We’ve talked about performance management on this blog several times before. But what if you don’t have any experience with this kind of data collection, analysis, and change implementation? How can you be confident about what changes need to be made? How should you know whether your changes have been effective, or how long to wait before making that determination?
I’m going to assume that you have some experience with managing a queue and holding yourself or your team accountable to staying within certain wait times and average handle times. You may have more experience than that, but even that experience alone has given you the skills you need in order to take the next step and get started with more serious performance management!
You already know how to pay attention to a data point and adjust behavior and/or processes to better achieve your desired result. To be successful at applying those skills to performance management, you’ll want to identify:
- what to ask (metrics)
- how to answer (metrics)
- getting “Before” right (metrics + data collection)
- how to react to “After” (data collection + action)
- your next “After” (data collection + action, perhaps metrics also)
Step One: What to Ask
The first step to getting started with performance management is deciding what question you want the data to help you answer. You’ll want to pick something small, simple, and specific. This is because you want there to be as immediate and unambiguous a connection between your actions and the data as possible.
“How can I improve customer satisfaction scores?” though specific, is too big and complicated a question, as multiple factors impact it. “How can I get more customers to complete satisfaction surveys?” or “How can changing routing for billing questions help to reduce wait times and/or transfers?” are better questions, and incidentally can actually help pave the way towards the bigger question you’re driving towards.
Step Two: How to Answer (And Consider Going One Level Deeper)
Once you’ve picked your small, simple, and specific question, you need to figure out how you’re going to measure the extent to which your changes are having an impact. You probably have a strong sense of how you’ll measure progress just from the question you’ve picked, as it’s usually intuitive to figure out how to measure something simple and specific. However, sometimes you might want to go one level deeper.
If you’re looking to have more customers complete surveys, tracking the rate of survey completion is an obvious metric you can use. But, you may want to take it one level deeper and measure whether certain types of site visitors are more or less likely to complete surveys, and target your solution accordingly. If you don’t have a strong sense for who that audience might be, it might be worth taking a look at visitor monitoring data to identify where the most effective leverage point might be. That said, general survey completions is probably a helpful enough question to guide your performance management efforts, without taking it one level deeper.
Performance management is driven by your vision for how you might improve performance for your team, guided by data collection and experimentation in possible solutions. Going one level deeper with your metrics depends on that vision of yours, and on your comfort level with the data required to determine what’s working and what’s not. So, consider going one level deeper, but by no means feel obligated to if it’s not the right fit.
As a second example- if you’re looking to use routing to reduce wait times and/or transfers, you’ll obviously want to track average wait time and number of transfers per day (or per week, depending on volume), but you may also want to try to identify what causes longer wait times or more frequent transfers.
Perhaps there are certain times of day when staffing is inadequate, but you want to solve that problem with smarter routing rather than with adding more staff to the schedule. In this instance, you’d want to track wait times during this time period apart from wait times during other times of day. When it comes to transfers, perhaps there are certain topics that tier one chat agents are not equipped to handle and so often result in transfers. Rather than resolve that by training all of tier one to handle those specific topics, you want to make it easier to get those conversations to the appropriate agent via routing rather than through a needless transfer. In this case, you might consider tracking transfers and routing for that topic apart from other types of transfers.
The purpose here is to establish the parameters of your problem and how you plan to go about solving it- that tells you what to measure and how to measure it.
Next time, I’ll talk about gathering baseline data and getting started with adjusting processes in response to what you’re learning from the data you’ve been collecting.