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Using Data to Encourage Risk-Taking and Foster Psychological Safety

Hillary Nussbaum

By: Hillary Nussbaum
June 08, 2021

Team members collaborating around circular table

As you think about driving high performance on your team, it’s easy to focus on certain tangible improvements like optimizing processes, upskilling team members, and hiring new talent. But your team will only go so far if you neglect to cultivate a key aspect of team culture — psychological safety. Psychological safety, most commonly defined as the knowledge that you won’t be punished for making a mistake, is critical to the success of the highest performing organizations; it allows teams and individuals to have confidence in taking risks of all kinds, from the most basic risk of opening a Pull Request for feedback, to the larger leaps necessary to drive true innovation and stay ahead of the competition.

With the right data and a clear strategy for analysis, you’ll be able circumvent some common biases and assumptions, while fostering the psychological safety necessary to keep improving as a team.

Software Engineers Need Safety to Deploy

Safety is a prerequisite of speed; developers who aren’t confident in their code might become a bottleneck if they’re hesitant to open a PR and receive feedback. When your team has a culture of safety, that developer can feel more secure subjecting their work to the review process. They know they’ll have the opportunity to work through their mistakes, rather than being penalized for them.

Psychological safety is also critical at the other end of your software development pipeline. Developers need to feel secure enough to deploy code, and that security can be found on two levels: the confidence that their deployment won’t break things, and the trust that they won’t be punished if it does.

The first is mainly a factor of process and tooling. Code Review and automated tests can offer some degree of confidence that buggy code won’t be deployed, while good coding hygiene, specifically the practice of keeping Pull Requests as small as possible, will mean that any damaging changes are easier to identify and reverse.

The second level, the trust that a developer won’t be punished if their code introduces a bug or causes an incident, is a matter of culture. It’s an engineering leader’s responsibility to create a culture of psychological safety on their team, and to ensure that mistakes are seen as a learning opportunity, rather than an occasion for punishment. In a blameless culture, the work is evaluated and discussed independently of the person who completed it, and every member of a team stands to benefit from the learning experience.

Without this foundation of trust, your team will be hard-pressed to deploy quickly and consistently, let alone take the larger risks necessary to pursue big ideas, innovate, and stay ahead of your competition.

Using Data to Create Psychological Safety

Data can play a key role in your efforts to cultivate a culture of psychological safety. Whenever you introduce data in your organization, it’s important to do so responsibly — be transparent, put all data in context, and avoid using it to penalize members of your team. But used properly, clear, objective metrics can help you combat intrinsic biases and check your assumptions, while keeping conversations grounded in fact. This makes it easier to keep conversations focused on the work, rather than the person behind that work.

Velocity can help surface high-activity Pull Requests that could be at risk of derailing your sprint.

Velocity can help surface high-activity Pull Requests that could be at risk of derailing your sprint.

For example, if a particular sprint is falling behind, you could frame the conversation in a general sense, asking the team why they’re moving slowly. But this framing risks putting your team members on the defensive — it could be construed as finding fault in your developers, and places blame on them for the slowdown.

With data from a Software Engineering Intelligence platform like Velocity, it’s easier to ensure that discussions remain focused on the work itself. In Velocity, for instance, it’s possible to identify at-risk work before it derails your sprint. You can pull up a report that highlights long-running, high-activity Pull Requests, then dig into those PRs with your team. If you keep the conversation focused on those specific units of work, you’ll be better able to surface the particular challenges that are slowing things down and work through them together.

To find out how data can help you create psychological safety and drive performance in your organization, reach out to a product specialist.

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