Leading Indicators or Systems Thinking?

Leading indicators for high-performance risk management systems

Risk professionals have identified that the world has changed and to effectively manage risk in today's complex organizational structures innovation, thoughtful leadership, and vision is imperative. That's why the traditional model of tracking incidents has become passe.  Lagging indicators have become a well-known feature in the risk manager's office. Research has shown that total recordable incidence rates (TRIR) are not statistically valid metrics to evaluate a company's safety performance. Reference the November 2020 publication from the Construction Safety Research Alliance on The Statistical Invalidity of TRIR as a Measure of Safety Performance. Risk management professionals have taken a new approach to control incidents and track progress, or at least recognize that the traditional model of tracking injuries and claims that occurred only reveals part of the organization's performance. Identifying these loss trends would be of value to help executive teams make informed, strategic decisions. For example, if automobile accidents occurred, then focus on defensive driver training. If employees keep slipping and falling in the same spot while doing the same task, then modify the workstation. Or, if strains keep occurring while performing this lift, then modify the task using assistive devices. These overarching themes were largely driven by insurance companies because they have access to the claims data. The idea is that with these data, analyses reveal trends, thereby giving organizations the knowledge to allocate time and resources to prevent claim recurrence.

This model has been in use for many years, and, yet, claims still occur. New thought leadership about predictive methods and leading indicators has emerged in the last decade. With books written such as, Big Data: A Revolution That Will Transform How We Live, Work, and Think. There must be a balance between how much data we capture and how we utilize these data. In some organizations, the desire to predict the future leads to collecting a large amount of information based on the hope that something will be obtained that is useful. The NASA Space Shuttle program was collecting 600 metrics a month, for example, right before the loss of the Columbia, none of which turned out to be helpful in predicting the loss or identifying the clear migration of the program to conditions of risk increase. (Leveson, N.G. Technical and managerial factors in the NASA Challenger and Columbia losses: Looking forward to the future in Handelsman and Fleishman (eds.), Controversies in Science and Technology, Vol. 2: From Chromosomes to the Cosmos}, Mary Ann Liebert, Inc., 2007.)

Identifying Leading Indicators

Leading indicators have been of interest to better identify strategies that yield proactive prevention method results. The theory is that when organizations implement these methods, it is more predictive that the organization will not experience a loss. With this thought, the logic comes about that when an organization is able to identify precursory cues to a catastrophic event, then we reduce risk and eliminate the bad outcome. These approaches seem like common sense because no organization intentionally wants to harm another person or set out to experience a catastrophic incident. Leading indicators are methods to help organizations push toward excellence that will yield results favorable towards proactive risk mitigation and prevention. Proactive prevention methods require a systematic combination of leadership, processes, rules, and sociology. Bridge the gap between technocratic and sociological.

What are some Basic Examples of Leading Indicators?

So what are some examples of data collection methods to help risk managers catch signals that precede an event? Here is an introductory list in no particular order.

• Visible leadership participation in safety practices

• Academic studies through scientific approaches to systemic problems

• Near-incident reporting

• Good catch reporting

• Strategic safety training

• Working with third-party experts

• Wellness programs

• Recognizing team members for doing a great job

• Follow-up methods across the system

• Ownership of problem-solving

• A formal program to onboard new employees

• Leadership training on safety management methods

• Fleet telematics

• Employee feedback channel about safety

• Safety coaching sessions from leaders or peer-to-peer, or both

• Safe observations

• Program audits

• Attending safety committee meetings

• Preventative maintenance programs

  • Fleet

  • Tools

  • Equipment

  • Machines

  • Facilities

• Safety perception surveys

• Activity hazard analyses

In sum, incidents rarely have a singular root causal factor, rather, incidents are the outcome of complex interrelated activities that include technocratic, psychosocial, technological, organizational norms, physical, and environmental conditions. Evaluation of these systems and their interrelations is the starting point for risk management professionals to truly grasp the greater meaning of a high-performing safety management system for proactive prevention methods across the enterprise.