Why Measure Team Effort?
Team effort is the collective amount of time that customer-facing teams allocate to supporting your customer experience.
CX leaders measure team effort to understand, manage, and scale their overall cost of serving customers. According to Gartner, customer-facing teams typically account for over two-thirds of the customer experience operating budget. Because headcount is a primary driver of your cost of service, measuring and reducing team effort is your biggest lever for reducing service cost, thus increasing ROI on your investment in customer experience.
Successfully measuring team effort means that you need to understand what’s causing team effort. Identifying what’s hardest for your teams helps you prioritize actions that need attention — whether customer expectations need re-setting or your teams need more resources like cross-functional support, technology, additional headcount, or supplemental training.
Measuring team effort helps you understand how effectively you allocate resources across the many moving parts of your customer experience. It can reveal mismatches that might not otherwise be obvious. Not all customer issues are created equal — ideally, you want to spend more resources solving severe problems that threaten your customer relationships than you do on a handful of innocent annoyances. Customer relationships, too, are not created equal. Ideally, your engagement model with your enterprise customers will look very different from your freemium customers. But in the fast-paced flurry of daily customer interactions, the only way to be sure is to measure team effort.
CX teams that measure team effort can easily understand where team time goes vs. where team time should go. As a result, they can allocate resources to correcting expensive imbalances and design operations that simultaneously delight customers and keep cost of service in check.
The Usual Suspects Don’t Capture Team Effort
Many CX leaders look to a laundry list of traditional metrics to help describe the customer-facing team’s contribution to customer experience. Employee experience (“EX”) surveys help companies understand how employees feel about their jobs and can help reduce turnover. Quality assurance (“QA”) rubrics assess things like employees’ tone during customer interactions, which can contribute to customer satisfaction. Operational metrics like first-response time (“FRT”), average handle time (“AHT”), and escalation rate help gauge the team’s efficiency. These metrics are crucial to measuring and delivering a great customer experience, but none capture team effort.
EX surveys can help you understand how difficult teams feel their jobs are — they might even show you that customer-facing teams are tired of repeatedly applying the same band-aids while cries for cross-functional support go unanswered. But they won’t tell you exactly what those band-aids are costing your organization in place of a more permanent solution.
QA rubrics tend to focus on factors that are within your team’s control, and with good reason. However, issues outside your team’s control can often consume the most resources — think incorrectly set customer expectations, persistent bugs, or delayed feature releases.
Operational metrics can also mask significant differences in team effort. For example, suppose you’re using case volume as shorthand for team productivity. In that case, you could easily misinterpret instances where fewer but more complex, higher-effort cases have a materially more positive impact on your customer relationships than a larger volume of simpler ones.
But what else do all of these metrics have in common?
Team Effort is Upstream of EX, QA, and Operational Metrics
Each of these metrics is heavily influenced by team effort. If customer-facing employees’ jobs are harder than they need to be, EX, QA, and process metrics will all suffer.
When customer-facing teams repeatedly tackle the same problems without cross-functional support, CX teams will suffer from low morale, expensive high turnover rates, and low Employee Promoter Scores (“EPS”). If customer-facing teams have to manage too much complexity, issues will surface later in QA scorecards. If your team isn’t empowered to solve customer problems with the right tools on their own, then operational metrics like AHT and escalation rate will suffer.
The common denominator across each of these unfortunate scenarios is a higher cost of service. And that limits your capacity to make wise investments in your CX, hurts your customer relationships and your ability to compete.
But you don’t have to wait for frustration and inefficient processes to show up in less-than-stellar QA scorecards, EPS surveys, and operational metrics. Instead, you can measure team effort to find out what’s hard for your team early and help make their jobs more enjoyable and more productive.
Trying to improve these metrics without measuring team effort is like trying to run a mile faster simply by doing it over and over again. You might get there eventually, but you’ll meet your goal much faster and more predictably if you optimize your speed by identifying and removing some of the friction that makes running fast harder for you. You might be more inclined to run fast at different times of day, on different surfaces, or find that what you eat and drink (or don’t) beforehand makes a big difference in your performance.
If every time an agent solves a problem is like trying to run that mile faster, solving some problems might feel like running in heels after eating a bacon cheeseburger. By contrast, others are more like running in performance shoes after a light snack. As a CX leader, your ability to differentiate between these scenarios at scale, regardless of the mile time, er AHT, and set your team up for success is critical to improving your team’s performance and reducing service costs.
Let’s say you’ve recently released a new integration. As customers begin to use it, you see an uptick in related inbounds. The integration is new to your customer-facing teams, too, and these inbounds are more challenging for your team to handle. So begins a telephone game between your customer-facing teams and Product and Engineering. They’re reporting the same bug over and over again and not getting the clarity they need. Your team feels frustrated and powerless to help customers, and it shows in their performance. AHT skyrockets. Your customers get annoyed.
How does everybody win in this all-too-common scenario? Measuring team effort.
Directly Measuring Team Effort = Happy Customer-Facing Teams Happy Customers, and a Happy Finance Team
The goal of measuring team effort is to understand what’s hard for your team, and thus, identify the most expensive parts of your customer experience. To do this, you need to monitor team effort in the channels where it unfolds across everyday organic customer interactions.
Many variables drive team effort, such as individual customers or customer segments that may consume more than their share of team time, themes, from product bugs to customer expectations, product groups, support tiers, and so on. As such, you need to measure team effort according to the variables that drive it and assign service cost to all relevant variables. Otherwise, what you need to address will be unclear.
Directly measuring organic customer feedback in channels like your helpdesk, call center, and chat is the most reliable way to get a holistic, deep understanding of how your team allocates time and why. Using AI, specifically Natural Language Understanding, “NLU,” can help identify the underlying themes causing team effort at scale. Understanding what teams find difficult and why enables you to make sense of and improve the process metrics.
Suppose you know why a set of longer-running cases required more effort. In that case, you can focus on addressing the root cause and making that specific problem easier to solve in the future, which will improve metrics like AHT and your escalation rate. When you see your team playing a never-ending game of whack-a-mole against a recurring problem, you can quickly advocate for a resolution, which will also reduce customer effort. When your customer-facing teams have fewer effort-causing variables outside their control and are better empowered to help customers, your QA and satisfaction scores will reflect the positive change.
When measured effectively using AI, team effort unlocks several positive outcomes that help improve employee experience, customer experience and reduce your cost of service.
Tactically, measuring team effort should help you identify opportunities for self-service and deflection and understand where better documentation could help customers solve problems quickly without draining your team’s time. Most importantly, measuring team effort can provide early warnings about specific issues draining team resources so that you can take appropriate action or line up additional support. Suppose you don’t measure team effort and the underlying themes. In that case, you could have several agents working to resolve different cases about the same issue long before you realize that the issue has morphed into a costly problem.
Strategically, measuring team effort will result in more engaged, happier employees that are less likely to turnover. And when you can ensure that team effort is well spent, you can reduce your cost of service across the board.
For more on our approach to measuring team effort, check out our infographic with 5 Benefits of the AI-Driven Team Effort Score.
