Risk-Based

(Asset) Facility Management Planning

Raymond Tan MBA BA(Hons) FCGP CSAM CAMA

Head of Asset Management Intelligence Support (AMIS)

Community Facilities Department.

Auckland Council

Overview

• References

• Auckland Council Approach

• Learnings

External RisksGroup Type Element Examples

Natural Event

MeteorologicalStrong wind, Flooding, Extreme rain, Extreme temperatures, Lightning, Drought

Geological/geotechnical Snow slide, Landslide, Earthquake, Tsunami, Volcanism

Fire, natural Forest, VegetationCosmic objects Meteorite (asteroid), Comet

Medical / biological

Plants and animalFungal, Parasite (Legionella,Giardia, Cryptosporidium), Bacteria, Viruses, Transferable diseases, Pandemic, Non pandemic

Technological

Release of harmful substances

Chemicals, Biological, Nuclear, Other

AccidentIndustrial fire, Industrial explosion, Transportation accident, Structural collapse, Other

Technical / human errorWater delivery, Food Safety, Sewage and waste, Transportation services, Financial services, Energy supply, ICT system failure

Human Behaviour

Malicious acts Organised crime, Sabotage, Espionage, Terrorism, War

Dysfunctional behaviour Psychotic (individuals), Negligence, Gangs, Other

Source: Auckland Council (Draft Natural Hazards Risk Management Action Plan 2017

Auckland Natural Hazard Risk Profile

Source: Auckland Council (Draft Natural Hazards Risk Management Action Plan 2017

Discussions, Guidance & Methods

2014 2014 2017

2016

2017

2010 2017 2017

Asset RisksGroup Type Element Examples

Asset

Capacity Natural wear and tear from frequency of use, stress during use

TypeConstruction method (e.g. seismic risk, weather tightness), materials used (e.g. asbestos risk, silica, lead)

Physical / Design Life Age-based deterioration/decay

ObsolescenceIrreplaceable critical components, outdated software not supported, incompatibility with newer components

Service Service Delivery Quality Reliability, increasing demand (or lack of),

Efficiency

Operating costsNot justified by new available technology to reduce costs significantly

Service costs Renewal or maintenance costs unsustainable

Design / Service Life

Pe

rfo

rman

ce

Years

Min Level of Service

Very Good

Average

Very Poor

Reduced service life

Asset renewed (original assumption)

Clause 6. Planning

6.1 Actions to address risks and opportunities

When planning for the FM System, the organisation shall consider issues…..and determine the

risks and opportunities that need to be addressed to

• give assurance the FM System can achieve its intend outcome(s);

• prevent, or reduced, undesired effects;

• ensure business continuity and emergency preparedness;

• achieve continual improvement.

The organisation shall plan:

a. Actions to address risks and opportunities, taking into account how these risks and opportunities can

change with time

b. How to:

– integrate and implement the actions into its FM system processes;

– evaluate the effectiveness of these actions.

ISO 41001:2018 Facility Management

ISO 31000:2018 Risk ManagementRisk Assessment and Management

Each asset class will have its own particular risk

profile that needs to be considered by the

organisation in terms of its corporate and

strategic objectives.

Application of a risk matrix based on

consequence and likelihood as set out in

standards such as AS4360 should be followed.

The flow chart from the IIMM Appendix 2 sets

out a good framework to follow. Importantly, a

documented outcome should be a risk

management plan that includes treatments and

operational activities to be applied; and by

whom.

2016 IPWEA Condition Assessment and Asset Performance Practice

Notes

ISO 31010

Our ApproachFramework, Principles and Processes

Council Top Strategic Risk - (Themes)

1. Health, Safety and Wellbeing

2. Cyber Security

3. Climate Change Adaptation and Mitigation

4. Crown reforms – housing and urban growth

5. Fit for purpose community assets

6. Significant internal and external disruptions

7. Service Delivery

8. Small Waters, Waste Systems and Stormwater management

9. Programme and Project Delivery

10. Consent Processing

11. Theft, Fraud and Corruption

ISO 55002:2018 Decision-making framework for asset management

Ris

k M

anag

em

en

t

Co

mp

liance

Man

agem

en

t

Operational planning & control

Value

Ris

k an

d o

pp

ort

un

itie

s

Re

qu

irem

en

ts

Decision –making Criteria

Asset Management Plan(s)

