Comparing teams’ performance is neither fair nor relevant.
I’m very excited to finally get to watch the Olympics this year. Countries all over the world will send their best professional athletes who, throughout the competition, will truly give it their all.
Within some Olympic teams, there will be a sense of rivalry between the athletes. But, in general, it’s far more likely that they will feel connected and supportive of each other because they share a common higher goal.
At first glance, the medal metric appears to be a convenient and objective measurement for comparing performance. Does that mean that 5 gold medals in athletics are a greater achievement than one gold medal by the volleyball team? Is the silver medal in rowing of equal value as the same medal for the hockey team? And is it better than the bronze medal for the eight-rowing team? It becomes quite obvious: comparing teams’ performance is simply not objective.
Why Do We Want to Compare Our Teams’ Performance?
Usually, the bonus systems in organizations are tightly coupled with assessing either individual or team-level performance. The performance metrics are collected and compared on a regular basis, and the results are listed in descending order. The top performers take the highest bonuses while the least performing teams get constructive feedback.
Now, let’s revise that practice for a moment. If our motivation is to reward high-performance individuals or teams, how does this approach connect to the benefits they bring to our business?
Let’s dig deeper here. What is the ultimate performance goal for every business? Hopefully, we all agree that it is to deliver results on time, with quality, in a consistent and predictable way.
How do we evaluate whether we’ve achieved that goal? We use evidence. We assess whether we’ve met our productivity objectives by tracking our flow metrics.
How Do We Measure Teams’ Performance?
Let’s analyze a few scenarios. The Cycle Time Scatterplots are of great help when it comes to cycle time and lead time analysis. They provide information about how quickly and consistently we deliver results to our customers.
The lines stretching across the graph are called percentile lines. We use percentiles to evaluate how much time we needed to complete 30%, 50%, 70%, 85% and 95% of our work.
Looking into the Cycle Time Scatterplot above, we can see that there are big gaps between the percentile lines. When the cycle time of our deliverables is growing, instead of staying consistent, this means that we’re constantly delaying our work. We’re struggling to deliver results in a predictable manner.
What is causing these deviations? The best chance of understanding where the delays come from is to analyze the outliers on the chart.
In most cases, you’ll observe that these items are delayed due to dependencies, blockers or bottlenecks. They were probably kept lingering in the process due to other, more important work taking place, or they’ve been constantly ignored because of the lack of pull policies in the workflow.
None of these obstacles have anything to do with an individuals’ or teams’ productivity. Your delays come from the accumulated waiting time caused by the inefficiency in your delivery workflow.
If you’re interested in learning more about how to enable a stable delivery workflow while promoting a supportive organizational culture, I’d be thrilled to welcome you to our Sustainable Predictability program.
It Doesn’t Make Sense to Compare Individuals’ Performance within Your Team
The fact that awarding individuals with higher performance doesn’t actually relate to your business objectives is almost beside the point. The bigger problem is that this approach creates competitiveness between teammates, which has the potential to negatively impact your business outcomes.
By creating a sense of rivalry, you essentially destroy any motivation within the team to collaborate effectively and support each other. And that unity is crucial when it comes to enabling the work to move smoothly down the funnel.
For example, if your developers are encouraged to push more and more work into the process to raise their productivity levels, but your QA is brimming with tasks, would they be motivated to stop starting new work and help the QA instead, in order to deliver work faster as a team? If they are competing against each other for the top spot on the productivity ladder, would they be focused on resolving the bottlenecks in the system and swarming outstanding work in progress to deliver results in a timely manner, even though these actions won’t make their individual metrics shine?
This approach puts their individual contribution above the contribution of the team as a whole. And when people are not encouraged to collaborate effectively, that directly impacts your delivery speed.
It Doesn’t Make Sense to Compare Different Teams Either
The same applies when it comes to comparing teams’ performance.
Different teams work on different projects, within a different context. Plus, they have different expertise and they operate in different workflows with different bottlenecks, blockers and dependencies. Your delivery speed is dependent on way more than the effort time needed to finish the work. A comparison of different teams would be simply irrelevant.
Even though it might be tempting to weigh up the cycle time trends between the teams, I highly recommend you to stay away from this approach. I can’t emphasize that enough, the main outcome would be to create a sense of competitiveness. Then, don’t be surprised if they lose the incentive to support each other.
Even if your development team is super efficient, nothing will be delivered if your deployment team is struggling to move the work further. Your workflow will get stuck in the deployment stage, you won’t be realizing a return on your investment and your clients will have to wait longer to receive what they’ve requested.
Comparing teams’ performance has a great potential to land you in some hot waters. At the end of the day, what we measure is what we value. If you communicate that you value individual teams’ performance, they will naturally strive to optimize for that metric. They are going to make choices, both consciously and subconsciously. And not all of these choices are going to result in the outcomes that you desire.
Use team metrics to identify the impediments in your system that prevent you from providing predictable delivery services. Create a workforce that operates together, as one well-oiled machine. Instead of competing, encourage an environment of trust, collaboration and support. That’s the ultimate approach to achieving fast and more predictable time to market, while sustaining high-quality customer relationships.
