Making the most of your safety data

Mar 30, 2022 | Article, OpSUITE Solutions, Permit to Work

One of the benefits of a digital safety system is being able to use the data to gain better safety-related insights. But how many companies take the step of analysing their safety data, let alone turning it into tangible action plans?

Obtaining relevant and valuable information from your safety database requires a systematic approach.

Safety performance indicators

Safety performance is measured using a combination of “leading” and “lagging” indicators.

Leading indicators are forward-looking and are used to identify trends and predict future risks.  They are sometimes derived from existing data using statistical techniques such as forecasting and extrapolation.   They might also be obtained by observing certain behaviours that indicate a lapse in safety discipline.  For example, the percentage of people attending safety training and their test scores.  Another example of a leading indicator is the number of unsafe behaviours observed in the plant areas. Identifying the most common root causes from incident investigations might reveal a leading indicator. Other examples might include the adherence to safety inspection schedules and the number of non-conformances reported during an inspection.

Leading indicators can help you prioritise the most critical safety interventions and take appropriate precautions.

Lagging indicators, in contrast, are backwards-looking and answer the question “what happened”, hopefully in a way that is possible to take action on.  Observing trends in lagging indicators makes it possible to identify areas of concern that help you focus on where you need to pay the most attention.   Examples of lagging indicators include the TRIR (total recordable incident rate), LTIR (lost time incident rate), lost workdays, recordable injuries, workers’ compensation costs, etc.

Deciding on the right metrics

Deciding on the right safety metrics for your organisation is essential.  You won’t easily improve what you don’t measure.  Your selected KPIs can also impact behaviours, especially if linked to incentives.

Deciding on the best KPI is easiest done top-down, starting with the primary objectives of your safety management system.  Getting the overall business alignment is essential. It is, therefore, necessary to ensure that any safety metrics align with other organisational performance metrics. For example, if your safety policy is to reach zero harm, you need to clearly define and measure “harm” and accurately track this.

Your safety metrics also need to be prioritised in accordance with the risk.  If a particular hazard is likely to lead to a severe incident, then this is something worth tracking.  The risks with the highest consequences need to be the top priority, and their related precautions closely monitored.    Unless a risk-based approach to prioritising KPIs is followed, you could clutter your performance metrics with irrelevant “noise” that can hide severe underlying problems.

Sometimes the best safety metrics will be direct and easy to identify; in other cases, they will be abstract and need to be derived using additional information.

A bottom-up approach can also help come up with usable metrics.  One example is to consider the vast amount of data captured in the electronic permit to work system.    Regularly analysing this data can lead to new insights into worker competencies, risk areas, productivity issues, etc.

When adopting a bottom-up approach, it is essential to ask the right questions and not try and analyse everything.   Again a risk-based approach is helpful.  The questions you ask should relate to the areas of highest risk and most significant consequences of an incident.

Just because there is some interesting looking data in the permit system does not mean that this will yield any helpful safety insights. 

For example, the time to prepare a permit is easy to measure, and you might ask, “Show me how long it takes to prepare a permit”. 

But then you need to benchmark the result somehow.  If the permit is prepared quickly, this could either be due to an experienced user or because someone is cutting corners.  It might also be a low-risk activity.  It would be hard to tell from the “average time to prepare a permit” whether there is an underlying safety issue or not.

Similarly, a permit that takes a long time to prepare could be due to many other factors such as delays in obtaining tools, none of which are related to actual safety risks.

A better question to ask might be: What is the most common rule that leads to a system warning or exception in preparing the permit? 

For example, suppose that 40% of permits result in a warning about the need to provide continuous gas monitoring, which the issuer subsequently overrides. In that case, you might want to investigate further. 

In this example, a subsequent investigation might find that people often override the requirement for gas monitoring devices because there is a shortage of monitors in the factory.   In practice, portable gas monitoring devices are shared between jobs in the same plant area. 

Once you have this insight, a more informed decision can be made as to whether to purchase more gas sensors or implement a different procedure.

When selecting a safety KPI from permit data, ask yourself what actionable outcomes will result should the measure deviate from the acceptable range.  If there are no clear action steps, this KPI might not be valid.

For example, suppose the permit preparation step indicates frequent user errors. This might indicate a training or competence problem, or perhaps the system logic does not work in the real world.  Your next step would then be to interview the individual concerned and either schedule additional training or update the system rules.

This type of data analysis is never static, and in the future, you will need to constantly revisit the validity of your safety KPIs and improve on these.  

PDF Reports

“Reports” have been a cornerstone of business systems since the very beginning.  Reports show data in easy to understand formats that business people can work with.  A PDF report is also easily distributed, so most systems will allow you to distribute these reports to a broad audience automatically.

Report writing software can help you connect to the underlying database and do basic processing.  But there are often some fundamental limitations with report writing tools.  It is usually impossible to do advanced statistics like extrapolation or forecasting in a report writing tool, which will require a different approach and skills. 

Reports are, however, static and if too repetitive can eventually be ignored.  As reports become outdated, they can be forgotten or difficult to maintain, and people eventually lose confidence in them.

