“I have worked as an engineering leader with multiple teams and diverse industries. I have managed teams from various backgrounds, and I never faced the need to measure my engineering team's performance. Why should I do it now?”
I was asked this question by a CTO a few weeks ago, and, if I’m being honest, I am asked this question during every pitch meeting. Many engineering leaders don’t feel the need to measure performance and usually believe that their experience and gut work better to understand the team's health. Some leaders also fear knowing the truth. As they say, sometimes ignorance is bliss, but here ignorance may be a blunder because it can cost you so much more money. Now if there’s a way to save cash for your business and your company, wouldn’t that be an achievement?
As an engineering leader, you want to ensure that your team is as successful and healthy as possible. But how can you do that? Is relying on your experience and gut instincts enough?
I am not saying your gut is wrong; I relied on gut decisions for many years too. But I became a better leader when I backed my instincts with data. I began using data to understand which engineer was stuck on what and was able to dive in to help at the right time. Knowing what type of work was taking more than ordinary time helped me better support my team, improving overall performance.
Last week, another CTO told me, “We invest in the continuous professional development of our team members with books, courses, conferences and ongoing mentoring.” I asked him how he knew if the team was doing better after providing these resources, and he had no response. Assuming teams will automatically improve as a result is often unfounded. Can you really validate that they are improving without any data? There’s no way to know if the learning resources are resulting in better work quality work if there is no way to measure it.
Every other department has some way to measure performance. In Sales, they have the number of deals closed; in Marketing, theyhave the ROI and the target audience reach. In HR, they have employee surveys, but for an Engineer - measuring the lines of code or the time spent on IDE and in the office is not the right way to go.
In my 10+ years of managing teams of talented engineers, here are a few reasons why I would implore engineering leaders to go beyond gut feeling and rely on metrics:
It has been established that you have the data and the tools to extract meaning from your team. So, what’s stopping you from deploying them to monitor your engineering team’s health? You don’t have to build all of it from scratch, instead you can use SaaS offerings like Insightly.AI, which would do it for you with a 5-minute no-code integration. After all, if you wouldn’t find a CFO playing it by ear, then why shouldn’t CTOs follow suit?
Data-driven metrics allow you to base your findings on cold, hard facts so you can manage your engineering teams efficiently. It drives the “who, what, why, when, and how” of managing teams and projects and eliminates any guesswork that may go into it. Decision-making will improve and become more targeted and effective. As an engineering leader, you will also be much better equipped to present the engineering org’s performance in front of the Board and CEO in a language they understand.
You may have read extensively about employee engagement in the past two years, especially in remote teams. There was also a lot of talk about employee burnout and, of course, the Great Resignation plaguing even the best of tech companies. In other words, the engineering world has been in constant flux.
To attract and retain talent, companies are readily embracing remote or hybrid models of work. Naturally, with distributed teams measuring productivity becomes tricky. Managers can no longer hover over their team’s shoulder to stay abreast of the progress and monitor every individual’s contribution. In such cases, metrics are instrumental in standardizing the process of measuring the performance - of any individual or the team as a whole. In a world where measuring output such as number of hours in the office is irrelevant, measuring outcomes such as releases and their quality is motivating to the engineers and beneficial to the company.
While there isn’t a lot that engineering leaders can do to hone poor communication skills amongst developers, what they can do is leverage metrics as the voice of developers. Using metrics can shed light on the various bottlenecks affecting the development process, in a more proactive way. As a result, engineering leaders can identify underlying issues, find ways to address them, and improve overall team productivity using real time data, and provide micro feedback that would avoid major issues to happen in the first place
Further, it could serve as a data-centric shared language that quantifies everyone’s efforts and works as the lingua franca of software development, regardless of the team or department.
When (communication-led) productivity is money, metrics could be your reliable friend in optimizing talent and resource utilization.
There are so many engineers; how do you decide who to hire? How do you choose who to appraise and when?
This is why the need for data-driven leadership is more critical now than ever. Using data as an objective standard to measure performance can make your job of hiring and promoting talent easier, fairer, and faster. While qualitative data and soft skills can’t be measured, they should be augmented with objective metrics.
In the next segment, I will be talking about the frustrations of tracking too many metrics. So stay tuned!