Upstream Intake Process
Product teams needed a more structured way to evaluate ideas and requests before they reached development. Too often, work entered the pipeline without alignment on user desirability, business viability, or technical feasibility (DVF). This led to churn, unclear priorities, and wasted effort across design, product, and engineering. The goal of this initiative was to introduce clarity earlier in the lifecycle, without slowing teams down.
My Role
As a Design Strategist, I led the design and implementation of a scalable upstream intake process to bring clarity, alignment, and measurable decision-making to how work entered the product pipeline. My focus was on designing a process my team would actually adopt by embedding it into existing tools and workflows rather than introducing new systems.
What was designed:
A lightweight intake system that aligned teams on value and evidence before development began.
DVF Framing
Framed the intake process around DVF, ensuring every request was evaluated holistically for desirability, viability, and feasibility before moving forward. This created a shared language for prioritization and reduced subjective decision-making across teams.
Jira Integration
Embedded the intake workflow directly into Jira to lower the barrier to adoption and meet teams where they already worked. This ensured consistent participation across product, UX, and technical teams without introducing new tools or processes.
Transparency
Designed a Kanban-style intake flow that allowed requests to be captured, refined, prioritized, and selected in a transparent, visual way. This increased visibility into decision status, reduced duplicate requests, and set clearer expectations across stakeholders.
Approach
I focused on establishing shared decision criteria early in the product lifecycle. Instead of optimizing downstream execution, I designed a lightweight but rigorous intake model that aligned teams on value, feasibility, and evidence before work entered active development.
Enablers
The conditions that enabled adoption and sustained use.
Collaboration
Partnered closely with a Business Analyst and Product Owner to align qualitative research insights with quantitative product metrics. This closed the loop between discovery and prioritization and ensured intake decisions were grounded in both evidence and business impact.
Supporting Tools
Integrated supporting tools to connect research directly to intake decisions:
-
Dovetail: Used fields and tags to structure qualitative data and link insights directly to intake items, improving traceability.
-
UserZoom: Connected survey and usability metrics to DVF scoring, grounding prioritization in user evidence rather than assumptions.
Outcomes
Improved prioritization clarity: Teams aligned earlier on what work should move forward, reducing downstream churn and rework.
Consistently higher-quality intake requests: Requests entered the pipeline with clearer problem definition, supporting evidence, and shared expectations.
Organic adoption by team: By embedding the process into Jira, the intake model was adopted within the team without formal change management.
Improved decision confidence at portfolio level: Leaders gained visibility into how and why work was prioritized, improving trust in portfolio decisions.
Reflection
This work reinforced the value of design strategy as decision infrastructure, not just solution design. By introducing clarity earlier in the lifecycle, teams spent less time debating priorities and more time solving the right problems. The outcome was not a single artifact, but a repeatable system that balanced rigor with usability and aligned teams around evidence-based decision-making.