Scott W. Hatten
July 6, 2014
In order to ensure accurate reporting on task-oriented risk, the organization must understand the real significance of the statistics they report.
The purpose of the study was to design and validate a dashboard tool that can validate the number of potential risks that occur within the organization. The Risk Dashboard Initiative (RDI) will review the number of employees, the hours worked, the average injury rate, the safety climate and other variables that will help determine the individual, department and organizational risk. The typical manufacturing employee tends to be a very skilled and safety aware (Silvestri, De Felice & Petrillo, 2012). Specifically, this study addressed the following research questions:
1. Can a single department or supervisor utilize a tool to measure current productivity and efficiencies and relate those mechanisms to predict the success and or failure of employees who are at a higher rick than other employees within the organization?
2. Does the motivation, employee retention, interaction with other employees, skill based education, supervisor, hours worked, specific job function allow for the prediction of risk? An assessment mechanism such RDI are typically used everyday within manufacturing organizations to help predict the potential for manufacturing loss, efficiency developers, and potential risk areas. The RDI was built from a previous tool that was created out the Risk Management Department called the Risk Management System (RMS). This tool was an overall organizational risk strategy tool and was centered around the functions of claims and payouts when employees were injured on the job. If a profile could be developed to determine the optimal employee productivity with minimal risk, then this data could be utilized with other organizational tools to measure optimum manufacturing workload.
References: Green, S. B., & Salkind, N. J. (2014). Using SPSS for Windows and Macintosh: Analyzing and understanding data (7th ed.). Upper Saddle River, NJ: Pearson Corner, P.D. (2002). An integrative model for teaching quantitative research design. Journal of Management Education, 26(6), 671. Silvestri, A., De Felice, F., & Petrillo, A. (2012). Multi-criteria risk analysis to improve safety in manufacturing systems. International Journal Of Production Research, 50(17), 4806-4821. doi:10.1080/00207543.2012.657968