Enterprise healthcare.
Agile design.
15 years of product design — leading $40M agile teams and consulting across distributed product orgs.
Non-Profit Founder
50+ free design education events — lectures, studio tours, and community workshops.
Design Mentor
400+ students supported via Discord, ADPList, and Hop — 100+ 1:1 mentorship sessions.
Event Speaker
Speaker and host at design conferences — sharing perspectives on UX and agile product design.
Giving leadership the whole picture.
A performance dashboard for ABC Bank's call center — replacing twenty hand-built spreadsheets with one automated view of productivity and quality across product lines, teams, and every individual rep.
The brief, at a glance.
- ABC Bank call center — reps phone customers to complete product applications
- Five product lines: personal loans, mortgages, car loans, life insurance, credit cards
- Rep goal: as many applications as possible — fast and accurate
- A uniform, automated dashboard for senior leadership
- Productivity and quality — by product line, team, and individual
- Lives as a new tab in XYZ Tool, available on demand
Aligning first: the Product Canvas.
Before designing anything, I run a facilitated conversation that walks stakeholders through four questions — captured together, in their words, on one shared canvas.
What's the problem?
Name the pain we're solving before any solution talk — agreed on and written down.
What are the business goals?
Define what success measurably looks like for the bank, so every design choice has a test.
Who are the users?
Identify everyone the experience touches — senior leadership, supervisors, and the reps behind the numbers.
What are the user needs?
What each user must be able to see and do for those goals to be met.
What's the problem?
Leadership can't quickly or reliably see performance across the call center — because the data reaches them through slow, hand-built supervisor reports that each measure things differently.
What are the business goals?
The problem, broken into achievable goals.
Automate the pipeline
Data flows from XYZ Tool to the dashboard with zero manual export or assembly steps.
Make it self-serve
Leadership opens the dashboard any time, on demand — nobody waits on a report request.
Keep it current
Same-day data freshness — what leadership sees reflects today, not last cycle's snapshot.
Standardize the metrics
One shared definition of productivity and quality that every supervisor and team is measured by.
Surface every level
Product line, team, and individual rep — all visible in one place, no gaps between reports.
Make it comparable
Any two teams or reps, side by side, on identical metrics and time ranges — trusted enough to act on.
Users.
Everyone the dashboard touches — not just the people who log in.
Senior leadership
Supervisors
Call-center reps
Analysts
User needs.
The outcomes and behaviors each user is trying to accomplish.
Senior leadership
Supervisors
Call-center reps
Analysts
The canvas, filled out.
Four questions answered — one shared page the whole project can point back to.
What's the problem?
Leadership can't quickly or reliably see performance across the call center — the data reaches them through slow, hand-built reports that each measure things differently.
What are the business goals?
Who are the users?
What are the user needs?
Compare and trust the numbers at the top; coach from problem areas in the middle; fairness and no surprises on the floor; consistent answers behind the scenes.
Creating hypotheses.
The canvas gives us the raw material — each hypothesis connects a goal, a person, an outcome, and a feature into one testable sentence.
| We will Achieve [business goal] | If [persona] | Attains [outcome] | Through [feature] |
|---|---|---|---|
| Zero report requests to supervisors | Senior leadership | Instant comparison of product lines, teams, and individuals | A self-serve overview with side-by-side comparison views |
| Best and worst product lines, obvious at a glance | Senior leadership | A side-by-side view of productivity and quality, at a glance | A ranked product-line leaderboard on the landing view |
| Best and worst product lines, obvious at a glance | Senior leadership | A side-by-side view of productivity and quality, at a glance | A quadrant chart plotting volume against rejection rate |
| Best and worst product lines, obvious at a glance | Senior leadership | A side-by-side view of productivity and quality, at a glance | Small-multiple trend cards, one per product line |
| Problems surfacing in days, not report cycles | Senior leadership | Problem areas that surface themselves — no hunting | Threshold-based alerts pinned to the top of the dashboard |
| Problems surfacing in days, not report cycles | Senior leadership | Problem areas that surface themselves — no hunting | A weekly digest of anomalies, delivered without logging in |
| Decisions made on today's data, not last month's | Senior leadership | Enough trust in the numbers to act on them | "Data as of" timestamps and a visible refresh cadence |
| Decisions made on today's data, not last month's | Senior leadership | Enough trust in the numbers to act on them | A metric glossary one click away from every number |
| Problems surfacing in days, not report cycles | Supervisors | A clear read on who needs coaching this week — and on what | Automated problem-area alerts on the supervisor's team view |
| One meaning of "top performer," everywhere | Call-center reps | Confidence they're measured the same as everyone else | A personal scorecard built on the shared metric definitions |
| Every decision citing one shared source | Analysts | Same-day answers to leadership's follow-ups | Saved views and exports that inherit the standard metrics |
Hypothesis prioritization.
Same hypotheses, now competing — value to the business against effort to build.
