This project explores and analyzes data on global layoffs from 2020 to early 2023 using SQL. The goal is to uncover trends in workforce reductions across companies, industries, countries, and funding stages.
Data was cleaned and explored using SQL (MySQL) in phpMyAdmin, and insights were drawn using aggregation, filtering, ranking, and window functions.
The dataset was cleaned prior to analysis:
- Handled missing and null values
- Standardized date formats
- Removed duplicates
- Verified data types
- The data spans from 2020 to early 2023
- Layoffs peaked in 2022, with 160,661 layoffs
- In just the first 3 months of 2023, layoffs already reached 125,677
- Amazon: 18,150
- Google: 12,000
- Meta: 11,000
- Salesforce: 10,090
- Philips & Microsoft: 10,000
116 companies reported 100% layoffs (73 of them in the USA).
| Industry | Total Laid Off |
|---|---|
| Consumer | 45,182 |
| Retail | 43,613 |
| Other | 36,289 |
| Transportation | 33,748 |
| Finance | 28,344 |
- USA: 256,559
- India: 35,993
- Netherlands: 17,220
- Sweden: 11,264
- Brazil: 10,391
A higher ratio suggests that companies in that country may have been less efficient with funding, potentially overhiring
Top - 5 most efficient countries:
| Country | Layoffs to Funds Ratio |
|---|---|
| Lithuania | 0.002 |
| Netherlands | 0.025 |
| Romania | 0.107 |
| United Kingdom | 0.143 |
| Norway | 0.146 |
Top 5 least efficient countries are:
| Country | Layoffs to Funds Ratio |
|---|---|
| Russia | 6.667 |
| Japan | 3.269 |
| Finland | 1.479 |
| Kenya | 1.39 |
| Denmark | 1.111 |
| Stage | Total Laid Off |
|---|---|
| Post-IPO | 204,132 |
| Unknown | 40,716 |
| Acquired | 27,576 |
| Series C | 20,017 |
| Series D | 19,225 |
Startups and post-IPO companies were hit hardest, indicating market pressure at all growth stages.
2020
- Uber, Booking.com, Groupon, Swiggy, Airbnb
2021
- Bytedance, Katerra, Zillow, Instacart, WhiteHat Jr
2022
- Meta, Amazon, Cisco, Peloton, Carvana, Philips
2023 (Q1 Only)
- Google, Microsoft, Ericsson, Amazon, Salesforce, Dell
- SQL (MySQL)
- Window Functions (
RANK,SUM OVER) - Aggregate Functions
- Joins & CTEs
- Data Cleaning Techniques
- phpMyAdmin