Tableau for human resource: How to analyze your HR data

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May 18, 2023

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HR data in tableau
In today's data-driven world, HR professionals have access to vast amounts of data that can be used to make informed decisions about their workforce. However, raw data alone is not enough. HR professionals need to be able to analyze their data effectively and communicate their findings to stakeholders. That's where data visualization tools like Tableau come in. Tableau can be used to analyze HR data in a visual and interactive way. In this article, we'll explore why it's essential for HR professionals to use data visualization tools like Tableau, how to get started with Tableau, and best practices etc. for analyzing HR data using Tableau.

Understanding HR Data

HR data includes any data related to an organization's workforce. This can include employee demographic data, performance metrics, turnover rates, recruitment metrics, and more. Analyzing this data can provide valuable insights into an organization's workforce, such as identifying areas for improvement, predicting future trends, and making informed decisions about hiring, training, and retention.

Steps for analyzing HR data, with Tableau

Here are the steps

Step 1. Define the research question or problem to be solved

  • Clearly define the purpose of the analysis and what questions you want to answer with the data.
  • Identify the relevant stakeholders who will be involved in the analysis and make sure their needs are considered.

Step 2. Collect relevant HR data from various sources and consolidate it into a single dataset

  • Gather data from various HR systems such as payroll, performance management, and employee surveys.
  • Ensure that the data is accurate, complete, and reliable.
  • Consolidate the data into a single dataset that can be easily analyzed in Tableau.

Step 3. Clean and prepare the data for analysis, including handling missing values, outliers, and formatting issues

  • Use Tableau's data preparation tools to clean and format the data for analysis.
  • Identify and handle missing values and outliers in the data.
  • Make sure that the data is properly formatted and consistent across all fields.

Step 4. Create visualizations using Tableau's drag-and-drop interface, selecting appropriate charts and graphs to represent the data

  • Use Tableau's drag-and-drop interface to create visualizations such as bar charts, scatter plots, and heat maps.
  • Choose the most appropriate visualizations for the data being analyzed and the questions being answered.
  • Make sure that the visualizations are clear, concise, and easy to understand.

Step 5. Use Tableau's data filtering, grouping, and sorting capabilities to explore the data and identify patterns and trends

  • Use Tableau's filtering capabilities to narrow down the data being analyzed and focus on specific subsets of the data.
  • Group and aggregate the data to explore patterns and trends in the data.
  • Use Tableau's sorting capabilities to rank and compare different aspects of the data.

Step 6. Apply statistical analysis techniques, such as regression or correlation analysis, to gain deeper insights into the data

  • Use Tableau's statistical analysis tools to uncover insights and relationships in the data.
  • Apply techniques such as regression analysis, correlation analysis, and time series analysis to gain deeper insights into the data.
  • Use statistical analysis to validate hypotheses and identify causal relationships in the data.

Step 7. Share the findings with other stakeholders using Tableau's interactive dashboards and presentations

  • Use Tableau's interactive dashboards to share the findings with other stakeholders.
  • Customize the dashboards to meet the needs of different stakeholders and provide relevant insights.
  • Use Tableau's presentation tools to create professional-looking presentations that summarize the findings.

Step 8. Monitor and track key HR metrics over time using Tableau's automated reporting features

  • Use Tableau's automated reporting features to track key HR metrics over time.
  • Monitor trends and patterns in the data and identify areas that need attention.
  • Use the insights gained from the analysis to make data-driven decisions.

Step 9. Continuously refine the analysis and visualizations as new data becomes available or the research question evolves

  • Continuously update the analysis as new data becomes available.
  • Refine the visualizations to make them more informative and actionable.
  • Update the research questions as needed to reflect new insights or changes in the organization.

Step 10. Use Tableau's integration with other HR and business tools to combine data from multiple sources for a more comprehensive view of the organization's performance

  • Use Tableau's integration with other HR and business tools to combine data from multiple sources.
  • Combine HR data with other business data to gain a more comprehensive view of the organization's performance.
  • Use Tableau's integration capabilities to automate data collection and analysis tasks.

Benefits of using Tableau for HR data

  • Improved decision-making: With Tableau's data visualization tools, HR professionals can quickly identify patterns and trends in their data, leading to more informed and data-driven decision-making.
  • Increased efficiency: Tableau's user-friendly interface and drag-and-drop functionality empower HR professionals to create custom reports and dashboards without relying on IT support, saving time and increasing efficiency.
  • Greater transparency: Tableau's interactive dashboards allow HR professionals to share their data with other stakeholders, promoting transparency and improving communication across the organization.
  • Time savings: Tableau's automated data connections and visualization features enable HR professionals to save time on manual data processing and analysis tasks, allowing them to focus on more strategic initiatives.
  • Customizability: Tableau's flexible platform allows HR professionals to create custom reports and dashboards tailored to their specific needs and goals, ensuring they get the insights they need.
  • Integration with other tools: Tableau integrates with a range of other HR and business tools, enabling HR professionals to combine data from multiple sources for a more comprehensive view of their organization's performance.

