Covid-19 Impact on Fintech Workforce

Apexio, a global fintech company based in Massachusetts, faced significant challenges between 2019 and 2023 due to the COVID-19 pandemic and the rapid growth of remote work. In 2020, driven by the increasing demand for digital financial services and the new opportunities in international markets, the company made several strategic decisions that, unfortunately, led to mass layoffs that had lasting effects well into 2024.
To understand the consequences of these actions and evaluate the company's hiring and firing practices during the pandemic, Apexio's HR department began a detailed analysis to examine workforce dynamics over recent years and develop strategies to prevent similar issues in the future. 

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Goals

The primary goal of this analysis is to evaluate the impact of the COVID-19 pandemic on Apeexio’s hiring and firing trends from 2019 to 2023, offering actionable insights for improving workforce management during critical periods.
This goal is divided into three sub-objectives:

• Analyze hiring and layoff trends: Examine how hiring patterns have changed over the years and identify significant shifts caused by the pandemic.

• Assess employee performance: Evaluate whether changes in the staff affected overall performance within the company.

• Track the impact on minority groups: Investigate how different demographic groups (such as age, gender, and race) were impacted by hiring and layoff decisions during this period.​

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To achieve these objectives, I will analyze various key performance indicators (KPIs) over the specified timeframe. The main metrics include:

• Attrition Rate: To assess the rate of employee turnover during the pandemic.

• Retention Rate: To measure how well the company retained staff during this time.

• Engagement Rate: To evaluate employee commitment and involvement in their work.

• Performance Rate: To determine how staffing changes influenced the company’s ability to meet its strategic goals.

• Satisfaction Rate: To understand employee satisfaction levels and how attrition and engagement influenced overall morale.

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By meeting these goals, the company aims to better understand how its hiring and firing strategies during the pandemic impacted workforce stability. Additionally, this analysis seeks to identify groups within the workforce who may have been disproportionately affected. The insights will be used to develop better workforce management strategies and recommend improvements to hiring and firing processes during periods of crisis.

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Stakeholders

​The success of this project depends on the teamwork and input of key stakeholders from different parts of the company. From the executive board to HR and employee representatives, each person has an important role in this analysis and the impact of its recommendations. Their different views help make sure the results meet business goals and employee needs, creating a fair and effective way to improve workforce management.

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• Executive Board

           Chief Executive Officer (CEO): Jhon Peters

           - Role:​​

• Define the main objectives of the analysis.

• Ensure that findings align with the company’s broader business goals.

 - Interests:​

• Understand the main causes of layoffs in the company.

• Develop strategies to prevent similar workforce challenges in the future.

• Protect the company’s reputation and maintain trust with stakeholders.

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• HR Department

  HR Manager: Sarah Johnson

- Role:​

• Provide historical data on hiring and terminations.

• Share insights about workforce composition and diversity.

• Give feedback on the effects of workforce decisions made during the pandemic.

- Interests:​

• Improve talent management and recruitment strategies.

• Reduce costs related to recruitment and termination.

• Increase employee retention and overall satisfaction.

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HR Data Analyst: Simón Zanetti

- Role:

• Analyze workforce data to identify trends and patterns.

• Create reports showing key metrics and trends for the HR Manager.

- Interests:

• Ensure data analysis is accurate and helpful for strategic decisions.

• Highlight opportunities to improve workforce planning.

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• Employees

Mark Frey: Labor Union Representative

- Role:

• Share feedback on how workforce decisions affected their satisfaction and laboral security through surveys, focus groups, and interviews.

- Interest:

• Advocate for fair and transparent workforce management practices.

• Influence policies that promote job security and workplace satisfaction.

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Data

The dataset contains a summary of the main indicators for each of the employees hired between 2019 and 2023. It includes information about the worker's profile, their employment history, and their performance during their time at the company. This data is collected from reports provided by the Human Resources department, surveys distributed among employees, and government reports.

