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

2

4

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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

18

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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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