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HR Analytics: How to Collect,
Analyze, and Act on HR Data

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Hacking HR Team

Posted on January 08, 2024

HR analytics, also known as people analytics, workforce analytics, or talent analytics, is the process of collecting, analyzing, and reporting data related to human resources. It enables organizations to measure the impact of HR policies and practices on business performance and outcomes and to make data-driven decisions to improve them.

HR analytics is not a new concept. However, it has gained more attention and importance in recent years as the availability and quality of HR data have increased, and the demand for evidence-based HR management has grown. HR analytics can help HR professionals answer critical questions, such as

  • How can we attract, retain, and develop the best talent for our organization?

  • How can we enhance employee engagement, well-being, and productivity?

  • How can we optimize our HR processes, such as recruitment, performance management, learning and development, and compensation?

  • How can we align our HR strategy with our business strategy and goals?

  • How can we demonstrate the value and impact of HR to our stakeholders?

How HR Analytics Can Boost Your HR Efficiency, Effectiveness, and Innovation

HR analytics can provide many benefits for HR professionals and organizations, including

  • Improving HR efficiency and effectiveness: HR analytics can help professionals streamline and automate their HR processes, reduce costs and errors, and improve quality and consistency. For example, it can help automate and optimize recruitment processes, such as sourcing, screening, and hiring candidates, by using data and algorithms to identify the best fit and potential for each role. It can also help monitor and evaluate the effectiveness of HR interventions, such as training programs, performance appraisals, and reward schemes, by measuring their impact on employee and business outcomes, such as retention, satisfaction, productivity, and profitability.

  • Enhancing HR decision-making and problem-solving: HR analytics can help make more informed and objective decisions based on data and evidence rather than intuition and gut feeling. Also, it can help solve HR problems by using data to diagnose the root causes, test hypotheses, and evaluate solutions. For example, identifying the drivers and predictors of employee turnover and designing and testing strategies to reduce it, such as improving employee engagement, offering flexible work arrangements, or providing career development opportunities.

  • Increasing HR innovation and value creation: HR analytics can help create value for organizations by using data to discover new insights, opportunities, and trends and applying them to design and implement new or improved HR policies and practices. It can also help demonstrate and communicate the value and impact of HR to their stakeholders, such as senior management, employees, customers, and investors, by using data to measure and report on the return on investment (ROI) and the strategic contribution of HR to the organization's goals and performance.

How to Overcome the Common Challenges of HR Analytics

HR analytics can also pose some challenges for HR professionals and organizations, such as

  • Data quality and availability: HR analytics relies on accurate, consistent, and timely data.  Yet, obtaining and maintaining data can be difficult, especially in large and complex organizations with multiple data sources and systems and different data standards and formats. HR professionals must ensure that their data is reliable and valid and have access to relevant and sufficient data for their analysis. They must also ensure their data is secure and compliant with legal and ethical regulations and standards, such as data protection, privacy, and consent.

  • Data analysis and interpretation: HR analytics requires having the appropriate skills, tools, and methods to analyze and interpret data. However, Human Resources professionals may not have a strong background or experience in data science, statistics, or analytics. Therefore, they may need to develop or acquire the necessary competencies and capabilities to perform and understand HR analytics, such as data literacy, analytical thinking, and critical thinking. They must also use suitable tools and techniques to conduct and communicate their analysis, such as software, dashboards, and visualizations.

  • Data action and implementation: HR analytics requires having the ability and willingness to act on and implement the findings and recommendations from the data analysis. Yet, HR professionals may face resistance or barriers from their stakeholders, such as managers, employees, or customers. Therefore, they need to ensure that their analysis is relevant and actionable and have the support and buy-in from their stakeholders to execute and sustain their solutions. They also need to monitor and evaluate the results and impact of their actions and make the required adjustments and improvements.

