RISK INTELLIGENCE:AN INTRODUCTION INTO THE PROJECT AND

CONSTRUCTION RISK MANAGEMENT

Research Presentation

WILLIAM A . BANKS, JR. , MSCMA ACEI – HOUSTON GULF COAST CHAPTER

APRIL 12, 2016© 2016 WILLIAM BANKS

AGENDA•Introduction

•Why Risk Intelligence Topic

•Objective, Scope & Research Methodology

•Risk Intelligence Concepts/Risk Management Comparisons

•Hypothetical Case Study – RQ

•Hypothetical Case Study – IQ

•What is next for Risk Intelligence?

•Risk Intelligence - Contribution

•Conclusion

•Q&A

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INTRODUCTION• Graduated From University of HoustonB.A. Political Science, Minor In Business Administration (2003)Between Fall 2003 – 2009 enrolled in Post-Baccalaureate, Math and CM courses

M.S. Construction Management (2015)

•Currently Employed by Bechtel Oil Gas & Chemical, Inc. (2000 To Present)15 Years Project Controls And Oil, Gas And Chemical ExperienceEstimating (4.5), Cost Engineering (1.5), Planning And Scheduling (9)

Schedule Risk Analysis (5)

•Previous Experience – Banks Total Contracting ServicesJack of all trades (Estimating, Laborer, Accounting, Drywall, Painting, etc).

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WHY RISK INTELLIGENCE TOPIC?

Why RISK INTELLIGENCE?

• This is personal.

• Participation in multiple schedule risk analyses there always seemed to be something lacking in the process of

obtaining accurate duration uncertainties (i.e. 3 point estimates), risk events and just sharing of knowledge.

• Where did the idea for this research originate?

• Attended a Project Controls 101 workshop hosted back in March 2014 by the Houston Gulf Coast Chapter of the

Association for the Advancement of Cost Engineering International (AACEI).

• Risk Management and Risk Intelligence presentation by James Arrow.

.

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WHY RISK INTELLIGENCE TOPIC?•Information collected for use with duration uncertainty (i.e. three point

estimates), risk event probabilistic and impacts can be subjective and based on subject matter experts biased opinions.

•Why and how this a problem?•Why?:A lack a certain risk intelligence that could provide inaccurate

data points which would skew the final risk analysis results.

•How?: Opinions can be “based on a feeling” and not reality. How do you validate that person's ability to assess risks?

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OBJECTIVE, SCOPE & RESEARCH METHODOLOGY•Serve as an introduction of risk intelligence concepts into the

project and construction industry.

•Using the idea of Risk RQ (Aptitude) & Risk IQ to demonstrate its applicability in duration uncertain estimates and risk register events.

•Open the door to possibly future research development, case studies etc. that would refine/supplement the concepts in the project risk management process.

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OBJECTIVE, SCOPE & RESEARCH METHODOLOGY•Comprehensive and detailed literature review with hypothetical case

study to demonstrate potential use.

•Literature review results•No previous research in the Project & Construction Risk Management

• Relates only to general business and financial risk management.

•No specific results in the area of cost and schedule risk analysis, as related to the Critical Path Methodology (CPM), risk events, etc.

•Three major and some supplementary works on the general topic of Risk Intelligence.

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METHODOLOGY – LITERATURE REVIEW DATABASE•Full Comprehensive and Intensive Literature Based Review

•Searched through 16 different journal databases• Notable ones: ASCE, AACEI, PMI, Google Scholar, UH Journal data

base.

•Results: • 32 Journal Articles

• 6 Relevant Books

• 27 Recommended/Best Practice (AACEI)/Standards (PMI)

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METHODOLOGY - REVIEW IMPORTANCE & FOUNDATION•Cornerstone books and journal article of research.

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METHODOLOGY – SYNTHESIZE INFORMATION• Establishing the “ connection” points between Risk Intelligence concepts, risk

management articles and industry practice:• How this would be beneficial to the industry?

