The safety journey varies because each organization is unique. But with a greater focus on consolidating EHS processes on a single software platform, digital transformation, and the implementation of EHS technologies, we can see a pattern emerge shared by many Enablon clients.
It goes something like this: At first, a company wants commercial software for incident management. They want a tool simply to track all accidents, injuries, and illnesses across the enterprise, for recordkeeping and compliance purposes.
Then they decide to expand the use of their EHS platform to other functions, such as audits, inspections, air quality, environmental compliance, etc.
At some point, they decide to leverage their EHS software system to be more proactive, instead of using it simply for compliance, reports, and to track lagging indicators (injuries, illnesses). They do this in many ways, such as capturing near misses, not just accidents, but also observations of at-risk or unsafe conditions or behaviors. They encourage frontline workers to enter observations by making it as easy as possible, through a mobile app.
Data on observations is then analyzed to identify hazards, risks, and behaviors that need to change. This is followed by corrective and preventive action plans to either eliminate hazards or control risks, and training sessions or other types of employee outreach to encourage the right behaviors.
Many organizations already have a program in place to capture near misses and incidents through mobile apps. But what about observations of at-risk or unsafe conditions or behaviors?
If your company does not have yet a program where workers can capture and report observations, here are five best practices to help you get started.
1) Provide Examples of What to Report
To make the training more effective, provide examples of the things to report. Maybe even stage situations on the plant floor as part of an exercise, and ask people to identify what should be reported. People are more likely to learn through actual examples, rather than theoretical explanations.
2) Remind That It’s Not About Assigning Blame
Emphasize over and over again that the purpose of the program is not to assign blame, but to improve workplace safety for everyone. Even better, show that the organisation is serious about this by providing two types of anonymity.
First, allow workers to submit an observation anonymously if they prefer. Second, give the possibility to submit an observation that involves another employee without naming the employee or even providing his location (so the employee that was observed can’t be identified later).
3) Include Contractors
Leading EHS mobile apps like Enablon Go can also be used by contractors of a host employer, making it easy for all workers, contractor and hiring organization alike, to report observations. The app can be installed with just a few steps by contractors who can start using it right away, without having to go through a complex IT process.
Also, contractors would only be able to enter incidents, near misses, other events, and observations through Enablon Go. They would not have access to your company’s Enablon platform either from the app or a desktop.
4) Compare Observations With Incidents
The number of reported observations is a leading indicator, but lagging indicators, such as incident rates, help to measure the effectiveness of the program. By comparing the number of observations and incident rates over time, you can have a good idea if observations are providing valuable insights into hazards and risks.
Note that there will be a lag time. For example, if the number of observations has been high since January, incident rates may start to decline only as of April, since it may take time to fully identify and eliminate hazards or control risks through action plans.
Comparisons between the numbers of observations and incidents may reveal one of the following:
- High observations + low incidents: Insights from observations are being successfully used to identify and address hazards and risks, thereby reducing incidents.
- Low observations + high incidents: Not enough observations are being captured to produce insights into hazards and risks, therefore incidents are staying high.
- High observations + high incidents: The quantity of observations is good, but not the quality, i.e. observations are not useful in producing valuable insights into hazards and risks.
- Low observations + low incidents: Safety performance has improved so much that there are fewer new hazards or risks to identify through observations.
- High observations + low incidents: Maybe most hazards were already known because of hazard assessments conducted regularly, and have been addressed; while many observations may not be valuable and aren’t revealing new hazards.
- High observations + high incidents: Observations may be successfully identifying hazards, but no action is taken, or controls are not successfully reducing risks of incidents. The problem is with execution or risk mitigation, not observations.
In general, simply aiming for a high quantity of observations is not enough. Quality also matters.
5) Start With a Pilot Program
If you want to proceed cautiously, consider running a safety observations pilot program at one site, before implementing the program across the entire enterprise.
The pilot should run for a specific duration. Answer these key questions to help determine the changes that should be made before rolling out the program everywhere:
- Are workers participating? What is the percentage of workers who reported at least one observation, and the average number of observations per worker?
- Is it easy to report observations? Are workers satisfied with the way observations are reported? Are there too many details to enter? Is the process quick and user-friendly?
- Are you getting the right number of observations? Are you getting a lot of observations because the program is working well? If you’re not getting enough observations, is it due to a lack of participation, unclear instructions, or because there are not many unsafe conditions or behaviors to report?
- Is there enough data per observation? Are you satisfied with the quantity and quality of details for each observation?
- What is the value of the observations? Are you getting too much noise and not enough signals? Are people entering random observations just for the sake of reporting something?
- Are you noticing differences between work groups? For example, are workers from the night shift participating less, are workers of a specific team participating more? How can these differences be explained?