Case studies: Examples of HR data analysis with Tableau

Example 1: Deloitte

    • Challenge: Deloitte wanted to improve its employee engagement and retention rates by better understanding the factors that influenced employee satisfaction.
    • How Tableau helped: Tableau was used to analyze employee survey data and identify the factors that had the greatest impact on employee engagement and satisfaction. The interactive dashboards created in Tableau allowed HR professionals to quickly identify trends and patterns in the data and drill down into specific areas of concern.
    • HR metrics tracked: Employee engagement scores, retention rates, job satisfaction scores, training completion rates, and turnover rates.
    • Insights gained: Deloitte was able to identify several factors that had a significant impact on employee engagement and satisfaction, including opportunities for career growth and development, work-life balance, and manager support. Deloitte was able to use this information to develop targeted programs and initiatives to address these areas of concern and improve employee retention rates.

Example 2: Unilever

    • Challenge: Unilever wanted to reduce its recruitment costs by improving its hiring processes and identifying the most effective recruitment channels.
    • How Tableau helped: Tableau was used to analyze recruitment data and identify the most effective recruitment channels and sources for different types of roles. The interactive dashboards created in Tableau allowed HR professionals to quickly identify which channels were driving the highest-quality candidates and which channels were not providing a good return on investment.
    • HR metrics tracked: Time-to-hire, cost-per-hire, candidate quality scores, recruitment source effectiveness, and candidate demographics.
    • Insights gained: Unilever was able to identify several recruitment channels that were driving high-quality candidates at a low cost, such as employee referrals and social media. Unilever was able to shift its recruitment budget to these more effective channels and reduce its overall recruitment costs while maintaining a high level of candidate quality.

Example 3: Hilton Worldwide

    • Challenge: Hilton Worldwide wanted to improve its employee scheduling processes to reduce overtime costs and improve employee satisfaction.
    • How Tableau helped: Tableau was used to analyze employee scheduling data and identify patterns and trends in employee shift preferences and overtime usage. The interactive dashboards created in Tableau allowed HR professionals to quickly identify areas of concern and make data-driven decisions about employee scheduling.
    • HR metrics tracked: Overtime usage, shift preferences, employee satisfaction scores, and scheduling compliance rates.
    • Insights gained: Hilton Worldwide was able to identify several areas for improvement in its employee scheduling processes, such as better alignment of employee preferences with shift schedules and improved scheduling communication with employees. Hilton Worldwide was able to reduce its overtime costs by 20% and improve employee satisfaction scores by 10% as a result of these improvements.

Example 3: LinkedIn

The professional networking platform, LinkedIn, used Tableau to analyze their HR data and gain insights into their employee retention rates. They faced the challenge of high employee turnover and wanted to identify the root causes of turnover in order to implement effective retention strategies.

By using Tableau, LinkedIn was able to track key HR metrics such as employee tenure, job satisfaction, and manager effectiveness. They also conducted surveys to gather additional data on employee attitudes and engagement. Using Tableau's data visualization features, they were able to identify patterns and trends in their data that helped them to pinpoint the causes of turnover.

For example, they found that employees who had a positive relationship with their manager were more likely to stay with the company. They also found that employees who were given the opportunity to learn and grow within the company were more likely to stay. Armed with these insights, LinkedIn was able to implement targeted retention strategies that addressed the root causes of turnover and improve their employee retention rates.

Best practices for analyzing HR data with Tableau

  • Define clear goals and objectives for HR data analysis.
  • Ensure data accuracy, consistency, and completeness before analyzing.
  • Use proper data visualization techniques to communicate insights effectively.
  • Create interactive dashboards that allow users to explore the data and answer their own questions.
  • Avoid cluttered or confusing dashboards that make it difficult to interpret the data.
  • Use appropriate metrics and benchmarks to compare HR data over time or against industry standards.
  • Consider the audience and tailor the analysis to their needs and level of expertise.
  • Collaborate with other departments or stakeholders to gain additional insights or context.
  • Keep data security and privacy in mind and only share data with authorized personnel.
  • Regularly review and update the HR data analysis process to ensure it remains relevant and effective.

