💸 Venture Capital Portfolio Risk Analysis: Evaluating Layoffs & Startup Failure Rates 

1. Executive Summary
This project aims to assist the Venture Capital (VC) management team in identifying investment portfolio risk levels and evaluating the health of the global startup sector (2020–2023). Utilizing a global layoffs dataset, the analysis covers stages from Data Cleaning & Standardization to Exploratory Data Analysis (EDA) using MySQL. By focusing on total startup shutdowns (percentage_laid_off = 1), this project maps out the primary risk concentrations across Funding Stages and Industry Sectors. Based on the analysis conducted, I recommend enhancing due diligence on startups in the Retail and Food industries that are in the early funding stages (Seed – Series B).

2. Business Problem

Background: Venture Capital management requires a data-driven risk evaluation based on historical performance to understand which sectors and funding stages carry the highest risk of capital loss.

Key Analytical Questions:

1. Data Integrity: How can we ensure the operational dataset is free from duplicate records and inconsistent formatting?

2. Shutdown Breakdown by Stage: Which funding stages are most vulnerable to complete shutdowns (100% layoff)?

3. Shutdown Breakdown by Industry: Which industries record the highest number of failed companies?

4. Yearly Top Risk Sectors: Which sectors dominated the highest layoff volumes during the initial pandemic year (2020)?

3. Tech Stack & SQL Methodology

Database Engine: MySQL / MySQL Workbench.

Data Cleaning & Staging:

• Data Isolation & De-duplication: Created a staging table (layoffs_staging2) and applied ROW_NUMBER() OVER(PARTITION BY ...) to identify and remove duplicate rows (row_num > 1).

• Standardization & Cleaning: Trimmed whitespace from company names (TRIM), standardized industry name variations (e.g., mapping 'Crypto%' to 'Crypto'), and removed trailing punctuation from country names.

• Type Casting & Imputation: Converted string date columns into standard DATE format using STR_TO_DATE() and populated missing industry records via SELF JOIN.

Advanced Analytics:

• Aggregations & Filtering: Isolated complete shutdown events (percentage_laid_off = 1 AND stage != 'Unknown') to calculate total failed companies (COUNT(company)) and their average failure year (AVG(YEAR(date))).

• Multi-CTE & Ranking: Employed WITH ... AS constructs and DENSE_RANK() OVER(PARTITION BY years ORDER BY laid_off DESC) to extract the top 5 most impacted industries per year.

 4. Key Insights

🔹 1. Failure Rate by Funding Stage 

Based on complete company shutdown events 

• Seed Stage (High Risk): Represents the most vulnerable funding stage with a total of 23 companies undergoing complete failure (averaging in year 2021).

• Series B & Series A: Ranked next with 19 companies (Series B) and 13 companies (Series A) experiencing total shutdowns.

• Acquired & Late Stage: 12 acquired companies still experienced complete failure, whereas later stages such as Series C (7 companies), Series E (3 companies), and Post-IPO (3 companies) recorded significantly lower failure counts.

🔹 2. Failure Rate by Industry Sector 

• Retail & Food (Top Risk): Experienced the highest number of company closures, each recording 13 failed companies (Retail failures concentrated earlier at an average year of 2020, while Food averaged at 2021).

• Finance & Education: Followed closely with 12 companies (Finance) and 9 companies (Education).

• Healthcare & Crypto: Each recorded 7 failed companies (both sharing an average failure year of 2022).

🔹 3. 2020 Industry Risk Landscape (Top 5 Ranked)

Based on total layoff volume during the first pandemic year (2020):

1. Transportation: 14,656 employees (Rank 1)

2. Travel: 13,983 employees (Rank 2)

3. Finance: 8,624 employees (Rank 3)

4. Retail: 8,002 employees (Rank 4)

5. Food: 6,218 employees (Rank 5)

5. Business Recommendations

1. Stricter Due Diligence on Early-Stage (Seed - Series B): Given that the highest concentration of shutdowns lies in Seed (23), Series B (19), and Series A (13), VCs are advised to tighten minimum runway requirements and unit economics evaluations before deploying capital into early-stage deals.

2. Allocation Mitigation in Retail & Food Sectors: Retail and Food lead in total company closures (13 companies each). VCs should consider an underweight allocation strategy or elevate operational readiness benchmarks for portfolios in these sectors.

3. Second-Wave Crisis Preparedness (Crypto & Healthcare): Failures in Crypto and Healthcare occurred later on average (2022). VCs need to closely monitor portfolio burn rates in Crypto and Healthcare during prolonged market downturns.