Reports have an important role in reporting safety-related information.  However, you need to be aware of their limitations and use them sparingly. When used wisely, reports can add value and remember “horses for courses” will apply when selecting the best tool.

An automatically generated PDF report sent to the right people with relevant information can save time and therefore improve productivity.  The timeous arrival of the report in an easy to understand format can avoid the person having to log into the system and manually search for information.  An example of this type of report is a shift handover report which is e-mailed to the incoming permit issuers.  This report might show a snapshot of all active, expired or planned permits at shift handover, making it easier for the issuer to prioritise the extension, issuing or revoking of permits for the next shift. 

As an alternative to a PDF report, you might consider a well-designed live “dashboard” visible across the organisation. 

Actionable, real-time analysis

It is usually good to analyse data in near real-time and take immediate action.  Real-time data analysis requires a different approach from writing reports. 

Poorly designed “real-time analysis” logic might send multiple false “alarms” to stakeholders through e-mail or mobile alerts.  “Crying wolf” in this way will eventually lead to people losing confidence in the system and ignoring warning messages.

A well designed real-time analysis, in contrast, will quietly monitor data to detect significant trends or abnormalities.   Each of these identified “events” can trigger a pre-defined process to validate and initiate action on the finding.  All of this can be automated.  The underlying system design obviously needs to be robust and well-engineered. 

In our example where we analyse permit to work data, it is usually possible to identify a particular training or competency requirement for a specific individual over time and then make clear recommendations in a single e-mail to the persons’ line manager.   Because training is not an immediate event, such an analysis might be compiled over some weeks. Then, the system creates an accurate consolidated report to substantiate the recommendation.  Again, all of this can be automated.

Real-time Displays

Real-time displays can be used to communicate the status of the plant in an easy to understand format.  Suitable industrial grade displays can be strategically positioned in the control room, permit office, workshop, laboratory and many other locations.

We have witnessed many examples where IT has installed large screens across the plant, only for these to be neglected.  A real-time display with appropriate information must add immediate value to the operations personnel.  If there is no clear plan for what information to display it is probably better that these screens are not installed in the first place.

Examples of actionable information on a real-time display could include the most recent shift handover information with temporary instructions, the status of abnormal jobs in progress, any exceptions or major events and overall production status.  This information can then be used by permit issuers and acceptors to prioritise and plan work better.

About “Big Data”

Over the past few years, there has been growing interest in using “big data” to gain new safety-related insights.   If some data is good, more is better, right?  When new devices are connected to the safety system for monitoring worker health, environmental conditions etc., the additional data can be beneficial in monitoring behaviours and elevated risk in the workplace.

According to Wikipedia, “Big Data” refers to data sets that are too large or complex to be dealt with by traditional data-processing application software.  This, therefore, will require a different technology platform, usually cloud-based.

While big data can be helpful for safety, remember it is not always a prerequisite to getting more out of your basic systems.  With the right KPI metrics and proper logic in the existing systems, you can also go a long way with “small data”.

The vision of using big data combined with advanced analytics and artificial intelligence is compelling and worth considering.  Our team is working actively to identify the best opportunities for these new, emerging technologies and incorporate them into the core IntelliPERMIT and OpSUITE products.

System Health Checks

Owing to the criticality of the data, a digital safety system should also undergo a regular “health check’.  This service is provided by Adapt IT for our customers. 

A regular system health check will analyse the system performance over a period and make specific technical and system recommendations.  But more importantly, a system health check can also help identify potential safety issues. 

Adapt IT has the necessary understanding and skills to “mine” the data, but gaining accurate insights should always be a collaborative effort. We do not necessarily have detailed knowledge of the actual operating environment and therefore will work with your team to design the best approach.

Typically a health check would include the following standard analysis:

  • The volume of transactions and system performance
  • Analysis of selected key transactions
  • Analysis of plant area, type of permit, individuals using the system, utilisation of the system for managing work orders etc

Perhaps of more interest from a safety perspective, these health checks can also include other helpful analyses, for example:

  • What safety rules needed to be temporarily overridden, and under what circumstances?
  • Were there any violations of procedure involving people with inappropriate training or competency profiles?
  • Under what circumstances did permits expire or need to be extended?
  • Were there any violations in isolation procedures, if so where and why?
  • How many working group interactions were identified, and under what circumstances were these managed?
  • Were there any outdated procedures or opportunities for improvement reported by users of the system?
  • Are there any suggestions or requests to update any of the rules for safe work?

It is recommended that your health check scope be developed with our consultants to fully unlock the underlying data’s safety-related potential.

In conclusion, there is likely a great deal of value locked inside your safety data.  Making the most of this will require a systematic approach, the right metrics, the right tools and the right collaborative approach with the system developer.

For more information

Adapt IT Manufacturing provides digital solutions that enhance safety performance and operational excellence to help industrial companies achieve more.

For more information on how IntelliPERMIT and OpSUITE can help you better manage your process safety please contact the team at Adapt IT.

By Gavin Halse and Henry Boshoff

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