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Empower Product Managers to Drive Program Success

SAFe Product Managers are responsible for aligning product vision with business goals, prioritizing features in the Program Backlog, and ensuring the successful delivery of value to customers. They work closely with Product Owners, who handle tactical execution at the team level. While tools like Jira Align provide high-level planning capabilities, they often lack visibility into the actual work being done. This gap can lead to misalignment, delays, and missed opportunities to address issues early.

 

PulsePoint AI complements Jira Align by providing actionable insights based on actual coding activity, delivered through daily and weekly reports. With customizable levels of technical abstraction, PulsePoint AI ensures that SAFe Product Managers and Product Owners have the information they need to collaborate effectively, make informed decisions, and keep development efforts aligned with strategic goals.

Ensure Alignment with Business Objectives

SAFe Product Managers must ensure that development efforts align with strategic goals while empowering Product Owners to manage tactical execution effectively. PulsePoint AI fosters this alignment by offering visibility into progress, prioritization, and team focus.

 

How PulsePoint AI Helps:

  • Validate Progress on Strategic Features: PulsePoint AI provides coding-based insights to verify that high-priority features are receiving the necessary attention. Product Managers can confirm that deliverables align with business objectives and address misaligned efforts proactively.

  • Spot Misaligned Efforts: PulsePoint AI’s coding activity reports highlight discrepancies between planned priorities in Jira Align and actual work. Product Managers can collaborate with Product Owners to realign efforts, ensuring optimal resource utilization and strategic focus.

  • Support Data-Driven Decisions: Historical reports from PulsePoint AI reveal how effort has been allocated across past PIs. Product Managers can analyze these patterns to adjust backlog priorities and improve planning for future iterations.

 

Example in Action: A SAFe Product Manager notices through PulsePoint AI that a high-value feature is lagging while a lower-priority task is consuming significant team effort. With these insights, they collaborate with Product Owners to reprioritize tasks, ensuring alignment with strategic objectives and efficient resource allocation.

Manage Dependencies Across Teams and ARTs

Managing dependencies is a shared responsibility between Product Managers and Product Owners. PulsePoint AI provides visibility into dependency progress, enabling effective collaboration and proactive risk mitigation.

 

How PulsePoint AI Helps:

  • Monitor and Address Dependency Risks: PulsePoint AI reveals whether dependent coding tasks are progressing or stalling, allowing Product Managers to collaborate with Product Owners to address risks before they impact delivery schedules.

  • Identify Recurring Dependency Issues: By reviewing historical reports, Product Managers can uncover patterns of delays or bottlenecks in dependencies, helping them address systemic causes and refine planning for future PIs.

  • Coordinate Teams Across Levels: PulsePoint AI equips Product Managers with actionable insights for alignment discussions with Product Owners and stakeholders. These data-driven discussions ensure timely resolution of critical dependencies.

 

Example in Action: PulsePoint AI shows that little coding activity has been recorded on a backend API dependency required by multiple teams. The SAFe Product Manager recognizes this as a potential delay and engages the relevant Product Owner to investigate. Through their discussion, the Product Owner identifies resource constraints within their team and takes steps to address the issue. Together, they implement a more structured process for handling dependencies, reducing the likelihood of similar delays in the future and improving collaboration across ARTs.

Enhance Collaboration Between Product Managers and Product Owners

PulsePoint AI acts as a shared source of truth, enabling both Product Managers and Product Owners to access consistent insights into real work being done. This shared understanding fosters better collaboration and ensures alignment between program-level strategy and team-level execution.

 

How PulsePoint AI Helps:

  • Promote Shared Visibility: With PulsePoint AI, Product Managers and Product Owners access the same insights into coding activity. Product Managers gain a high-level understanding of progress, while Product Owners use detailed data to guide team execution effectively.

  • Support Joint Problem-Solving: PulsePoint AI highlights coding challenges, allowing Product Owners to engage with engineers to resolve issues while keeping Product Managers informed. This shared problem-solving ensures alignment across tactical and strategic layers.

