Using Predictive Analytics to Enhance Global Talent Acquisition

Companies face increased competition for in-demand skills and talent and must address the challenges of meeting changing business needs. One solution is to develop data-driven recruitment strategies supported by predictive hiring tools.

Predictive analytics is becoming integral to the global talent acquisition process. It enables companies to streamline hiring processes, predict candidate success, and effectively match skills to job needs in international markets. Using data analytics and AI tools, like Alberni, improves the hiring process and boosts the quality of international hires.

Let’s learn more about using predictive analytics to develop data-driven recruitment strategies and improve talent acquisition.

Understanding Predictive Analytics

Predictive analytics uses historical data to make predictions about future outcomes. It employs statistical modeling, data mining, machine learning, and artificial intelligence (AI) to identify patterns in the data and uncover potential risks and opportunities. 

Predictive analytics differs from traditional analytics in several ways:

Predictive analytics has real-world applications across many industries. For example, it enables:

• E-commerce platforms to make recommendations on products and content based on customers’ past behaviors and preferences - Amazon uses predictive analytics in demand forecasting and supply chain management

• Financial institutions to evaluate mortgage applicants’ creditworthiness by analyzing their credit history, financial behavior, and employment status - HSBC uses its AI tool to detect suspicious activities and prevent fraud

• Healthcare providers to identify and treat high-risk patients by analyzing their medical history - Geisinger’s risk model uses more than 800 factors to identify patients with chronic diseases who are at high risk of being admitted to the emergency department

• Manufacturers to predict equipment failures and reduce maintenance costs by monitoring the operational health of their machinery - the Metso Metrics for Mining solution collects and analyzes data from equipment sensors to identify failure patterns and predict potential problems

Many organizations use predictive analytics to support data-driven recruitment strategies. For example:

• Xerox analyzed and compared the characteristics of long-term employees against employees who left, reducing call centre turnover by 20%.

• Unilever employed AI-powered online games in its graduate recruitment process, reducing hiring time from four months to four weeks.

• Deloitte analyzed high-performing talent to create individual career development plans, improve employee retention, and develop succession plans.

• Vodafone predicted candidates’ performance and cultural fit, improving hiring decisions and reducing turnover rates.

• L'Oréal evaluated resumes to find the best-suited candidates, improving the quality of new hires and reducing time-to-hire.

Note: Access to current information and real-time data is the key to effectively implementing predictive analytics. HR professionals can access domain-specific knowledge about global employment law through Borderless AI’s proprietary AI agent, Alberni.

The Role of Predictive Analytics in Talent Acquisition

Predictive analytics supports global talent acquisition in many ways. Using data analytics in global hiring enables organizations to:

• Match skills to job needs

• Streamline the talent acquisition process

• Identify more potential hires

• Reveal deeper insights on potential hires

• Increase the diversity of the hiring pool

• Reduce turnover rates

• Develop existing talent

Match skills to job requirements

Being proactive is an effective talent acquisition strategy. Predictive analytics enables companies to determine what skills they require in different international markets and where talent gaps may arise. Most candidates are passive job seekers (i.e., they do not consistently seek new employment). Predictive hiring tools allow talent acquisition teams to source, engage with, and evaluate potential candidates before vacancies arise. They can also uncover new areas of growth or fill organizational needs.

Streamline the talent acquisition process

Predictive analytics improves the efficiency of the global talent acquisition process. Data analytics and predictive hiring tools identify and remove inefficiencies in the recruitment process. Analyzing response and engagement metrics helps create more effective job postings. AI tools automate resume ranking and candidate screening, also making the process more objective. This streamlines the hiring funnel and reduces the time to hire.

Note: Alberni automates the process of quickly and compliantly creating global employment agreements. 

Identify global top talent

The best global talent is not always easy to find. They might not apply to advertised positions or have access to key postings. Predictive tools analyze data related to top performers to identify alternatives to effective recruiting. Recruiters can expand their search pool and target higher quality candidates. They can also customize recruitment strategies for different international markets.

Reveal deeper insights into candidates

Predictive tools support deeper analysis of candidates to find the best match for specific jobs. Analyze historical data on previous hires to evaluate their performance, and identify factors that related most closely to their success. Then, evaluate applicants’ assessment results and job performance to determine their fit with the role and probability of success. Uncovering these types of insights reveals better quality hires and a better fit for the role. 

Using AI in talent acquisition streamlines the process, as it can automatically screen candidates by parsing resumes (i.e., based on missing keywords, phrases, and other requirements) and scanning social media profiles.

Increase diversity of the hiring pool

Hiring international employees also increases organizational diversity. Predictive analytics identifies areas within your organization that lack diversity and helps create recruitment strategies to attract diverse candidates and build a more inclusive workforce. According to a Harvard Business Review study, predictive analytics can increase diversity by 35%, and reduce gender bias by 15%.

Reduce turnover rates

Hiring and training new employees is an expensive, time-consuming process. Predictive analytics enables HR professionals to analyze the fit and longevity of candidates from specific demographics and personality types. They can analyze work histories and other historical data to identify candidates who are most likely to remain with the company over the long term. Predictive analytics can also identify issues within the company that affect employee engagement and satisfaction, enabling management to make changes to the workplace to improve retention.

Develop existing talent

The power of predictive analytics does not end at global talent recruitment, it also enables HR professionals to support professional development. Predictive models can analyze current employees’ skills and provide opportunities for career development. You can use predictive analysis to customize training programs that support employee growth and contribute to organizational success.