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Dataset Specifications

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Tools

Excel

Excel was chosen for this project because it's versatile and effective for managing data during all stages, from cleaning to visualization. It's particularly suited for this analysis due to its ability to handle moderate data volumes, its user-friendly interface, and its compatibility with the organization’s existing processes. The project is divided into three main phases:

1. Data Cleaning and Transformation: Removing errors, standardizing formats, and preparing the data for analysis.

2. Analysis: Generating insights and trends using metrics and custom formulas.

3. Visualization: Creating clear charts and dashboards tailored for stakeholders such as HR executives and the finance team.

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The key Excel features used in the project include:

• Power Query: To simplify data preparation by automating tasks like importing, transforming, and loading data into the analysis workflow.

• Advanced Formulas: For creating custom metrics that provide deeper insights, such as calculating retention rates or performance trends.

• Power Pivot: For building data models and connecting multiple datasets to power an interactive dashboard.

• Macros: For creating interactive elements that enhance user engagement and design.

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​While Excel has some limitations in handling very large datasets, it is well-suited for this project’s scope and enables efficient collaboration across teams. Its strong visualization capabilities and integration with other reporting tools make it an ideal choice.

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Methodology

This project employed a structured approach to data analysis using Excel's advanced features. The methodology includes four main stages: data cleaning and transformation, analytical computation, data modeling, and enhancing user interaction through macros.

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Data Cleaning and Transformation

Power Query was a critical tool for preparing raw data and ensuring it was ready for analysis. The following steps were undertaken to clean and transform the data:

• Eliminated columns that were not useful for the project, such as "MaritalStatusID," "GenderID," and "EmpStatusID," to focus only on relevant information.

• Generated additional columns from existing data, such as "employee_age," which was calculated based on the "DOB" (Date of Birth) column.

• Rearranged columns into a logical and intuitive order to facilitate easier navigation and understanding.

• Applied best naming practices to improve readability. For instance, the "MaritalDesc" column was renamed to "employee_marital_status" for greater clarity.

• Standardized data types for consistency, such as converting the "employee_last_review_engagement" column from string to decimal format.

• Applied targeted replacements to clean or standardize data as needed.​

• Loaded the cleaned and transformed datasets into Excel tables or Power Pivot for further analysis.​

This systematic and automated process significantly reduced the risk of manual errors, improved the quality of the data, and ensured a reliable foundation for subsequent analysis.

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Data Modelling

Power Pivot was integral to creating a scalable and robust data model, enabling advanced analysis and integration of multiple datasets. Its features allowed for seamless data connections, efficient calculations, and interactive visualizations, supporting a cohesive and dynamic workflow. Key techniques included:

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• Established relationships between datasets, such as linking employee information, departmental data, and performance metrics, to create a unified framework.

• Enabled cross-table analysis without the need for manual lookups, improving efficiency and scalability.

• Developed advanced measures and calculated fields to enhance the depth of analysis.

• Powered interactive dashboards by integrating Power Pivot data models with slicers, pivot tables, and visualizations.

By combining Power Pivot's relational modeling capabilities with DAX and interactive features, the project delivered a highly efficient and adaptable data analysis solution. This approach ensured that insights were comprehensive, actionable, and accessible to stakeholders.

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Data Analysis

The analysis phase employed a combination of advanced Excel features and functions to extract meaningful insights from the data. These tools and techniques ensured the data was transformed into actionable insights while maintaining flexibility and precision. Key methods included:

• Custom Metrics:

  • Organized the data by using tables, allowing automatic updates and easy filtering, ensuring calculations stayed accurate as new data was added.

  • Formula-based columns were created using Excel to extract and manipulate data directly within the tables. These formula-driven columns transformed raw data into meaningful metrics.

  • The KPIs, such as employee engagement or employee satisfaction, were calculated using calculated columns within tables or DAX, ensuring adaptability and accuracy.

• Dynamic Analysis:
  Advanced formulas and techniques were used to enable flexible and insightful analysis:

  • LOOKUP Functions: VLOOKUP, HLOOKUP, and the more robust XLOOKUP were utilized to retrieve specific data points from structured datasets, ensuring efficiency in cross-referencing information.

  • Conditional Logic: IF, AND, OR, and IFS functions categorized data into meaningful groups, such as high-performing and underperforming employees.