  • Enable Proactive Discussions: PulsePoint AI identifies potential risks or areas needing focus, enabling Product Managers to initiate productive conversations with Product Owners. These discussions ensure tactical challenges are resolved in a way that aligns with program goals.

 

Example in Action: PulsePoint AI reveals that a critical deliverable is falling behind. The Product Manager works with the Product Owner, who identifies and resolves a resource constraint impacting progress. This collaboration ensures the deliverable gets back on track, maintaining alignment with program objectives.

Gain High-Level Progress Visibility

While Jira Align provides an overview of planned work, it doesn’t reflect the real progress being made in coding. PulsePoint AI offers objective, up-to-date insights into actual coding activity, giving Product Managers a clear view of what’s truly happening across teams.

 

How PulsePoint AI Helps:

  • Monitor Feature Progress: PulsePoint AI provides visibility into coding activity, ensuring Product Managers can identify which tasks are advancing and which are stalled. This allows Product Managers to align efforts with priorities and redirect resources where needed.

  • Identify Delays: PulsePoint AI highlights tasks with little or no coding activity, helping Product Managers proactively address delays. This ensures discussions with Product Owners focus on resolving specific blockers and keeping sprints on track.

  • Leverage Historical Data for Patterns: Weekly PulsePoint AI reports enable Product Managers to interpret historical coding data and identify potential patterns of bottlenecks or inefficiencies. For example, by reviewing consistent delays in testing, Product Managers can work with Product Owners to refine workflows or allocate more resources to QA efforts.

  • Provide Stakeholder Updates: PulsePoint AI generates comprehensive progress data based on actual coding activity, enabling Product Managers to craft detailed and reliable updates for stakeholders. This ensures accuracy without requiring disruptive inquiries to developers.

 

Example in Action: A SAFe Product Manager reviews PulsePoint AI and discovers that a critical feature marked “In Progress” in Jira Align shows no coding activity over the past three days. Recognizing a disconnect, they engage the Product Owner to investigate. Together, they uncover a blocker involving unclear requirements and work with the team to resolve it, ensuring the feature is back on track for timely delivery.

Understand the Impact of Unplanned Work

Unplanned work disrupts both program objectives and team-level execution. PulsePoint AI provides visibility into coding activity outside of planned objectives, helping Product Managers and Product Owners understand its impact and address underlying causes.

How PulsePoint AI Helps:

  • Identify Deviations from Planned Work: PulsePoint AI reports on all coding activity, including tasks linked to Jira items and unlinked work such as bug fixes or refactoring. This visibility helps Product Managers understand the root causes of unplanned work and collaborate with Product Owners to improve planning and reduce disruptions in future PIs.

  • Quantify the Cost: While PulsePoint AI does not track time directly, it reveals the volume of unplanned work through coding activity insights. Product Managers can use this data to assess the impact on overall productivity and adjust resource allocation or sprint planning accordingly.

  • Analyze Patterns Over Time: Historical data from PulsePoint AI highlights recurring trends in unplanned work, such as frequent last-minute requests or emergency bug fixes. These insights help Product Managers and Product Owners address systemic inefficiencies, reducing disruptions in future PIs.

 

Example in Action: PulsePoint AI shows that ~15% of the ART’s coding activity in the last PI was spent on unplanned tasks, such as urgent bug fixes. After analyzing historical trends, the Product Manager identifies recurring production issues as the root cause. Collaborating with Product Owners and the RTE, they allocate buffer time in upcoming sprints to handle high-priority fixes and improve backlog grooming to reduce unplanned work.

Conclusion

PulsePoint AI unlocks business agility by empowering SAFe Product Managers to make quicker and more confident decisions. Acting as a shared source of truth between Product Managers and Product Owners, PulsePoint AI enhances understanding and awareness through actionable insights into real coding activity. This shared visibility strengthens collaboration, ensuring alignment, addressing challenges, and driving value delivery. By providing the clarity needed to bridge strategic goals and team-level execution, PulsePoint AI enables faster, more informed decision-making—key to achieving and sustaining business agility.

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