Research Presentation RISK INTELLIGENCE: AN INTRODUCTION INTO THE PROJECT AND CONSTRUCTION RISK MANAGEMENT

Transcription

1 Research Presentation RISK INTELLIGENCE: AN INTRODUCTION INTO THE PROJECT AND CONSTRUCTION RISK MANAGEMENT WILLIAM A. BANKS, JR., MSCM AACEI HOUSTON GULF COAST CHAPTER APRIL 2, WILLIAM BANKS

2 Introduction Why Risk Intelligence Topic Objective, Scope & Research Methodology Risk Intelligence Concepts/Risk Management Comparisons AGENDA Hypothetical Case Study RQ Hypothetical Case Study IQ What is next for Risk Intelligence? Risk Intelligence - Contribution Conclusion Q&A 2

3 INTRODUCTION Graduated From University of Houston B.A. Political Science, Minor In Business Administration (23) Between Fall enrolled in Post-Baccalaureate, Math and CM courses M.S. Construction Management (25) Currently Employed by Bechtel Oil Gas & Chemical, Inc. (2 To Present) 5 Years Project Controls And Oil, Gas And Chemical Experience Estimating (4.5), Cost Engineering (.5), Planning And Scheduling (9) Schedule Risk Analysis (5) Previous Experience Banks Total Contracting Services Jack of all trades (Estimating, Laborer, Accounting, Drywall, Painting, etc). 3

4 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 workshop hosted back in March 24 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. 4

5 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? 5

6 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. 6

7 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. 7

8 METHODOLOGY LITERATURE REVIEW DATABASE Full Comprehensive and Intensive Literature Based Review Searched through 6 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) 8

9 METHODOLOGY - REVIEW IMPORTANCE & FOUNDATION Cornerstone books and journal article of research. 9

10 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?

11 METHODOLOGY OVERVIEW Literature Review Research Journal Database Risk Intelligence (R.I.) (variations of) Research Importance/Foundation Cornerstone Research Synthesize Information Concepts /Themes History Benefits Limitations Groups of thoughts Groups of Applications Groups of Trends Latest Developments Concept and Themes Additional Methods/Feedback Draft and Final Project/Research Complete Unifying R.I. concepts and applications to construction risk management Questionnaire/ Constructive Feedback Review an Incorporate and Refine Implementation/Case Study (Non-Tested) Suggested Implementation of Concepts and Case Study

12 WHAT IS RISK INTELLIGENCE? What is Risk Intelligence? an individual s or an organization[s] ability to weigh risks effectively (Apgar 26). 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 2). ability to estimate probabilities accurately (Evans 22). ability to think holistically about risk and uncertainty [to] effectively use forward-looking risk tools in making better decisions (Tilman 23). 2

13 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. Skills (noted as FF on Overview Slide) Dylan Evans, Risk Intelligence How To Live With Uncertainty (noted as DE on Overview Slide). Five Cognitive abilities that decrease Risk Intelligence 2. Risk Intelligence Quiz (Risk Quotient or RQ (Risk Aptitude)) 3

14 RISK INTELLIGENCE CONCEPTS David Apgar, Risk Intelligence Learning to Manage What We Don t Know.. 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.

15 RISK INTELLIGENCE CONCEPTS Fredrick Funston and Stephen Wagner, Risk Intelligence Surviving and Thriving in Uncertainty Risk Management Enterprise.. 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. Sustain Operational Discipline

16 RISK INTELLIGENCE CONCEPTS Dylan Evans, Risk Intelligence How To Live With Uncertainty. 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

17 RISK INTELLIGENCE CONCEPTS Dylan Evans, Risk Intelligence How To Live With Uncertainty 4. Risk Intelligence Quiz (Risk Quotient or RQ) 5 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 %, 5%, % give a scores of zero, while all others are a score of Yielding a maximum K factor of 5. 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.

18 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).

19 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 Current Practice Risk Intelligence Practice Risk Identification Checklist (historical) Assumption Analysis (current assessment Brainstorming (creativity) Uncertainty Bias Broad Range of Stakeholders for Risk input Identify Trigger Conditions 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 Analysis (Assessment (Qualitative/ Quantitative), Measurement) Risk Work shops Interview process Estimating techniques Historical information Probability-Impact Matrix Monte Carlo simulation (use for probabilistic) 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) Risk Response (Management, Mitigation) Communicate Roles/Responsibilities Response timing Response Strategies (avoid, transfer, mitigate, accept) Document Responses 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) Risk Review (Monitor, Report) Monitor triggers Risk Awareness Manage Contingencies Sequence risky projects in a learning pipeline (DA) Maintain constant vigilance (FF) Anticipate causes and failures (FF) Sustain Operational Discipline (FF) 9

20 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 Current Practice Risk Intelligence Practice 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 Interview process Roles/Responsibilities Risk Awareness assessment Brainstorming (creativity) Estimating techniques Response timing Manage Contingencies Uncertainty Bias Response Strategies (avoid, Historical information transfer, mitigate, accept) Broad Range of Stakeholders Probability-Impact Matrix Document Responses for Risk input 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 Take enough of the right risks Anticipate causes and fastest (Risk IQ)/Risk Triage Cognitive Short Cuts (DE) (FF) failures (FF) (DA) 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) Sequence risky projects in a learning pipeline (DA) Sustain Operational Discipline (FF) Legend: DA = David Apgar; FF = Fredrick Funston; DE = Dylan Evans 2

