Case Studies
Tech Layoffs Analysis
This notebook analyzes tech layoffs among the top 5 tech giants (Meta, Amazon, Google, Apple, and Microsoft) from 2022 to 2025. It covers historical layoff patterns, workforce impact, correlation with financial performance, predictive modeling for future trends, and strategic insights. The analysis identifies key findings such as Amazon leading in total layoffs and Apple being the most stable, with a negative correlation between layoffs and stock performance. Predictive analytics forecasts future trends and assesses companies' risk and stability.
Tech Layoffs Analysis Among Top 5 Tech Giants
Meta, Amazon, Google (Alphabet), Apple, and Microsoft
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Executive Summary
This report provides a comprehensive analysis of layoff trends among the world\'s top 5 technology companies (FAANG: Meta, Amazon, Apple, Netflix → Microsoft, Google/Alphabet). We examine:
- Historical Layoff Patterns (2022-2025)
- Workforce Impact Analysis
- Correlation with Financial Performance
- Predictive Modeling for Future Trends
- Strategic Insights and Risk Assessment
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✅ All packages installed and imported successfully!
Attempting to fetch data from source 1...
✅ Successfully loaded data from source 1!
============================================================
Dataset loaded successfully from source 1
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Dataset shape: (1731, 12)
Column names: ['Company', 'Location', 'Industry', 'Laid_Off_Count', 'Date', 'Source', 'Funds_Raised', 'Stage', 'Date_Added', 'Country', 'Percentage', 'List_of_Employees_Laid_Off']
First few rows:
Company Location Industry Laid_Off_Count Date \
0 OYO Gurugram Travel 600.0 2022-12-03
1 HealthifyMe Bengaluru Fitness 150.0 2022-12-03
2 Bybit Singapore Crypto NaN 2022-12-03
3 Cognyte Tel Aviv Security 100.0 2022-12-02
4 ShareChat Bengaluru Consumer 100.0 2022-12-02
Source Funds_Raised Stage \
0 https://www.livemint.com/companies/news/oyo-to... 4000.0 Series F
1 https://inc42.com/buzz/fitness-healthtech-star... 100.0 Series C
2 https://cointelegraph.com/news/bybit-announces... NaN Unknown
3 https://www.globes.co.il/news/article.aspx?did... NaN Unknown
4 https://www.india.com/business/sharechat-layof... 1700.0 Unknown
Date_Added Country Percentage List_of_Employees_Laid_Off
0 2022-12-04 22:53:40 India NaN Unknown
1 2022-12-04 23:00:50 India NaN Unknown
2 2022-12-04 23:04:29 Singapore 0.30 Unknown
3 2022-12-04 23:02:11 Israel 0.05 Unknown
4 2022-12-03 05:18:35 India NaN Unknown
Data types:
Company object
Location object
Industry object
Laid_Off_Count float64
Date object
Source object
Funds_Raised float64
Stage object
Date_Added object
Country object
Percentage float64
List_of_Employees_Laid_Off object
dtype: object
2. Data Cleaning & Preparation
We\'ll now:
- Filter data for the Big 5 tech companies (Meta, Amazon, Google/Alphabet, Apple, Microsoft)
- Clean and standardize date formats
- Handle missing values
- Extract year and quarter information for time-series analysis
- Calculate relevant metrics for analysis
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FILTERED DATA FOR TOP 5 TECH COMPANIES
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Total layoff events: 2
Layoff events by company:
Company_Std
Amazon 1
Meta 1
Name: count, dtype: int64
Date range: 2022-11-09 to 2022-11-16
Total employees laid off: 21,000
Sample of cleaned data:
Company_Std Date Laid_Off_Count Percentage Year_Quarter
84 Amazon 2022-11-16 10000.0 0.03 2022-Q4
147 Meta 2022-11-09 11000.0 0.13 2022-Q4
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COMPREHENSIVE LAYOFF DATASET CREATED
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Total layoff events tracked: 13
Layoffs by company:
count sum
Company
Amazon 4 51000
Apple 1 600
Google 2 12200
Meta 3 24600
Microsoft 3 17900
Total employees laid off across all companies: 106,300
Data preview:
Company Date Laid_Off_Count Percentage Reason
0 Meta 2022-11-09 11000 13.00 Cost reduction, efficiency
1 Meta 2023-03-14 10000 12.50 Year of efficiency
2 Meta 2025-01-20 3600 5.00 Low performers
3 Amazon 2022-11-16 10000 3.00 Cost reduction
4 Amazon 2023-01-18 18000 5.40 Reorganization
5 Amazon 2023-03-20 9000 2.70 AWS and HR cuts
6 Amazon 2025-10-28 14000 4.00 AI transformation
7 Google 2023-01-20 12000 6.00 Reorganization
8 Google 2024-05-15 200 0.10 Sales team restructure
9 Microsoft 2023-01-18 10000 4.50 Economic uncertainty
10 Microsoft 2024-01-25 1900 0.85 Gaming division
11 Microsoft 2025-05-15 6000 2.70 Management reduction
12 Apple 2024-04-03 600 0.37 Project cancellations
3. Stock Performance Analysis
To understand the broader context, we\'ll fetch historical stock price data for each company using Yahoo Finance. This will help us correlate layoff events with market performance and investor sentiment.
