increase in learning time
Pull Requests per month maintained
According to a global survey by LinkedIn, 74% of employees want to learn during their spare time at work, yet the #1 barrier is the lack of time!
Many engineers are curious and analytical by nature and dislike inefficiency, meaning they often have a natural inclination to thinking about the “meta” of work, for example:
Answering these questions requires dedicated time to learn and explore, which can be difficult to find at fast-paced startups, like Super Obvious.
Chief Technology Officer Huanhuan Huang wanted to support her team’s desire to learn, and, based on experience at a previous company, knew it was possible to get creative in parsing out some time – as long as she got buy-in from the rest of the leadership team.
While Huanhuan knew that increasing learning time would bring long-term benefits to the team, she also needed to get buy-in from leaders across the business. As is the case for many startups, Super Obvious needed to maintain delivery at a strong level.
The engineering team identified a good time slot for learning – one Friday afternoon per 2-week cycle. Next, Huanhuan needed a way to demonstrate the team’s ability to deliver while experimenting with this increase in learning & development. The delivery data was important for gaining alignment from the rest of the company’s leadership and board.
One of the metrics from DORA research, <code-text>Merge Frequency<code-text>, captures volume of work output by showing the number of PRs merged.
Multitudes makes it easy to see <code-text>Merge Frequency<code-text> for the company as a whole, across teams, or across repos. Huanhuan decided to use Multitudes’s <code-text>Merge Frequency<code-text> metric to show leadership the impact of the increased learning time. Multitudes showed the team’s historic <code-text>Merge Frequency<code-text> was around 20 merged PRs per person per month.
“Alongside the holistic view of team health, this simple insight tells the whole story.”
— Huanhuan Huang, Chief Technology Officer, Super Obvious
The team set aside calendar blocks for every other Friday afternoon. Huanhuan consistently told the team what she would be learning each of these Fridays herself, to set an example and encourage the team to adopt this new practice. Finally, the team also dedicated some time early the following week for folks to show off what they had learned, as a way to share the new knowledge and ensure accountability.
Meanwhile, Huanhuan began sharing the Multitudes’s <code-text>Merge Frequency<code-text> data with leadership and the board on a monthly basis, to show how delivery was tracking.
For 4.5 months after the team started the experiment, <code-text>Merge Frequency<code-text> held steady at an average of 20 merged PRs per person per month. It was clear to everyone that delivery did not decline; in the last month of data, the team actually ended on a high of 26 merged PRs per person per month.
Moreover, the extra learning time resulted in a triple-win scenario where:
“Learning time is a chance to get some thorns out or build a cool little thing that ends up improving the product, and it’s very motivating to get that done and dusted!”
— Michael Hutton, Lead Developer, Super Obvious
It’s been so well received that other teams in the company are also looking at adopting the same approach!
Note: Just prior to starting learning time in early February, the team was coming off of a major release, and had been working extra hard (not to mention they had extra part time help), hence the higher Merge Frequency value in January and February relative to March
To more easily monitor <code-text>Merge Frequency<code-text>, Huanhuan could set a custom target for <code-text>Merge Frequency<code-text>. This way, when there is a dip below this target, the Multitudes app will not only highlight the insight, but also provide recommended actions on how to get back on track. Multitudes also has a <code-text>Types of Work<code-text> chart that shows volume of issues completed in Jira, which can be another helpful datapoint to ensure delivery isn't declining.
The team might also want to monitor and/or set a custom target for <code-text>Out Of Hours<code-text> work, to ensure that the team is not compensating for the learning time by working extra hours elsewhere.
Regardless of how they choose to innovate, Huanhuan can be confident that Multitudes will provide a reliable source of truth to ensure that delivery remains on track.