Risk Management for Construction Dr. Robert A. Perkins, PE Civil and Environmental Engineering...

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Risk Management for Construction Dr. Robert A. Perkins, PE Civil and Environmental Engineering University of Alaska Fairbanks

Transcript of Risk Management for Construction Dr. Robert A. Perkins, PE Civil and Environmental Engineering...

Page 1: Risk Management for Construction Dr. Robert A. Perkins, PE Civil and Environmental Engineering University of Alaska Fairbanks.

Risk Management for Construction

Dr. Robert A. Perkins, PE

Civil and Environmental Engineering

University of Alaska Fairbanks

Page 2: Risk Management for Construction Dr. Robert A. Perkins, PE Civil and Environmental Engineering University of Alaska Fairbanks.

Class for DOT Construction Managers

• Get started– Who we are– Where we are– Why are we here?

• Book and Syllabus• Handout Material

– Electronic– http://www.faculty.uaf.edu/ffrap/CM%20Cours

e%20Info/CM%20Index.html

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Risk and Safety

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Class Outline

• Class 1, Basic risk concepts applied to project and construction management

• Class 2, Specific risk concepts applied to construction – qualitative risk analysis

• Class 3, Quantitative risk analysis, a little probability, tools.

• Class 4, Risk Assessment

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• Class 5, – Risk Management, owner’s perspective– How contractors manage risks

• Class 6, Presentations and Wrap up

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Today

• Risk in general

• Risk in projects

• Risk in construction

• Analysis of Risk

• Management of Risk

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Assessments

• Quiz following Class 4, 30%– Definitions– Problems

• Practicum, 60%– Team project– Risks from a project– Plan for handling them

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“Clouded his future is…The future is always in motion”

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Estimation of Future Events

• AKA “divining”

• Oracle at Delphi to my financial analyst

• Pigeon guts, Roman augers

• “The diviners have seen a lie, and have told false dreams; they comfort in vain (Zechariah 10. 2).

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Management

• An understanding of and dealing with the stochastic nature of management systems.– designating a process having an infinite progression

of jointly distributed random variables.– of, pertaining to, or arising from chance; involving

probability; random– from the Greek stochastikos meaning, proceeding by

guesswork

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Estimates

• Estimates are essentially guesses and often have a serious downside if they are wrong.

• The reason they are guesses is that there are future events (“states of nature”) that are uncontrollable and these events will control the outcome.

• Regarding what we can say about these future events, there is a continuum.

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Terms• Certainty

– If we have full knowledge (we believe) of the future. We might approximate that if we have a firm quote from a bonded sub or supplier.

• Risk– Many estimating decisions are made under “risk.” In technical terms,

“risk” means we feel we can state the probability of the events. For example, we know the price of concrete in the summer is likely to be $200/CY but may vary by 15%.

• Uncertainty– We recognize alternate states of nature may happen, but we don’t have

a clue how likely they are. – Note the difference between the technical use of terms and the common

usage. While the entire future is “uncertain,” if we feel confident we know the probability of the future we say there is “risk” and limit the use of “uncertain” to situations where we do not know the probability of events.

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• Knowns

• Known-unknowns

• Unknown-unknowns

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• Road freeze up by October 1

• Foreman quitting

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Examples

– Projects• Nature of Projects

– Project cycle» Graphs, ease of change vs. completion» Cost of change vs. design

– Work Breakdown Structure

• DOT Projects– Type– What can go wrong?

• Participation

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• Risks must be evaluated according to the project cycle.

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WBS

• Work Breakdown Structure

• The tasks needed to complete the project

• Tie WBS to risks

• Contracting strategies

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High Level WBS

• Planning

• Pre-design

• Design

• Procurement

• Construction

• M&O

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Mid-level Pre-design

• Survey

• Soils

• ROW

• Environmental

• Public

• Other

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More Detail - Soils

• Review Records

• Schedule Drilling

• Drill

• Analysis

• Report

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Finer Detail - Drill

• Costs– Labor– Equipment– Subcontract

• Schedule– Permits and approvals– Section A– Section B– Section C

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And more

• Labor– Bare– Benefits

• Vacation

– Supervision

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Nomenclature - sometimes

• Program

• Project

• Phase

• Task

• Sub-task

• Work Packages

• Etc.

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More

• Coordination Matrix

• Who is responsible, involved, needs to be copied, and, almost forgot,

• Who will do the work

• Contract v. In-house

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WBS to RMP

• Risk Management Plan

• Risks should be considered with respect to the WBS

• Who is responsible for apprizing risk

• Minimizing Risk

• Reporting on Risk

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Forecasting, Time

• Short-term– 1-3 years– Generally based on current knowledge

• Medium-term– 3-15 years– typically the issue

• Long-term– >15 years

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Your Organization’s Risks

• Discuss

• Who manages?

