📊
Analytics Leadership · Prioritization Playbook

Stop Being
Overwhelmed.
Start Delivering What Matters.

A field guide for analytics teams on how to receive, interrogate, prioritize, validate, and launch requests — with confidence and clarity.

📥 Step 1 — Intake
🔍 Step 2 — Classify
❓ Step 3 — Question
📐 Step 4 — Score
🔬 Step 5 — Validate
🚀 Step 6 — Launch
🔍 Classify First — Always

Every request is one of two things.

Before you write a single query, answer this question. Your entire prioritization strategy flows from it.

?
🤔
CURIOSITY-DRIVEN

"I was just wondering..."

Someone wants to explore data without a clear business decision tied to the outcome. Valuable for discovery — but queued differently.

You'll hear things like:
◆ "Can we pull a report to see if..."
◆ "I'm curious whether there's a trend..."
◆ No decision linked to the findings
◆ No real deadline with consequence
⚠️ Not bad — just queued differently. Be transparent about why.
VS
🚀
IMPACT-DRIVEN

"This informs a real decision."

Tied to an executive review, a business decision, cost savings, or customer experience outcome. These move the needle.

You'll hear things like:
◆ "We need this before the MBR next week"
◆ "Leadership is asking for this"
◆ A clear decision will be made on findings
◆ Hard deadline with a real business consequence
✅ Prioritize these. Document the business decision up front.
❓ The Prioritization Conversation

Ask these 5 questions.
Every. Single. Time.

These aren't optional. They surface hidden assumptions, expose fake urgency, and protect your team's focus before a single line of SQL is written.

💡
Question 1
"How will this help?"

What specific outcome or action will this enable? What changes if you do this vs. don't?

Listen for:
A decision, a process change, a metric improvement — not just "it would be good to know."
🔥
Question 2
"Why is this a priority right now?"

What makes this urgent today vs. two weeks from now? What event or deadline is driving this?

Listen for:
A business review, leadership ask, or deadline — not just "because I need it."
⚖️
Question 3 — The Power Move
"Should I deprioritize something else for this?"

My team is working on [X] and [Y]. If I pick this up, one of those gets pushed. Which trade-off are you comfortable with?

💥 This is the most powerful question.
Stakeholders who say "everything is priority" change their tune fast when asked to trade off against real work.
📉
Question 4
"What happens if we don't?"

If this analysis doesn't happen this week, what's the business consequence?

⚠️ If the answer is "nothing" — it's curiosity.
🎯
Question 5
"What does done look like?"

If I hand you this Friday — what format? A slide? A number? A dashboard? A recommendation?

✅ Misaligned deliverable format = re-work.
“
Not every request deserves equal urgency. Your job as an analyst is to protect the team's focus — and to help stakeholders understand that prioritizing everything is the same as prioritizing nothing.
— Director of Analytics
📐 Score It

Rate before you commit.

Score the request across three dimensions. The scores guide — they don't decide. Use your judgment, but be able to defend your call to your director.

💥
Business Impact
Does this drive a real business decision, cost savings, or CX outcome?
⏱️
Urgency
Is there a real deadline with a real consequence attached?
🔧
Effort Required
How much team bandwidth does this actually consume?
Your score = your decision
🔴
12–15 pts → Do Now
High impact, urgent, manageable effort. Get it on the calendar today.
🟡
9–11 pts → Prioritize This Week
Strong case. Consider what trade-off is needed to fit it in.
🔵
6–8 pts → Queue It
Worth doing, but not urgent. Schedule with a clear ETA.
⚪
<6 pts → Defer / Decline
Politely decline with a clear rationale. Protect the team.
🏗️ The Delivery Pipeline

Once you commit — follow the chain.

Every step in this pipeline exists for a reason. Skipping one creates a trust deficit you'll spend weeks recovering from.

📥
Capture
Intake the Request
Before interpretation creep sets in
🔍
Classify
Curiosity or Impact?
Sets the entire priority lane
❓
Question
5 Hard Questions
No query until Q3 is answered
📐
Score
Score & Decide
Objective + context = decision
📋
Scope
Set Expectations
Written scope confirmed before you start
🔬
Validate
Peer Review + QC
Non-negotiable before sharing
📚
Document
Log the Process
Reproducible by anyone in 30 min
🚀
Launch
Insight + Release
Data tells. Insights sell.
📋
SCOPE CONFIRMATION

Set written expectations
before you start

Vague commitments = disappointed stakeholders. Every request needs a written scope confirmation before a single line of code is written.

✅ In Scope
What will be delivered, in what format, by when
🚫 Out of Scope
What will NOT be done in this iteration
💬 Send a Slack/email confirmation and wait for reply before starting.
🔬
DATA VALIDATION

Wrong numbers
destroy trust permanently

Peer review is not optional. A wrong insight is worse than no insight. Do not present unvalidated numbers to leadership.

●
Row count & null check on key fields
●
Date range verified (correct fiscal period?)
●
Totals cross-validated against source
●
Peer reviewed: logic, spot-checks, charts
●
Peer sign-off documented with name + date
💡 Insight Articulation

Data tells. Insights sell.

You haven't done your job until you've answered "so what?" three times. A number without a story is just noise.

The "So What?" Ladder
📊
The Finding
"Contact rate increased 12% WoW"
↓
So what?
💰
The Implication
"That's ~$2M in unplanned contact cost"
↓
So what?
🎯
The Action
"We must address digital deflection by Q2 or miss savings target"
🔑
Key Findings
3–5 bullets. Metric → Direction → Magnitude → vs. Baseline. Nothing more.
💡
Business Implications
The "so what." Why does this finding matter to the business? What risk or opportunity does it reveal?
✅
Recommended Actions
Specific. Assigned. Time-bound. "Monitor trends" is not an action.
🔭
What We're Watching Next
Commit to a review cadence. Set an escalation threshold. Follow through.
🚀 Launch

Before you hit send — check the list.

The release email isn't the deliverable. The insight is. The email is just the vehicle.

Pre-Launch Checklist
✓
All data quality checks passed
✓
Peer review completed and sign-off documented
✓
Methodology documented and saved (Confluence, GCS, etc.)
✓
Scope confirmed with stakeholder before work began
✓
Numbers spot-checked by a second set of eyes
✓
Key insights clearly stated — not just data
✓
Recommended actions are specific + time-bound
✓
Deliverable saved in shared team drive
🎉
Released! Ship it.
Anatomy of the Release Email
Subject:
[Analytics] {Request Title} — Findings & Recommendations
1
Context (1 sentence)
What was asked and why
2
🔑 Key Findings
3–5 bullets. Metric, direction, magnitude
3
💡 What This Means
Business implications — the "so what"
4
✅ Recommended Actions
Owner, action, deadline — no vague suggestions
5
📁 Documentation Link
Where to find the methodology + query + data
✅ Peer reviewed · 🔬 Data validated · 📚 Documented
⭐ The Principles

The rules that protect your team.

5
Questions to ask before any work begins
3x
Ask "so what?" three times to find the real insight
2
Pairs of eyes on every number before it ships
0
Exceptions to the peer review rule
🛡️
Protect focus ruthlessly
Saying no (or "not now") to low-value requests isn't blocking your stakeholders — it's protecting your team's ability to do their best work on what actually matters.
✍️
Write everything down
Verbal agreements evaporate. A written scope confirmation before work starts, and documented methodology after, is the baseline standard — not a nice-to-have.
💡
Insight over output
Your stakeholders don't need more data. They need clarity, direction, and confidence to act. If your deliverable doesn't answer "so what?" — it's not done yet.