Before the program formally launched, the small-scale process was managed with a simple spreadsheet – one column of organizations to match with a column of a dozen or so volunteers. But once the program was formalized across Atlassian’s ever-growing global workforce, the Foundation team needed to scale.
In cooperation with the Intelligent Automation (IA) team, which falls under the umbrella of Atlassian IT, and using the Jira platform to host the data and leveraging Workato – a low-code to no-code integration platform as a service – to connect that data to other systems, the Foundation team automated the process of linking Atlassian volunteers to nonprofit organizations. Thanks to time-saving automation and an effective partnership, the team saw a 90 percent success rate (volunteers actively engaging) in 2021.
The system works kind of like a dating app – but without the drama. Here’s how we did it.
Making the match, thanks to automated data
In playing Cupid between skilled volunteers and organizations in need of those skills, the IA team created an algorithmically driven process that assigned organizations to each volunteer through a bot, saving the Foundation team from managing that complicated first step.
The process was relatively simple, thanks to Jira Service Management. “You can spin this up, customize the fields, and hand it off to a team in a matter of weeks,” says Srividya Sathyamurthy, an IT manager on the IA team. “That’s what makes Jira so powerful.”
Like any dating app worth its salt, we start with profiles! Atlassian’s nonprofit partners create profiles through Jira Service Management, indicating where they are located, the skills they’re looking for in a volunteer match, and their project needs. Likewise, employees create their own profiles listing their location and skillsets.
From there, the IA Team spins up an automation using Jira Service Management and Workato pulls the data from employees and organizations to create matches based on need. “The automation process saves so much brain and people power,” Lauren says. “We don’t need to spend a whole week looking over spreadsheets to match A with B. Instead, our team can focus on more valuable and creative work, such as developing campaigns and resources.”
Matches are then passed to a bot that sends a message to volunteers over Slack, announcing which projects are matched to whom and how to get started. If they’re too busy to respond, a bot nudges them with gentle reminders. And, just like in real life, if a volunteer isn’t keen on a project, they can “swipe left” (not literally ) and see what other organizations are in need of their skills.
The results of this matchmaking process have been better than we could have hoped. In 2021, when the team launched the inaugural program, there were two periods of volunteer matching. The initial period, which used an early version of the matching process, saw a 58 percent rate of engagement (measured as the percentage of volunteers accepting a volunteer opportunity through the system). The second period saw a 90 percent engagement rate – by the numbers, 69 of the 76 projects attracted volunteers.
Partnering up with IT
Before Engage 4 Good formally launched, skills-based employee volunteering was sporadic and ad hoc. “Matching was never done proactively back then,” says Lauren. In 2020, there were 31 projects matched manually from July to December. “At that time, whenever someone would ask us to help, we’d tap an employee on the shoulder and ask, ‘Hey can you get on this project?’” she remembers.
Those projects weren’t overwhelming tasks for the Foundation team – but it was a sign that more projects and demands would come. With those demands, there would be a need by the Foundation team for matchmaking at an enterprise level. That’s when Lauren and her team connected with Atlassian’s IA team, which was already working with the Foundation to automate other processes.
“Since we knew them as a stakeholder, we were trying to show more of what an IT team could bring to the table as far as business value,” says Srividya. “It was a great opportunity to leverage Jira and the processes that we’d already built.”
Helping business teams understand the business value that can be unlocked – streamlined processes, developing solutions from within, keeping headcount from becoming bloated – through close partnership with IT is a huge part of Atlassian IT’s directive: enable and empower the company to scale.
Unlike engineering, customer service, and IT teams, it’s not common for non-technical teams like the Foundation to implement technical products as a solution. Jira is simply not a tool those teams normally reach for to solve problems.
But stepping back to look at the requirements and needs of the Engage 4 Good program – data processing, document processing, attaching files, filtering, and reporting – it’s a match made in heaven.
Saving time and creating team efficiency
Considering the fact that this process connected Atlassian’s global workforce to organizations with specific needs across multiple time zones, we estimate it saved the Foundation Team a week’s worth of work per matching period.
This is on top of the efficiency with which the automation can match volunteer skills to the right organizations. “Some projects needed skills that were so generic that there were 15 volunteer profiles matched to it,” Lauren says. “We needed to replicate the accuracy of matching by hand, but in a way that saved us time. We’ve accomplished that with this new process and Atlassian-led technology.”
Lauren credits a large part of the success to the ease of working with the internal IT team that understood the vision and values of the program. The Foundation team could have used an external vendor, but Lauren doubts the end result would have been as successful. “Working with an external vendor, there are only so many opportunities to ask for changes and push the parameters of the project,” she says. “Not to mention the customization and flexibility of Jira, which is a major plus.”
“It’s amazing to have the ability to work with someone in IT at the company to build this from the ground up,” Lauren says. “I think it really changed the user experience and the success of this program.”