Use statistics and data confidently in verbal discussions using the Data Citation Formula — and critically evaluate data used by others.
THE DATA CITATION FORMULA Format: "[Source] shows that [metric] is [rounded number], compared to [benchmark], suggesting [implication]." Example: "World Bank data shows India's female labour force participation is around 24%, compared to 61% in China — suggesting we are leaving an enormous productivity pool untapped." This single-sentence formula contains: source + metric + number + benchmark + implication. Complete data argument in one sentence.
WEAK data use: "India has a lot of startups so we're doing well in entrepreneurship." STRONG data use: "India had over 112,000 DPIIT-recognized startups as of 2024 — the third-largest startup ecosystem globally. More importantly, 13 unicorns were minted in 2023 alone, suggesting the ecosystem is not just growing in width but increasing in depth." WEAK data use: "GST has simplified taxes." STRONG data use: "Before GST, India had 17 central taxes, 13 state taxes, and 23 cesses — over 50 tax categories. Post-GST, that consolidated into a 4-tier rate structure. Compliance burden for manufacturing companies with multi-state operations dropped by approximately 30% according to KPMG estimates."
This GD is designed for data-heavy discussion. Cite at least 2 specific numbers. Challenge data used by others with the context question: 'That number is interesting — what is the comparison benchmark?' or 'Is that aggregate data or does it break down differently by income group?'
A consumer goods company claims its new product launch was 'very successful' because it achieved ₹100 crore in revenue in Year 1. What questions would you ask to evaluate whether this is actually a success?
💡 Hint: Your questions should all be about context: Compared to what target? Compared to competitors' launches? What was the marketing cost to generate this revenue? What is the gross margin? What is the repeat purchase rate? Data without context is meaningless.
The Data-Dense Argument: Speak for 90 seconds on 'The state of employment in India' using at least 4 specific data points. Before you start, spend 3 minutes building your data bank for this topic from memory. Record the speech. Review: Are numbers rounded? Did you source each one? Did you contextualize them with benchmarks?
Rate yourself honestly on today's performance. Track this across 30 days to measure growth.
Goldman Sachs analysts are trained to never present raw data. Every number must be contextualised — compared to a benchmark, a trend, or an expectation.
An analyst says in a meeting: 'India's GDP growth is 6.5%.' The MD stops them immediately.
The MD asks: '6.5% compared to what?' The analyst rebuilds: 'India's GDP growth of 6.5% is below last year's 7.2%, below China's 6.8%, but above the IMF's revised forecast of 6.1% — we're underperforming our potential but beating pessimistic expectations.'
A number without context is noise. A number with context is insight. In a GD, if you say 'this number is significant because it is higher/lower than X', you immediately elevate the discussion.
Pick 3 data points about Indian business. For each, find a comparison point. Practice presenting each as: '[Number] is [higher/lower] than [benchmark], which means [implication].'
India's literacy rate is 77.7%. Is this good or bad? What comparisons would you use, and what conclusion would you draw?
Complete all exercises and the speaking drill before marking complete. This unlocks Day 12.