Founded in 2007, Doodle has become the most established scheduling platform, seamlessly coordinating group meetings, events, and one-on-ones.

By integrating with all major calendar platforms, Doodle ensures effortless planning for both teams and individuals, allowing users to focus on what matters most while Doodle handles the logistics.

I recently had the pleasure of talking to Jens Naie, CTO at Doodle and Timofey Yevgrashyn, Agile Coach and Trainer, where they revealed the story behind their business agility transformation.

The Challenge with Story Point Estimates

Behind Doodle’s success is a dedicated team of about one hundred employees. Engineering at Doodle today includes three product development teams and an additional growth team.

Before adopting Nave, Doodle relied on traditional estimation methods like story points and T-shirt sizes. However, these methods often led to inaccuracies and stress.

“Estimates are always wrong,” Jens states. “Teams would commit to a due date and then end up working overtime to meet it. This was something we needed to change to improve work-life balance.”

The need for a new approach became apparent. “Using traditional estimates caused a lot of stress at the end of projects,” Tim adds. “We wanted to create a more relaxed work environment and focus on quality.”

The Transition to Probabilistic Forecasting

Doodle’s journey from story point estimates to no estimates began in 2020 when Tim joined the company. “We introduced Nave as a feedback tool at the end of 2020,” Tim recalls.

Doodle Team Dashboard by Nave | Image

The teams at Doodle use Nave’s analytics suite to track their performance. They observe nearly a 2x improvement in cycle time compared to the same period last year. See a dashboard with your own data

The Nave platform allowed their teams to gain insights from data and foster a culture of continuous improvement. Each team has a Delivery Manager who acts as a People Manager and an Agile Coach, helping to improve processes and coordinate efforts.

The real turning point came when Nave was used to replace traditional estimation methods with probabilistic forecasting. “Switching from estimates to probabilistic forecasting was a game-changer,” Jens notes. “Using statistics instead of fixed dates allowed everyone to work more relaxed and focus on quality.”

Tim conducted workshops to educate teams on Kanban, emphasizing the importance of the key flow metrics and practices such as implementing WIP limits.

Doodle Team Cycle Time Breakdown Chart by Nave | Image

Doodle’s engineering teams use the Cycle Time Breakdown Chart to track the time spent in each process state.

“We played the Kanban board game with each team to highlight these concepts,” Tim says. This hands-on approach helped teams understand and apply the probabilistic forecasting method effectively.

Initially, some teams experimented with T-shirt size estimates, believing it would help them better manage their workload. However, Tim explains, “Our delivery managers and teams tried using T-shirt sizes for a while, but it turned out to be a waste of everyone’s time. The cycle times were often longer than expected, leading to more confusion and delays. Teams decided to trust the probabilistic forecasts instead.”

Doodle Team Cycle Time Histogram by Nave | Image

Tracking the Cycle Time Histogram, one Delivery Manager at Doodle, Liudmyla Sribna, says her team managed to shorten the cycle time of their tickets and deliver more of them in 2024 compared to 2023.

Realizing the Benefits

Within six months, Doodle saw significant improvements. “We started to really rely on probabilistic forecasts,” Tim explains. The shift allowed teams to focus on delivering high-quality work without the pressure of arbitrary deadlines.

At first, teams were skeptical of the new forecasting method. “Developers didn’t believe the forecasts initially,” Tim shares. “They thought they could complete tasks faster than what the data suggested. But after a few iterations, they realized the forecasts were far more reliable than their own predictions. This built trust in the data-driven approach.”

“Our cycle time averages around seven days now,” Tim notes, indicating a dramatic improvement in efficiency.

Doodle Team Monte Carlo simulation by Nave | Image

Doodle’s teams started using Monte Carlo simulation to forecast delivery dates. In a couple of experiments comparing the team’s estimations with the probabilistic forecasts generated by the platform, Nave gave astonishingly precise results.

Doodle didn’t stop there. The company continues to refine its processes, driven by data insights from Nave. “We regularly review our processes and look for areas of improvement,” Tim explains. This commitment ensures Doodle remains agile and responsive to changing needs.

Nave’s success at Doodle extended beyond engineering. “Our people operations team uses Nave to track their processes and improve efficiency,” Jens shares. This cross-departmental adoption underscores the platform’s versatility and value.

For companies struggling with delivery challenges and time-to-market pressures, Jens and Tim offer clear advice. “Understand your workflow and use a tool like Nave to gain actionable insights,” Jens advises. Tim adds, “Having an easy-to-use feedback mechanism is crucial. It enables teams to make data-driven decisions and continuously improve.”

If you haven’t connected Nave to your management platform, now is the time! Create a dashboard with your own data and start forecasting today

I hope that Doodle’s story inspired you to explore the concept of probabilistic forecasting, especially if your current approach doesn’t work well for you. With Nave, you can come up with reliable delivery forecasts in less than a minute! That’s how you build credibility and foster a more efficient, stress-free work environment for your teams.

Start making data-driven decisions today and experience the difference it can make for your company! I wish you a productive day ahead, and I’ll see you next week, same time and place, for more managerial insights! Bye for now.

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