• How could the concepts “fit” in the current industry risk management and analysis practice?

• How to apply the concepts for ease in understanding and its applicability?

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Implementation/Case Study (Non-Tested)

Draft and Final Project/Research Complete

Additional Methods/Feedback

Concept and Themes

Synthesize Information

Research Importance/Foundation

Literature Review Research – Journal Database Risk Intelligence (R.I.) (variations of)

Cornerstone Research

Concepts/Themes History Benefits Limitations Groups of

thoughts

Unifying R.I. concepts and applications to construction

risk management

Questionnaire/ Constructive

Feedback

Review an Incorporate and

Refine

Suggested Implementation of Concepts and Case Study

Groups of Applications

Groups of Trends

Latest Developments

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METHODOLOGY – OVERVIEW

WHAT IS RISK INTELLIGENCE?• What is Risk Intelligence?

• “…an individual’s or an organization[s] ability to weigh risks effectively (Apgar 2006).”

• “…awareness of risk at all levels… [to]…generate a rationalized approach to identifying, discussing, measuring and managing all the vital opportunities and risks the enterprise faces (Funston 2010).”

• “…ability to estimate probabilities accurately (Evans 2012).”

• “…ability to think holistically about risk and uncertainty…[to]…effectively use forward-looking risk…tools in making better decisions…(Tilman 2013).”

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RISK INTELLIGENCE CONCEPTS• Risk Intelligence Concepts – Summary

• David Apgar, “Risk Intelligence – Learning to Manage What We Don’t Know.”• Four Steps (noted as DA on Overview Slide)

• Includes the Risk IQ Quiz

• Fredrick Funston and Stephen Wagner , “Risk Intelligence – Surviving and Thriving in Uncertainty – Risk Management Enterprise.”

• 10 Skills (noted as FF on Overview Slide)

• Dylan Evans, “Risk Intelligence – How To Live With Uncertainty• (noted as DE on Overview Slide)

1. Five Cognitive abilities that decrease Risk Intelligence

2. Risk Intelligence Quiz (Risk Quotient or RQ (Risk Aptitude))

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RISK INTELLIGENCE CONCEPTS

• David Apgar, “Risk Intelligence – Learning to Manage What We Don’t Know.”

1. Recognize which risks are learnable

2. Identify risks you can learn about the fastest

3. Sequence risky projects in a "learning pipeline"

4. Keep networks of partners to manage all risks.

RISK INTELLIGENCE CONCEPTS• Fredrick Funston and Stephen Wagner , “Risk Intelligence – Surviving and Thriving

in Uncertainty – Risk Management Enterprise.”1. Check Your Assumptions at the Door

2. Maintain Constant Vigilance

3. Factor in Velocity and Momentum

4. Manage the Key Connections

5. Anticipate Causes of Failure

6. Verify Sources and Corroborate Information

7. Maintain a Margin of Safety

8. Set Your Enterprise Time Horizons

9. Take Enough of the Right Risks

10. Sustain Operational Discipline

RISK INTELLIGENCE CONCEPTS• Dylan Evans, “Risk Intelligence – How To Live With Uncertainty

1. Cognitive Capacity of Individual Brains

2. Key to Risk Intelligence is how much a person knows about something and judging the truth or falsehood of given statements (from a risk intelligence quiz).

3. Cognitive abilities that decrease Risk Intelligence• Availability Heuristics

• Wishful Thinking

• Confirmation Bias

• Ambiguity and Uncertainty Intolerance

• Hindsight Bias

RISK INTELLIGENCE CONCEPTS• Dylan Evans, “Risk Intelligence – How To Live With Uncertainty

4. Risk Intelligence Quiz (Risk Quotient or RQ)• 50 statement questionnaire that measures how much a person knows about something and judging

the truth or falsehood of a given statement. • Identifies the confidence of one's ability to accurately make probabilistic assessments by measuring

their risk intelligence quotient• An indicator that measures the over or under confidence are the calibration curves. It counts the

number of statements that were true, a score of zero equates to a high RQ. • Uses a percentage scoring

• 0%, 50%, 100% give a scores of zero, while all others are a score of 1

• Yielding a maximum K factor of 50.