Implementing Predictive Analytics in Talent Acquisition

Predictive analysis is an ongoing process and depends on the quality of your data. Follow these steps to incorporate predictive analytics into the international talent acquisition process.

1. Collect data: Begin by collecting key historical data from various sources (e.g., human resources database, resumes, job boards, social media). The breadth, relevance, diversity, and quality of the data directly impact the quality of the predictive analytics.

2. Pre-process data: Clean, format, combine, and organize the data to ensure its quality and usability within the predictive model. This step may include removing inconsistent and duplicate data, filling in missing data, normalizing data formats, and sampling data for accuracy.

3. Choose an analytical approach: Select the type of analysis, algorithms, and predictive model (e.g., decision tree, neural network) required to fit your recruitment goals (e.g., predicting candidate success, identifying gaps in skills). Your recruitment strategy will guide the predictive analytics process.

4. Train the predictive hiring model: Program the predictive model to analyze some data to identify trends and predict outcomes. Predictions will improve with time as the predictive model analyzes more data.

5. Make predictions: Use the trained predictive model to analyze new data and forecast future talent acquisition outcomes (e.g., identify the most likely successful candidates, and predict potential gaps in talent).

6. Apply insights: Use the results of predictive analysis to support data-driven recruitment strategies, as well as improve the efficiency of the hiring process. Examples include amending job descriptions, using alternative hiring sources, and changing incentive packages for employees.

Combining Responsible AI with Predictive Analytics

AI-powered recruitment tools are integral in improving the efficiency and efficacy of global talent acquisition. However, biases in the hiring process, faulty recruitment practices, diversity concerns, and other issues create different challenges. 

One solution is to combine predictive analytics with responsible AI. This involves purposefully designing ethical and equitable AI systems to ensure they are fair, transparent, and unbiased. The benefits of combining predictive analytics with responsible AI include:

• Reducing bias: Removes historical biases from data prior to identifying patterns and predicting outcomes, which reduces discrimination in the hiring process

   

• Improving candidate matching: Evaluates candidates’ skills and competencies, instead of education and previous job titles, to make fairer predictions on which candidates have a higher chance of success in specific roles

   

• Increasing efficiency: Automates talent screening to evaluate larger numbers of applications, reducing time-to-hire

   

• Supporting diversity and inclusion: Removes favoritism of demographics, and identifies gaps in hiring practices, to develop hiring strategies that attract a more diverse global talent pool

   

• Improving data: Creates cleaner, more unbiased, and fairly sourced data sets, providing better quality data and insights into hiring needs and trends

   

• Reducing turnover: Predicts employee turnover and creates strategies to improve retention (e.g., customizing training programs, providing career development opportunities) 

Global Talent Acquisition Metrics and KPIs

Predictive analytics enables HR teams to measure the success of the global talent acquisition process, as well as the effectiveness of specific recruitment strategies. The metrics and key performance indicators (KPIs) you choose when developing data-driven recruitment strategies will guide decision-making to improve them going forward. 

Use predictive hiring tools to track and measure the following global talent acquisition metrics and KPIs:

• Cost per hire: Calculate the total cost of recruitment per vacancy. This helps to determine the return on investment in your talent acquisition efforts and identify methods of improving global recruitment strategies.  

   

• Time-to-hire: This metric measures the efficiency of the global talent acquisition process (i.e., the longer it takes to hire someone, the more resources must be invested). Reducing time to hire creates a better candidate experience and reduces the likelihood that they will lose interest during the hiring process. 

   

• Offer acceptance rate: Calculate the percentage of accepted job offers. This rate ties directly to brand quality and competitiveness of your compensation. Gather feedback from candidates who turned down an offer to collect more data.

   

• Quality of hire: Evaluate how well new employees perform in their roles and how long they stay with your organization. Length of employment is often directly related to the quality of the employee. However, how you define quality can depend on both quantitative performance data and qualitative assessments.

   

• Retention rate: Measure the percentage of new hires who remain with the organization over a given period of time. This rate reflects the effectiveness of your talent acquisition process, as well as the quality of the work environment. A low retention rate may indicate issues related to hiring, onboarding, management, or company culture.

   

• Candidate experience: Evaluate the candidate’s recruitment experience to understand your company’s reputation as an employer. Measurement strategies include calculating Net Promoter Score (NPS), conducting post-interview surveys, and reviewing communication with candidates.

   

• Sourcing channel: Calculate the effectiveness of different sourcing channels based on the number and quality of applicants. Compare different sourcing channels and identify alternatives if necessary.

   

• Diversity: Track and measure the demographics of global talent, and calculate the percentage of diverse hires as compared to the whole. This will enable you to adjust candidate sourcing and make changes to the hiring process to address bias.

Conclusion

Predictive analytics enables organizations to develop data-driven recruitment strategies that improve the efficiency and quality of global talent acquisition. Companies can use predictive hiring tools to effectively match skills to job needs, streamline the hiring process, identify more potential hires, and gain deeper insights into candidate suitability. This increases the quality and diversity of the workforce, reduces turnover rates, and increases employee satisfaction.

Making global recruitment analytics part of the overall hiring process will make your organization more competitive in attracting and retaining top talent. Predictive hiring tools support a proactive approach to recruitment by forecasting future talent needs and identifying potential areas of growth. Recruitment professionals can use AI-powered tools to evaluate key metrics and KPIs and improve their talent acquisition processes.

It’s important to ask the right questions to find the right partner for your organization. Contact us today to see how we can help you navigate emerging AI trends and hire talent in over 170 countries worldwide. Alberni, our AI agent for global employment, will ensure you stay up-to-date with changing employment laws and regulations.