How can you measure the impact of employee selection on organizational outcomes?

1 Criteria and indicators

Defining criteria and indicators to measure the impact of employee selection is a key first step. Depending on the type, level, and goals of the job and organization, these criteria and indicators can vary, but some common examples include quality and quantity of work output, turnover and retention rates, employee engagement and satisfaction, customer satisfaction and loyalty, innovation and creativity, teamwork and collaboration, and diversity and inclusion. It is important to ensure that these criteria are aligned with the strategic objectives of the organization and are measurable, relevant, and valid.

2 Methods and tools

The next step is to choose the methods and tools that can help you collect and analyze the data related to the criteria and indicators. Surveys and questionnaires can provide feedback from employees, customers, and other stakeholders about their perceptions, attitudes, and experiences. Tests and assessments measure skills, abilities, knowledge, and personality traits in comparison to job requirements. Performance appraisals evaluate results and behaviors of employees and candidates. Interviews and focus groups explore opinions, feelings, and stories of stakeholders. Lastly, observations and audits monitor activities, processes, and outcomes to identify any issues or opportunities for improvement. When selecting methods and tools, consider availability, reliability, validity of data as well as feasibility, cost, and time of implementation.

3 Analysis and interpretation

The final step is to analyze and interpret the data collected from the methods and tools, and to draw conclusions and recommendations based on the findings. Descriptive statistics can be used to summarize and present the basic features of the data, such as the mean, median, mode, frequency, distribution, and variation. Inferential statistics can be used to test hypotheses and make inferences about the relationships, differences, and effects of the variables in the data. Qualitative analysis can be used to identify themes, patterns, and meanings from textual or visual data. The type, level, purpose of the data, research questions, and objectives should all be considered when choosing which way of analysis and interpretation to use.

4 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?