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Ineffective Call Centers Need Performance Management
By RICHARD SNOW
VP & Research Director at Ventana Research
Advances in technology, tools and an understanding of business processes all lead to a simple statement: You can make your contact center more effective and a more valuable contributor to the top and bottom line.
Ventana Research believes organizations can improve the operational performance of their contact centers by aligning the agents, the processes and systems being used to a common set of business-driven goals. To achieve this, organizations should follow a three-step process we call Understand, Optimize and Align.
To Understand, business managers acquire baseline information that can be used to measure their processes both currently and historically. To Optimize, they employ models and algorithms to create forecasts and plans that can change the way they view the contact center. To Align, they establish procedures for setting goals, scoring, notifying and automating the performance management process.
Managing operational performance in a contact center begins with determining what to measure, how to extract the data from which to derive the measures and how to apply the measures to improve performance.
What to Measure
As regards what to measure and how to find data, most contact centers are managed tactically, focusing on transactional throughput. This approach is typified by the wallboards that display supposed key performance indicators, such as number of calls in each queue, number of calls processed today and average length of call. However, these numbers, taken directly from the telephone switching equipment, really indicate only the efficiency of the center, not its effectiveness in resolving the customers’ issues.
Likewise, companies look at agent performance, but again the measures are mostly transactional – average time taken to handle a call, number of first-time call resolutions, quality of call handling and the like. These performance-related metrics are derived relying on a basic Business Intelligence tool that can extract data from the switching equipment and case management software.
In today’s contact centers, quality measures typically are generated by recording calls, listening to them and subjectively grading how well the agents handled them. These assessments then can be used to shape the training of agents.
Business-Driven Metrics
Developing business-driven metrics – in a sales environment, how many orders were completed, the average length of a call to complete an order or the comparative performance of agents against business-related goals – requires data from a combination of data sources, including the switching equipment and customer relationship management and enterprise resource planning systems. These metrics usually are available to the appropriate level of management and indicate the performance of the center, its team and individuals.
Today advances are being made in measuring and data analysis. Measures can be extended from one to another end of a process, across the enterprise. This capability assists in finding where a process is broken and therefore what action should be taken to improve its overall business performance.
For example, in a technical help desk environment such a measure might identify recurring calls about a common product fault, which could be passed back to manufacturing for correction; in a customer support environment, it might show that misleading marketing materials were generating calls. These uses of metrics represent a move toward analyzing why calls happen; isolating root causes can lead to corrective action that in turn can cut call numbers dramatically.
Analyzing Content
Advances are occurring in another aspect of call center management as well. Many call-recording vendors are enhancing their products to analyze the content of calls automatically, even to the extent of tracking the pitch of the caller’s voice to try to determine his or her mood. Most of these tools also include the ability to "screen scrape" what the agent is doing at the desktop, a feature that can help improve the underlying support processes. For example, an examination may reveal that a particular category of data often is needed at the CSR desk but requires a number of keystrokes to access. This could lead to a redesign to make it easier to extract that data from a business application, speeding agent resolution of a call.
These products eliminate the need for manual analysis and can identify agent training needs and even evaluate true customer satisfaction automatically. In a Voice over Internet Protocol environment, it is possible to do all of this in real time, even to the extent of automatically alerting a supervisor to listen to a call and take control if need be.
Contact centers are notorious for both the diversity of technologies they contain and the proprietary nature of the individual pieces of equipment. In the past, extracting data from them required a lot of custom-built software and high degrees of cooperation among the many vendors, all of which were expensive.
ETL Tools
Fortunately, this is changing. Tools to support extraction, transformation and loading (ETL) of data from one source to another, long a bottleneck, have become much more sophisticated. More importantly, new vendors that focus entirely on contact centers have brought to market software that makes it possible to extract data that previously was unattainable. Once the data is in a common repository, it is relatively easy to do cross-analysis, derive mature metrics and present them in ways meaningful to users.
With more mature metrics are available, the challenge is to use them to improve effectiveness as well as efficiency. Some observers suggest adopting the Six Sigma approach: set targets, measure and reduce variation at all stages until the measures fall within the targets, then repeat with more exacting targets.
The problem with doing that in a contact center is that degrees of variation at the outset are huge because they are people-related. So bringing about improvement is largely a people issue, which means three things are required: training related to individual performance, metrics related to the business objectives and an understanding of them internalized by the agents.
The contact center is one of the key interfaces with customers. As long as the metrics used to evaluate and manage it all relate to transactional efficiency rather than business effectiveness, no new technology will produce improvements in measures such as customer satisfaction and levels of up-selling. The tools are available today, but it is more important that executives set business- and customer-related goals for contact centers and that contact center managers change the processes and train agents to deliver against those goals.
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Richard Snow is a regular monthly contributor to TMCnet. A complete archive of his columns can be found here: http://www.tmcnet.com/tmcnet/columnists/columnist.aspx?id=100035&nm=Richard%20Snow
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