Statistical evaluation and analysis of safety intervention in the determination of an effective resource allocation strategy

Abstract

This paper provides an analytical background for the development of an effective safety intervention program with the aim of minimizing incident rates. Safety intervention data were collected from the environmental health and safety department of an American-owned oil company in the Niger-Delta region of Nigeria. A safety model was developed to determine the safety intervention factors and interactions which minimize incident rates, with the aim of predicting a better resource allocation strategy. Five main safety intervention factors (factor A: leadership and accountability; factor B: qualification selection and pre-job; factor C: employee engagement and planning; factor D: work in progress; factor E: evaluation, measurement and verification) were highlighted and investigated to show their effects on incident rate performance. Analysis of variance test showed that four safety factors (A, C, D, and E) were significant. Statistical techniques such as response surface design plots were used to determine the resource allocation method. The developed safety model recommended the allocation of 16.66% of the available resources to the significant safety intervention activities in order to achieve the desirable incident rate. In order to reap the benefits of this research, it will be important to concentrate more efforts and resources on significant factors which have positive impacts in minimizing incident rates.

Introduction

This paper provides an overview of a statistical technique to assess a safety intervention program from a business perspective. A safety model was developed in order to determine the safety intervention factors and interactions which yielded the desired incident rate reduction. The developed model could be used to better predict the allocation of resources which in turn minimizes the cost of incident prevention. The safety model was obtained using analysis of variance while response surface methodology was used to determine the resource allocation methodology. Overall, the model developed in this research work presents the foundation for the use of response surface methodology in the determination of an effective resource allocation method, which is necessary to in the reduction of incident rates. Findings from this work offer a new dimension into the practice of the quantification and statistical analysis of safety intervention activities.

Contemporary safety and health programs have over the years been based on theoretical and qualitative analysis. This has prevented industrial organizations and companies from adequately developing and implementing successful health and safety intervention programs aimed at decreasing or eliminating incidents. Numerous organizations have been known to keep records of past incidents for analysis, motivational and incentive programs, as well as employee training. Unfortunately, these record-keeping activities were based on qualitative measures which lack effective quantitative and statistical analysis. Past incident data could be instrumental in the establishment of safety intervention programs necessary for the effective allocation of resources.

In this paper, an attempt has been made to develop an effective safety and health program that incorporates qualitative and quantitative techniques to relate past incident rates, human resources allocation procedures and intervention activities to assess the effectiveness of a safety intervention program. A safety intervention could be described as an attempt to alter or change how things are done in order to improve safety. In the industrial sector, a safety intervention could be in the form of a new program, practice, or initiative and idea which is intended to improve safety. Safety interventions in the workplace include job redesign, a training program, and incentive programs for safety practices, inspections, hazard analysis activities, and other administrative procedures. Safety interventions occur at different levels of an industrial safety system. In the workplace, major safety decision-making and intervention efforts are often concentrated towards the level of organization of the safety management system.

At the level of the organization of the safety management system, various interventions are put in place by the respective local, state and federal governments, industries, professional bodies, and others in order to change workplace safety policies, procedures, structures and organizations. These include several laws, regulations, standards and programs such as restructuring of the safety committee, setting up periodic inspection schedules, hazard assessment, as well as implementation of safety performance incentives. To facilitate this work, the organization of the safety management system was divided into the technical and human sub-systems. Although the regulations put in place at the level of the organization of the safety management system affects these sub-systems, numerous management planning activities are performed at the level of the technical sub-system. These include all controllable measures and policies which are thought to be instrumental to the reduction of incident rates.

At this level, various interventions are put in place in order to change the organization. These include changes to the job procedures, the implementation of a new design or redesigning the work/task as well as the working environment. The most complicated aspect of the safety process occurs at the level of the human sub-system. This involves various interventions put in place to change the human knowledge or cognition. These include competence, attitude, motivation or behavior related to safety. Human behavior is quite complicated and cannot be easily predicted (Widdershoven, 1999). Behavioral patterns in humans vary and are subject to change at any time. These behavioral patterns could be a function of physiological conditions, individual opinions and state of mind, stress level, cognitive workload as well as other complicated variables (Conarda & Matthews, 2008). Due to the complexity of the human behavioral patterns, it may be difficult to determine the quality of the safety intervention.

One method of dealing with this difficulty is to assume that the quality of the intervention is constant and acceptable for all safety activities. For this research work, the safety interventions are measured in man-hours, which do not necessarily reveal the true quality of the safety intervention. For example, an ineffective safety awareness program or training session may last for three hours or more, without making any significant impact towards changing the behavior of the employees. Several research works have highlighted the difficulties in predicting the contribution of the human sub-system to the level of errors in a safety model (Iyer et al., 2004, Shakioye and Haight, 2008). This is evident especially in situations where the actual correlations between the technical sub-system, interventions and incidents rates are distorted.