HR Analytics Application to Different HR Domains and Functions

The applications of HR analytics are feasible in various HR domains and functions, such as recruitment, retention, performance, engagement, learning, diversity, and well-being. Here are some examples of how you can leverage HR analytics in different areas:

  • Recruitment: HR analytics can help improve the recruitment process and outcomes by using data to source, screen, and select the best candidates for each role. It also allows us to measure the quality and effectiveness of the hiring process. For example, HR analytics can help identify the best sources and channels to attract qualified and diverse candidates, such as job boards, social media, or referrals. HR analytics can also help assess the fit and potential of candidates by using data and algorithms to score and rank candidates based on their skills, experience, and personality. Moreover, HR analytics can also help evaluate the hiring process: by using data, you can measure each stage's time, cost, efficiency, and the satisfaction and retention of new hires.

  • Retention: HR analytics can help improve the retention rate and reduce the turnover rate of employees. Using data will help us understand and predict the reasons and risks of employee attrition and design and implement strategies to retain and engage talent. For example, HR analytics can help identify the drivers and predictors of employee turnover, such as job satisfaction, compensation, career development, or work-life balance. It can also help segment and profile employees based on turnover risk and intention and target them with personalized and timely interventions, such as feedback, recognition, or incentives. HR analytics can also help measure the impact and ROI of retention strategies by using data to compare the costs and benefits of retaining versus replacing employees.

  • Performance: HR analytics can help improve the performance and productivity of employees and teams. Using data, we can set and monitor performance goals and expectations and provide feedback and coaching to employees. For example, HR analytics can help define and measure performance indicators and outcomes, such as sales, revenue, customer satisfaction, or quality. It can also help us track and analyze performance data and trends, such as performance ratings, feedback, or achievements. HR analytics can also help provide feedback and coaching to employees by using data to identify their strengths.

Preparing for the Future Trends and Developments of HR Analytics

HR analytics is not a static or fixed process. It is a dynamic and evolving process that adapts to the changing needs and preferences of HR professionals, organizations, and the external environment. It is also influenced by technological, data, and analytics advances, which create new possibilities and opportunities. Here are some of the trends and developments that will shape the future of HR analytics:

  • Artificial intelligence and machine learning: Artificial intelligence (AI) and machine learning (ML) enable machines to perform tasks that typically require human intelligence, such as learning, reasoning, and decision-making. AI and ML can enhance and transform HR analytics by enabling HR professionals to automate and optimize their HR processes, discover and generate new and deeper insights, and predict and prescribe future actions and outcomes. For example, AI and ML can help HR professionals automate and optimize their recruitment processes by using natural language processing (NLP) to analyze and match resumes and job descriptions. With Computer vision, HR can also assess and score video interviews. AI and ML can also help HR professionals discover and generate new and deeper insights by using data mining and text mining to uncover hidden patterns and trends or using sentiment analysis and emotion recognition to measure and understand employee emotions and attitudes. With the help of AI and ML, HR professionals can predict and prescribe future actions and outcomes by using regression and classification to forecast employee turnover and performance or by using recommendation and optimization systems to suggest and implement the best solutions and actions.

  • Big data and analytics: Big data and analytics are technologies that enable the collection, storage, processing, and analysis of large and complex data sets that are characterized by their volume, variety, velocity, integrity, and value. Big data and analytics can expand and enrich HR analytics by enabling HR professionals to access and leverage more diverse data sources and types, analyze and integrate data at scale and speed, and extract and deliver more valuable information and knowledge. For example, Big data and analytics can help HR professionals access and leverage more diverse data sources and types, such as social media, mobile devices, sensors, or biometrics, which can provide more and richer data about employees and their behaviors, preferences, and needs. Big data and analytics can also help HR professionals analyze and integrate data at scale and speed by using cloud computing, distributed computing, or parallel computing, which can handle and process large and complex data sets faster and more efficiently. Both technologies can help HR professionals extract and deliver more valuable information and knowledge by using data visualization, data storytelling, or data journalism, which can present and communicate data more engaging and compellingly.

  • Ethics and privacy: Ethics and privacy are issues that concern the moral and legal principles and standards that govern the collection, use, and sharing of data. Both are particularly crucial for personal and sensitive data, such as data related to HR and employees. Ethics and privacy can challenge and constrain HR analytics by imposing more regulations and restrictions on HR professionals and organizations and by raising more expectations and demands from employees and customers. Such is the case of the General Data Protection Regulation (GDPR), which is a law that protects the data rights and privacy of individuals in the European Union and requires organizations to obtain consent, provide transparency, and ensure security and accountability for the data that they collect, use, and share. Ethics and privacy can also raise more expectations and demands from employees and customers, such as the right to access, correct, delete, or transfer their data, the right to know how their data is used and for what purpose, or the right to opt-out or object to certain data practices or decisions.