SAMP

Value provided by assets

Organisational objectives

Pro

fit

Context / business environment

Stakeholders / societal expectations

Source: ISO 55002:2018

Performance(Technical / Functional)

RiskCost

Value

Adapted from ISO 55010:2019

AM Considerations - Linkages

IDF Programmes of work agreed(Drop down from LTP)

Identify

Define

Deliver

34

25

Renewal / ReplacementYes - Renew like for like?N – Upgrade / Replace

Asset Disposal / Decommission

0

Investment for change Asset Creation

Operations

Maintenance

1

AMISAssessment, Information Mgmt

/ Decision Support

• Asset deterioration assessment,

remaining useful life evaluation

• Asset fit-for-purpose, technical

performance, e.g. energy

usage, etc.

• Investment options

assessments

Risk

• Building codes and regulation

compliance evaluations

• Capacity assessments

against current building

codes

• Evaluate options to meet

legislation

Condition

• Asset Risks / Hazards

identification

• Asbestos risk assessment

• Seismic risks evaluation

• Pre-demolition surveys

Compliance

Asset Performance Assessment (Model Input)

Asset Information Management (Model Input)

• Asset information, e.g. location,

physical attributes

• Asset management information,

e.g. condition, technical

performance, capacity, etc.

Data Validation

Data Integration

• Incorporating location-based

analytics and geospatial

integration to facility

management planning.

• Provision of innovative solutions

to spatial data collection,

harmonisation and integration

with other assets systems.

Data collection

• Validation of asset information

handed over from developers

(224c), or project completion

• Conducting periodic asset data

audits on-site against various

asset management sources to

ensure accuracy of data including

condition assessments

Descriptive

Decision Support (Model Analysis & Output)

• Organisation and Visualisation of

unstructured data

• Development of interactive

dashboard to present asset

performance information.

• Develop of Facility management

plans to inform budget decisions

PredictivePrescriptive

• Analysis of options post

assessment

• Divestment, Reinvestment

evaluation

• Impact analysis of options

• Support prioritisation of asset

solutions

• Medium to long term risk-

renewals profiling

• Capital vs short term

maintenance cost estimates

• Whole-of-life costs estimation

Criticality x Condition = Risk

Qualitative /

Quantitative Quantitative Temporal

❑ Simplification (1 to 5 ranking)

❑ Risk-based approach:

Likelihood (Probability) vs Consequence (Impact)

❑ Condition= Likelihood = Probability of asset failure

❑ Criticality =Consequence = Level of Impact

❑ Temporal, Quantitative, Qualitative Dimensions

Key Considerations

❑ Asset criticality in terms of:

▪ Health & Safety (e.g. fire safety systems, security)

▪ Impact on overall asset system (e.g. roof, plumbing)

▪ Impact on Service (e.g. aesthetics)

▪ Regulatory / legislative requirements (e.g. building code, heritage, environmental)

❑ Physical condition based on the facility lifecycle affected by:

▪ Usage (e.g. wear & tear)

▪ Design life / Deterioration profile (e.g. material, construction type)

▪ Environmental or other external effects (e.g. coastal, marine, slips, storms, vandalism)

▪ Asset (Technical) Performance (e.g. breakdowns, utility costs)

Key Considerations

Criticality (Impact) / Failure Probability

Probability of Failure

Imp

act

(Cri

tica

lity)

3

3

21

1

2

4 5

4

5High

Low

Low High

Scheduled / Continuous Monitoring

Regular Monitoring

Scheduled / Planned Renewal

Scheduled Maintenance / Low Priority Renewal

High

Low

Low High

Imp

act

Likelihood

High Impact / Low Probability (repair / maintain)

Low Impact / Low Probability (repair / maintain)

High Impact / High Probability (renew / rehabilitate

Low Impact / High Probability (renew / rehabilitate

Yr 1-5 Yr 6-10 Yr 11-15

Risk ProfileRenewal Projection

Yr 16-20

Risk-Based Renewals

Requirements to address Asbestos, Heritage and Seismic

Asset Risk Assessment Program (ARAP) - Blueprint Program Sponsor - Rod SheridanBusiness Owner - Raymond TanProgram Manager - Ben MeadowsProgram Coordinator - Tracy MassamSub Program Lead – Surveys - Jimmy Bester (Asbestos), TBC (Seismic), TBC (Compliance)Sub Program Lead– Evaluations - TBCSub Program Lead – Decision Advice - TBCSub Program Lead – Design & Scoping - TBCSub Program Lead – Projects Delivery - TBC

