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From Burden to Blessing: Tapping Into Your Historical Safety Data

3 · 4 · 2024 by Claire Styles

EHSQ data – there is an awful lot of it. Serious Injuries and Fatalities (SIFs), Non-Conformance Reports (NCRs), Corrective and Preventive Actions (CAPAs), Job Hazard Analyses (JHA), air emissions data—the list goes on, and on!

Without a digital system to collect, store, and analyze it all, managing data can be a huge burden. But what if it could be a blessing instead? With a complete digital system, data becomes one of your most valuable assets—and its worth only grows with time.

That’s the power of historical data. It’s filled with insights, patterns, and predictions that help you guarantee the safety of your employees, the integrity of your products, and the efficiency of your operations.

Real-time analysis gets a lot of buzz, but there are plenty of reasons to take a closer look at your historical data as well.

#1. Trend analysis and forecasting

Ever heard the saying ‘history repeats itself’? By looking for recurring patterns, tracking cyclical behaviors, or identifying long-term trends, historical data helps you predict future outcomes and develop effective strategies.

  • Looking at historical data on workplace incidents can show when accidents tend to happen most. If a plant manager notices more accidents during shift changes, they can focus on safety measures during those times.
  • By analyzing equipment breakdowns and maintenance schedules, predictive maintenance models can predict when machinery might fail. Maintenance managers can then plan preventive maintenance, cutting downtime and lowering the chances of accidents.

#2. Risk analysis and decision-making

Analyzing past incidents and identifying historical patterns of risk helps you quantify risks, estimate probabilities, and develop mitigation strategies with confidence.

  • Analyzing past food safety incidents and recalls helps quality managers spot risks tied to ingredients, suppliers, or production methods. By noticing trends in contamination or quality issues, they can take targeted steps to prevent future problems.
  • Going over past regulatory inspections and audits provides insights into compliance risks and areas of improvement. By digging into past inspection findings, EHSQ managers can prioritize corrective actions, update SOPs, and schedule training programs to keep up with rules and standards.

#3. Evaluating and monitoring change

Historical data provides a benchmark for measuring change and progress. By comparing current data with past trends, you can evaluate interventions, strategy shifts, and new technology, gauging the success of your efforts and tweaking your strategies as needed.

  • As a quality manager, comparing current product quality metrics with past trends helps assess the impact of recipe modifications or ingredient substitutions on consumer satisfaction. If a recipe change leads to fewer customer complaints or improves product shelf life, it signals a successful adjustment. And, any decline in product quality metrics suggests a need for further refinement in recipe or ingredient selection.
  • By comparing current incident rates with past trends, a safety manager can monitor their progress toward achieving a zero-harm goal. Analyzing the root causes of past incidents can also reveal areas for improvement, allowing for adjustments to safety procedures and training programs.

#4. Uncovering hidden insights

By bringing together historical data from various sources and using advanced data analysis techniques, you can discover surprising connections that might not be obvious when looking at individual datasets. This can lead to innovative solutions.

  • Reviewing historical data on environmental incidents, such as chemical spills or emissions violations, helps EHSQ managers identify risks linked to specific manufacturing processes. Armed with this information, they can tweak processes or tighten environmental controls to prevent recurring incidents.

Driving improvement: a historical data success story

One of TenForce’s long-term clients, a leading global agribusiness specializing in sweetening solutions and high-value starch products, is reaping the rewards of their extensive historical data.

Over the span of a decade with TenForce, they’ve accumulated a wealth of valuable data, which they’ve transformed into insightful visualization dashboards:

  • Tracking the number and types of improvement opportunities submitted, along with their originating departments.
  • Identifying areas earmarked for improvement and monitoring the status of associated actions, including high-priority items and any obstacles hindering progress.

This approach tracks tasks spanning various areas, such as management of change and audits, offering a clear view of progress made. By consolidating this data into a single system and creating various visualizations has enabled them to make a tangible impact across the organization. They’re able to identify trends, share knowledge, and incentivize employees to actively engage in the reporting and improvement process.

A word of caution

At its best, historical data allows you to learn from past failures and mistakes to make wiser choices. But historical data carries the risk of misinterpretation and manipulation.

When using historical data, it’s important to avoid cherry-picking and confirmation bias by looking at the full picture and considering all perspectives. Remember, historical data loses meaning when taken out of context.

Best practices for using historical data responsibly and effectively

  • Don’t rely solely on isolated datasets. Do integrate diverse data sources to gain comprehensive insights.
  • Don’t overlook the importance of data accuracy and integrity. Do ensure that data is properly documented, validated, and maintained to uphold its reliability.
  • Don’t limit analysis to surface-level trends. Do employ advanced data analysis techniques to uncover hidden correlations and insights.
  • Don’t neglect the context surrounding historical data. Do consider the broader organizational, regulatory, and industry context to create effective EHSQ strategies.
  • Don’t view historical data as static. Do continuously update and refine historical data sets with new information and insights.
  • Don’t work in silos. Do encourage collaboration between EHSQ professionals, data analysts, and other stakeholders to utilize diverse expertise and perspectives.
  • Don’t underestimate the importance of data privacy and security. Do safeguard sensitive EHSQ data from unauthorized access or misuse.
  • Don’t delay action. Do use historical data analysis as a proactive tool for identifying trends, predicting potential risks, and implementing preventive measures.
  • Don’t overlook the value of historical data for learning and continuous improvement. Do use historical data to analyze past incidents, identify root causes, and implement corrective actions to prevent recurrence and drive ongoing improvement.
  • Don’t forget to communicate findings and insights effectively. Do ensure clear and transparent communication of analysis results and actionable recommendations to relevant stakeholders, fostering informed decision-making and accountability in EHSQ management.

There’s no time like the present

By having all your data in one system, a means to visualize it, and the best practices to use it effectively, you can transform it into actionable intelligence that drives progress across your organization. From analyzing trends and predicting outcomes to mitigating risks and driving improvement, historical data can shape safer, more efficient operations.

Ready to tap into your data? Let’s start the conversation today.

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