How to Start or Advance Your HR Analytics Journey in Five Steps

HR analytics is not a solo or isolated activity. It is a collaborative and integrated activity that involves multiple stakeholders. HR professionals, managers, employees, and customers. Here are some steps and tips to help you get started or advance your HR analytics journey:

  1. Assess your current state and readiness: Before embarking on your HR analytics journey, you must assess your current state and readiness. As a first step, identify your strengths and weaknesses, opportunities and threats, and gaps and needs. You need to evaluate your HR data, such as the quality, availability, and accessibility of your data and the data sources and systems you have or require. You also need to evaluate your HR skills, such as the knowledge, competencies, and capabilities that you have or require for HR analytics and the training and development that you have or need. You also need to evaluate your HR culture, such as the awareness, understanding, and attitude that you have or need for HR analytics and the support and buy-in that you have or need from your stakeholders.

  1. Define your HR objectives and questions: After assessing your current state and readiness, you need to define your HR objectives and questions and prioritize and scope them. You must align your HR objectives and questions with your business strategy and goals and ensure they are relevant and meaningful for your stakeholders. You also need to focus on the HR objectives and questions that have the most potential value and impact for your organization and are feasible and achievable with your data and resources. You also need to make your HR objectives and questions clear and specific and use the SMART criteria: making them Specific, Measurable, Achievable, Relevant, and Time-bound.

  2. Collect and manage your HR data: After defining your HR objectives and questions, you need to collect and manage your HR data and ensure they are reliable and valid. Identify and access the data sources and systems that contain the data you need and ensure they are secure and compliant. Clean and organize your data, and ensure they are accurate, complete, consistent, and timely. You must protect and respect your data and ensure that they are ethical and legal and that you have the consent and permission from your data owners and subjects.

  1. Analyze and interpret your HR data: After collecting and managing HR data, you must analyze and interpret it, ensuring it is accurate and meaningful. You will select and apply suitable techniques and models, such as descriptive, inferential, and predictive analytics, to explore, describe, explain, and predict your data. You can use relevant tools and software to perform and automate your analysis, such as Excel, R, Python, or Power BI. Interpret and validate your findings and conclusions, ensuring that they are reliable and valid and that they answer your question or solve your problem.

  1. Communicate and act on your HR data: After analyzing and interpreting it, you must communicate and act on your findings and recommendations and ensure they are relevant and actionable. Use practical ways and channels, such as reports, dashboards, or stories, to present and share your results and insights with your stakeholders. Use persuasive and engaging language and visuals, such as charts, graphs, or images, to convey your message and influence your audience. To implement and execute your solutions and actions, ensure they are aligned and supported by your stakeholders. Lastly, measure and evaluate the outcomes and impact of your solutions and actions and make necessary adjustments and improvements.

Final Thoughts

HR analytics is a powerful and valuable process that can help HR professionals and organizations improve their efficiency and effectiveness, enhance their HR decision-making and problem-solving, and increase their HR innovation and value creation. HR analytics can also help HR professionals and organizations address the current and future challenges and opportunities in HR and business, such as remote and hybrid work, employee experience, diversity and inclusion, and digital transformation. However, HR analytics takes work. It requires having the right and enough data, skills, and culture and following the best practices and principles of HR analytics.

We have an excellent resource if you want to learn more about HR analytics and how to get started or advance your HR analytics journey. We have created a free ebook, A Guide to People Analytics: HR Metrics that Matter, where you can find more tips, tools, and templates to help you master HR analytics and achieve better outcomes for your employees and your organization. This ebook is a must-have for anyone who wants to optimize their HR analytics process and create more value and impact with HR data. Click on the button below and fill out a short form to get your free copy and start your HR analytics journey today!

Download A Guide to People Analytics: HR Metrics that Matter

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