What tools and technologies do you use for talent analytics?

1 Data sources

The first step in talent analytics is to collect and integrate data from various sources, such as your applicant tracking system (ATS), your human resource information system (HRIS), your employee engagement surveys, your performance reviews, your social media platforms, and your external market data. You need to ensure that your data is accurate, consistent, and compliant with data privacy and security regulations. You also need to define the metrics and indicators that are relevant and meaningful for your talent objectives, such as time to hire, quality of hire, turnover rate, diversity score, or employee satisfaction.

2 Data analysis

The next step in talent analytics is to analyze and interpret your data using various methods and techniques, such as descriptive, predictive, or prescriptive analytics. Descriptive analytics helps you understand what has happened in the past and what is happening now in your talent landscape. Predictive analytics helps you forecast what will happen in the future and what factors will influence your talent outcomes. Prescriptive analytics helps you recommend what actions to take and what scenarios to consider to achieve your talent goals. You can use tools such as spreadsheets, dashboards, reports, or visualizations to display and communicate your data analysis results.

3 Data integration

The third step in talent analytics is to integrate your data analysis results with your talent acquisition processes and decisions. You need to use your data insights to inform and improve your sourcing, screening, interviewing, hiring, onboarding, and retention strategies. You also need to use your data insights to evaluate and adjust your talent acquisition policies and practices, such as your employer branding, your candidate experience, your diversity and inclusion initiatives, or your compensation and benefits packages. You can use tools such as feedback loops, action plans, or automation to implement and monitor your data integration actions.

4 Data innovation

The final step in talent analytics is to innovate and experiment with your data and insights to create new value and opportunities for your talent pool. You need to use your data insights to identify and explore new trends, challenges, or solutions in your talent market. You also need to use your data insights to create and test new hypotheses, models, or frameworks for your talent acquisition objectives. You can use tools such as artificial intelligence, machine learning, or natural language processing to enhance and automate your data innovation activities.

Talent analytics is a powerful and essential tool for global talent acquisition. It can help you attract, hire, and retain the best talent for your organization, as well as align your talent strategy with your business strategy. By using the right tools and technologies for talent analytics, you can gain a competitive edge and a sustainable advantage in the global talent market.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?