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This project explores the intricate relationship between remote work, job satisfaction, mental health, and productivity across various industries and regions. Conducted during my time as a Junior Data Analyst Intern at Vephla University (under Vephla Group), this project combined Microsoft Excel, Power BI, and basic survey validation to deliver actionable workforce insights.
- Microsoft Excel – Data modelling, pivot tables, dashboards
- Power BI – Interactive visuals, advanced chart types
- Google Forms – Primary data collection (for validation)
- GitHub – Project documentation and portfolio showcase
- To analyse how different work modes (remote, hybrid, onsite) impact employee productivity, stress, and job satisfaction.
- To examine company support, mental health resources, and virtual meeting frequency as influencing factors.
- To recommend data-backed strategies for improving workforce wellness in modern work environments.
- Primary Source: Kaggle – Remote Work and Mental Health Dataset
- Secondary Source: A brief internal survey was conducted using Google Forms, validating similar patterns.
- Data Structure: Each row represents an employee’s experience. Columns cover demographics, work mode, stress, mental health, and productivity.
- No missing values or duplicate entries
- No major transformations were necessary
- Introduced a Data Dictionary for better stakeholder clarity
- Segregated variables into:
- Independent: Gender, Age, Region, Work Mode, Industry
- Dependent: Satisfaction, Stress Level, Productivity Change
- Employees who reported poor sleep were more likely to experience decreased productivity.
- Frequent virtual meetings (8+) strongly correlated with higher stress levels.
- Africa had the lowest access to mental health resources, yet high report rates of mental conditions.
- Company support was a critical factor for remote work satisfaction.
- Introduce mental health coverage as part of staff insurance
- Promote flexible scheduling and hybrid arrangements
- Encourage shorter virtual meetings and fewer per day
- Offer commute support or flexible resumption for on-site staff
- Remote work did not always reduce stress — without support, it could increase it
- Employees working on-site but close to work reported lower stress than expected
- Burnout was prevalent in roles like Data Science, Management, and Design
- Donut Chart: Work Mode Distribution
- 100% Stacked Bar: Mental Health by Job Role
- Line Chart: Productivity Change vs Years of Experience
- Clustered Charts: Stress by Region, Satisfaction by Work Mode
- Treemaps, Pie Charts, etc.
- Used Gauge, Ribbon, Funnel, and Decomposition Tree
- Created a multi-line chart showing productivity across experience bands
- Included a map chart to show regional distribution
- Data was regional, not country-specific
- No time-based variables (e.g., no way to compare pre- vs post-pandemic trends)
- Primary survey responses were skimmed due to time constraints
- Collect more detailed country-level data
- Introduce timestamps to observe trends over time
- Expand dataset to include qualitative feedback from employees
Hi, I'm Oluwademilade Adeniyi, a passionate data analyst with experience in Excel, Power BI, and cross-industry analytics. I was the Team Lead for this project, working with a rotating team of 10 to deliver insights on employee productivity and well-being.
This project was a powerful learning experience and a meaningful contribution to the conversation on employee wellness in the digital age. Through real data, storytelling, and practical recommendations, I demonstrated how thoughtful analytics can reshape workplace decisions.
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