Projects Delivery

• Construction• Divestment

Design & Scoping

• Approvals• Commission• Consenting

Decision Advice

(Invest / Divest) Local Board

• Governing Body• Staff

Evaluations / Investigations

• Prioritise remedial actions

• Evaluate options• Concept• Business Case• High-level

costing

Surveys / Inspections• Pre-inspection preparation –

building plans, consent review, legislation review: RMA, MCA, BA

• Survey, inspection• Materials collection & testing

(asbestos/ mould/lead)• Seismic calculation (Initial/Detail)• Current code compliance

evaluation (e.g. fire safety, accessibility, weather-tightness)

• Heritage• Sticker / Notices deployment• Report development

Deliverables• Asset Risk report• Media release• Stakeholder communication

(messaging)

• Prioritised list for investigation/optimisation

• Stakeholder communication (messaging)

• LB/GB report• Memo • Stakeholder

communication (messaging)

• Project Initiation• LB/GB report• Memo• Stakeholder

communication (messaging)

• Asset renewed• Asset optimised• Asset Divested• Stakeholder

communication (messaging)

Other Program Resources

CF (AMIS) / Building Control / Legal CF (I & D) / CS (SS&I)

CF (I&D/S&LA) / LBS CF (I&D/S&LA) CF (PD/S&LA)

Business InputsIES / Corp / Panuku / CS /

SS&IIES / Corp / Panuku / CS / SS&IIES / Corp / Panuku / CS /

SS&I / Finance

Benefit Realisation

IES / Corp / Panuku / CS / SS&I

Program Governance

ARAP Steering Group

Capex Delivery

& AM Steering Group

H&S Steering

Committee

Sub Program Tasks

Gateway / PMF conformance

Administration / Communications / Legal / Democracy (Deliverable: Communication Plan)

Core Program Resources

Asbestos Assessment

Asbestos Containing Material - ACM

• Asbestos cement (AC) sheets, slates & pipes, roof

sheets

• Insulation/sprayed lagging

• Asbestos textiles (rope, yarn and cloth)

• Sprayed coatings (textured ceilings)

• Bitumen felts and coated metal (decramastic tiles)

• Flooring materials (i.e. vinyl/tiles)

• Textured coatings and paints.

• Reinforced plastics – Electrical (Bakelite) boards &

fittings

• Millboard, paper and building (roofing) paper products

• Mastics, sealants, putties and adhesives

• Automotive brake pads, lifts brake disks

• Possible contaminant in baby powder, various foot &

shoe powders & even make up.

Asbestos is present in 1000’s of products (usually encapsulated in a resilient matrix)

HARDIPLANK - ASBESTOS

WEATHERBOARDASBESTOS CLADDING FIBRE

CEMENT TILES

Results

Building (EPB) Amendment Act 2016

The Act and its underpinning regulations and methodology came into fully effect from 1 July 2017

Key changes:

• National rules and methodology will supersede all Council EPB policies

• Divides NZ into zones of high, medium, and low seismic risk

• Stepped approach to identification, assessment and management of EPBs depending on seismic risk zone

• Councils to identify potential EQP buildings based on building ‘profile’ categories and advise owners. Council has discretion to identify buildings outside these profile categories.

Strike the right balance between:

I- Protecting people from harm in an earthquake

II- The cost of strengthening

III- The impact on built heritage

URM Pre-1976 buildings Falling hazard components

Seismic Assessment

No. Buildings Assessed Area (m2) of Assessed Buildings215

(≈ 6% total listed AC) buildings)417,896

(≈20% estimated total area of A) buildings)

Seismic Risk Category No. Buildings Area (m2)

High (NBS<%34) 67 44,082

Moderate (%34≤NBS<%67) 88 141,088

Low (NBS≥%67) 34 176,603

N/A (Non-building assets, Demolished, etc.) 26 56,123

10% of the total area of AC owned buildings is estimated to be EQP.