• The “K” factor is the indication in how the person attempted to evaluate the truth of the statements. An indicator that measures the over or under confidence are the calibration curves. It counts the number of statements that were true, a score of zero equates to a high RQ.

RISK MANAGEMENT STEPS• Introduction of Risk Intelligence - Project and Construction Risk Intelligence

• Review of the Risk Management Steps (taken from “Managing Risks in Construction Management by Nigel Smith)

• Risk Identification,

• Risk Analysis (Assessment (Qualitative or Quantitative), Measurement),

• Risk Response (Management, Mitigation)

• Risk Review (Monitor, Report).

METHODOLOGY - CONCEPTS AND THEMES• Macro Overview – Risk Intelligence application in the Project and Construction Risk

Management process (Current vs Risk Intelligence Practice)Risk

Intelligence Concepts

Risk Identification Risk Analysis (Assessment (Qualitative/ Quantitative),

Measurement)

Risk Response (Management, Mitigation)

Risk Review (Monitor, Report)

Current Practice

• Checklist (historical)• Assumption Analysis

(current assessment• Brainstorming (creativity)• Uncertainty Bias• Broad Range of

Stakeholders for Risk input• Identify Trigger Conditions

• Risk Work shops• Interview process• Estimating techniques• Historical information• Probability-Impact Matrix• Monte Carlo simulation (use

for probabilistic)

• Communicate• Roles/Responsibilities• Response timing• Response Strategies (avoid,

transfer, mitigate, accept)• Document Responses

• Monitor triggers• Risk Awareness• Manage

Contingencies

Risk Intelligence Practice

• Recognize which risks are learnable (DA)

• Which risks one can learn the fastest (Risk IQ) (DA)

• Risk Triage• Verify and corroborate

information (FF)• Sustain Operational

Discipline (FF)

• Risk Intelligence quiz (RQ)• K-Factor (DE)• Cognitive Short Cuts (DE)• Maintain a margin of safety

(FF)• Set your enterprise time

horizons.(FF)• Risk Intelligence Quiz and

risk triage (Risk IQ) (DA)• Sustain Operational

Discipline (FF)

• Keep network of partners to manage all risks (DA)

• Sequence risky projects in a learning pipeline (DA)

• Factor in velocity and momentum (FF)

• Manage key connections (FF)• Take enough of the right risks

(FF)• Sustain Operational Discipline

(FF)

• Sequence riskyprojects in a learning pipeline (DA)

• Maintain constant vigilance (FF)

• Anticipate causes and failures (FF)

• Sustain Operational Discipline (FF)

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METHODOLOGY - CONCEPTS AND THEMES• Macro Overview – Risk Intelligence application in the Project and Construction Risk Management

process (Current vs Risk Intelligence Practice)

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Risk Intelligence Concepts

Risk Identification Risk Analysis (Assessment (Qualitative/ Quantitative),

Measurement)

Risk Response (Management, Mitigation)

Risk Review (Monitor, Report)

•Checklist (historical) •Risk Work shops •Communicate •Monitor triggers•Assumption Analysis (current assessment

•Interview process •Roles/Responsibilities •Risk Awareness

•Brainstorming (creativity) •Estimating techniques •Response timing •Manage Contingencies

•Uncertainty Bias •Historical information •Response Strategies (avoid, transfer, mitigate, accept)

•Broad Range of Stakeholders for Risk input

•Probability-Impact Matrix •Document Responses

•Identify Trigger Conditions•Monte Carlo simulation (use for probabilistic)

•Recognize which risks are learnable (DA)

•Risk Intelligence quiz (RQ)•K-Factor (DE)

•Keep network of partners to manage all risks (DA)

•Maintain constant vigilance (FF)

