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Silo AI

How Silo AI is building their feedback culture

The best things about Teamspective

  • It works on multiple levels: individuals, project teams and organization
  • No forced hierarchy – a great match for self-directed teams
  • Guidance for writing feedback in Teamspective
  • It's positively light-weight and easy to use
  • Level of service has been excellent – the advantage of working with a startup
Challenge

Finding a solution for peer-to-peer feedback

In the spring of 2020, Aliisa Holkko and Tuuli Suominen from the People Operations of Silo AI were preparing to make a decision: either stick with the old pulse tool or choose a new one from the 50 products they had listed.

"Our people had told us earlier that they'd want more feedback. Our professionals work in project teams with low hierarchies and a high level of self-direction. We have no direct managers, so we need a lot of peer-to-peer feedback. We wanted a solution that would help people ask for and give each other feedback, in addition to having a pulse questionnaire" Aliisa explains.

Solution

Three-level feedback implementation

Silo AI wanted to develop their feedback processes on three levels: individuals, organization and projects. From Teamspective's standpoint, this was a perfect match with the product roadmap, as new features for pulse questionnaires and project feedback were already in the making. Testing Teamspective showed Aliisa that the search for a solution could be stopped.

"We believe that people need to be responsible for their own personal feedback. So the solution should not be admin-heavy. We also wanted the solution to work in Slack. Finally, we want our project teams to collect insights from our customers. Teamspective listened to us and they've been very proactive in developing a tool to match our needs. I don't think the same level of service could have been possible from any large corporation," she describes. "That's the benefit of working with another startup."

Training and implementation

According to people at Silo AI, the tool itself is easy to use and doesn't require much training. Instead, internal training was organized for the broader concepts around feedback: positive psychology, growth mindset and neuroscientific findings related to learning and stress, which are all tightly related to feedback.

The implementation was done in three steps. First, in the summer of 2020, people started to ask for and give each other personal feedback. "We encourage people to ask their colleagues and customers for feedback whenever they feel a need for it, but to do it at least a few times per year," Aliisa describes.

Next, the pulse questionnaire was taken into use. The weekly, multi-select, Slack-integrated pulse questionnaire lets everyone share their feelings and thoughts about e.g. workload, psychological safety, and clarity of goals. Based on the pulse results, their plan is also to share tips and ideas on how everyone could contribute to developing the working practices.

Third and finally, customer project teams at Silo AI can collect feedback from their customers with Teamspective. The goal here is to improve collaboration and open up discussion with customers both in the short and the long term with carefully considered questions. This is a part of Silo AI's plan to build long-lasting and thriving customer relationships – it all starts with feedback and continuous improvement.

Results

Successful partnership and rapid development

"When we got started in June 2020, we were well aware that Teamspective is not yet complete. But we saw a lot of potential, and we were willing to test it, give feedback, and then implement it to our whole team. And our collaboration has been great! In addition, we have been quite surprised by the speed of development from their then-2-person team," Aliisa laughs.

"Teamspective helps our people give each other professional-level feedback independently, effectively and respectfully. Given the right chances, anyone can master their feedback skills." - Aliisa Holkko, People Operations Specialist at Silo AI

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