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www.dbo2.com
Benchmark Your Leading Indicators
to Manage Jobsite Risk
Barry Nelson DBO2 Inc.
11 April 2007
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Agenda
Why we need new leading indicators
Defining a "normal" safety observation
The relationship between safety observations and claims
The next generation of safety observation metrics
Suggested actions from this presentation© DBO2 Inc. 2007
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Why We Need New Leading Indicators
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Why We Need New Leading Indicators
"The problem is, so many managers are tied to accident numbers because OSHA requires them to be. It’s a lousy measure. You’re measuring stuff over which you have damn little control. Many of the things OSHA requires flies in the face of what really improves a safety system."
--Dan Petersen
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Why We Need New Leading Indicators
Lagging indicators present significant disadvantages for most organizations
Challenges relative to lagging indicators:Time: information is months in arrearsFrequency: often there are far too few incidents to see a patternRelevance: falling off a ladder does not necessarily mean I have a ladder problem
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Leading Indicators Help Us Get Ahead of the Problem
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Leading indicators:
Precede a future eventAre condition- or behavior-basedAre reasonably reliable, but more valuable when combined and validated with other leading indicatorsProvide cumulative insight: more observations are generally considered a leading indicator of reduced lossEnable us to pinpoint metrics that are out of the “norm," such as an unusually high number of unsafe observations
Defining a Leading Indicator
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As metrics, percentage safe and unsafe have significant limitations:
They do not consider:The size of the projectThe severity of the observationThe perceptions, bias and competency of the observerHow quickly open issues are resolvedThe correlation between observations and claims
They are too easily manipulated by observers
Why We Need New Leading Indicators
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Defining a "Normal"Safety Observation
Defining “Normal” Observations
Research background and methodology
Over 13 million safe and unsafe/at risk observations analyzedOver 4684 contractors on 3241 projectsMarch 2006 to February 2007 periodSafety professionals and non-safety professionals collecting observations
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Safety Metric
Total Monthly
Averages
Number of Inspections 31.4Number of Inspectors 2.2
Number of Observations 2211Number of Unsafe Observations 62.7Number of Safe Observations 2149
Number of Unsafe Observations Per Inspection 2.7Number of Safe Observations Per Inspection 67.1
Monthly Benchmarks:Inspections, Inspectors,
Unsafe/Safe Observations
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Safety MetricTotal Monthly
Averages
Safe Fall Protection Observations 81.0Unsafe Fall Protection Observations 19.0Safe Housekeeping Observations 87.3Unsafe Housekeeping Observations 12.7Safe PPE Observations 884.8Unsafe PPE Observations 6.3PPE Issues Needing Follow Up 0.2Fall Protection Issues Needing Follow Up 3.4Housekeeping Issues Needing Follow Up 3.6
Monthly Benchmarks:Fall Protection, Housekeeping, PPE
© DBO2 Inc. 2007
Safety MetricTotal Monthly
Averages
Number of Low Severity Items Observed 37.2Number of Medium Severity Items Observed 16.3Number of High Severity Items Observed 6.4
Percentage of Subcategories Inspected 24.4
Monthly Benchmarks:Severity of Observations/Subcategories
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Defining “Normal” Observations
On average, companies should expect to see the following distribution for severity of unsafe observations:
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Average Number of Inspections By Project
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Average Number of Inspections By Company
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Average Number of Inspectors By Project
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Average Monthly Unsafe Observations By Project
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Average Monthly Safe Observations By Project
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Average Safe Observations Per Inspection By Project
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Average Unsafe Observations Per Inspection By Project
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Severity of Observations Per Inspection By Project
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High Severity Observations Per Inspection By Project
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Percentage of Subcategories Inspected By Project
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Comparison of Fall Protection, PPE, and Housekeeping Unsafe Observations
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The Relationshipbetween
Safety Observations and Claims
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How Number of InspectorsCorrelates to Loss
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Increasing Inspector CountDecreases Total Claims
0
10
20
30
40
0.03 0.09 1.06 1.09 1.53
Company Ave. Total Claims
% R
ecor
ds
1 Insp Count 3-23 Insp Count
How Single Safety Metrics Correlate to Loss
*Correlation is the degree to which two or more attributes or measurements on the same group of elements show a tendency to vary together.
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The Relationship Between Safety Observations and Claims
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The Relationship Between Safety Observations and Claims
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How Safety Metrics Correlate to Unsafe Observations
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Summary Results forSite Scoring System
Top 100 Sites1 in 2 sites
will have loss
Bottom 667 Sites
8% of all loss1 in 75 sites
will have loss
Margin of Error - + 4%
Tying Safety Observations to Loss
Top 333 Sites92% of all
loss1 in 4 sites
will have loss
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The Next Generationof Safety Observation Metrics
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Easily rank projects by:SeverityUnsafeSafe Safety and Non-Safety Professional Observations
The Next Generation ofSafety Observation Metrics
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The Next Generation ofSafety Observation Metrics
Risk Index Components
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Combining Leading andLagging Indicators
Leading Indicator
Lagging Indicator
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Suggested ActionsFrom this Presentation
Suggested Actions From this Presentation
Focus on increasing observers, which leads to:
Identification of more unsafe observations Identification of more high severity issues Development of focused action and intervention plans
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Set specific internal goals according to minimum expectations, for example:
1 inspection per week per observer>1.5 unsafe observations per inspection.20 housekeeping unsafe observations per inspection.13 fall protection unsafe observations per inspection
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Suggested Actions From this Presentation
© DBO2 Inc. 2007
Monitor the following metrics most closely, because they are shown to correlate with each other:
Falls: expected increase in claimsUnsafe observations: expected increase in high severity itemsHousekeeping: expected increase in falls and claimsMedium severity items: an expected increase in more unsafe observationsPPE: early indicators of housekeeping and fall issues
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Suggested Actions From this Presentation
© DBO2 Inc. 2007
Conclusion
Continue to shift your focus from lagging to leading indicators.
Complement your percentage safe/unsafe metrics with more specific, targeted observation metrics.
A single safety metric may be a poor risk indicator.Consider a combination of safety observation metrics.
Pay close attention to the real correlation between observations and claims.
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