Penome is a product planning and prioritization tool designed to help Product Managers (PMs), CXOs, and engineering teams structure their feature planning and decision-making before execution. Unlike traditional execution-focused tools like Jira, Asana, or Monday, Penome operates at the pre-execution stage, ensuring that prioritization decisions are backed by data and stakeholder alignment. It provides a centralized, AI-driven system for gathering feedback, generating ideas, and structuring roadmaps, making it easier for organizations to plan effectively before moving into execution.
Role:
UI/UX Designer, Strategist
Industry:
Prdouct Management
Duration:
15 weeks
People Involved:
2 Designers
Problem Statement
In many organizations, Product Managers (PMs) plan and prioritize features without a structured system, relying on spreadsheets or undocumented logic. This results in inefficiencies, misalignment between stakeholders, and difficulties in justifying prioritization decisions. Key issues included:
Lack of a centralized and scalable feature planning process.
CXOs struggle to visualize and validate prioritization decisions.
Absence of a data-backed decision-making framework, leading to weak justifications during roadmap meetings.
Current roadmap tools (Jira, Asana, Monday) focus on execution, not strategic planning.
Goals & Objectives
Penome was designed to bridge the gap between ideation and execution by providing a structured, data-driven tool for PMs and stakeholders to plan features collaboratively. Our key objectives:
Create a structured prioritization system that integrates feedback, ideas, and stakeholder validation.
Provide visual decision-making tools (impact-effort graph, contribution score, voting system).
Ensure ease of adoption by integrating with existing product management ecosystems (e.g., Jira, Slack, Figma).
Improve alignment between PMs, CXOs, and engineering teams through transparency and data-driven insights.
Research
Our research involved a combination of competitor analysis, AI-driven insights, and user journey mapping.
Competitor Analysis: Evaluated existing tools like Aha!, ProdPad, Productboard, and Jira Product Discoveryto identify gaps in feature planning and prioritization.
User Personas & Journey Maps: Developed detailed personas to understand the pain points of PMs, CXOs, and engineering teams.
AI-Assisted Insights: Used ChatGPT and QoQo.ai to refine problem validation and prioritize key feature requirements.
Wireframes & Early Concept Testing: Designed initial wireframes to validate usability and user flows.
Approach: Designing a Structured Planning System
Our approach was centered around simplicity, familiarity, and scalability.
Simplicity: Ensured the UI/UX was minimalistic and intuitive, reducing the learning curve.
Familiarity: Used patterns from widely-used tools like Jira and Asana to maintain familiarity while improving upon feature planning.
Scalability: Designed the system to evolve into a full-fledged execution tool in later phases while focusing on planning initially.
User Testing & Feedback: Iterated based on closed-group feedback, refining the roadmap and prioritization mechanisms.
Design Solution: A Data-Driven Planning System
Penome introduces a comprehensive, AI-enhanced prioritization system that captures feedback, transforms it into ideas, evaluates those ideas collaboratively, and produces an actionable, evidence-backed roadmap.
Feedback Collection
Multi-source Input: Feedback can be pulled from internal teams (sales, support), user interviews, and even social media (e.g., X/Twitter) by providing handles during onboarding.
Competitor Intelligence: PMs can input competitor Twitter handles to allow Penome’s AI to collect feedback and generate actionable insights based on industry trends.
Structured Feedback Entries: Users can tag each piece of feedback (e.g., client, internal, competitor) to organize and filter insights.
Idea Generation
AI-Based Suggestions: Feedback can be grouped automatically and used to generate ideas through AI.
Manual Control: PMs and Contributors can also manually combine feedback into new ideas, allowing flexible input.
Multiple Ideas per Feedback: A single feedback item can spawn multiple solution ideas.
Idea to Epic Conversion
Idea Evaluation: Ideas are considered or discarded based on potential value.
Epic Formation: Selected ideas are turned into epics—concrete, well-defined items that are ready to be scoped and estimated by the execution team.
Initiatives, Features & Goals
Initiatives: A collection of epics that together move the needle on a particular strategic area.
Features: The top-level modules or capabilities of a product—each can include several initiatives.
Goals: Organizational targets set per product. Each goal can contain multiple initiatives. The North-Star Goalrepresents the primary long-term objective.
Canvas Module
Vision & Problem Statements: PMs can define key product problems and attach solutions to them.
Linking: Attachments, web links, and tagged initiatives make the canvas more actionable.
AI Context Generation: The system can auto-generate content based on minimal input.
Roadmap & Prioritization
Voting Mechanism: Contributors are given 100 chips to vote on epics before the roadmap meeting.
Contribution Score: Based on the GLC framework (Goals, Leverage, Confidence), this score informs how valuable each epic is.
Impact-Effort Graph: Visual representation of epics plotted by impact and effort helps in decision-making.
Flexible Views:
Now-Next-Later: Broad timeframes for agile planning.
Monthly/Quarterly: Calendar-based planning.
Goal-Based & Feature-Based Views: Epics grouped under relevant goals or features.
Product Portfolio & User Management
Multi-product View: PMs can manage several products under one organization.
Role Management: PMs (Admins), Contributors, and Viewers have different levels of access.
Role-based Billing: Only PMs and Contributors are billed; Viewers access the platform for free.
Integrations & Admin Controls
Jira Integration: Connect roadmap planning with task execution systems.
Admin Controls: Settings for terminology, voting chip allocation, AI settings, roadmap layouts, and notifications.
Stripe Billing Integration: Simplified invoice and subscription management.
Results & Future Scope
What impact has Penome made so far?
Success Metrics:
High Adoption & Activation Rates: Early users found value in seamless onboarding.
Organic Market Interest: Jira’s Design Head signed up for testing without outreach, indicating industry demand.
Beta Deployment: A client is already using Penome within their organization, with early feedback shaping Phase 2.
Future Scope:
Phase 2 Developments:
Integrations with Slack, Figma, VS Code, Jira to streamline workflows.
Task Execution Module to evolve into an execution tracking tool like Jira or Asana.
Enterprise Pricing Models to scale for larger organizations.
Visual Design Improvements to refine differentiation between feedback, ideas, and epics.
Key Learnings & Growth
The Biggest Takeaways
UI Token System Could Have Been More Scalable – Primitive tokens were used, but semantic tokens would improve scalability.
Lack of Prototyping Slowed Implementation – A stronger prototyping phase could have saved dev time.
Card UI Needs Better Differentiation – Feedback, ideas, and epics currently look similar, requiring visual refinements.
Time Management Was Crucial – A junior designer was removed from the project, requiring prioritization to stay on track.
Final Thoughts: Why This Project Matters
Penome is positioned to redefine product planning and prioritization by bridging the gap between ideation and execution.
With early traction from industry professionals and organic interest from Jira’s team, its potential for growth is evident. This project reinforced the importance of:
Structured planning and prioritization frameworks
AI-driven insights for decision-making
Stakeholder collaboration in product development
Moving forward, further design iterations and integrations will enhance Penome’s usability, ensuring its place as a key tool in modern product management.
