Prototyping And Iteration With Stakeholders

Why this matters

Mental model: The Triple Fit

• User fit: Does it answer the stakeholder’s question in their language?
• Data fit: Is the metric defined, sourced, and reliable enough?
• Workflow fit: Is the interaction (filters, drilldowns, refresh) natural in their daily process?

Each iteration should improve at least one of these fits without breaking the others.

Core workflow (5 steps)

1. Scope the question: Capture the decision, audience, and success criteria.
2. Low-fi prototype: Sketch wireframes or a simple BI mock with mocked/sampled data.
3. Feedback session: Demo, ask targeted questions, log decisions and open items.
4. Iterate: Convert feedback to a prioritized backlog, timebox, and update the prototype.
5. Converge: Freeze scope, define acceptance criteria, and promote to production-ready build.

Worked examples

Example 1: Sales KPI dashboard (executive audience)

Request: "We need a sales performance dashboard."

Low-fi prototype: A sketch with three tiles on top: Total Revenue (MTD), Pipeline Value, Conversion Rate; below that a trend line and a top-10 customers table.

Feedback questions:

• Which definition of revenue (bookings vs invoiced) matters for decisions?
• What time grouping suits you—week or month?
• Do you need drilldown from region to rep?

Iteration outcome: Execs chose bookings, monthly view, and region-to-rep drill. Added a target line to the trend to show goal attainment. Acceptance: "Above-the-fold tiles and trend must load in under 3 seconds with previous month comparison."

Example 2: Support backlog report (operations audience)

Request: "Show backlog by priority and SLA risk."

Prototype: Heatmap of tickets by priority x age bucket; filter by product; table of SLA breaches.

Issue discovered: "SLA risk" definition was inconsistent across products.

Iteration: Created a temporary derived field: SLA_risk = due_date within 24h and status not Resolved. Marked it with an info tooltip in prototype. Parallel data governance task opened to standardize SLA rules.

Example 3: Finance variance view (FP&A audience)

Request: "Explain monthly variance vs budget."

Prototype: Waterfall chart with variance breakdown and a table of top variance drivers.

Feedback: Finance wanted both absolute and percentage variance and a switch for currency vs local currency.

Iteration outcome: Added toggles for currency and variance mode, and pinned a variance-explanation note field that analysts can update per close cycle.

Who this is for

• BI Developers working with business stakeholders on dashboards and reports.
• Analytics engineers who translate business questions into metrics and visualizations.
• Data-savvy product owners wanting faster analytics feedback cycles.

Prerequisites

• Basic BI tool familiarity (e.g., building charts, filters, simple data models).
• Understanding of key metrics in your domain (sales, ops, finance, product).
• Comfort with simple data sampling and mock data creation.

Learning path

1. Learn to capture outcomes and acceptance criteria from stakeholders.
2. Practice low-fidelity sketching and lightweight KPI definitions.
3. Run a structured feedback session and log decisions.
4. Timebox iterations and track scope changes visibly.
5. Promote a beta to production with a release checklist.

Tactics you can apply today

• Use a one-page brief: decision, audience, 3 must-have metrics, success criteria, risks.
• Start with mocked or sampled data to avoid blocked sprints.
• Ask for "what would you remove?" not just "what to add?" to keep scope lean.
• End each session with a commit: what changes, by when, and how acceptance will be checked.

Decision this dashboard supports:
Primary audience:
Top 3 metrics (definitions included):
Must-have interactions (filters/drill):
Data refresh & source:
Success criteria for v1:
Risks/assumptions:
Next iteration plan (changes + date):
Owner:

Exercises

These mirror the tasks below. Do them now, then check solutions. If logged in, your progress will be saved.

Exercise 1: Low-fi dashboard prototype and feedback plan

Create a low-fidelity prototype (ASCII or paper) for this scenario: "Marketing wants to track weekly website signups, conversion rate from visit to signup, and top acquisition channels. They need a weekly view and a channel filter." Write 8 focused feedback questions you will ask in a 15-minute review.

Exercise 2: Iteration plan with acceptance criteria

From Exercise 1, draft a one-iteration plan. Include changes you will make, acceptance criteria, a timebox, and risks with mitigations.

Self-check checklist

• Is the prototype light enough to change in minutes, not hours?
• Do your questions probe definitions, edge cases, and decisions?
• Are acceptance criteria testable by a non-technical stakeholder?
• Is the timebox short (1–3 days) for fast learning?

Common mistakes and how to self-check

• Jumping to high fidelity too soon: If changes take more than an hour, step back to a lighter prototype.
• Vague metrics: Write a one-line metric definition and a small example table before building charts.
• Endless scope creep: Freeze v1 after 2–3 iterations; move extras to a v2 backlog.
• Unclear ownership: Name a single decision owner; log decisions with date and reason.
• No acceptance criteria: Agree on what "good" looks like before the next build.

Practical projects

• Rebuild one existing dashboard you own as a low-fi prototype and run a 20-minute feedback session; compare outcomes.
• Create a "prototype kit" (blank tiles, trend, bar, table, notes) you can reuse for any new request.
• Run a 2-iteration spike on a metric with unclear definition; document the before/after definition and acceptance criteria.

Next steps

• Schedule a stakeholder session for a current open request and bring a low-fi prototype.
• Adopt the mini-brief template for every new dashboard.
• Set a default cadence: 2-day iteration cycle with a 15-minute review.

Mini challenge

Pick any recurring report. In 30 minutes, produce a lighter prototype that answers the same question with fewer elements. In your next check-in, ask: "What did we remove that you didn’t miss?" Capture one permanent simplification.

Quick Test

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