Historically, engineering departments have been without reliable, objective metrics, leaving engineering leaders at a disadvantage in conversations with executives and board members. It’s part of the reason engineering is often viewed as a ‘black box’ — where departments like sales and marketing have clear numbers that demonstrate the efficacy of their processes, or their direct impact on the company’s bottom line, engineering has been reliant on reporting progress in ways that often raise more questions than they answer.
A list of features completed, for example, doesn’t convey the amount of work that went into delivering each feature, and doesn’t account for variations in difficulty or complexity. When a list is shorter one quarter, the immediate conclusion may not be that the features were more complicated, but that the engineering team is starting to fall behind.
Reporting on incidents is similarly flawed. The frequency of incidents may increase when the engineering team is encouraged to pursue an ambitious product roadmap without being afforded the time to address technical debt. These incidents may be seen as a reflection of subpar work by the engineering team, when in reality they’re a result of poor planning and prioritization.
To communicate effectively with the rest of the business, engineering needs to speak the language of the rest of the business. To do that, engineering leaders need objective metrics. Objective metrics translate across teams, individuals, and projects. They provide a concrete basis for critical conversations about everything from resource allocation to strategic decisions. Rather than simply asking stakeholders to trust your conclusions, you can use data to show them how you got there.
For example, you can make the case for increasing headcount by explaining that your current team isn’t large enough to keep up with the proposed product roadmap, or you can look at a throughput metric like Deploy Volume and illustrate the engineering team’s capacity with concrete numbers. On the flip side, you can demonstrate the success of a recent hiring push and illustrate the effectiveness of your onboarding practices with a graph of your team’s Cycle Time (a great proxy for engineering speed), demonstrating how quickly new hires are getting up to speed.
Trust is important, but it’s not enough. When you’re advocating for your department — pushing for key resources, raising an issue, or celebrating a success — data will help you make a stronger case.
Of course, metrics are not a replacement for experience, intuition, and expertise. As the expert, it’s still your job to put metrics in context, analyze them, and draw the right conclusions. When communicating with key stakeholders, you’ll need to choose the metrics that matter most to the rest of your organization, and situate them within the larger story of your department.
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