Proposal For Data Collection In Training Program Evaluation

Proposal for Data Collection in Training Program Evaluation at Insurance Company

The insurance company has tasked me with designing a comprehensive data collection plan to evaluate its new-hire training program for insurance agents. The primary goal is to identify ways to enhance retention rates, as a significant proportion of agents leave prematurely, incurring additional costs and impacting organizational effectiveness. This proposal outlines the specific data to be collected, the tools to be used, and the methodological considerations necessary for a rigorous evaluation aligned with best practices in training assessment research.

Data to be Collected and Rationale

The evaluation will focus on capturing both perceptions and attitudes of the newly hired agents regarding the training process and their onboarding experience. This includes collecting data on their satisfaction, perceived effectiveness of the training, confidence in applying learned skills, and perceived organizational support. The core reasons for collecting this data are to understand the factors influencing retention and to identify areas for potential improvement in the training and onboarding process, thereby reducing early attrition and long-term turnover.

Specifically, the data collected will include agents' perceptions of the clarity of training content, the relevance of training to actual job duties, the adequacy of support during orientation, their confidence in handling insurance policies post-training, and their overall satisfaction with the training process.

This data is crucial as it provides insight into the training program's immediate impact and perceived value, which are strong predictors of retention (Salas et al., 2015). Understanding these perceptions can inform modifications in training design, delivery, and support mechanisms, ultimately leading to higher retention rates and reduced costs associated with turnover.

Data Collection Tool: Likert Scale Survey Statements

The survey instrument will consist of five statements designed to gauge agents’ attitudes towards various aspects of the training program. Each statement will be rated on a 5-point Likert scale with options: "Strongly Agree," "Agree," "Neutral," "Disagree," and "Strongly Disagree."

Sample Survey Statements:

1. The training content was relevant and applicable to my daily responsibilities.
2. I feel confident in my ability to effectively perform my duties after completing the training.
3. The training provided sufficient support and resources during the onboarding period.
4. The training program increased my overall understanding of the insurance policies offered.
5. I am satisfied with the training process and feel prepared to serve clients effectively.

This Likert scale facilitates quantitative analysis of subjective perceptions, enabling the measurement of attitudes that influence retention. The five-point scale captures nuances in opinions, providing a reliable basis for statistical analysis (Ajzen, 2012).

Classification of Data and Its Justification

The data collected through the Likert scale survey are quantitative because they generate numerical values representing levels of agreement, which can be statistically analyzed. Each response option can be assigned a numerical score (e.g., 1 for "Strongly Disagree" up to 5 for "Strongly Agree"). Quantitative data allow for descriptive statistics such as mean scores, frequency distributions, and correlations with retention data, facilitating objective evaluation of trends and relationships.

The need for quantitative data stems from the goal of identifying measurable factors influencing agent retention. These data enable comparison across different cohorts, tracking changes over time, and assessing the impact of modifications to the training process with statistical rigor (Creswell & Creswell, 2018).

Sample and Data Collection Method

The target sample will include all newly hired insurance agents who have recently completed the training program within the last 6 months. A stratified random sampling method will be employed to ensure representation across different training cohorts and geographical regions, reducing sampling bias and increasing the generalizability of findings.

The data will be collected via online surveys distributed through secure email links, ensuring ease of access and prompt responses. This method optimizes response rates, enhances data security, and supports large-scale data collection in a cost-effective manner (Dillman, Smyth, & Christian, 2014). Reminder emails will be sent to increase participation, and incentives such as entry into a raffle may be used to motivate completion.

Technology Options for Data Collection

Online survey platforms like Qualtrics or SurveyMonkey will be utilized due to their user-friendly interfaces, data security features, customizable question formats, and analytical tools. These platforms facilitate efficient data collection and management, allowing real-time monitoring of response rates and initial analysis.

Additionally, these technologies support anonymity, which encourages honest responses—an important factor when assessing perceptions that may be sensitive or critical. The choice of online surveys aligns with best practices for organizational research, enhancing data quality and respondent convenience (Tourangeau, 2014).

Overall, leveraging digital survey tools ensures a robust, scalable, and efficient data collection process aligned with current data collection standards in research and evaluation.

Conclusion

This data collection plan provides a structured approach to evaluating the effectiveness of the insurance company's training program. By employing a Likert scale survey to gather quantitative perceptions from a well-defined sample, and utilizing secure online platforms, the plan aims to generate reliable data to inform improvements. Ultimately, the insights obtained will help address key issues related to agent retention, supporting the company's strategic objectives to reduce turnover costs and enhance training quality.

References

• Ajzen, I. (2012). The theory of planned behavior. In P. van Lange, A. Kruglanski, & E. T. Higgins (Eds.), Handbook of Theories of Social Psychology (pp. 438-459). Sage Publications.
• Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.
• Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, Phone, Mail, and Mixed-Mode Surveys: The Tailored Design Method (4th ed.). Wiley.
• Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2015). The Science of Training and Development in Organizations: What Matters in Practice. Psychological Science in the Public Interest, 16(2), 74-101.
• Tourangeau, R. (2014). Designing Effective Surveys. University of Michigan Press.
• UK Data Service. (2020). Qualitative and Quantitative Data. https://ukdataservice.ac.uk/
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• Fink, A. (2017). How to Conduct Surveys: A Step-by-Step Guide. SAGE Publications.