Abstract
Talent identification is important to both public and private sector organizations, it helps to create the workforce of an organization. The study examined the influence of networking on talent identification in both public and private sectors. The research design selected was descriptive. The research tool is a structured questionnaire shared among two private and public schools within two selected education districts in Lagos. Stratified sampling was used to pick out the districts and the respective schools. The analysis was carried out using Excel 2019. This was placed on a Likert scale to determine the influence of networking based on the logic that a mean score of 3 on the Likert scale represents neutral influence, a mean score of less than 3 represents negative influence and greater than 3 represents a positive influence. The range for interpreting the Likert scale mean score is 1.0 -2.4 (Negative influence), 2.5 – 3.4 (Neutral influence), and 3.5 – 5.0 (Positive influence). It was found that the networking process (political, ethnic, and religious influence) always have a positive effect on talent identification in the public sector. This mostly refers to those who are incompetent. On the other hand, the networking process had minimal influence on talent identification in the private sector. However, the private sector employs reliable recruitment agents based on competency and professionalism. Hence the study recommends that the networking process in the public sector should be reduced and recruitment agents should work with the human resources department to ensure that talents recruited are gotten from a reliable process. Talent identification is important to both public and private sector organizations, it helps to create the workforce of an organization. The study examined the influence of networking on talent identification in both public and private sectors. The research design selected was descriptive. The research tool is a structured questionnaire shared among two private and public schools within two selected education districts in Lagos. Stratified sampling was used to pick out the districts and the respective schools. The analysis was carried out using Excel 2019. This was placed on a Likert scale to determine the influence of networking based on the logic that a mean score of 3 on the Likert scale represents neutral influence, a mean score of less than 3 represents negative influence and greater than 3 represents a positive influence. The range for interpreting the Likert scale mean score is 1.0 -2.4 (Negative influence), 2.5 – 3.4 (Neutral influence), and 3.5.