We will achieve zero report requests to supervisors if senior leadership attains instant comparison of product lines, teams, and individuals through a self-serve overview with side-by-side comparison views.
We will achieve best and worst product lines, obvious at a glance, if senior leadership attains a side-by-side view of productivity and quality through a ranked product-line leaderboard on the landing view.
We will achieve best and worst product lines, obvious at a glance, if senior leadership attains a side-by-side view of productivity and quality through a quadrant chart plotting volume against rejection rate.
We will achieve best and worst product lines, obvious at a glance, if senior leadership attains a side-by-side view of productivity and quality through small-multiple trend cards, one per product line.
We will achieve problems surfacing in days, not report cycles, if senior leadership attains problem areas that surface themselves through threshold-based alerts pinned to the top of the dashboard.
We will achieve problems surfacing in days, not report cycles, if senior leadership attains problem areas that surface themselves through a weekly digest of anomalies, delivered without logging in.
We will achieve decisions made on today's data, not last month's, if senior leadership attains enough trust in the numbers to act on them through "data as of" timestamps and a visible refresh cadence.
We will achieve decisions made on today's data, not last month's, if senior leadership attains enough trust in the numbers to act on them through a metric glossary one click away from every number.
We will achieve problems surfacing in days, not report cycles, if supervisors attain a clear read on who needs coaching this week through automated problem-area alerts on the supervisor's team view.
We will achieve one meaning of "top performer," everywhere, if call-center reps attain confidence they're measured the same as everyone else through a personal scorecard built on the shared metric definitions.
We will achieve every decision citing one shared source if analysts attain same-day answers to leadership's follow-ups through saved views and exports that inherit the standard metrics.
Iteration one, built.
The three quick wins become one leadership screen inside XYZ Tool — small enough to ship, real enough to learn from.
A ranked product-line leaderboard on the landing view
A quadrant chart plotting volume against rejection rate
A self-serve overview with side-by-side comparison views
Alerts, digests, timestamps, the glossary, rep scorecards, saved views — the other eight hypotheses stay in the backlog until iteration one teaches us where the value really is.
Prioritization, round two.
Eight hypotheses return from the backlog — joined by four new ones from critiquing what we just built, marked in plum.
We will achieve best and worst product lines, obvious at a glance, if senior leadership attains a side-by-side view of productivity and quality through small-multiple trend cards, one per product line.
We will achieve problems surfacing in days, not report cycles, if senior leadership attains problem areas that surface themselves through threshold-based alerts pinned to the top of the dashboard.
We will achieve problems surfacing in days, not report cycles, if senior leadership attains problem areas that surface themselves through a weekly digest of anomalies, delivered without logging in.
We will achieve decisions made on today's data, not last month's, if senior leadership attains enough trust in the numbers to act on them through "data as of" timestamps and a visible refresh cadence.
We will achieve decisions made on today's data, not last month's, if senior leadership attains enough trust in the numbers to act on them through a metric glossary one click away from every number.
We will achieve problems surfacing in days, not report cycles, if supervisors attain a clear read on who needs coaching this week through automated problem-area alerts on the supervisor's team view.
We will achieve one meaning of "top performer," everywhere, if call-center reps attain confidence they're measured the same as everyone else through a personal scorecard built on the shared metric definitions.
We will achieve every decision citing one shared source if analysts attain same-day answers to leadership's follow-ups through saved views and exports that inherit the standard metrics.
We will achieve one answer to any "who or where" question if supervisors attain the ability to drill from a bad number to the reps behind it through clickable leaderboard rows that open team and rep drill-downs.
We will achieve rejection spikes caught the week they start if supervisors attain visibility into why applications are being rejected through a ranked rejection-reason panel with week-over-week movement.
We will achieve decisions made on today's data, not last month's, if senior leadership attains enough trust in the numbers to act on them through shared time-range presets replacing the fixed 30-day window.
We will achieve team comparisons that are finally apples-to-apples if senior leadership attains instant comparison of product lines, teams, and individuals through an "organization average" benchmark row in every comparison.
Iteration two, built.
Three round-two quick wins layered onto the same screen — each one a direct answer to a gap we found in iteration one.
Clickable leaderboard rows that drill from a line to its teams and reps
A ranked rejection-reason panel with week-over-week movement
Shared time-range presets, plus an org-average benchmark in Compare
Alerts, digests, the glossary, rep scorecards and saved views remain — iteration two's usage data decides what earns iteration three.
How each actor reaches the goal.
Actors on the left, one shared goal on the right — and where their paths converge.
The problem we set out to solve Leadership couldn't quickly or reliably see performance across the call center — the data reached them through slow, hand-built reports that each measured things differently.
Automate the pipeline
Make it self-serve
Keep it current
Standardize the metrics
Surface every level
Make it comparable
What I'd bring.
Fifteen years turning high-stakes enterprise problems into systems people actually want to use — pairing business strategy with real craft, shipping my own products, and bringing teams along, from $40M agile orgs to the 400+ designers I've mentored.