Decision Framing Workshop Kit

Decision Framing Workshop Kit — Facilitator Guide

Purpose: Turn a vague business ask into a clear decision, a testable analytics question, and a short, committed plan for analysis and action. This kit is optimized for a focused 2-hour session with a cross-functional group (requester, potential data/analytics contributors, decision owner, and 1–2 stakeholders).

Learning Outcomes

• Convert an ambiguous request into a concise decision statement.
• Map stakeholders and their interests and influence.
• Generate and evaluate options using a simple decision tree canvas (options, costs, outcomes).
• Define 1–3 metrics of success that are measurable and meaningful.
• Rapidly check data feasibility and create a short analytics brief / action plan.

Before the Session — Preparation

• Invite 6–10 participants. Aim for: decision owner, requestor, one analytics practitioner, one operations/implementation representative, one customer or product rep (where relevant), and a facilitator.
• Distribute the ask or background materials 48 hours in advance (one-page problem note).
• Print or share templates electronically: Stakeholder Map, Decision Tree Canvas, Metrics Worksheet, Data Feasibility Checklist, Follow-up Action Template.
• Reserve a whiteboard or collaborative virtual canvas (Miro, MURAL, Google Jamboard) and ensure screen sharing and file access work.

Materials

• Slide deck (6–8 slides): purpose, agenda, templates, example decision, next steps.
• Printable/virtual worksheets for each template below.
• Timer visible to participants, sticky notes (physical or digital), pens/markers.

Timed Agenda (2 hours)

1. Welcome & context (10 min)
2. Stakeholder mapping (15 min)
3. Problem framing & decision statement (20 min)
4. Options and decision tree (20 min)
5. Metrics-of-success worksheet (15 min)
6. Quick data-feasibility checklist (10 min)
7. Prioritization & action planning (15 min)
8. Wrap-up, owners, and next steps (5 min)

Facilitator Script & Activity Details

1. Welcome & Context (10 min)

Goal: Clarify the session's purpose and what success looks like.

• Introduce facilitator, roles, and expected outputs (decision statement, metrics, feasibility notes, committed next steps).
• Read the one-page problem note aloud (or ask requester to summarize in 2 minutes).
• Set norms: be concise, focus on the decision, surface assumptions explicitly.

2. Stakeholder Mapping (15 min)

Goal: Identify who cares about this decision, their interests, and influence.

1. Activity (8 min): Ask participants to place stakeholders on a 2x2 map: Influence (low–high) vs. Interest (low–high). Use sticky notes or virtual pins.
2. Discussion (7 min): For each high-interest or high-influence stakeholder, note their main concerns, what outcome they want, and the data they trust.

3. Problem Framing & Decision Statement (20 min)

Goal: Move from a broad problem description to a short decision statement that the analytics work will inform.

1. Activity (12 min): Use this template on a single slide or large card:
   • Context (one sentence)
   • Decision to make (one short sentence — actionable)
   • Who will decide
   • When the decision is needed
2. Refine as a group (8 min): Push for specificity. Replace vague verbs with options (e.g., 'increase retention by X', 'reduce downtime by Y', 'stop offering feature Z to segment A').

4. Options & Decision Tree (20 min)

Goal: Lay out the realistic options, expected outcomes, and costs/constraints so the analytics can compare alternatives.

1. Activity (12 min): Use the Decision Tree Canvas. For each option, capture:
   • Description of option
   • Expected positive outcomes (qualitative + potential numeric)
   • Key costs or risks
   • Who would implement
2. Discussion (8 min): Identify which outcomes are critical to distinguish options and which can be measured.

5. Metrics-of-Success Worksheet (15 min)

Goal: Choose 1–3 measures that will show whether the chosen action worked and are practical to measure.

Use the table below as the worksheet. Ask: will this metric change if we choose option A vs B?

6. Quick Data-Feasibility Checklist (10 min)

Goal: Rapidly surface whether the required data exists, is accessible, and trustworthy enough for an initial analysis.

