Why this matters
Dashboards only add value when they drive a decision or action. As a BI Analyst, you must capture when, why, and how users will make decisions so you can translate them into metrics, visuals, and alerts that people actually use.
- Real tasks you will face: interview stakeholders, define decision statements, translate needs into metrics and specs, avoid vanity dashboards, and align on success criteria.
- Outcome: a clear, testable use case for each dashboard tile or page that ties directly to a decision.
Concept explained simply
Dashboard use cases describe a specific decision a person makes, the trigger that prompts it, the information needed, and the action taken. Capturing these upfront keeps the build focused and measurable.
Mental model: Decision-first dashboarding
Think of each dashboard element as a decision assistant. For each decision, answer these seven questions:
- Who decides? (role)
- When and how often? (moment/frequency)
- What triggers the decision? (event/threshold)
- What question do they ask? (plain-language question)
- What information do they need? (metrics, dimensions, filters)
- What action can they take? (playbook/next step)
- How do we know it worked? (success metric)
Use Case Canvas (copy this template)
- Role & scenario:
- Decision statement: "If [trigger], then [role] will [action] within [timeframe]."
- Key question(s):
- Metrics & definitions:
- Dimensions (cuts) & filters:
- Thresholds & targets:
- Update latency needed:
- Visualization ideas:
- Action path / playbook:
- Ownership & permissions:
- Success metric (leading/lagging):
Decision Log (keep this lightweight)
Track: date, decision, owner, data used, outcome, follow-up. Use it to refine thresholds and retire unused visuals.
Worked examples
1) Executive revenue pacing dashboard
- Role & scenario: VP Sales reviews weekly revenue pacing Monday 9am.
- Decision: If weekly pacing < 90% of target by Wednesday EOD, reallocate pipeline to priority deals.
- Metrics: Booked revenue (current week), target, pacing %, pipeline coverage (4x rule).
- Dimensions: Region, segment, product line.
- Threshold: 90% pacing by Wed; 4x pipeline for month.
- Latency: Daily refresh is enough.
- Visuals: KPI cards (booked, pacing), line vs target, heatmap by region.
- Action: Assign top 10 deals to senior reps; send enablement request.
- Success: Month-end revenue; leading indicator: pacing recovers within 2 days.
2) Marketing campaign optimization
- Role & scenario: Performance marketer checks ads every morning.
- Decision: If CPA for any ad set > $35 for 2 consecutive days, pause and reallocate 20% budget to top performers.
- Metrics: CPA, CTR, spend, conversions.
- Dimensions: Channel, campaign, ad set, creative.
- Threshold: CPA > $35 for 2 days; CTR < 0.8% is risky.
- Latency: Intraday (hourly) preferred.
- Visuals: Sorted table with conditional formatting, trend sparkline per ad set.
- Action: Pause underperformers; duplicate best creative.
- Success: Weekly blended CPA; leading indicator: share of spend on top quartile ads.
3) Support operations monitoring
- Role & scenario: On-call support lead monitors queue during business hours.
- Decision: If open tickets > 120 or backlog age > 48h median, trigger surge staffing.
- Metrics: Open tickets, backlog age p50/p90, SLA breach rate, tickets per hour.
- Dimensions: Tier, channel, issue type.
- Latency: Near real-time (5–10 min).
- Visuals: KPI with traffic lights, line chart for arrivals vs capacity, queue by issue type.
- Action: Page on-call, add chatbots, update status message.
- Success: SLA adherence; leading indicator: queue length drops within 30 minutes.
Who this is for
- BI Analysts and Data Analysts who translate stakeholder needs into dashboards.
- Product, Marketing, Ops professionals defining data requirements with analysts.
Prerequisites
- Basic understanding of KPIs, dimensions, and data refresh/latency.
- Comfort interviewing stakeholders and writing clear requirements.
Learning path
- 1) Learn to elicit decisions and questions before metrics.
- 2) Practice writing decision statements and use case canvases.
- 3) Translate decisions into metrics, dimensions, and visuals.
- 4) Validate with stakeholders; adjust thresholds and latency.
- 5) Track adoption and outcomes; iterate.
How to capture dashboard use cases (step-by-step)
- Frame the decision.
Ask: What decision will you make with this? When? What will you do differently? - Write a decision statement.
Template: If [trigger], then [role] will [action] within [time]. - List questions, then metrics.
Start with plain-language questions. Only then map to metrics and definitions. - Define cuts and filters.
Which segments matter? Which filters must be default and which optional? - Set thresholds and targets.
Agree on alert levels and success criteria to avoid debate later. - Confirm latency and access.
How fresh must data be? Who can see what (roles, row-level security)? - Sketch visuals.
Pick the simplest visual that answers the question at a glance. - Document the action path.
Make the next step obvious (who to notify, what to change).
Interview prompts you can reuse
- Walk me through the last time you needed this data. What decision did you make?
- If this metric spikes/drops, what would you do in the next hour/day?
- Which version of this number do you trust today? How is it defined?
- What would make this dashboard obviously useful on a busy day?
Common mistakes and how to self-check
- Mistake: Starting with visuals. Fix: Start with decisions and questions; only then choose visuals.
- Mistake: Vague ownership. Fix: Name the role/owner in each decision statement.
- Mistake: No thresholds. Fix: Agree on targets and alert levels during requirements.
- Mistake: Over-refreshed data. Fix: Set latency to the minimum needed to make the decision.
- Mistake: Undefined metric. Fix: Add exact definitions and grain (daily, weekly, event-level).
- Mistake: No action path. Fix: Document the next step, tool, or process to act.
Self-check checklist
- Each dashboard element ties to a specific decision statement.
- Metrics are defined (formula, grain, source, filters).
- Thresholds/targets are explicit and agreed.
- Latency and permissions are documented.
- Action path and success metric exist.
Practical projects
- Create a Decision Log for one team and use it to refine thresholds over two weeks.
- Redesign an existing dashboard: remove elements that do not map to a decision.
- Build a use case pack (3 canvases) for Exec, Marketing, and Ops, then validate live.
Exercises
These mirror the graded exercises below. Do them here, then submit your answers in the exercise blocks.
Exercise 1: Draft a Decision-First Use Case (Retail)
Scenario: A store manager must prevent stockouts for top SKUs.
- Write a decision statement.
- List key questions.
- Define metrics, dimensions, thresholds, latency.
- Sketch visuals and the action path.
Exercise 2: Translate Decisions into Dashboard Requirements (SaaS)
Scenario: A product manager wants to improve free-to-paid conversion.
- Map decisions to metrics and definitions.
- Specify dimensions, filters, and segments.
- Set targets, alert thresholds, and refresh cadence.
- Document roles and permissions.
Quick checklist before you move on
- Decision statements are specific and time-bound.
- Metrics have clear formulas and grain.
- Thresholds/targets are set and owned.
- Data latency matches the decision window.
- Action path is obvious and feasible.
Mini challenge
Pick any weekly meeting you attend. Write one decision statement the meeting should enable. Draft the minimal dashboard element (one KPI or chart) that would make that decision faster. Keep it to 3 metrics max and a single threshold.
Who this is for, again (sanity check)
If you regularly turn stakeholder needs into dashboards and want them to be used for real decisions, this subskill is for you.
Next steps
- Apply the Use Case Canvas to one real stakeholder request this week.
- Run a 20-minute validation session to confirm thresholds and latency.
- Create a lightweight Decision Log and review outcomes after two weeks.
Quick Test
Anyone can take the test for free. Only logged-in learners will see saved progress and scores in their profile.
When you are ready, start the Quick Test below to check your understanding.