•Which risks one can learn the fastest (Risk IQ)/Risk Triage (DA)

•Cognitive Short Cuts (DE)•Take enough of the right risks (FF)

•Anticipate causes and failures (FF)

•Verify and corroborate information (FF)

•Maintain a margin of safety (FF) •Factor in velocity and momentum (FF)

•Set your enterprise time horizons.(FF)

•Manage key connections (FF)

•Risk Intelligence Quiz and risk triage (Risk IQ) (DA)

Current Practice

Risk Intelligence

Practice

•Sequence risky projects in a learning pipeline (DA)

•Sustain Operational Discipline (FF)

Legend: DA = David Apgar; FF = Fredrick Funston; DE = Dylan Evans

METHODOLOGY - CONCEPTS AND THEMES• Macro Overview – Focus on the following concepts

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Risk Intelligence Concepts

Risk Identification Risk Analysis (Assessment (Qualitative/ Quantitative),

Measurement)

Risk Response (Management, Mitigation)

Risk Review (Monitor, Report)

•Checklist (historical) •Risk Work shops •Communicate •Monitor triggers•Assumption Analysis (current assessment

•Interview process •Roles/Responsibilities •Risk Awareness

•Brainstorming (creativity) •Estimating techniques •Response timing •Manage Contingencies

•Uncertainty Bias •Historical information •Response Strategies (avoid, transfer, mitigate, accept)

•Broad Range of Stakeholders for Risk input

•Probability-Impact Matrix •Document Responses

•Identify Trigger Conditions•Monte Carlo simulation (use for probabilistic)

•Recognize which risks are learnable (DA)

•Risk Intelligence quiz (RQ)•K-Factor (DE)

•Keep network of partners to manage all risks (DA)

•Maintain constant vigilance (FF)

•Which risks one can learn the fastest (Risk IQ)/Risk Triage (DA)

•Cognitive Short Cuts (DE)•Take enough of the right risks (FF)

•Anticipate causes and failures (FF)

•Verify and corroborate information (FF)

•Maintain a margin of safety (FF) •Factor in velocity and momentum (FF)

•Set your enterprise time horizons.(FF)

•Manage key connections (FF)

•Risk Intelligence Quiz and risk triage (Risk IQ) (DA)

Current Practice

Risk Intelligence

Practice

•Sequence risky projects in a learning pipeline (DA)

•Sustain Operational Discipline (FF)

Legend: DA = David Apgar; FF = Fredrick Funston; DE = Dylan Evans

RISK INTELLIGENCE – HYPOTHETICAL CASE STUDY (RQ)• Risk Aptitude (RQ) and Duration Uncertainty – Hypothetical Case Study

• Assume SME has provided duration uncertainties• In form of three point estimates - optimistic, most likely or pessimistic in dollars (cost) unit of time

(schedule) or percentages of each.

• Assume the Risk Intelligence Quiz is filled out and calculated.

• Separate Risk Aptitude (RQ) worksheet will categorize and calculate the necessary scores.

• Calibration Curves used to visual see the Over and Under confident levels.

• Based on the results of the RQ, this could aide in what “numbers” apply for the Monte Carlo simulation

• If there is a Low RQ score – Under confident – Decrease the optimistic and pessimistic durations by using the percentage score as a factor

• If there is a Low RQ score – Over confident – Increase the optimistic and pessimistic durations by using the percentage score as a factor.

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HYPOTHETICAL CASE STUDY – RISK APTITUDE QUIZ EXAMPLE - RQ

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• Risk Aptitude (RQ) worksheet

Risk Assessor is absolutely sure that a statement is true; enter a “1” in the 100% category Risk Assessor is completely convinced that a statement is false; enter a “1” in the 0% category. Risk Assessor has no idea at all whether the statement is true or false; enter a “1” in the 50% category. Risk Assessor is fairly sure that the statement is true, but is not completely sure; enter a “1” in the 60%,

or 70%, or 80%, or 90%, categories, depending on the certainty. Risk Assessor is fairly sure that the statement is false, but is not completely sure; enter a “1” in the 40%,

or 30%, or 20%, or 10%, categories, depending on the certainty.

