Most organisations collect drug and alcohol testing data. Far fewer actually analyse it. Test results are recorded, filed, and forgotten — pulled out only when an auditor asks or when something goes wrong. This is a missed opportunity.

Your testing data contains patterns, trends, and signals that can materially improve your safety program, reduce your risk exposure, and inform decisions about resource allocation. But only if you know what to look for and how to act on what you find.

Positive Rate Trends

Your positive rate — the percentage of tests that return a non-negative result — is the most fundamental metric in your testing program. But a single number tells you very little. The value lies in how that number changes over time.

What to Look For

• Upward trend — A rising positive rate may indicate a worsening substance use issue within your workforce, a change in the availability of certain substances in your region, or that your current deterrence measures are insufficient.
• Downward trend — A declining positive rate typically suggests that your testing program is having a deterrent effect. Workers know they may be tested and are modifying their behaviour accordingly.
• Stable rate — A consistent positive rate is not necessarily a problem, but it should prompt reflection. Is the rate within acceptable parameters for your industry? If it has been stable for years despite an active program, are there additional measures that could drive further improvement?
• Sudden spikes — A sharp increase in positive rates in a particular period warrants immediate investigation. Was there a change in testing methodology? A specific incident? A new substance entering the market?

What to Do

Track your positive rate quarterly at minimum. Plot it over time to identify trends that would be invisible in monthly snapshots. If the trend is concerning, investigate contributing factors before making program changes.

Seasonal Patterns

Substance use does not occur uniformly throughout the year. Many organisations observe seasonal patterns in their testing data that reflect social, environmental, and workplace factors.

• Post-holiday periods — Positive rates often increase in early January and after Easter, reflecting increased social consumption during holiday periods.
• Event weekends — In regional areas, major sporting events, festivals, or community celebrations may correlate with higher positive rates on the following Monday or Tuesday.
• Seasonal workforce changes — Industries that employ casual or seasonal workers (agriculture, hospitality, construction) may see positive rate fluctuations aligned with workforce composition changes.
• End of financial year — In some organisations, the stress associated with EOFY reporting, performance reviews, or contract renewals correlates with increased substance use.

Understanding seasonal patterns allows you to adjust your testing schedule proactively. If you know that positive rates historically rise after the Christmas break, scheduling additional random selections in January sends a clear message and provides an early detection mechanism.

Department and Site Comparisons

Aggregate positive rates mask significant variation at the department and site level. One department may have a zero positive rate while another has a rate three times the organisational average. Without disaggregated data, you cannot identify where the problem actually is.

How to Analyse

• Break down positive rates by department, location, team, and shift.
• Compare like with like — a department that has been tested 50 times provides a more reliable positive rate than one tested five times.
• Look for patterns over multiple quarters rather than drawing conclusions from a single period.
• Consider confounding factors — departments with younger demographics, higher-risk roles, or different supervision structures may naturally have different rates.

What Elevated Rates Might Indicate

• A cultural issue within a specific team or site
• Inadequate supervision or leadership at that location
• Higher stress levels or poorer working conditions
• A substance supply issue in the geographic area
• Workforce composition differences

Elevated rates are not automatically a disciplinary issue — they are a diagnostic signal that something in that area warrants further investigation and potentially targeted intervention.

Testing Frequency Analysis

How often are you actually testing? Many organisations set a target testing frequency — for example, 50% of the workforce per year — but do not systematically track whether they are meeting it.

• Overall frequency — Are you meeting your policy’s stated testing targets? If you committed to testing 50% of the workforce annually, are you on track at the six-month mark?
• Distribution — In truly random selection, some individuals will be selected multiple times and others not at all. But if the pattern is extremely uneven — some people tested four times while others have never been tested — it may indicate a problem with your selection methodology.
• Testing type distribution — What proportion of your tests are random, for-cause, post-incident, and pre-employment? An organisation that conducts dozens of random tests but has zero for-cause tests may have a supervisor training gap.

Using Data to Adjust Your Program

Data without action is just record keeping. The purpose of analysis is to inform decisions that improve your program’s effectiveness.

• Increase testing frequency where positive rates are elevated or where seasonal patterns predict higher risk periods.
• Target supervisor training at departments or sites where for-cause testing is underutilised relative to what the data would suggest.
• Invest in support services where data indicates a persistent substance issue that testing alone is not resolving.
• Adjust your substance panel if trend data suggests that new substances are emerging in your workforce that your current testing does not detect.
• Review your policy if data shows that certain policy provisions (such as consequences for first positive) are not producing the intended behavioural change.

Benchmarking Against Industry

Your data is most meaningful in context. A 3% positive rate might be excellent in one industry and alarming in another. Where possible, compare your results against:

• Industry averages published by testing laboratories and industry bodies
• Historical data from your own organisation
• Contractual benchmarks set by principal contractors or clients

Be cautious with benchmarking — differences in testing methodology, substance panels, workforce demographics, and selection methods can make direct comparisons misleading. Use benchmarks as a reference point, not an absolute standard.

Turning Data into Action

Your testing data is an asset. Treat it as one. Regular analysis, clear reporting, and data-informed decision making transform a compliance exercise into a strategic safety tool.

Want to see what your testing data is really telling you? Start a free trial of FairTest and access real-time dashboards, trend analysis, and exportable reports that turn raw results into actionable intelligence.