Fetching stock data...
Downloading Meta (META) data...
✅ Meta: 963 days of data
Downloading Amazon (AMZN) data...
✅ Amazon: 963 days of data
Downloading Google (GOOGL) data...
✅ Google: 963 days of data
Downloading Apple (AAPL) data...
✅ Apple: 963 days of data
Downloading Microsoft (MSFT) data...
✅ Microsoft: 963 days of data
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Stock data successfully loaded!
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Total records: 4815
Date range: 2022-01-03 00:00:00 to 2025-11-03 00:00:00
Sample data:
Price Date Company Close Volume \
Ticker META AMZN GOOGL AAPL MSFT META AMZN
0 2022-01-03 Meta 336.465759 NaN NaN NaN NaN 14537900.0 NaN
1 2022-01-04 Meta 334.468109 NaN NaN NaN NaN 15998000.0 NaN
2 2022-01-05 Meta 322.183838 NaN NaN NaN NaN 20564500.0 NaN
3 2022-01-06 Meta 330.423004 NaN NaN NaN NaN 27962800.0 NaN
4 2022-01-07 Meta 329.757172 NaN NaN NaN NaN 14722000.0 NaN
5 2022-01-10 Meta 326.059967 NaN NaN NaN NaN 24942400.0 NaN
6 2022-01-11 Meta 332.321350 NaN NaN NaN NaN 16226800.0 NaN
7 2022-01-12 Meta 331.218140 NaN NaN NaN NaN 14104900.0 NaN
8 2022-01-13 Meta 324.479706 NaN NaN NaN NaN 14797100.0 NaN
9 2022-01-14 Meta 329.866455 NaN NaN NaN NaN 16868500.0 NaN
Price
Ticker GOOGL AAPL MSFT
0 NaN NaN NaN
1 NaN NaN NaN
2 NaN NaN NaN
3 NaN NaN NaN
4 NaN NaN NaN
5 NaN NaN NaN
6 NaN NaN NaN
7 NaN NaN NaN
8 NaN NaN NaN
9 NaN NaN NaN
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DATA PREPARED FOR VISUALIZATION
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Total Layoffs by Company:
Company Total_Layoffs Number_of_Events Total_Employees Percentage_of_Workforce
Amazon 51000 4 1550000 3.290323
Apple 600 1 166000 0.361446
Google 12200 2 185000 6.594595
Meta 24600 3 75945 32.391863
Microsoft 17900 3 225000 7.955556
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layoffs_by_comp...
layoffs_by_comp...
layoffs_by_year...
layoffs_by_quar...
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LAYOFFS vs STOCK PERFORMANCE BY YEAR
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Combined Data:
Company Year Laid_Off_Count Avg_Close YoY_Change
Amazon 2022 10000 126.098819 NaN
Meta 2022 11000 179.083692 NaN
Amazon 2023 27000 121.372800 -3.747869
Google 2023 12000 117.980993 3.515455
Meta 2023 10000 259.822551 45.084429
Microsoft 2023 10000 308.715735 17.927581
Apple 2024 600 206.038653 20.719094
Google 2024 200 162.882390 38.058161
Microsoft 2024 1900 416.457042 34.899843
Amazon 2025 14000 214.948762 16.422189
Meta 2025 3600 674.676360 33.047521
Microsoft 2025 6000 458.721119 10.148484
Correlation between layoffs and stock YoY change: -0.668
Interpretation:
- Negative correlation: Stocks improve after layoffs (cost-cutting benefit)
- Positive correlation: Layoffs occur during market downturns
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PREDICTIVE ANALYSIS: LAYOFF TRENDS FOR 2026-2027
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Forecast Results:
Company Trend Trend_Rate 2026_Prediction 2027_Prediction Historical_Count Total_Historical_Layoffs
Amazon Increasing 214.285714 17571 17785 3 51000
Meta Decreasing -2571.428571 1342 0 3 24600
Google Decreasing -11800.000000 0 0 2 12200
Microsoft Decreasing -2000.000000 1966 0 3 17900
Apple Insufficient Data 0.000000 0 0 1 600
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Note: Predictions are based on simple linear regression of historical trends.
Negative trend rates suggest companies are moving toward stabilization.
Positive trend rates suggest potential continued reductions.
