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How Tempo Uses Tecton to Transform Time Tracking

  • Pauline Brown
Last updated: November 15, 2023

An ML-powered solution that optimizes the time-logging experience

Time tracking isn’t fun—but it’s required for effective project planning and capacity management. 

Tempo, the creators of the top-rated time-tracking app in the Atlassian Ecosystem, Timesheets by Tempo, set out to solve this problem and successfully implemented a machine learning (ML) powered solution to revolutionize time-tracking for developers. 

By leveraging their comprehensive data resources, ML expertise, and the power of Tecton’s feature platform, Tempo has crafted a time-tracking solution that substantially reduces the friction typically associated with logging work hours for Jira users. Read on to discover the challenges they faced, why they decided to solve them with machine learning, and the results they achieved with Tecton.

The challenge: Overcoming the limitations of a rule-based solution

For product leaders, understanding time allocation is crucial for effective project planning and capacity management. However, for this system to work, employees must accurately and promptly log their time spent on various tasks. Conventional time-tracking systems are often perceived as disruptive and time-consuming, and have been a significant stumbling block for employees who prefer not to interrupt their workflow.

Timesheets by Tempo’s previous rule-based solution was innovative but encountered limitations when it came to linking calendar events (e.g., meetings) to specific Jira tickets. The true value of Timesheets by Tempo lay in understanding the context of these meetings—the projects, clients, or products discussed. The inefficiency of keyword searches and the challenges associated with maintaining and updating a rule-based approach prompted Tempo to consider machine learning as a potential game-changer.

The solution: Integrating machine learning with Tecton’s feature platform

In a pioneering move, Tempo assembled a cross-functional team to create an ML-powered time-tracking solution. After considering various options, the team selected Tecton’s feature platform, citing its real-time serving capabilities, low-latency online serving, compatibility with their existing data warehouse (Snowflake), and support for their team’s foray into ML.

By integrating Tecton into their existing tech stack, the Tempo team could automate data ingestion from diverse sources, including IDEs, calendars, Jira, and millions of work logs. Tecton’s platform served to materialize these data into features, which were then served through an API to generate work log suggestions based on a user’s specific timeframe.

The results: A new era of frictionless time tracking

The ML-powered time-tracking solution from Tempo has been successfully rolled out for all cloud-based customers of Timesheets by Tempo. The new system uses advanced ML models to predict and display the most suitable work log suggestions, leading to faster and more accurate time tracking.

Users now log their time 43% faster, with ML suggestions freeing up valuable time for developers to focus on more productive tasks. The increase in time-tracking adoption has also led to more timely and accurate reporting, enabling more informed decision-making and effective project management.

The future: Leaning into machine learning

Tempo’s successful implementation of Tecton’s feature platform for their ML-powered time-logging solution is a shining example of ML technology’s transformative potential. By streamlining the time-logging process and reducing developer friction, Tempo enables organizations to understand resource allocation better and foster more efficient time management. This is a leap forward for the time-tracking industry and a significant win for product development teams everywhere.

Buoyed by the success of their first ML-powered solution, Tempo is poised to explore new opportunities to automate aspects of portfolio management. They plan to leverage the features developed with Tecton’s platform for future initiatives, potentially reusing them for new applications. As they continue to refine their products and improve user experiences, Tempo is paving the way for the next generation of time management solutions.

Check out Tempo’s full story.

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Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

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or

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Interested in trying Tecton? Leave us your information below and we’ll be in touch.​

Unfortunately, Tecton does not currently support these clouds. We’ll make sure to let you know when this changes!

However, we are currently looking to interview members of the machine learning community to learn more about current trends.

If you’d like to participate, please book a 30-min slot with us here and we’ll send you a $50 amazon gift card in appreciation for your time after the interview.

CTA link

or

CTA button