1. Identify the top 2–3 metrics and list the likely data sources.
2. For each data source, answer: Is the data captured? Who owns access? Is it timely? Is quality sufficient?
3. Use yes/no and quick notes. If critical data is missing, identify proxy measures that could be used for a first pass analysis.

7. Prioritization & Action Plan (15 min)

Goal: Decide what analysis will be done, who will do it, and when the decision will be made.

1. Choose 1 analysis approach (quick experiment, retrospective analysis, A/B test, pilot, dashboard).
2. Fill the Follow-up Action Template with: Analysis task, Owner, Due date, Dependencies, Data needs, and Decision checkpoint.
3. Confirm the communication plan: who will be updated and how findings will be presented.

8. Wrap-up (5 min)

Restate the decision statement, metrics selected, the committed next actions, owners, and dates. Capture any open risks or assumptions explicitly.

Printable Templates (copy-paste friendly)

Stakeholder Map (quick table)

Columns: Stakeholder | Role | Interest (high/med/low) | Influence (high/med/low) | Key Concerns | Data they trust

Decision Tree Canvas (fields)

1. Decision statement
2. Option A — Description, Expected outcomes, Costs/risks, Implementation owner
3. Option B — (same fields)
4. What metric(s) will distinguish options?

Metrics-of-Success Worksheet (fields)

• Metric name
• Why it matters
• How it's measured (unit)
• Baseline value
• Target and timeframe
• Owner
• Frequency
• Data source
• Assumptions / known quality issues

Quick Data Feasibility Checklist (questions)

• Is the required data collected today? (Y/N)
• Who owns the dataset / table?
• Is historical data available for the required window? (Y/N)
• Is the data timely enough for the decision cadence? (Y/N)
• Are the identifiers needed to join sources available and reliable? (Y/N)
• Any known quality issues that would invalidate analysis? (brief note)
• Suggested proxy metrics if primary data is unavailable

Follow-up Action / Analytics Brief Template (one page)

1. Decision statement
2. Analytic question to answer
3. Recommended analysis approach (e.g., A/B, regression, cohort analysis, dashboard)
4. Primary metrics (as defined above)
5. Data sources and access owners
6. Assumptions and known data gaps
7. Deliverables (report, slide deck, dashboard prototype) and due dates
8. Owner(s) and reviewers
9. Decision checkpoint (date & attendees)

Facilitation Tips & Common Pitfalls

• Keep returning to the decision: analytics is valuable only if it changes what someone will do.
• Limit scope: prefer a smaller, measurable question you can answer well over a broad, political reframe that never finishes.
• Surface assumptions aloud and record them — they become testable hypotheses.
• Avoid over-specifying methods in the workshop; let the analytics owner recommend the best approach after an initial scoping of data.
• If stakeholders disagree on success metrics, ask them to rank metrics; use majority + decision owner veto to move forward.

Remote / Hybrid Adaptations

• Use a shared virtual board with templates pre-loaded. Assign colored sticky notes for each participant role.
• Breakout rooms work well for options generation; reconvene for synthesis and voting.
• Capture decisions and templates in a shared doc immediately; send the follow-up analytics brief within 24 hours.

What Success Looks Like After the Workshop

Within 48 hours: a one-page analytics brief with committed owners and dates. Within 2–4 weeks: initial analysis or prototype that maps back to the agreed metrics. The final decision should be made against the metrics and checkpoints developed in this workshop.

Example Mini-Case (short)

Problem: Marketing asks to 'improve campaign performance.' Decision framing outcome: Decide whether to reallocate budget from Channel X to Channel Y for Q4. Metrics chosen: CPA by channel, conversion rate by segment, incremental revenue per campaign. Data feasibility: CPA and conversion are available in the ad platform, but customer revenue needs a join with billing DB (owner identified). Action: analytics will deliver a 2-week comparative cohort analysis and a recommended allocation by Oct 1. Decision owner: Head of Marketing.

Next Steps & Recommended Extensions

• Convert the Metrics Worksheet and Follow-up Action Template into a simple interactive form so outputs are stored with the content item and can be tracked over time.
• Optionally create a short dashboard template that maps the selected metric(s) for ongoing monitoring after the decision is implemented.

End of kit.