Introduction
Many people jump straight into formulas, PivotTables and charts when working in Excel. The result is often confusion, weak insights, or numbers that do not answer any real question. A simple way to avoid this is to slow down and think before analyzing. The DIG method—Discover, Introspection, and Goal Setting—provides a clear thinking structure for Excel data analysis. When combined with ChatGPT, it becomes a strong study and practice tool. This guide explains the DIG method step by step, shows how it applies to Excel work and provides ready-to-use prompts that can be applied to any dataset. This article is written as an educational study note for students, analysts and professionals who want clearer reasoning and better outcomes from Excel analysis.
Step 1: Discover — Understand the Data Before Analysis
Purpose:
Discover focuses on understanding what the data represents before calculations or visualizations begin.
At this stage, the goal is not to analyze but to read the data carefully and question it.
What to examine
- What the dataset is about
- What each row represents
- What each column measures
- Time coverage and frequency
- Units of measurement
- Missing values, duplicates, or strange entries
Excel actions
- Review column headers and sample rows
- Check data types (text, numbers, dates)
- Count records and blanks using
COUNT,COUNTA,COUNTBLANK - Use filters to scan for unusual values
Study notes
- Write down assumptions
- Note unclear column names
- Identify fields that may need cleaning
- Record known data limitations
ChatGPT prompt for Discover
I am working with an Excel dataset.
Here are the column names and a few sample rows:
[Paste column names and 5–10 sample rows]
Help me:
1. Explain what each column likely represents
2. Identify possible data quality problems
3. Suggest basic checks I should run in Excel
4. Highlight assumptions that could affect analysis
Step 2: Introspection — Question the Data
Purpose:
Introspection is about asking thoughtful questions and exploring patterns inside the data. Instead of forcing conclusions, you allow the data to show behavior, changes, and relationships.
Questions to explore
- How does the data change over time?
- What differs across categories or groups?
- Which values are unusually high or low?
- Are there trends, cycles, or sudden shifts?
- Which variables appear connected?
Excel actions
- Build PivotTables to group and summarize
- Calculate averages, medians, and growth rates
- Create simple charts (line, bar, scatter)
- Apply conditional formatting to highlight extremes
Study notes
- Record visible trends
- Note surprises and contradictions
- Identify outliers and possible explanations
- Write early hypotheses without treating them as facts
ChatGPT prompt for Introspection
These are the columns in my Excel dataset:
[Paste column list]
My early observations are:
[List 2–3 things you noticed]
Help me:
1. Suggest useful PivotTables to explore patterns
2. Identify relationships worth examining
3. Explain trends I should test for
4. Flag possible outliers and what they could indicate
5. Recommend Excel formulas to support this analysis
Step 3: Goal Setting — Turn Insights into Decisions
Purpose: Goal Setting ensures analysis leads to a clear outcome rather than more tables and charts. This step connects insights to decisions, policy questions, or business actions.
Questions to define
- What decision needs to be made?
- What question must the data answer?
- What metric defines success or failure?
- Who is the audience?
- What level of precision is needed?
Excel actions
- Define key performance indicators (KPIs)
- Summarize findings in clean tables
- Build simple dashboards
- Highlight decision-ready numbers
- Prepare charts for non-technical audiences
Study notes
- Write the final analysis question
- List metrics used
- Note risks and limitations
- Clarify what the analysis does not answer
ChatGPT prompt for Goal Setting
Based on these findings from my Excel analysis:
[Paste key insights]
Help me:
1. Define clear analysis goals
2. Turn insights into decision-focused questions
3. Identify the most meaningful KPIs
4. Suggest how results should be presented
5. Point out risks of misinterpretation
Reusable Master Prompt: Full DIG Method
I am analyzing an Excel dataset using the DIG method
(Discover, Introspection, and Goal Setting).
Dataset context:
[Brief description of the dataset]
Columns:
[Paste column names]
Sample rows:
[Paste 5–10 rows]
Apply DIG by:
1. Explaining what the data represents and its limitations
2. Guiding introspection through patterns and relationships
3. Helping define clear goals, KPIs, and decisions
Keep responses practical and focused on Excel analysis.
Closing Note
The DIG method builds discipline into Excel work. Discover keeps assumptions in check. Introspection strengthens reasoning. Goal Setting ensures analysis leads to useful outcomes. When paired with ChatGPT, DIG works as both a learning framework and a repeatable workflow. It applies well to agriculture markets, finance, surveys and operational datasets and anywhere Excel is used to support decisions. Used consistently, DIG turns Excel from a spreadsheet tool into a thinking tool.
GlenH - Dec 22, 2025gghayoge at gmail.com