By Adam Sharman, Senior Partner, dsifer

A recent report by the Business Leaders’​ Health and Safety Forum shows that New Zealand continues to lag behind the rest of the world when it comes to health and safety in the workplace. Of course, the $ value impact is just one impact resulting from workplace fatalities, injuries and poor health.

In our work with organisations and industry bodies, we see that the top performing organisations consider workplace health and safety across an ecosystem of considered, human centric job design, environment design and culture & leadership dimensions. This is not something that can be fixed through a policy document of lines in an annual report.

As a starting point, our analysis with organisations we work with identifies 1. Insufficient training, 2. Fatigue or burnout induced by poor work design and high levels of overtime, and 3. Cultural complacency as being the most significant contributors to poor health & safety performance.

Of course, it is not as simple as just saying, let’s just fix these priority factors; for sustainable change, a data-driven approach to identifying and addressing their underlying drivers as an ecosystem should be applied. For example, organisations, especially manufacturers, are struggling to attract the number and calibre of talent they need to run their operations, leading to high levels of overtime as the current workforce picks up the slack. A data-driven approach to the analysis.

For the highest impact, organisations should apply data analytics to three key dimensions of health & safety:

1. Complete, accurate and timely data capture. The accurate and timely capture of H&S data forms the baseline of understanding the true picture of an organisation’s H&S performance. Whilst this may seem obvious, it is surprising how many organisations do not accurately capture data on their H&S incidents, beyond those that result in injury. Complete H&S data should capture all relevant data required using a methodology (whether online or offline) that reduces data quality risk through non-compliance error.
2. Combine data sources for deeper insights. With a baseline of complete, accurate and timely data, analysis can be conducted through combination of data sets to provide deeper insights in to underlying drivers of H&S incidents and trends. Combining H&S data with workforce planning data, for example can identify relationships between job design dimensions, such as shift patterns, and H&S trends. These insights can support targeted prioritisation of intervention activities and resources for maximum impact.
3. Communicate the impact. The insights gathered through combining quality data sources support the analysis of the organisational impact resulting from poor H&S trends. Identifying the commercial and/or productivity impact of negative H&S performance, can support sponsorship and change management activities that drive support for H&S interventions and catalyse sustainable behaviour change.

Of course, the rationale for supporting improvement in H&S performance for the purposes of improving individual health, safety and wellbeing is worthy enough in isolation of any organisation performance impact. However, it can’t be ignored that customers and investors are increasingly prioritising Environmental, Social and Governance (ESG) factors in the purchasing and investment decision analysis, including evidence that an organisation is taking care of its employees.

As such, the imperative to focus on H&S performance is not just a zero-harm initiative, it is a strategic imperative.

A holistic approach using evidence-based decision making to understand the true root cause drivers of negative health and safety performance, combined with leadership that is genuinely committed to improvement in this area is the only sustainable approach to turning these statistics around.