Your Business Analytics System

🔄 Quick Recall: In the previous lesson, you learned data storytelling — using the Situation-Complication-Resolution structure, choosing the right chart types, and following the pyramid principle to lead with answers when presenting to executives. Now you’ll integrate every concept from this course into a complete, reusable system.

Your Integrated Analytics System

This course covered six layers of business analytics capability. Here’s how they connect:

The sequence matters. You can’t build a useful dashboard without good metric design. You can’t design good metrics without a framework connecting them to strategy. And the best analysis in the world is wasted without clear communication.

The Complete Process

When facing any business analytics challenge, follow this five-step process:

Step 1: Start with the decision. What decision does this analysis support? Who makes it? How often? What would change their choice? If you can’t name the decision, you’re not ready to start analyzing.

Step 2: Choose your framework and metrics. Map the decision to the relevant framework (BSC perspective, OKR, or North Star). Select the leading and lagging indicators that inform it. Apply the vanity metric test to every proposed metric.

Step 3: Gather and analyze. Use AI for data exploration with context-rich prompts. Apply diagnostic techniques — cohort analysis for time-based trends, funnel analysis for conversion problems, comparative profiling for performance gaps.

Step 4: Build the view. Design a dashboard or report using the three-layer narrative. Place metrics with visual hierarchy. Include comparisons that give every number context.

Step 5: Communicate for action. Structure your findings using SCR. Lead with the answer (pyramid principle). Choose chart types that match the analytical question. Anticipate questions and prepare backup detail.

✅ Quick Check: Why does the analytics process start with “what decision does this support?” rather than “what data do we have?” Because starting with data produces analytics. Starting with decisions produces insights. The data you have is irrelevant if it doesn’t inform a specific decision — and the decision you need to make tells you exactly what data to look for.

Course Review

Building Your Playbook

Use this prompt to create a customized analytics system for your business:

Help me build a business analytics system.

Business: [describe your business, size, industry]
Key decisions made by leadership: [list 3-5]
Current analytics state: [what do you track now?
what tools do you use?]
Biggest analytics gap: [what do you wish you could
see or understand?]

Design a system that includes:
1. Balanced Scorecard with 3-4 metrics per
   perspective, tied to our specific business
2. A KPI hierarchy (North Star → Strategic →
   Operational → Diagnostic)
3. Leading/lagging indicator pairs for top 5 KPIs
4. Executive dashboard layout with the three-layer
   narrative
5. AI prompt templates for our recurring analysis
   questions
6. A monthly analytics review agenda

Implementation Roadmap

This week: Apply the vanity metric test to every metric you currently track. Cut the ones that don’t pass.

This month: Build a KPI hierarchy for your team or business. Define your North Star, pair leading indicators with your top lagging indicators, and create a simple dashboard with the three-layer narrative.

This quarter: Add AI to your regular analytics workflow. Create context-rich prompt templates for your recurring questions. Run your first cohort analysis on a metric that matters.

Key Takeaways

• Business analytics is a six-layer system: frameworks define what matters, metric design separates signal from noise, dashboards make it visible, AI accelerates exploration, diagnostic techniques find root causes, and communication turns insight into executive action
• The entire system starts with one question: “What decision does this analysis support?” — starting with data produces dashboards; starting with decisions produces insights
• The vanity metric test (“If this changed, would I act differently?”) is the single highest-impact concept because it operationalizes analytics thinking in one question applicable to any metric at any level
• Low dashboard adoption almost always signals a relevance problem, not a design problem — when analytics tools genuinely support the decisions people make, they use them voluntarily
• Every analytical finding needs the communication layer to create value — the Situation-Complication-Resolution structure and pyramid principle ensure your insights reach the people who can act on them