K‐Factor Scoring‐‐‐> 0 1 1 1 1 0 1 1 1 1 0 K0 10 20 30 40 50 60 70 80 90 100 Check

Question No. Question Answer 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Field9 Early planning can increase schedule, decrease cost and help with productivity T 1 1 1

11The rule of thumb of time for compressive strength or curing time is at 15 calendar days.  F 1 1 0

15Over vibration of concete increases the chances of elimnating voids while curing in the formwork. F 1 1 1

21 Common joining of steel members are by rivets, bolts and welds. T 1 1 122 Slenderness ratio is the allowable compressive load or unit stress for a column. T 1 1 033 A pipe silverweld is weld that does not require an pressure test. F 1 1 038 Piping insulation is installed prior to the joining of two pipe spools. F 1 1 141 Two popular methods of pipe leak testing area hydrostatic and pneumatic. T 1 1 145 All piping insulation must be installed prior to hydrotesting. F 1 1 0

Total 5 5 5 5 5 5 4 4 4 4 4 50 36

HYPOTHETICAL CASE STUDY –RISK APTITUDE WORKSHEET - RQ

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• Calibration Curves

CRQ ERQ TRQ PTRQ RRQ DRRQ DRERQ LRQ HRQ ORQ URQ

Category Estimates TRUE Percent True Residuals 100 ‐ R (100‐R) x (Estimates) Low RQ High RQ Overconfident UnderconfidentT R 100

a b c d=(c/b)*100 e=d‐a f = 100 ‐ e g=f x bh=IF(ABS(e)>10,1,0)

i=IF(ABS(e)<=10,1,0) j==IF(e>0,1,0) k==IF(e<0,1,0)

0 5 3 60 60 40             200 1 0 1 010 5 1 20 10 90             450 0 1 1 020 5 3 60 40 60             300 1 0 1 030 5 1 20 (10) 110           550 0 1 0 140 5 1 20 (20) 120           600 1 0 0 150 5 2 40 (10) 110           550 0 1 0 160 4 3 75 15 85             340 1 0 1 070 4 4 100 30 70             280 1 0 1 080 4 4 100 20 80             320 1 0 1 090 4 3 75 (15) 115           460 1 0 0 1100 4 1 25 (75) 175           700 1 0 0 1

TOTAL 50 26 4750 8 3 6 5WEIGHTED MEAN 95

RQ SCORE 90K‐Factor 72

Low RQ ‐ Underconfident Score 26Low RQ ‐ Overfident Score 28High RQ ‐ Underconfident Score 16High RQ ‐ Overfident Score 18

Primavera Risk Analysis – Monte Carlo Simulation software

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60

20

60

20 20

40

75

100 100

75

25

0

10

20

30

40

50

60

70

80

90

100

110

0 10 20 30 40 50 60 70 80 90 100

ProN

o. of statements m

arked True

Percentile Category

"Calibration Curves "

HYPOTHETICAL CASE STUDY – CALIBRATION CURVES - RQ

• The next slide shows the example using Primavera Risk Analysis – Monte Carlo Simulation software

HYPOTHETICAL CASE STUDY – MONTE CARLO EXAMPLE - RQ

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• Risk Aptitude (RQ) and Duration Uncertainty – Hypothetical Case Study• Below is a set of activities with original duration uncertainty estimates provided by SME

• The RQ score showed the SME had a LowRQ score and was Overconfident (Risk Aptitude (RQ) worksheet )

• Apply the adjustment to the duration uncertainty• Same formula applied to pessimistic estimate

• Below is a set of activities with based on the Risk Aptitude RQ adjustment

HYPOTHETICAL CASE STUDY – MONTE CARLO EXAMPLE - RQ

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RISK INTELLIGENCE – HYPOTHETICAL CASE STUDY - IQ• Risk IQ -

• Assume SME has completed the Risk IQ Worksheet

• Assume the Risk IQ Worksheet is filled out and calculated.

