impacts to the customer experience.
This was extremely valuable when modifications to myAccount, the utility’s online payment and account platform, required PSEG’s customers to authenticate and create new passwords. On the surface, the changes seemed simple and the company expected a smooth transition.
After the modifications were made, however, the call center started receiving a higher than normal call volume for myAccount-related issues. The challenge was to quantify the increased call volume with data and prove a relationship between the call volume and the myAccount changes.
Here is how the new solution works: The myAccount call volume was already being captured in the website category with data charted on a weekly basis and broken down by overall volume and percentage of dissatisfied repeat callers (Figure 1). As the chart illustrates, the go live for the myAccount modification (first full week of July) was plotted on the chart and matched the 100 percent increase in call volume and rise in dissatisfaction.
This hard data was further supported by reviewing the returned calls in the category. There was no need to have each agent keep a personal count of the calls, no need to randomly search recorded calls. The data was right in front of the analysts, giving them a clear view of what was driving higher dissatisfaction rate and call volume.
In addition to tracking the call volume, PSEG tracked customer impacts as a percentage of disaffection and repeat calls (Figure 2). Looking at the data, PSEG was able to determine that dissatisfaction rose 22 percent, but repeat calls remained flat, indicating that although customers were upset, their issues were resolved on the first call.
The solution also provides the ability to quantify the impact on average handle time (AHT) which can then be converted into a full-time equivalent (FTE). This allows the call center to approximate how many representatives are required to handle dissatisfied callers along with the impact AHT has the on the FTE requirement. Figure 3 shows the spike in AHT of 31 percent and a doubling of FTE after the modifications were made to the myAccount system.
Interaction Analytics enables companies to quickly identify and quantify the impact of operational changes and modifications to the customer and the call center. Data gained from these analytics systems helped PSEG Long Island identify and create a measurable resolution as the call volumes returned to their steady state. This served as a great lesson learned, produced an overall positive change for the customer and established a precedent for potential future issues.
David Johnson is senior business consultant at NICE Systems. Fred Daum is director of customer contact and billing at PSEG Long Island.