Assessed Buildings

Decision-Making Framework

• Defines and considers different options that may be applied to remediate the risk once a building is

identified as being EQP

• Considerations when comparing the advantages of each option against its alternatives are:

- The building current use and importance level

- If the building is of heritage value

- Any future programme that has been planned or likely to be planned for the building in future

- Financial parameters

Seismic Risk Management Policy

• provides a guideline to define the most economically and structurally viable upgrading level to which a

building can be possibly upgraded to

• Identify a wide spectrum of influential parameters that could play a major role in establishing this guideline

• Examine the impact of identified parameters on two important measures that drive the policy, being risk

and cost

Current Activity

Estimating Risks with Models

Embedding spatial dimension in asset risk

profiling: Towards a better of management of

community assets in Auckland Council

Methodology

Spatial Analysis

Principal Component Analysis

Decision Tree Analysis

Extraction of multiple spatial variables from existing topographic and hydrological dataset using GIS to identify buildings that are exposed to flood-related variables.

A statistical procedure to find spatial variables that significantly contribute to flooding and derive associated principal components for decision tree analysis

A predictive modelling tool to classify the flooding risk of community building in terms of risk index value

Spatial Analysis

➢ Getting sample points➢ Building corners and centroid generation➢ 984 buildings exposed to flood risk

• 430 entire building • 554 partial building

Dataset and variablesThemes Data used Derived variables

Asset Community buildings footprint data information (vector)

(i) proportion of building area exposed to flood

Topography Digital elevation model – Urban and Rural (LIDAR)

(ii) building centroid ground level; (iii) building corners ground level; (iv) elevation difference between building corners and building central location

Topography Digital surface model (LIDAR) (v) Surface elevation above ground level

Topography Slope (LIDAR) (vi) Slope (in degrees)

Hydrological Flood plain (based from hydrological modelling)

(vii) Floodplain level

Hydrological Flood prone area (based from hydrological modelling)

(viii) Minimum level; (ix) spill level; (x) depth of flood prone area

Hydrological Overland flow paths (based from hydrological modelling)

(xi) Overland flow path catchment area

Hydrological Coastal inundation (based from raster spatial modelling)

(xii) Coastal inundation depth

Asset Building valuation (xiii) Proportion affected building value exposed to flood

Decision Tree and Principal Component Analysis

Importance of components:

PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9

Standard deviation 2.3265 1.4396 1.3184 1.1520 1.00801 0.90203 0.87363 0.68406 0.45379

Proportion of Variance 0.3866 0.1480 0.1242 0.0948 0.07258 0.05812 0.05452 0.03342 0.01471

Cumulative Proportion 0.3866 0.5346 0.6588 0.7536 0.82617 0.88429 0.93881 0.97223 0.98694

PC

A1

PC

A2

PC

A3

PC

A4

PC

A5

PC

A6

PC

A7

PC

A8

PC

A9

PC

A1

0 PC

A1

1 PC

A1

2 PC

A1

3 PC

A1

4

Building centroid ground level

Elevation diff bet bldg corners & centroid

Coastal inundation depth

Flood plain level

Flood prone minimum level

Flood prone spill level

Flood prone depth

Overland flow path catchment area

Proportion of building value exposed to flood

Proportion of building area exposed to flood

Slope (in degrees)

Surface elevation above ground level

Urban LiDAR

Rural LiDAR

➢ 3,428 point locations for 984 buildings➢ Shows the % of data that falls to each nodes ➢ The average response value at that node are

displayed for the branch➢ Decision tree consist of:

• 6 internal nodes• 8 terminal nodes

➢ The developed tree used to predict the test and train building datasets for the flooding risk scores

Results and Discussion:

15616%

26327%

29630%

9410%

434%

182%

10310%

111%

Building Count by Predicted Flood Risk Index

Score: 299 Score: 413 Score: 490 Score: 537

Score: 643 Score: 692 Score: 724 Score: 808

Lessons Learned

• Never assumed everyone knows the

risks

• Don’t rely completely on IT systems

• Complacency and ignorance is real

• Plan / Prioritise assessment of critical

assets

• Understand the difference between

asset and business (service) risks

Where can you find information?