Why this framework exists
Design teams invest against gut instinct rather than structured evidence of where the friction actually is — usually because nobody has mapped the full customer journey, let alone quantified which moments matter.
Enterprise hardware sales cycles are long and multi-stakeholder. Four distinct audiences — Economic Buyer, Clinical Champion, Technical Stakeholder, End User — each want different things, at different moments, and they don’t all care about the same jobs.
This prototype is the map. It’s built on the Ulwick Outcome-Driven Innovation method: every job a customer tries to get done across the eight lifecycle stages is rated on Importance and Satisfaction. Where those gap wide, design has leverage. Where they don’t, design doesn’t.
The data came from customer interviews, stakeholder workshops, and internal review. It’s not the answer — it’s a shared starting point that replaces "I think" with "we measured."
Four people buy enterprise hardware — and none of them want the same thing
Every job in the matrix below is scored against one of these four people. Color-coded throughout the rest of the framework so you can see at a glance whose pain is being quantified.
The eight stages, ranked by where we have leverage
Every stage in the enterprise hardware buying and ownership journey. The accent bar at the top of each card reflects that stage’s average opportunity score — the taller the bar, the wider the gap between importance and current satisfaction. Click a stage to filter every view below. Execute and Confirm carry the most risk to customer trust.
Select a stage to read its definition. The accent bar on each card encodes the average opportunity score — the wider the importance-satisfaction gap, the brighter the accent.
All 40 jobs, sortable and filterable
Sort by any column. Click a row to highlight the matching dot in the opportunity quadrant.
| Rank | Stage | Type | Segment | Job Statement | Opp | ROI |
|---|
From interview to Opportunity Score
Every job is rated on Importance (how much it matters) and Satisfaction (how well it’s served today) on a 1–10 scale. The Ulwick formula amplifies gaps — jobs where customers care a lot but get little relief. That amplified score is the Opportunity Score.
Where the gaps cluster — stages by job type
Every cell is a group of jobs grouped by lifecycle stage and job type. Darker fill means a wider importance-satisfaction gap (higher avg opportunity score). Click a cell to filter to that slice. The pattern tells the story: Emotional jobs during Confirm and Execute are where customer trust erodes fastest — those cells glow brightest because no one has designed for them yet.
Importance vs Satisfaction — where the gaps are
Each dot is a job. Position maps Importance and current Satisfaction. Color groups the job type, dot size reflects ROI priority. The bottom-right "Opportunity" zone — high importance, low satisfaction — is where design investment has the highest leverage.
The three jobs design should fix first
Pulled from the matrix by ROI Priority — high opportunity, high business impact, low effort. All three are emotional jobs in the Confirm and Execute stages. Notice what’s NOT here: new features. These are communication and reassurance gaps.
Which stages carry the most risk
Ranked bar view of the same data the heatmap summarizes. The shape of this chart is the argument — Execute and Monitor are far outside the tolerance band of the rest. Those are the stages where customer trust erodes fastest.
What this framework changes
Most roadmaps are built on the loudest voice in the room. This one is built on 40 jobs, scored, ranked, and prioritized.
The next time engineering asks why we’re investing in a post-sale communication cadence instead of another dashboard, the answer is a number, not a hunch. Three decisions fall out of this data:
First, stop treating Sales as separate from Implementation — the Confirm and Execute stages carry the most risk and the fastest wins. Second, emotional jobs outrank functional ones on ROI almost everywhere in the lifecycle, which means our communication patterns matter as much as our feature velocity. Third, the Evolve stage is underinvested — renewal risk is already written into the gap scores today.
This prototype is interactive on purpose. Every stakeholder gets the same view of the same data. Disagreement moves from "I think" to "here’s the score, and here’s why I’d weight it differently" — which is the conversation a design leader wants their cross-functional partners to be having.