Predictive Safety Analytics: Improving Workplace Quality

Most organizations have spent years implementing robust applications stressing accountable management leading towards strong safety and employees’ health. Predictive safety analytics will be an end-to-end desired solution for these organizations looking to improve workplace safety and business outcomes.  

Businesses across the globe leveraging the advantage of big data and advanced analytics to gain deeper insights can deploy predictive safety analytics to assign their scarce resources in an optimal way to address workplace safety in injury prevention and injury management. Predictive safety analytics is an approach to leverage data using various sophisticated analytics techniques to promote better safety outcomes. This analytical approach helps organizations to get to the root of the problem and identify the potential factors that likely can cause damage before they occur. 

The main objective of predictive safety analytics is to help organizations in developing prevention strategies by identifying various factors that can cause workplace incidents or collateral damage. For example, there are a few insights that are frequently hidden and not found in accident reports -like equipment operation and management data, vehicle telemetry, geospatial, socio-demographic, human resource, employee training, industry equipment, etc., which can be decoded to identify the original cause of the problem and helps you in preventing the future outcomes of the same.

How Predictive analytics can Improve Workplace Safety?

These advanced analytics techniques can reduce workplace mishaps and incident occurrence rates at greater speed. Below we have discussed a few ways how you can leverage predictive analytics to improve organizational safety and health.

• Determine the metrics that can provide the ability to make proactive evidence-based safety decisions in actionable measures, which is more advanced than the traditional reactive reporting of claims after incidents.
• Identifying the work processes or operations areas that are prone to have the highest risk for the occurrence of accidents in the future.
• How can you advance your research and improve the impact of proposed changes to training, teaming, and rostering to immerse the workplace changes in real-time and make suggestive decisions accordingly?
• When organizations have to deal with budgetary constraints to improve safety programs, the predictive safety analytics approach can help in measuring the preventive measure and suggest best practices given the highly variable nature of accident data to offer the best value across a range of future outcomes.
• Companies today are equipped with unprecedented data from various sources, and leveraging safety analytics can help in measuring the predictive breakdowns of operating equipment and the possibilities that will lead to equipment failure and accidents with more accuracy.

How predictive safety analytics will work for you?

Industries are at risk of failing to identify the precautionary or strategic measures to operate safely and make safety decisions. Why?  Businesses are operating in an environment where they are acquainted with the breadth and volume of data that are generated as a part of business operations – and the organizations are rarely using it to make informed and safe decisions. Below we have shared a structured approach on how can leverage predictive safety analytics with minimum effort and cost.

1. Data acquisition and optimization

Collect data and construct modeling data by aggregating, manipulating, and joining. Integrate data optimization strategies to manipulate your business data with your own external data sources to create an integrated data set that is ready for analysis. Gathering information from various data sources, business units, etc., is mostly raw data, which needs to be optimized for further analysis including the calculation of all derived metrics.

2. Data preparation and validation

Model development and segmentation is the second stage where we explore the acquired data to identify the causes and perform segmentation analysis. Validating the effectiveness of safety levers and conducting the deep dive insight to understand what, why, and how the organizations can prioritization of causes to be addressed. During this phase, we can choose and apply various analytics modeling techniques to apply to extract data. Applying powerful statistical techniques can help organizations in discovering the relevant relationships between safety outcomes and operational metrics that lead to predictions about where and when the accidents are most likely to happen, under what circumstances, all before they happen in the future.

3. Model deployment and prediction

The cost of data analytics has dropped considerably in recent years, making methods like smart safety analytics has become cost-effective. By effectively implementing advanced data analytic strategies, companies can explore more opportunities for effective innovations to reduce costs associated with improving safety and cutting the number of workplace incidents that might occur. Developing a training model to work on sample data to validate employee health and safety and measuring business environmental health to identify at-risk factors and develop strategies to describe must-apply actions. Commencing ongoing segment analytics and monthly reporting can help in making preventive decision making and implementation. 

Understanding and expanding data collection, setting up the organization to immerse predictive safety analytics model, and scaling the data exploration most organizations have an opportunity to apply smart safety analytics regardless of the degree of workplace safety they are willing to achieve. Harnessing the power of available data is truly enhancing the efficiency of businesses, improving safety outcomes, lowering costs related to workplace safety management, and helping in building a responsible business architecture. As mentioned above implying the power of technology can help your organization to be more effectively proactive than being a reactive decision-maker. 

To enhance your organization’s safety at the workplace or be willing to know more about predictive safety analytics and how you can leverage the same for your business. SoulPage can help you build AI-driven predictive decision-based solutions for your workplace to improve overall business outcomes. To know more about SoulPage, contact us.