• Technical Risks

• Performance Risks– AKA Programmatic Risks

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Forecasting Methods

• Subjective methods– from within firm

• User Expectation methods– from outside the firm

• Statistical Methods– extrapolation

• Modeling methods

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User Expectation Methods

• Customers asked to forecast needs– Availability of gravel

• Pilot trials– test demand in one location– Alyeska tests of trenching in permafrost

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Statistical

• Time series

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Subjective Methods

• Jury of Executive Opinion– meeting of in-house experts

• Delphi Method– Aims to remove domineering effect of senior

company officials– Three rounds

• 1st anonymous• 2d knows results of first, but not authors• 3d discussion following 2d round

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Extrapolation

• From time series

• (See next)

• Various methods of extrapolation

• All based on past data

• Which is likely to change in future

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Known data

Extrapolated data

from Rose, 1976

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Some terms

• Precision

• Accuracy

• Biased

• Precise estimate

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Accurate, not precise

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Precise, not Accurate

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Precise, not Accurate

Bias (left)

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Experts

• Feedback– Jury– Delphi– Etc.

• Get parameters

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“Precise Estimate”

• Use the best number(s) you have.

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Other Precise

• Breakeven• Sensitivity• Examine the impact that variability will

have

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Problems

• Problems (or events) => Decisions

• Kinds of problems– Simple

• Cash or credit card

– Intermediate• Buy or lease equipment

– Complex• Open a new plant in New Jersey or Alabama

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The Decision Process

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Rational Decision Making

• Recognition of problem

• Definition of goal• Assembly of data• Select criteria• Interrelationship

– objective– alternatives– data– criteria

• Predict outcomes• Choice of best

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Recognition of Problem

Define the problem area, carefully and completely determine all uncontrollable conditions (random events) inherent in the situation.

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Define Goal or Objective

• A problem is something that prevents us from achieving our goal

• Determine the objective(s) to be achieved and how attainment of the objectives is to be measured.

• But what is the objective?

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Assembly of Data

• Accounting Data• Cost• Benefits• Difficulties

– Allocation of Overhead– non-market consequences (shadow prices)– Intangibles

• Define precisely all alternative actions that can be taken, and calculate the payoff (degree of attainment of objectives) in each case.

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Identify Feasible Alternatives

• Do nothing

• Brainstorming

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Select Criteria

• Non-profits

• Time

• Use money most efficiently– Fixed input– Fixed output– Neither fixed

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Model Interrelationships

• Select and apply a decision criterion (rule) which orders the alternatives and defines which one is the best or optimum alternative.

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Model Interrelationships

• Room Capacity = (l * w )/ k

• k is factor based on seating– k = 0.5 for expensive fixed seats– k = 0.7 for cheap movable seats

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Numeric Models: Scoring

• Unweighted 0-1 Factor Model

• Unweighted Factor Scoring Model

• Weighted Factor Scoring Model

• Constrained Weighted Factor Scoring Model

• Goal Programming with Multiple Objectives

Chapter 2-6

Page 55: Risk Management for Construction Dr. Robert A. Perkins, PE Civil and Environmental Engineering University of Alaska Fairbanks.

Numeric PS Models:Scoring

• Unweighted 0-1 Factor Model

• Unweighted Factor Scoring Model

• Weighted Factor Scoring Model

• Constrained Weighted Factor Scoring Model (c=0 or 1)

• S = ∑(x)

• S = ∑(s)

• S = ∑(s·w)

• S = ∑(s·w) ∏(c)

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Predict Outcomes

• From model

• Arrange in orderly way

• Resolve consequences– market– extra-market

• State intangibles

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Choose Best

• Using all relevant experience and judgment, make a choice from among the alternatives.

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Home Fire Insurance

• House cost $150,000

• full insurance cost $1400/yr

• p of fire 0.004/year

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More on Models

• Idealized view of reality

• Representing the STRUCTURE of the problem, not the detail

• Deterministic or stochastic

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Caveats

• Project decisions are made by Project Manager --- NOT by models!

• A model APPROXIMATES, but does NOT DUPLICATE reality!

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Types of Models:Nonnumeric

• Sacred Cow• Operating Necessity• Competitive Necessity• Product Line

Extension• Comparative Benefit

Model

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Choosing the Model

• Dependent on wishes and philosophy of management

• 80% of Fortune 500 firms choose “nonnumeric” models

• Firms with outside funding often chose scoring models

• Firms without outside funding often chose profit / profitability models

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Risk in Construction

• All the risks belong to who?

• Unless

• Which party should bear risk?

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Risk management

• Minimizing risks – regardless of whose risk it is

• Equitable sharing of risks among the various project partners.

• Contrast with Risk Assessment

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• The parties must be prepared to discuss and decide on the following issues:

• What are the levels of risk are realistic to assume?

• Who can best assume each risk?

• What levels and kinds of risks are properly and most economically passed on to insurance carriers?

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Fisk’s Categories of risk

• Construction-related risks– Crane failure

• Physical risks (subsurface conditions)– Differing site conditions

• Contractual and legal risks– Law suits

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• Performance risks– Project does not meet expectations

• Economic risks– Loose money or cost overruns

• Political and public risks– Lots

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Exculpatory Clauses

• Seek to reduce risk with contract language

• Limitation thereof