The Struggle to Find Skilled Employees in Nigeria
Finding the right employees has long been a challenge for organisations in Nigeria. According to a report by the National Bureau of Statistics, the unemployment rate in Nigeria stood at a staggering 33.3% in the fourth quarter of 2020. However, even with a large pool of potential candidates, employers often struggle to find individuals with the necessary skills and qualifications for specific roles, hampering their ability to remain competitive in the market.
The Power of Data and Analytics in Recruitment
In the face of this challenge, data and analytics offer a promising solution by bringing objectivity and efficiency to the recruitment process. By leveraging data-driven insights, employers in Nigeria can make evidence-based decisions, leading to better candidate matches, reduced staff turnover, and ultimately, improved organisational performance.
Understanding the Recruitment Journey with Data and Analytics.
The recruitment process involves several critical steps, from identifying the need for a new employee to selecting the best candidate from a pool of applicants. Let’s explore how data and analytics can revolutionise each stage:
Job Description: Analytics can help organisations understand the precise skills and qualifications required for a role by analysing data from successful employees in similar positions. This data-driven approach ensures that job descriptions accurately reflect the desired competencies, increasing the chances of attracting the right candidates.
Sourcing Candidates: Data-driven platforms like LinkedIn can help identify potential candidates based on their skills, experience, and location within Nigeria. By leveraging these platforms, employers can access a broader talent pool and target candidates with the specific qualifications they seek.
Screening Applications: Applicant tracking systems (ATS) and pre-screening assessments can automatically filter candidates based on predetermined criteria, saving time and ensuring consistency in the evaluation process. These tools can analyse resumes, cover letters, and other application materials, flagging the most promising candidates for further consideration.
Interviews: Interview analytics can analyse factors like tone, word choice, and body language to identify top candidates objectively. By leveraging these insights, employers can minimise the impact of unconscious biases and focus on the candidate’s relevant skills and qualabilities.
Hiring Decision: Performance metrics from past hires can help predict the likelihood of success for new candidates, leading to better hiring decisions. By analysing data on employee retention, productivity, and performance, organisations can identify the characteristics and qualities that contribute to successful hires.
Success Stories from Nigeria
While still in its early stages, some Nigerian companies like Andela, Jobberman and Beshortlisted have started to embrace data-driven recruitment strategies. For example, Andela uses coding challenges and data analytics to identify top software engineering talent across Africa, enabling them to connect these skilled individuals with global opportunities.
Addressing Ethical Considerations
As data and analytics become more prevalent in recruitment, it’s crucial to address ethical considerations like bias in algorithms and candidate privacy. Companies in Nigeria must ensure fairness and transparency throughout the recruitment process by regularly auditing their algorithms for potential biases and implementing robust data privacy measures to protect candidate information.
The Future of Recruitment in Nigeria
The future of recruitment in Nigeria is poised to embrace advanced technologies like artificial intelligence and big data analytics. These innovations will enable employers to make more accurate predictions and enhance candidate matching algorithms, ultimately addressing the challenge of finding skilled employees more effectively.
AI-powered chatbots and virtual assistants can streamline the recruitment process by answering candidate queries, scheduling interviews, and providing personalised guidance throughout the application journey. Additionally, machine learning algorithms can analyse vast amounts of data to identify patterns and predict the likelihood of a candidate’s success based on their qualifications, experience, and other relevant factors.
Conclusion:
In summary, data and analytics have the potential to revolutionise the recruitment process in Nigeria, enabling organisations to make smarter hiring decisions and gain a competitive edge in the talent market. By embracing data-driven strategies and staying up-to-date with emerging trends, companies in Nigeria can build high-performing teams that drive business success and contribute to the nation’s economic growth.
