Supposedly low-value calls may convey important information. Mining their content can help companies diagnose problems and make lasting business improvements.
What do you do when the call volumes and costs of your call center are on the rise? If you’re like many managers, you try to automate further. That’s sensible, since automated self-care menus and other applications let you handle higher call volumes and be stingier with staff. In addition, call lines unclog and customers stay relatively happy.
But wait. Those routine informational queries and requests that you’re trying to funnel into automated channels can hold valuable messages for senior managers. So-called low-value calls may be signaling more fundamental problems in areas such as customer record keeping, billing systems, or even product quality. Mining the content of those calls can help you diagnose underlying ills and provide for lasting business improvements.
That’s what a European telecom operator learned when it tried to reduce call center costs while responding to high—and increasing—call volumes. The company had already run out the string on automation by successfully adding voice recognition and other such tools. So it focused on understanding the reasons for the low-value inbound-call inquiries its agents were handling. The goal: perhaps to eliminate both the calls and any underlying service problems.
Getting to the root causes for the calls wasn’t easy. The system that agents used to categorize calls had become complicated over time as new products were introduced (a common situation in many call centers). Few agents fully complied with the tracking procedures. Worse, cooperation between the call center and key business units—marketing and sales, service provisioning, billing, and postsales service—was strained. The business units were convinced that the call center was solely responsible for poor service outcomes. The absence of incentives linking call center activity to the different units’ P&Ls only reinforced the negative attitudes.
To address these problems, the company created what it called a customer care council—a small, permanent team, drawn from across the organization, that was tasked with analyzing incoming calls and identifying problems, determining their causes, and recommending improvements. This group reported to a new cross-functional executive committee, which evaluated the business rationale behind the ideas for improvement and oversaw any changes. Meanwhile, managers created new tracking procedures, performance criteria, and incentives to encourage the business units and the call center to cooperate and focus together on customer service issues.
The effort quickly began to pay off. The call center’s operating expenses and the number of low-value calls fell by 1.5 percent within six months. Customers reported no ill effects. Subsequent pilot projects identified additional moves that managers expect will lower operating expenses by an additional 3 to 4 percent within a year. Notably, many of the recommendations unearthed marketing and communication problems that hadn’t been identified previously (exhibit). Some of the fixes were even product related, including the elimination of a personal identification number that turned out to be a little-known but persistent source of irritation to customers whenever they activated service or upgraded to a new tariff plan.
By tearing down organizational silos that inhibit cooperation, companies can both make call centers more efficient and begin to use the rich customer data they generate as a way to diagnose problems elsewhere. Improved products and services and better communication with customers can follow.