Building Repeatable Analysis

The Repetition Problem

In the previous lesson, we explored reporting for different audiences. Now let’s build on that foundation. Most analysis work is repetitive:

• Monthly reports on the same metrics
• Weekly performance reviews
• Quarterly business reviews
• Customer analyses following similar patterns

If you start from scratch each time, you’re wasting effort. If you build reusable workflows, analysis that took hours takes minutes.

What to Make Reusable

Not everything should be templated. Focus on:

High-frequency analyses Things you do weekly, monthly, or quarterly.

Stable structures Analyses where the questions stay similar, even if data changes.

Sharable workflows Analyses that others on your team also perform.

Anatomy of a Reusable Analysis

A complete reusable analysis has:

1. Documentation

What the analysis does:

• Purpose and question it answers
• Audience and use case
• Key output metrics

How it works:

• Data sources and refresh timing
• Transformations and calculations
• Key assumptions

How to use it:

• Step-by-step instructions
• What to update each time
• Common issues and troubleshooting

2. Data Pipeline

Input specification:

• What data format is expected
• What columns are required
• What time periods to include

Transformation steps:

• Data cleaning rules
• Calculated fields
• Aggregation logic

3. Analysis Template

Standard visualizations:

• Charts that show the key patterns
• Pre-configured with consistent formatting

Calculation framework:

• Standard metrics calculated
• Comparison points set up
• Variance calculations ready

4. Output Template

Report structure:

• Section headings
• Chart placement
• Summary format

Distribution setup:

• Who receives the output
• What format they prefer

Building Your First Template

Step 1: Do the Analysis Once Manually

Complete a full analysis the normal way. Note:

• What data you pulled
• What calculations you made
• What charts you created
• What structure the final report had

Step 2: Identify Repeatable Elements

What stays the same each time?

• Data sources
• Metrics and calculations
• Chart types
• Report structure

What changes?

• Date ranges
• Specific values
• Insights interpretation

Step 3: Create the Template

For spreadsheets:

• Create a workbook with:
  • Data input sheet (where fresh data goes)
  • Calculation sheet (formulas that process data)
  • Output sheet (charts and summaries that auto-update)
• Document how to refresh

For AI-assisted analysis:

• Create a prompt template:

## Monthly Sales Analysis Template

Analyze this sales data for [MONTH]:

[Paste data here]

Provide:
1. Total sales vs. previous month ($ and %)
2. Sales by region (table with % change)
3. Top 5 products by revenue
4. Key insights (3-5 bullets)
5. Anomalies or concerns to investigate

Quick check: Before moving on, can you recall the key concept we just covered? Try to explain it in your own words before continuing.

Step 4: Document and Test

Write instructions someone else could follow. Run the template with new data to verify it works.

AI-Powered Analysis Automation

Use AI to create and run repeatable analyses:

Creating analysis templates:

I perform a monthly customer churn analysis. Help me create a reusable template.

Currently I:
1. Pull data from [source]
2. Calculate churn rate by segment
3. Compare to previous months
4. Identify top churn reasons
5. Create a summary for leadership

Create a prompt template I can reuse each month by just pasting in new data.

Running templated analysis: Save your template and reuse:

## Monthly Churn Analysis - [January 2026]

[Paste your saved prompt template]

Data:
[Paste fresh data]

Building an Analysis Library

Over time, build a library of reusable analyses:

ANALYSIS LIBRARY
├── Recurring Reports
│   ├── Monthly sales summary
│   ├── Weekly traffic report
│   └── Quarterly business review
├── Ad-Hoc Templates
│   ├── Customer segment profile
│   ├── Product performance deep-dive
│   └── A/B test analysis
├── Data Quality Checks
│   ├── Standard data validation
│   ├── Anomaly detection
│   └── Reconciliation checks
└── Calculation References
    ├── Revenue calculations
    ├── Retention metrics
    └── Statistical tests

Document each with:

• Purpose
• How to use
• Last update date
• Owner

Practical Workflow Example

Monthly Sales Report Workflow:

Week 1 of each month:

1. Data Pull (5 min)

   • Export from sales system
   • Place in template input sheet

2. Refresh Analysis (10 min)

   • Update date range in template
   • Check calculations refresh correctly
   • Review auto-generated charts

3. Generate Insights (30 min)

   • Run AI prompt with updated data
   • Identify key changes from last month
   • Note anomalies or trends

4. Create Report (15 min)

   • Update executive summary
   • Add insight commentary
   • Finalize and distribute

Total time: ~1 hour Without template: ~4-6 hours

Exercise: Plan a Reusable Analysis

Pick an analysis you perform repeatedly.

Document:

1. What’s the question it answers?
2. What data does it use?
3. What calculations are involved?
4. What output does it produce?
5. What stays the same vs. what changes?

Sketch a template for automating it.

Key Takeaways

• Repetitive analyses should be templated—save mechanics time for thinking time
• Reusable analyses have: documentation, data pipeline, analysis template, output template
• Build templates by doing analysis once, then extracting repeatable elements
• Create AI prompt templates for analyses you repeat regularly
• Build an analysis library over time—organized, documented, maintained
• Time investment in templates pays back quickly with regular analyses

Final lesson: put it all together with a complete end-to-end analysis.

Up next: In the next lesson, we’ll dive into Capstone: End-to-End Analysis.