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Competency vs. Productivity: Defining Success in Performance Reviews

Rachel Roth

By: Rachael Roth
January 20, 2023

Developer coding with multiple screens

Performance reviews in engineering are often tied to compensation. End-of-year and mid-point check-ins can be great opportunities to discuss individual goals and foster professional growth, but too often they are used as ways to assess whether direct reports are eligible for raises or promotions based on their ability to hit key metrics. 

For engineering leaders, a more valuable way to use performance reviews is as a structured opportunity to have a conversation about a developer’s progress and work with them to find ways to grow in their careers through new challenges. This benefits both developers and organizations as a whole — developers are able to advance their skills, and companies are able to retain top engineers who are continually evolving. Even senior engineers look for opportunities for growth, and are more likely to stay at an organization that supports and challenges them.  

The key to achieving this is by focusing on competency, rather than productivity measurements, when it comes to evaluating compensation and performance. But how do we define competency in engineering? 

What is competency in engineering? 

Where productivity might measure things like lines of code, competency looks at how an engineer approaches a problem, collaborates with their team to help move things forward, and takes on new challenges. 

Questions to consider when evaluating a developer’s competency might include:

  • How thoughtful are their comments in a Code Review?
  • Do they make informed decisions based on data? 
  • How do they navigate failure? 
  • How do they anticipate or respond to change? 

Engineering leader Dustin Diaz created a reusable template for evaluating competency in engineering, which he links to in this post. The template borrows from concepts in The Manager’s Path, by author and engineering leader Camille Fournier, and is modeled after the SPACE framework, and outlines levels of competency for engineers at different levels of seniority. The matrix can be helpful for leaders looking to hone in on areas like collaboration, performance, and efficiency/quality. It includes markers of competency for different tiers of engineers, including anticipating broad technical change, end-to-end responsibility on projects, and taking initiative to solve issues. 

Performance review essentials 

We’ve addressed how performance reviews during a difficult year can be especially challenging. Yet no matter the circumstances, there are principles of a successful performance review that will always be relevant.  

Reviews should always include: 

  • Compassion and empathy — With the understanding that employees could be under a lot of stress, a performance review shouldn’t add to any pressure they’re experiencing. 
  • Specific units of work — In order to provide useful feedback, bring examples of work to discuss during a review. By focusing on the work itself, the review remains objective, and can open the door for a coaching conversation. 
  • Objective data to check biases — There are many common performance review biases, as well as ways to correct for them by contextualizing data, checking assumptions, and taking circumstance into account. It’s important not to let unconscious biases inform your analysis of a developer’s work. 

Aligning developer and company incentives

When performance reviews are based on hitting productivity benchmarks that are implicitly linked to compensation, developers might be less focused on ambitious goals and more on checking boxes that they believe will earn them a raise; rather than challenging themselves, they will likely be incentivized to play it safe with easy-to-achieve goals.

Encouraging a focus on competency invites engineers to make decisions that have more potential to move the needle in an organization, and to take risks, even if they could lead to failure. 

During our webinar on data-driven leadership, Sophie Roberts, Director of Engineering at Shopify shared why rewarding productivity over growth could have adverse effects: “You end up in a situation where people want to get off projects that they don’t really think they have executive buy-in, or try and game the work they’re doing,” Roberts said. “I’ve canceled people’s projects and promoted them the next month, because how they were approaching the work was what we expect from a competency level of people who are more senior…They may try to get work that is a more sure shot of moving a metric because they think that’s what’s going to result in their promotion or their career progression.”

An emphasis on competency can improve the following:

  • Risk-taking. If engineering leaders foster psychological safety within teams, developers are more likely to take risks without the fear of being penalized for failure. If metrics are not tied to compensation, developers will likely be more ambitious with their goal-setting.
  • Flexibility and adaptability. Failure and change are both inevitable in engineering organizations. Instead of trying to avoid mistakes, emphasize the importance of learning and of implementing thoughtful solutions that can have a lasting impact.
  • Upskilling and developer retention. Investing in the professional development of an engineer is a vote of confidence in their abilities. Engineering leaders can boost retention through upskilling or by enabling individuals to grow into more senior positions. 

Using metrics to assess competency

Data-driven insights can provide engineering leaders with objective ways to evaluate developer competency, without tying metrics directly to compensation. They can help you assess a developer’s progress, spot opportunities for improvement, and even combat common performance review biases

One effective way to use metrics in performance reviews is to quantify impact. In our webinar on data-driven performance reviews, Smruti Patel, now VP of Engineering at Apollo, shared how data helps IC’s on her team recognize their impact on the business during self-evaluations. 

“It comes down to finding the right engineering data that best articulates impact to the team and business goals. So if you think about it, you can use a very irrefutable factor, say, ‘I shipped X, which reduced the end-to-end API latency from 4 or 5 seconds to 2.5 seconds. And this is how it impacted the business,” she said. 

In the same discussion, Katie Wilde, now Senior Director of Engineering at Snyk Cloud, shared how metrics explained a discrepancy between one engineer’s self-evaluation and her peer reviews. This engineer gave herself a strong rating, but her peers did not rate her as highly. When Wilde dug into the data, she found that it was not a case of the individual being overconfident, but a case of hidden bias — the engineer’s PRs were being scrutinized more heavily than those of her male counterparts. 

In both instances, data helped provide a more complete picture of a developer’s abilities and impact, without being directly tied to performance benchmarks or compensation.

Defining success in performance reviews

Overall, metrics are able to provide concrete data to counteract assumptions, both on the part of the reviewer and the engineers themselves. By taking a holistic approach to performance reviews and contextualizing qualitative and quantitative data, including having one-on-one conversations with developers, leaders can make more informed decisions about promotions and compensation for their teams. 

Keep in mind that performance reviews should be opportunities to encourage growth and career development for engineers, while gaining feedback that can inform engineering practices.

Most importantly, rewarding competency is an effective way to align developer goals with business goals. This way, leaders are invested in the growth of valuable members of their team who make a significant impact, while engineers are recognized for their contributions and able to grow in their careers. 

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