Reducing Serious Injury Potential Through Deep Incident Analysis
Over 1,000 incident and hazard records were reviewed, with 57 identified as having serious injury potential. The findings revealed key patterns in control failure, human error, and supervisory practices that informed targeted improvement strategies. The analysis aimed to uncover systemicweaknesses in control implementation, human error, and operational practicesthat contribute to high-risk exposures.

Our Approach
Using the SCALE© Analysis Process, we applied astructured methodology to assess:
- Severity and risk context of incidents.
- Effectiveness and enablement of critical controls.
- Human error types and operational antecedents.
- Exposure trends across time, divisions, and work cycles.
The analysis also benchmarked the organisation’s SIFpexposure against global standards and examined demographic patterns to identifyhigh-risk periods and divisions.
Research and Insight
Key findings highlighted several areas for improvement:
- 11.1% of incidents had SIF potential, with the highest risks linked to uncontrolled energy release, working at height, falling objects, and vehicle-person impacts.
- 86% of SIFp incidents were rated in lower severity categories, suggesting underestimation of risk potential.
- 91% of failed control implementation was hindered by equipment issues or unclear procedures.
- 58% of SIFp events involved unintentional errors—slips, lapses, or mistakes—often due to poor hazard perception or decision-making under pressure.
- The 6am–8am shift period showed double the SIFp exposure compared to other times.
- One division had a disproportionately high SIFp rate despite low incident frequency.
Tangible Outcomes
In response, the leadership team:
- Initiated a review of incident severity categorisation to improve accuracy and investigation depth.
- Enhanced supervisor coaching to improve hazard awareness and decision-making during critical tasks.
- Focused on improving control reliability in high-risk contexts such as tensioned lines, fall protection, and vehicle operations.
- Increased field supervision during early shift hours to mitigate elevated risk.
- Encouraged deeper pre-task planning with targeted questions to identify and treat potential hazards.
This data-driven approach has helped the organisation betterunderstand the nature of serious injury risks and implement practicalstrategies to reduce exposure and improve safety outcomes.
To learn more about how Meta Incident Analysis andthe SCALE© Analysis Process can help uncover hidden risks and improvecontrol reliability in agricultural settings, contact the Incident Analyticsteam.
Key insights
11%
of incidents had SIF potential, with the highest risks linked to uncontrolled energy release, working at height, falling objects, and vehicle-person impacts.
86%
of SIFp incidents were rated in lower severity categories, suggesting underestimation of risk potential.
Download full case study
Get in touch
Let us show you what we can do for your business