  • Aggregation Functions: SUMIFS, COUNTIFS, and AVERAGEIFS allowed data to be summarized across multiple criteria, supporting multi-dimensional breakdowns by factors like department or gender.

  • Comparative Analysis: Formulas like PERCENTILE and RANK evaluated individual performance against team benchmarks or historical trends.

• Pivot Tables:

  • Used extensively to summarize and analyze large datasets interactively. Combined with the use of Power Pivot, 

  • Features like Show Values As enabled quick calculations of percentage contributions, differences from previous periods, and running totals.

  • Slicers and filters made it easy to explore the data dynamically, allowing stakeholders to drill down into specific regions, departments, or time frames.

• Data Formatting:

  • Applied conditional formatting to highlight trends, anomalies, or KPIs exceeding targets, using color scales and icon sets for improved readability.

  • Standardized numeric, date, and percentage formats to ensure clarity and consistency across all outputs.

This comprehensive approach to data analysis harnessed Excel's powerful features to provide actionable insights while ensuring flexibility, scalability, and accuracy.​​

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Data Visualization

Data visualization was a crucial component of the project, focusing on creating clear, engaging, and professional visuals to communicate insights effectively. The following Excel's advanced design tools and formatting features were utilized to enhance the presentation and usability of the dashboard:

• Custom Shapes and Design Elements:

  • Used shapes to create visual boundaries, highlight key metrics, and add stylistic elements to the dashboard.

  • Grouped and aligned shapes for a clean, organized layout, ensuring visual consistency.

  • Applied shadows and gradients to shapes for a modern, professional appearance.

• Gridlines and Alignment:

  • Leveraged gridlines and snap-to-grid functionality to ensure precise alignment of charts, shapes, and text elements.

  • Maintained consistent spacing and balance across the dashboard for a polished look.

• Grouped Charts:

  • Combined multiple chart types into a single visualization to present complex data relationships clearly, such as using bar and line graphs to compare performance trends against targets.

  • Grouped charts with labels and shapes to create cohesive visual units, improving readability and context.

• Custom Formatting:

  • Customized chart elements such as axis labels, data points, and legends for clarity and emphasis.

  • Removed unnecessary elements like chart borders or gridlines to create a cleaner visual focus.

• Interactive Visual Elements:

  • Added slicers and buttons integrated with charts to allow users to filter and explore data dynamically.

  • Used color coding, icons, and conditional formatting to highlight trends, outliers, or key performance areas.

These visualization techniques ensured the data was not only informative but also visually appealing, helping stakeholders quickly grasp insights and make data-driven decisions.

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User Interaction

Macros played a critical role in enhancing the project’s interactivity and user experience, creating a dynamic and intuitive interface for the user. Some of the features applied here were:

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• Designed buttons and controls to dynamically hide and show graphs based on user actions, such as selecting a category or applying a filter.

• Enabled users to focus on specific visualizations, such as drilling down into charts or metrics with a single click.​

This combination of interactivity and automation transformed the Excel dashboard into a powerful and user-friendly tool, enabling stakeholders to explore and analyze data effortlessly while maintaining a polished, professional design.​

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Results

The analysis revealed significant workforce shifts influenced by the pandemic, including rising attrition and declining retention from 2019 to 2022, with partial recovery by 2023. Employee engagement and performance saw sharp declines during the pandemic, highlighting challenges in maintaining morale and productivity. Representation trends exposed retention and equity gaps, particularly for younger female employees and minority groups. These findings emphasize the need for targeted strategies to rebuild stability, enhance diversity, and improve engagement post-pandemic.

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Insights

• Workforce

  • The headcount increased consistently in 2020 (+15%) and 2021 (+10%) but declined in 2022 (-7%) and slightly in 2023 (-1%), suggesting a possible shift in hiring strategies or increased terminations during the last two years.

  • The attrition rate has risen steadily from 13% in 2019 to 36% in 2022 and slightly dropped to 29% in 2023. This indicates growing challenges in retaining employees, especially between 2021 and 2022.

