Overview

Prendio, a trusted eProcurement SaaS solution for the life science space, has strategically enhanced its engineering productivity by prioritizing deeper SDLC visibility. This focus on clear insights has empowered their teams at every level to proactively identify and resolve development bottlenecks, drive better constructive conversation leading to significant improvements in feature delivery.

The Challenge

The development team at Prendio faced limitations in gaining a clear and comprehensive understanding of their software delivery at the process & people level. Traditional methods of sprint retros and subjective reviews lacked the granularity needed to make improvements.

Challenges Faced

• Limited SDLC Visibility: Difficulty in tracking progress and identifying bottlenecks across the entire development lifecycle.
• Lack of Granular Sprint Insights: Challenges in understanding the flow, trend, and efficiency within individual sprints and across sprints.
• Insufficient Data for Optimization: Difficulty in obtaining actionable data focused on improving team and individual-level velocity.
• Need for Proactive Identification of Issues: Challenges in identifying potential roadblocks early in the development process.

Discovering a Solution

Seeking a more effective approach to gain deep visibility into their SDLC, Rens explored solutions that could provide comprehensive data and insights in a user-friendly way.
The decision to adopt a new visibility-focused strategy was based on several key factors:

• Real-Time Visibility: Offering up-to-date information on sprint progress and potential SDLC bottlenecks.
• User-friendliness: The ability to comprehend insights, without being overwhelmed with too much information.
• Actionable Insights: Providing a clear path to productivity improvement in areas that need attention.
• Improved Collaboration: Facilitating better communication and collaboration within and across teams through shared visibility.

This approach led them to Typo, which enabled the team to gain a clear understanding of their development flow, identify bottlenecks impacting cycle time and deployment frequency, and implement targeted improvements.

Implementation Process

Typo implementation was simple as it is designed to integrate seamlessly with Prendio’s existing development workflows, ensuring minimal disruption.

• Integrated Dashboards: Utilizing their existing Git & issue management tools to provide a unified view of SDLC and sprint insights.
• Clear Metrics and Goals: Defining specific, measurable goals for the teams and focusing on improving cycle time and deployment frequency.

• Team Empowerment: Providing teams with the necessary training to get the data and insights they need to identify and implement their own improvements.
• Iterative Refinement: Continuously monitoring data and feedback to further optimize the focus on specific metrics & improvement journey.

Typo empowered the team to proactively identify and address inefficiencies impacting their cycle time and deployment frequency.

Impact on Operations

The enhanced SDLC and sprint visibility brought about a significant transformation in how the Prendio team operated, fostering a culture of continuous improvement focused on key delivery metrics, which improved their time to market.

• Data-Driven Optimization: Sprint reviews became more centered around data related to SDLC and sprint performance, leading to more effective improvement initiatives.
• Proactive Bottleneck Identification: Teams are now able to identify and address potential roadblocks earlier in the development lifecycle, whether it is due to scope creep or a ticket pending QA.
• Measurable improvement: Enhanced understanding of bottlenecks led to targeted improvements, resulting in a 27% reduction in cycle time & 20% increase in deployment frequency.

Conclusion

Today, Prendio leverages Typo to enhance the SDLC visibility to continuously optimize its software delivery process, prioritize improvements effectively, and measure success based on tangible metrics like cycle time, sprint completion rate, and deployment frequency.