SmartSafetyInsights, not instincts
The innovative data driven approach to a safer workplace
Coert du Plessis, Partner, Deloitte22 November 2011
Number 1
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Most workpalces now effectively measure safety performance
Feb-10 Mar-10 Apr-10 May-10 Jun-10 Jul-10 Aug-10 Sep-10 Oct-10 Nov-10 Dec-10 Jan-110
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Total Recordable Injury Frequency Rate | Dashboard
TRIFR (C) TRIFR (B) TRIFR (A) QTR Moving AVG
TR
IFR
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Some are using visual ways of presenting the results
30% of injuries to the right hand
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And some innovative design principles....
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Measure the size of the problem
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SmartSaftey 101
Safety systems focus
Safety systems & people programs
Safety integrated into business
Ope
ratio
nal
Effe
ctiv
eE
mbe
dded
Sa
fety
ma
turi
ty
The Smart Safety Maturity Model
Data analytics maturity
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SmartSaftey 101
Granular profiling
Safety systems focus
Statistical reporting & trend analysis
Safety systems & people programs
Safety integrated into business
Real time Predictive analysisO
pera
tiona
lE
ffect
ive
Em
bedd
ed
Sa
fety
ma
turi
ty
The Smart Safety Maturity Model
Data analytics maturity
Hindsight
Insight
Foresight
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SmartSaftey 101
Granular profiling
Safety systems focus
Statistical reporting & trend analysis
Safety systems & people programs
Safety integrated into business
Real time Predictive analysisO
pera
tiona
lE
ffect
ive
Em
bedd
ed
Sa
fety
ma
turi
ty
Zero Harm
Smar
t Saf
ety
Slipst
ream
The Smart Safety Maturity Model
Data analytics maturity
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How it works
Existing Data
Smarten Data
Analyse
Granularinsights
Focused interventions
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Sharpening the usual levers
HSE Strategy, Plans,
Programs and Projects
HSE Infrastructure
Safety Mindset
Policy & Safety Procedures
Workforce Profile
Education, Training & Coaching
Job & Task Design
Workflow design
Site Profile Optimisation
Equipment, Tools and
Procurement Standards
Data Driven Decisions(Granular = Grades of control)
Performance Management -
Behaviour Change
Comms & Message
Campaigning
Investment planning & Budgeting
Operational levers
Activity Clusters
People levers
Safety leadership levers
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SmartSaftey 101
Granular profiling
Safety systems focus
Statistical reporting & trend analysis
Safety systems & people programs
Safety integrated into business
Real time Predictive analysisO
pera
tiona
lE
ffect
ive
Em
bedd
ed
Sa
fety
ma
turi
ty
The Smart Safety Maturity Model
Data analytics maturity
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Analysis example| Self Organising Maps (SOMs)
- Multifunction - Visual - No assumptions - Simultaneous - Proximity = similarity
Number of events I was involved in
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Five features cover 25% of the workforce and 43% of the severe incidents [Actual client result]
25% of the workforce 43% of the severe incidents
= Not covered by the 5 SOM attributes
= Covered by the 5 SOM attributes
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Window 2 of 500 – Fatigue exception rate
My ratio of fatigue exceptions
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Number of events I was involved in
My ratio of fatigue exceptions
1. Logic is correct - keep doing it
2. Counter intuitive - protect
3. Counter intuitive - don’t reward
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Number of events I was involved in
My ratio of fatigue exceptions
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Feature 1: Fatigued, “Nappy Valley”, Maintainer employees Nappy Valley – C-Australia, 2006 Census
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Barriers to insight
Insight
Dataquality
Security and data access
Data mountain
Analytic skills
Experience
What would you do differently if you could know who will get hurt next...
Your call.
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