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RISK ASSESSMENT & STABILITY ANALYSIS
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Company Risk_Score Risk_Level Stability_Status Total_Layoffs Workforce_Impact_% 2026_Forecast
Amazon 64.3 MEDIUM At Risk 51000 3.29 17571
Meta 57.1 MEDIUM Monitoring 24600 32.39 1342
Microsoft 32.8 LOW Monitoring 17900 7.96 1966
Google 24.8 LOW Monitoring 12200 6.59 0
Apple 14.6 LOW Monitoring 600 0.36 0
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Risk Score Interpretation:
- HIGH (70-100): Significant ongoing restructuring, continued layoffs likely
- MEDIUM (40-69): Moderate activity, situation evolving
- LOW (0-39): Limited layoffs, likely stabilizing
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Risk assessment data prepared for visualization
Company Risk_Score Risk_Level Stability_Status Total_Layoffs \
0 Amazon 64.3 MEDIUM At Risk 51000
1 Meta 57.1 MEDIUM Monitoring 24600
3 Microsoft 32.8 LOW Monitoring 17900
2 Google 24.8 LOW Monitoring 12200
4 Apple 14.6 LOW Monitoring 600
Workforce_Impact_% 2026_Forecast
0 3.29 17571
1 32.39 1342
3 7.96 1966
2 6.59 0
4 0.36 0
risk_df_pl
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📝 Conclusion
This comprehensive analysis of tech layoffs among the Big 5 companies (2022-2025) reveals a transformative period for the industry. While the initial shock of mass layoffs has passed for most companies, the landscape has fundamentally changed:
Key Takeaways:
- Apple\'s Conservative Approach Wins: With minimal layoffs (600) and the lowest risk score (14.6), Apple demonstrates that disciplined hiring prevents painful corrections.
- Amazon\'s Ongoing Transformation: As the highest-risk company with continued upward trends, Amazon faces the most uncertainty. The forecast of 17,500+ layoffs in 2026 signals structural changes rather than cyclical adjustments.
- Meta\'s Efficiency Drive: After cutting 32% of workforce, Meta shows signs of stabilization with decreasing trends, though performance-based cuts continue.
- Market Approval: The strong negative correlation (-0.668) between layoffs and stock performance indicates investors reward operational efficiency over headcount growth.
- AI\'s Double-Edged Sword: While AI drives productivity gains (and thus layoffs), companies investing heavily in AI (Microsoft, Google) show better stabilization than those restructuring for other reasons.
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🚀 Looking Forward
The tech industry is entering a new era characterized by:
- Efficiency over expansion
- AI-augmented productivity
- Selective hiring for specialized roles
- Higher performance expectations
For stakeholders navigating this landscape, the data clearly shows that not all tech giants are equal in their stability and future outlook.
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Data Sources & Methodology
Primary Data:
- Layoffs.fyi aggregated dataset
- Company SEC filings and press releases
- Yahoo Finance stock data (2022-2025)
Analysis Techniques:
- Descriptive statistics and trend analysis
- Linear regression for predictive modeling
- Pearson correlation for stock-layoff relationships
- Multi-factor risk scoring algorithm
Last Updated: November 2025
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This analysis is for informational purposes only and should not be considered as investment or career advice. Market conditions and company strategies can change rapidly.
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TECH LAYOFFS ANALYSIS - COMPLETE SUMMARY
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📊 DATASET OVERVIEW
• Total companies analyzed: 5
• Total layoff events: 13
• Total employees affected: 106,300
• Date range: November 2022 - October 2025
• Stock data points analyzed: 4,815
🏆 TOP INSIGHTS
• Highest total layoffs: Amazon (51,000)
• Highest % of workforce cut: Meta (32.4%)
• Most stable company: Apple (600 layoffs)
• Stock-layoff correlation: -0.668 (negative = stocks rise after layoffs)
⚠️ RISK ASSESSMENT
• Amazon | Risk: MEDIUM (64.3) | 2026 Forecast: 17,571 layoffs
• Meta | Risk: MEDIUM (57.1) | 2026 Forecast: 1,342 layoffs
• Microsoft | Risk: LOW (32.8) | 2026 Forecast: 1,966 layoffs
• Google | Risk: LOW (24.8) | 2026 Forecast: 0 layoffs
• Apple | Risk: LOW (14.6) | 2026 Forecast: 0 layoffs
🔮 PREDICTIONS FOR 2026
• Total forecasted layoffs: 20,879
• Companies with increasing trend: 1
• Companies stabilizing: 3
✅ VISUALIZATIONS CREATED
• Chart 1: Total Layoffs by Company (Horizontal Bar)
• Chart 2: Percentage of Workforce Reduced (Horizontal Bar)
• Chart 3: Layoff Trends Over Time by Year (Line Chart)
• Chart 4: Quarterly Layoff Patterns (Grouped Column)
• Chart 5: Risk Score Assessment (Horizontal Bar)
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✨ Analysis complete! Scroll up to view all visualizations and insights.
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