• Assume Project Team has provided risk event probability of occurrence and severity of impact based on original assessments.

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HYPOTHETICAL CASE STUDY– RISK IQ QUIZ EXAMPLE - IQ

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RISK IQ

IDENTIFIED RISK NAME:

PROBABILITY OF OCCURRENCE

Express as a percentage

SEVRITY IMPACTExpress in days ‐ minimum and a maximum impact

QUESTION NO. QUESTIONS SCORE RANKING JUSTIFICATION SCORESCORE CHOICES

11. How often do you have experiences related to the risk (i.e. exposure to the risk)?

If you are learning everything about the risk, enter 2.If you have historical information or some knowledge about the risk, enter 1.If you know very little about the risk enter 0.

2 2,1,0

21. How relevant are the experiences to what might influence the risk?

Evaluating the "range of implications" for different possibility of factors.   Does the current expereince level aide in elminating non‐value added or noise factors and focuses on the value added factors?Answer is a "yes ", enter 2.Answer is a maybe enter 1.Answer is a "no" enter 0.

1 2,1,0

3 1. How surprising are these experiences?The improbability of  experiences.The rank of scoring is a 2,1,0 based on whether you suspect your typical experiences are unearthing more unexpected or improbabe news than those of others.

0 2,1,0

41. How diverse are these experiences as sources of information?

Do you keep up with information (learning) about the risks from previous encounters, projects, news, etc. This ranks how you compare to others, ranking a score of 2,1 0.

1 2,1,0

51. How methodically do you keep track of what you learn from them?

How often are you recording what is being learned? In others words, not just from the companies learnings, but learning from other companies, articles, news, etc. Tracking what failed and what succeeded in controlling the risks. 

2 2,1,0

RISK IQ RAW SCORE 6RISK IQ SCORE 60%

TOTAL QUESTION 5

Enter the name of the risk either identified from the risk register or risk analysis workshop for cost and schedule risk analysis data collection

• Risk Register

HYPOTHETICAL CASE STUDY– RISK REGISTER EXAMPLE- IQ

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Schedule Impact Adjustments :Percentage used to adjust the severity = 100% - 60% = 40%.

Severity Min = 20d x .40 = 8d20d – 8d = 12d

Severity Max = 40d x .40 = 16d40d – 16d = 24d

WHAT IS NEXT FOR RISK INTELLIGENCE• Industry Practice and Academic Contribution (Any Graduate students in the room ??)

• Since this research served as a “plant the seed” introduction, some ideas below for future endeavors

• Development of a Risk Intelligence quiz, as it pertains to the particular industry (i.e. Commercial, Residential, Oil and Gas, General, etc.)

• Further refinement to the application of the Risk Intelligence IQ score and how it is applied to duration uncertainties.

• After using the adjustments to duration uncertainty follow a project to validate the accuracy of following risk intelligence concepts and its use with duration uncertainty.

• Develop a mass survey that discusses the concepts of risk intelligence to find out more if the industry is aware of the principles and if they are, which companies are attempting to practice them.

• Further refinement of risk intelligence as presented today and application into the industry.

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RISK INTELLIGENCE - CONTRIBUTION•Provide a different approach in gathering and validating cost and

schedule risk analysis data when running simulations.

•Attempt to further increase the importance of always “thinking risk.”

•Identify individual gaps and how to increase risk assessment confidence levels.

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CONCLUSION

•Introduced Risk Intelligence concepts into Project and Construction Risk Management process.

•Overview of the current and risk intelligence practices and how they relate to the overall risk management process.

•Provided hypothetical case studies that demonstrated the use of RQ, duration uncertainty, evaluation of the risk assessor confidence level and Risk IQ and the risk register

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QUESTIONS & ANSWERS

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