Data Analysis In Occupational Health And Safety Management

World Day for Safety and Health at Work (OSH) 2021 highlights the importance of strengthening Occupational Safety and Health Management systems, both at the national and corporate levels.

We will focus on the business world, on the importance of creating and investing in occupational health and safety systems. In this sense, organizations can find in the analysis of HR data. H H. an opportunity to know the variables that impact the accident rate, evaluate the effectiveness of preventive measures or obtain a level of risk to anticipate in decision-making.

Objectives of Occupational Health And Safety Management

The Occupational Health and Safety Management System encompasses a discipline that seeks to prevent injuries and illnesses caused by working conditions and the protection and promotion of employees’ health.

This implies, among other actions, identifying dangers and risks and implementing preventive measures to reduce the accident rate. Furthermore, it is conceived as a continuous improvement system to anticipate, recognize, evaluate and control all risks that may affect safety and health at work. Thus, being a management system, its principles are focused on: plan, act, verify, adjust.

To respond to all of this, we have in data analysis a powerful tool that can help us make more objective decisions based on data that allow us to improve the management of safety and health at work.

First Steps of Data Analytics In Health And Safety

As in any data analysis project, and especially in the field of HR. . HH, it is imperative to involve from the beginning all stakeholders or stakeholders: responsible for the prevention, production areas, processes, human resources, IT area, legal, data protection, etc.

The starting point will be one or more questions related to the business, giving us relevant information about the process we want to improve. In this case, for example:

• What activities are most likely to be an incident or accident?

• What factors have a more significant impact on the risk of a specific activity?

• Is there a relationship between the days of the week and the accident rate?

• Does training in health and safety or implementing some corrective measures influence reducing the accident rate?

• Are there subcontractors with higher workplace accident rates?

We also need to know the data on incidents and accidents and with what period: activity, date, and place of the incident or accident, its severity, location of the injuries, corrective actions, inspections, etc. And it is also interesting to cross them with the information from the HR systems. HH., Related to the professionals involved: experience, prevention training, seniority, subcontractor company or not, etc.

From the initial questions, we will pre-select the initiatives that allow us to address a strategic issue for the organization and that are feasible due to having sufficient data. We will prioritize having the first results in 2-3 months (the so-called minimum viable product) and sponsoring the project. This will allow us to communicate the results of this pilot project and for the data culture to permeate the organization.

Also Read: RPA – Threat or Opportunity For The Business World?

How Do We Analyze Occupational Health and Safety Data?

Once the question or questions on which we are going to focus and the existing data have been identified, we will define the most appropriate methodology: classical methodology, with a clear objective, planning, and defined deliverables; or agile methods, with a high-level objective and scope and sprints of a determined duration, defining after each sprint the narrower scope of the next.

At this time, we can also set up the project team, usually multidisciplinary, incorporating the appropriate profiles: business analyst, project manager, data engineer, data scientist, psychometrician, scrum master, agile coach, computational linguist, developer of software, etc. All those involved must participate in the project initiation meeting, in which they align expectations and finish defining the requirements.

In the initial phase, the data extraction, treatment, and cleaning (ETL) will be carried out, at which time the data history with which we are going to work is defined. It is also interesting to assess the relevance of incorporating external data, such as the weather or the calendar of holidays, or the age of the work machines, for example.

The analysis phase can begin once the analytical table has been made with the clean data, according to the project objective and the available data. According to these, the type of analytics to be addressed will also be chosen:

• The descriptive-analytical or inferential statistics will allow us to identify linear relationships between variables relevant and accidents and know, in quantitative terms, how they are impacting incidents and accidents in the organization. Likewise, we can study the effectiveness of preventive measures in terms of their impact on the probability of incidents and accidents.
• A predictive model will be helpful if the goal is to anticipate. It is possible, for example, to obtain a level of risk related to the probability of an incident occurring in a specific activity, taking into account the historical data and the variables that have the most significant weight in that prediction.

It is essential to take steps little by little: start from descriptive analysis to understand what is happening and move towards predictive analytics in HR that allows us to anticipate decision-making based on data and positively impact people’s safety and health. In the latter case, it would also be possible to simulate scenarios or test the impact of certain decisions in simulators or dashboards custom-built for the organization.

Whatever the objective and the analysis methodology, on this path to incorporate the culture of data in health and safety, we will find value, providing more excellent knowledge about the factors that impact incidents and accidents. And that affects the health of working people. This will allow us to prevent them, thus increasing productivity and efficiency and a more significant commitment from the people of the organization and other stakeholders.