Advanced techniques for HR Data analysis with Tableau

In addition to the basic data visualization features, HR data analysis can be a complex task, as HR data tends to be voluminous and diverse. However, with the help of advanced data visualization tools like Tableau, HR professionals can gain valuable insights from their data. Here are some advanced techniques for HR data analysis with Tableau in detail:

  1. Understand the business context and define the problem statement to be solved: Before starting the data analysis, it's essential to understand the business context and define the problem statement to be solved. For instance, if the problem statement is to reduce employee turnover, HR professionals need to analyze data related to employee satisfaction, compensation, benefits, and performance.
  2. Clean and prepare the data: Once the problem statement is defined, HR professionals need to clean and prepare the data. This process involves removing duplicates, handling missing values, and transforming variables if necessary. Data cleaning ensures that the analysis is based on accurate and reliable data.
  3. Select appropriate visualization techniques: Tableau provides various visualization techniques, including bar charts, scatter plots, heat maps, and box plots. HR professionals need to select the appropriate visualization technique based on the nature of the data and the insights to be gained. For example, a scatter plot can be used to visualize the relationship between employee satisfaction and performance.
  4. Utilize Tableau's advanced features: Tableau provides advanced features like sets, groups, and hierarchies that can be used to create complex analyses and visualizations. For example, sets can be used to group employees based on their performance, and hierarchies can be used to drill down into the data.
  5. Incorporate calculations and statistical analysis: Tableau provides a range of calculations and statistical analysis features, including regression analysis, forecasting, and clustering. HR professionals can use these features to uncover trends, patterns, and relationships in their data.
  6. Use Tableau's data blending capabilities: HR data can be stored in multiple sources, including spreadsheets, databases, and HR systems. Tableau's data blending capabilities can be used to combine and analyze data from multiple sources, providing a holistic view of HR data.
  7. Explore and analyze data using interactive dashboards: Tableau's interactive dashboards allow HR professionals to explore and analyze data using filters, drill-downs, and other interactive features. For example, a filter can be used to analyze employee turnover by department, and a drill-down can be used to analyze employee turnover by location.
  8. Utilize Tableau's geospatial analysis capabilities: Tableau's geospatial analysis capabilities can be used to analyze and visualize HR data based on location. For example, HR professionals can use a map to visualize the distribution of employees across different regions.
  9. Collaborate with stakeholders: Tableau allows HR professionals to share dashboards, reports, and insights with stakeholders, facilitating data-driven decision-making. For example, HR professionals can share a dashboard showing the correlation between employee satisfaction and turnover with senior management.
This is a powerful tool for HR data analysis, providing a wide range of data visualization and analytics features that can help HR professionals to make better decisions and drive business outcomes. By using Tableau to analyze their data, HR professionals can gain insights into critical metrics such as employee turnover, recruitment metrics, and employee engagement.

However, it's important to approach HR data analysis with care and attention to ethical considerations, particularly when using advanced analytics techniques such as predictive analytics and machine learning. HR professionals should always keep the best interests of their employees in mind and work to ensure that their data analysis efforts are ethical, transparent, and compliant with relevant regulations and laws.

FAQs: Frequently asked questions

Can Tableau analyze sensitive HR data while maintaining data security?

Yes, Tableau provides robust security features, including user authentication, data encryption, and role-based access control, to ensure that sensitive HR data is protected while being analyzed.

Can Tableau integrate with existing HR systems and databases?

Yes, Tableau has extensive integration capabilities, allowing it to connect with various HR systems and databases, such as HRIS, ATS, and performance management systems, to analyze data from multiple sources.

Can Tableau help in identifying employee retention strategies?

Absolutely, Tableau can analyze HR data related to employee satisfaction, compensation, performance, and more to identify factors influencing employee retention and inform the development of effective retention strategies.

Can Tableau provide insights into workforce diversity and inclusion?

Yes, Tableau can analyze HR data to provide insights into workforce diversity and inclusion metrics, such as gender and ethnic representation, pay equity, and promotion rates, helping organizations foster a more inclusive work environment.

Can Tableau help in workforce planning and forecasting?

Yes, Tableau's advanced analytics capabilities, such as predictive modeling and forecasting, can be leveraged to analyze historical HR data and project future workforce trends, enabling organizations to plan for talent needs and succession planning.

Can Tableau assist in tracking and analyzing employee performance metrics?

Absolutely, Tableau can analyze performance metrics, such as goal attainment, performance ratings, and training completion, to track individual and team performance, identify areas for improvement, and support performance management processes.


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