Identifying Value And Viewpoints When Decomposing Epics

The Problem: Why Identifying Value and Viewpoints Matters When Decomposing Epics

Decomposing epics into smaller, more manageable user stories is a critical part of agile software development. However, if not done thoughtfully with clear goals in mind, this process can lead to fragmented delivery of value to users and disjointed products that fail to meet core needs.

Therefore, when breaking down epics, development teams must carefully identify the key value propositions for target user groups as well as incorporate diverse viewpoints from stakeholders. This upfront analysis provides crucial context for guiding how larger roadmap items should be divided into actionable sprints.

Neglecting value and perspectives during decomposition risks delivering features users don’t find meaningful or impactful. It also increases misalignment across the organization on what problems the product is supposed to solve. This article explores best practices for avoiding these pitfalls – enabling teams to decompose epics in ways that drive customer-centric value.

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Key Challenges in Identifying Value and Viewpoints

While considering value and viewpoints may sound straightforward, several common challenges can make it difficult:

Obtaining quality user research is time-consuming and complex
Stakeholders often disagree on which users and needs to prioritize
Teams struggle avoiding overly solution-focused mindsets vs. focusing on actual underlying problems
Organizations lack skills and practices for integrating diverse opinions into decisions

Due to these roadblocks, many teams end up decomposing epics based on technical considerations or pet solutions rather than high-value outcomes for customers. Others become paralyzed by stakeholder tensions and inability to reconcile contrasting wants into coherent roadmaps.

The following sections outline processes and techniques for overcoming each of these challenges – enabling fact-based evaluation of user perspectives and collaborative integration of inputs when breaking down epics.

Best Practices for Analyzing User Needs

High-quality user research provides the foundation for identifying value during epic decomposition. Here are proven methods for uncovering substantive, representative insights across customer segments:

1. Conduct Open-Ended Discovery Research

Start by conducting qualitative research like user interviews to form an initial hypothesis of customers’ goals and struggles. Open-ended discovery techniques minimize assumptions and uncover unexpected directions for exploration in later research.

2. Define Preliminary Personas and Problem Statements

Compile key themes from discovery into potential user personas with summaries of their goals and issues to solve. These guide target outcomes to validate in subsequent research. Clearly frame provisional problem statements as well.

3. Test and Refine with Quantitative Research

Design surveys and usability tests to quantify findings from discovery across wider samples of users. Analyze results to determine high-priority needs to address and refine personas and problems accordingly.

4. Synthesize Final User Stories

Compile all outputs into well-defined user stories reflecting the most significant, high-prevalence insights uncovered for key user segments. Attach relevant metric-driven persona details and problem statements.

These steps avoid decomposing epics based on hunches or untested assumptions around user value. Instead they anchor decisions in rigorous research – enabling teams to map stories directly against validated outcomes customers care about.

Examples of Decomposing Epics Based on Value and Viewpoints

With credible user insights in hand, teams can evaluate epics against findings to determine high-ROI decompositions. For example:

Epic: As a user, I want to be able to easily track my health so I can improve my fitness.

Problems to Address

Users struggle to consistently log diet, exercise, biomarkers
Users have difficulty correlating behaviors with outcomes
Users lack personalized recommendations for incremental improvement

Value-Driven Decomposition

Streamline data entry flows across tracking categories
Summarize longitudinal analytics views highlighting key correlations
Provide personalized health programs with progressive milestones

This example highlights how clarifying core problems guides division of a complex epic into simpler but still impactful stories. Contrast this with decomposing solely by capabilities – i.e. log food, log exercise, etc – which obscures broader user goals.

Epic: As a team manager, I want better insight into my team’s workflows so I can identify improvement opportunities.

Problems to Address

Managers unsure where teams spend time and how work flows
Process inefficiencies and blockers are opaque to managers
Hard for managers to quantify potential process optimization impact

Value-Driven Decomposition

Provide overview of team-level cycle time and throughput
Visually map primary workflow stages with details on variability
Estimate achievable throughput increases from streamlining workflows

Again this example shows how anchoring decomposition in specific user problems and needs enables more targeted, valuable deliverables – rather than vaguely defined analytics functionality.

Quantifying and Prioritizing Value Delivery

Alongside mapping stories to key user problems, teams should quantify potential value to be delivered through decomposed epics to inform ROI-driven prioritization and planning. Useful quantitative value metrics include:

User Coverage – Total addressable users affected by capability (% of target audience)
Individual Value – Projected increase in key usage or success metric per user from feature (mins saved, accuracy gained, etc)
Revenue Impact – Estimated influence on conversion rates, lifetime value, or other financial metric

To determine these numbers, triangulate between historical usage analytics, user research confidence levels, and market size modeling. Compare value delivery across proposed decompositions to guide sequencing and resourcing of work.

Documenting prospective value numerically also supports clearer tracking of outcomes post-release to validate and improve future assumptions. Prioritize decompositions delivering maximum measurable improvement for key user segments.

Integrating Diverse Viewpoints

Beyond users, decomposing epics should incorporate viewpoints from all key stakeholders – from executives and product leaders driving strategy to engineers building solutions. Cross-functional collaboration combats siloed thinking but raises tensions across competing opinions and priorities.

To enable unified epic breakdowns amid varied perspectives, leverage techniques like:

Vision Framing Exercises

Facilitate interactive sessions for stakeholders to define shared principles and priorities guiding decisions – highlighting core similarities often obscured by surface-level disagreements.

Collaborative Decomposition Sprints

Decompose complex epics cross-functionally over a concentrated period, using lightning demos and fast feedback cycles to quickly navigate tradeoffs. Accelerate shared understanding of considerations and constraints.

Laddering User Outcomes

Structure all perspectives against detailed user stories quantified by problem priority rather than individual preferences. Debate is framed constructively by anchoring on improving outcomes for agreed-upon target users.

This diversity of inputs ensures epics support organizational strategy while still solving customers’ highest-value difficulties – enabling coherent roadmaps reflecting both market pull and technical realities.

Overcoming Common Pitfalls

Avoiding the following common pitfalls when identifying value and viewpoints enables stronger epic decompositions:

Solution-first mindsets – Frame epics around user problems, not predetermined tech features or components.
Under-representing stakeholders – Seek inputs spanning all key groups early and often.
Failing to quantify impact – Tie all stories clearly to measurable value improvements for target users.
Lacking research rigor – Anchor firmly in substantive quantitative and qualitative insights.
Ignoring iteration – Continuously re-evaluate and enhance decomposition approaches against new learnings.

Avoiding these pitfalls accelerates value delivery while enhancing organizational cohesion around solving customers’ highest-priority problems.

Measuring Success

Teams can gauge the effectiveness of their approach to identifying value and viewpoints when decomposing epics by metrics like:

Number of user research citations referenced per decomposed story
Ratio of value-focused stories vs. technical stories in decomposition backlogs
Stakeholder survey ratings of cross-functional alignment
Value quantification accuracy post-implementation

Tracking indicators tied directly to the core goals of understanding users and unifying perspectives provides critical visibility into progress – enabling continuous tuning until decomposition processes reliably yield customer-centric, high-ROI delivery vehicles aligned to organizational priorities.