  • Retention rates have fallen over the years, from 92% in 2019 to 79% in 2022, followed by a slight rebound to 84% in 2023. The drop from 2021 to 2022 (-6%) is particularly notable and aligns with rising attrition rates.

  • Employee engagement saw a concerning decline between 2019 (76%) and 2022 (63%). However, a recovery of 73% in 2023 (+17%) suggests potential improvements in engagement strategies recently.

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• Performance 

  • Satisfaction ratings increased slightly between 2022 and 2023 (+1.6%) after a sharper rebound in 2022 (+4.7%) from a significant decline in 2020 (-15.6%). The sharpest drop occurred between 2019 and 2020, suggesting external or internal stressors impacting satisfaction levels.

  • The score ratings fell steeply between 2019 and 2021 (-19.7%) but recovered substantially in 2022 (+19%). However, 2023 saw another decline of -6.8%, indicating a potential inconsistency in efforts to sustain improvement.

  • Attendance ratings remained consistently high throughout the years, with only minor fluctuations. The largest drop occurred in 2022 (-0.8%) but stabilized in 2023 (+0.5%).

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• Representation 

  • The workforce composition has shifted significantly, with younger age groups (20–25 and 25–30) experiencing notable declines in female representation.

  • Mid-career employees (30–35) have remained relatively stable, while older age groups (35–50) show low overall representation across genders.

  • Male representation in most age groups has been more consistent compared to females, though slight declines are also observed.

  • White employees show consistent growth in representation for both genders, with females increasing significantly by 2023.

  • Black and Asian employees experienced fluctuations in representation, with both groups having low and unstable percentages.

  • Other racial groups (Hispanic, Native, and Others) show marginal or stagnant representation, with little to no growth for females.

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Implications​

• Workforce

  • The increasing attrition rates and declining retention levels from 2019 to 2022 highlight significant challenges in maintaining workforce stability. These trends likely resulted in higher turnover costs, lost productivity, and disrupted operations.

  • The consistent drop in engagement rates, especially from 2019 to 2022, suggests a growing disconnect between employees and organizational goals. Low engagement may have negatively impacted employee performance and overall morale.

  • The combination of rising attrition and reduced retention indicates potential vulnerabilities in the organization’s ability to retain high-performing talent, especially during periods of crisis or organizational change.

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• Performance

  • Persistent dissatisfaction, especially during 2020-2021, may indicate disengagement or dissatisfaction with workplace conditions during the pandemic period.

  • Performance scores show volatility, particularly with a recent dip in 2023, indicating that initiatives to drive improvement may not be sustainable or evenly implemented.

  • The score samples suggest ongoing performance management challenges and a need to address underperformance, which could reflect emerging issues such as burnout or dissatisfaction.

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• Representation

  • The decline in representation among younger female employees (particularly in the 25–30 age group) highlights potential retention and recruitment issues exacerbated by the pandemic.

  • Disproportionate impacts on minority groups suggest underlying inequities that may need to be addressed in workplace policies.

  • The stagnation in representation for certain racial groups, particularly Hispanic and Native employees, indicates a lack of targeted diversity efforts during the pandemic years.

  • Uneven recovery among different age and gender groups suggests potential long-term impacts on workforce stability and organizational diversity.

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Recommendations

• Develop a structured employee retention program, focusing on improving workplace satisfaction through tailored benefits, career growth opportunities, and regular feedback mechanisms.

• Conduct exit interviews, surveys and focus groups to identify root causes of attrition and identify specific barriers faced by certain demographics.

• Invest in initiatives to boost engagement, such as recognition programs, team-building activities, and clearer communication of company goals.

• Provide ongoing training and development opportunities to foster growth and commitment among employees.

• Implement proactive workforce planning strategies to stabilize headcount and reduce over-reliance on hiring during growth periods.

• Strengthen onboarding and mentorship programs to help new hires integrate more effectively, reducing turnover risks.

• Equip managers with tools to identify and address disengagement early, emphasizing empathy and transparency in leadership. Also, cultivate an inclusive and supportive workplace culture, ensuring employees feel valued and heard.

• Monitor and address unconscious bias in hiring and retention practices, focusing on underrepresented racial groups