21 METHODOLOGY - CONCEPTS AND THEMES Macro Overview Focus on the following concepts Risk Intelligence Concepts Current Practice Risk Intelligence Practice 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 Interview process Roles/Responsibilities Risk Awareness assessment Brainstorming (creativity) Estimating techniques Response timing Manage Contingencies Uncertainty Bias Response Strategies (avoid, Historical information transfer, mitigate, accept) Broad Range of Stakeholders Probability-Impact Matrix Document Responses for Risk input 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 Take enough of the right risks Anticipate causes and the fastest (Risk IQ)/Risk Cognitive Short Cuts (DE) (FF) failures (FF) Triage (DA) 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) Sequence risky projects in a learning pipeline (DA) Sustain Operational Discipline (FF) Legend: DA = David Apgar; FF = Fredrick Funston; DE = Dylan Evans 2

22 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. 22

23 HYPOTHETICAL CASE STUDY RISK APTITUDE QUIZ EXAMPLE - RQ K Factor Scoring > Question No. Question Answer 9 Early planning can increase schedule, decrease cost and help with productivity T The rule of thumb of time for compressive strength or curing time is at 5 calendar days. F Over vibration of concete increases the chances of elimnating voids while curing in the 5 formwork. F 2 Common joining of steel members are by rivets, bolts and welds. T 22 Slenderness ratio is the allowable compressive load or unit stress for a column. T 33 A pipe silverweld is weld that does not require an pressure test. F 38 Piping insulation is installed prior to the joining of two pipe spools. F 4 Two popular methods of pipe leak testing area hydrostatic and pneumatic. T 45 All piping insulation must be installed prior to hydrotesting. F Total % % 2% 3% 4% 5% 6% 7% 8% 9% % K Check Field 5 36 Risk Assessor is absolutely sure that a statement is true; enter a in the % category Risk Assessor is completely convinced that a statement is false; enter a in the % category. Risk Assessor has no idea at all whether the statement is true or false; enter a in the 5% category. Risk Assessor is fairly sure that the statement is true, but is not completely sure; enter a in the 6%, or 7%, or 8%, or 9%, categories, depending on the certainty. Risk Assessor is fairly sure that the statement is false, but is not completely sure; enter a in the 4%, or 3%, or 2%, or %, categories, depending on the certainty. Risk Aptitude (RQ) worksheet 23

24 HYPOTHETICAL CASE STUDY RISK APTITUDE WORKSHEET - RQ CRQ Category ERQ TRQ PTRQ RRQ Estimates TRUE Percent True Residuals T R b c a TOTAL 5 26 WEIGHTED MEAN RQ SCORE K Factor Low RQ Underconfident Score Low RQ Overfident Score High RQ Underconfident Score High RQ Overfident Score d=(c/b)* Calibration Curves e=d a 6 4 () (2) () (5) (75) DRRQ DRERQ R ( R) x (Estimates) f = e g=f x b LRQ HRQ Low RQ High RQ ORQ URQ Overconfident Underconfident h=if(abs(e) i=if(abs(e)< >,,) =,,) j==if(e>,,) k==if(e<,,) 5 Primavera Risk Analysis Monte Carlo Simulation software 24

25 HYPOTHETICAL CASE STUDY CALIBRATION CURVES - RQ "Calibration Curves " ProNo. of statements marked True Percentile Category The next slide shows the example using Primavera Risk Analysis Monte Carlo Simulation software 25

26 HYPOTHETICAL CASE STUDY MONTE CARLO EXAMPLE - RQ 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 26

27 HYPOTHETICAL CASE STUDY MONTE CARLO EXAMPLE - RQ 27

28 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. 28

29 HYPOTHETICAL CASE STUDY RISK IQ QUIZ EXAMPLE - IQ RISK IQ IDENTIFIED RISK NAME: Enter the name of the risk either identified from the risk register or risk analysis workshop for cost and schedule risk analysis data collection PROBABILITY OF Express as a percentage OCCURRENCE Express in days minimum and a maximum SEVRITY IMPACT impact QUESTION NO. 2 QUESTIONS SCORE RANKING JUSTIFICATION. 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. If you know very little about the risk enter. Evaluating the "range of implications" for different possibility of factors. Does the current expereince level aide in elminating non value added or noise. How relevant are the experiences to what factors and focuses on the value added factors? might influence the risk? Answer is a "yes ", enter 2. Answer is a maybe enter. Answer is a "no" enter. 3. How surprising are these experiences? 4. How diverse are these experiences as sources of information? 5. How methodically do you keep track of what you learn from them? The improbability of experiences. The rank of scoring is a 2,, based on whether you suspect your typical experiences are unearthing more unexpected or improbabe news than those of others. 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,. 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. RISK IQ RAW SCORE RISK IQ SCORE TOTAL QUESTION SCORE SCORE CHOICES 2 2,, 2,, 2,, 2,, 2 2,, 6 6% 5 Risk Register 29

30 HYPOTHETICAL CASE STUDY RISK REGISTER EXAMPLE- IQ Schedule Impact Adjustments : Percentage used to adjust the severity = % - 6% = 4%. Severity Min = 2d x.4 = 8d 2d 8d = 2d Severity Max = 4d x.4 = 6d 4d 6d = 24d 3

31 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. 3

32 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. 32

33 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 33

34 QUESTIONS & ANSWERS 34