Avoid Call Center Schizophrenia from Pay for Performance – Part 2 of a 2-Part Blog Series


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Whenever I have an opportunity to visit a business partner’s call center, I take a few minutes to conduct a rather un-scientific test, call it morbid curiosity.  As I pass by cubicles and am introduced to call center staff, I always ask how agent performance is assessed.  To me, the variety of responses I hear speaks volumes and perhaps helps explain the responses I get from call center agents when I pose the exact same question. Typical responses are a shrug of the shoulders, a shaking of the head and a quick glance to co-workers for reinforcement.  They don’t know, feel they cannot explain the complexities or simply don’t remember.

Call center agents are expected to know and retain more and more information in today’s complex business environments.  Unfortunately, our short-term and working memory capacities have not increased to accommodate this environment.  Agents are also expected to generate customer perceptions that the service was excellent while managing the call to the operational metrics.  Talk about feeling committed…to an asylum! 

If you want your agents to feel less like they NEED to be committed but rather be committed to the customer experience, keep in mind and act in accordance with the very basics of their job expectations.  And be clear about those expectations.  One business partner I visited earlier in 2010 had their KPIs updated in real-time on dozens of flat screens in the call center.  Another business partner created banners as a colorful reminder of the quarter’s call center initiatives.  Great ideas because the agents understood why the KPIs were important, what impact they individually have on them and how they benefit from effectively performing to these.  Don’t assume this is the case without testing your assumption.

A balanced scorecard can serve as a visual cue for agent success.  Well-designed balanced scorecards are typically made up of four parts:

  1. Metrics by which performance will be assessed,
  2. Performance objectives for each metric,
  3. Weighting applied to each metric (an indication of relative importance), and
  4. An individual agent’s performance on each metric.


Selecting performance metrics

Traditionally, call centers have managed performance based on the goal of operational efficiency.  We see this drive for efficiency continue today through the management of call center agents to metrics like average handle time, number of calls handled, after call work, etc.  While these are very important metrics, the fallacy is in managing a call center to only these internally-focused metrics.  Customers do not care how much time an agent has to spend filling out paper-work or electronic forms after the call ends.  Rather they care that an agent is available within a reasonable amount of time when they call.   Customers care even less about how long they need to spend on the phone with a (single) call center agent, as long as the problem has been resolved with that call.  A 30-minute call might end with a delighted customer, a frazzled call center manager and a very confused agent.  Are you seeing the disposition toward schizophrenia now? 

The key to success is in selecting a variety of metrics that speak to the customer experience and balancing them with the business need for efficiency (we will speak more about this balance when we talk about scorecard weighting).  Best-in-class business partners also incorporate other data sources into their agent scorecards such as internal quality monitoring data, chat, text, SMS and email data, etc.


Setting performance objectives

We’ve all been in situations where a goal was picked out of thin-air by a well-intentioned executive and then carved into stone for us to follow.  In the absence of this scenario, the best set goals are based on actual historical performance.  Important elements to consider in setting performance goals are:

  • Mean or Median? (measures of central tendency)- In order to set a goal for future performance, we must first have an understanding of how we’ve performed in the past.  Measures of central tendency indicate the point on a performance continuum where the members of a group or dataset tend to gather.  While the mean (often referred to as the average) is more widely-reported in call centers, it is most useful in groups whose performance is relatively normal (normal from a statistical standpoint, that is).  A normal distribution is one in which a majority of group member performance is centered around the middle of the performance continuum and the distribution of performance is perfectly symmetrical to the right and left– in short, a bell curve.  Unfortunately, this type of distribution is not typical of call center performance.  As such, the median (the point at which half of the group’s members fall above and below) may be a better way to determine how the call center “typically” performs on any given metric. 


  • Time frame of historical data– Having decided whether the mean or median will be the most appropriate statistic for determining a baselineof past performance, we must now define a time frame to represent history.  At bare minimum, Customer Relationship Metrics recommends that at least three months of data be used to minimize the impact of anomalies in performance and non-normative events impacting performance.  Ideally, a larger time frame would be used which encompasses all stages of a company’s business cycle or seasons (1 year).  The danger in using more than a single year of historical data to establish a performance baseline is the possibility of negating or underplaying recent performance gains – essentially making the performance goal too easy to achieve.


  • Predicting the future – Once a historical baseline of performance has been established, the same data set can then be used to make predictions about future performance (statistical modeling).  Performance objectives can then be based around those predictions.  Some business partners have also found some success if applying a 5% to 7% “lift” to historical performance and using that lift as the performance goal for the following year.   


Metric weighting

The weighting applied to each metric on a scorecard indicates its relative importance to the call center and to the larger organization.  Before arbitrarily applying weighting or points to each metric, think about the organizational goals that have been set for the fiscal year and the ways in which the call center contributes to these goals.  Doing so will help you make the first critical decision – whether to focus on the customer’s experience or on organizational costs.  Weighting within each category of metrics (operational vs. customer experience, etc.) can then be determined based on the degree of impact each metrics has on the category outcome (ex: issue resolution has a higher impact on customer experience than courtesy, so issue resolution should have a higher point or weighting allocation associated with it).


Individual agent performance

If one of your goals in implementing a balanced agent scorecard is to keep agents informed about their performance and incite healthy competition, ensuring that your agents have ready access to accurate scorecards will be a key determinant in the success of the initiative. 

During one of my recent visits to a business partner, I took my usual walk through the call center and was quite pleased to see the number of agents who were logged in to Customer Relationship Metrics’ MPM real-time agent scorecards.  MPM (Metrics Performance Manager) is a reporting tool that Customer Relationship Metrics uses as part of our applied business intelligence services to gather data from disparate sources.  We’ve found that one of the outputs of this reporting tool that can be very motivating to agents are the scorecards.  In this call center, agents were actively managing their own performance and receiving immediate feedback from the system about the changes they were making to their interactions with customers.  Feedback from the ACD about their efficiency, feedback from customer satisfaction surveys, feedback from the Quality Assurance team are all in a single location, updated in real-time.  Imagine the burden you would remove from your supervisors if your agents were that tuned-in to their own performance!

Republished with author's permission from original post.

Carmit DiAndrea
Carmit DiAndrea is the Vice President of Research and Client Services for Customer Relationship Metrics. Prior to joining Metrics, Carmit served as the Vice President of Behavior Analytics at TPG Telemanagement, a leading provider of quality management services for Fortune 500 companies. While at TPG she assisted clients in measuring behaviors, and provided management services to assist in affecting change based on newly created intelligence.


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