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l16diagnsprjctrl - Problem Diagnosis& Introduction to...

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Unformatted text preview: Problem Diagnosis & Introduction to Project Dynamics 1.040/1.401J Nathaniel Osgood 4/13/2004 Topics Problem Diagnosis Pareto Analysis Fishbone Diagram Scatterplots Systems Thinking and System Dynamics Causal Loop Diagrams System Dynamics Insights into Causes of Problems Discussed Last Time : Exploratory Analysis Pareto Analysis Fishbone Diagram Scatter Diagram Causal Loop Diagram Pareto Analysis Correctly addressing a small portion of project components can provide control over the remaining project components. Help identify the contributors to given types of performance, mostly cost and quality performance. Group A: a small portion of the major cost components that account for a significant portion of the total cost Group B: all cost component other than Group A and C components Group C: a large portion of the minor cost components that account for a trivial portion of the total cost Pareto Analysis Example: Drivers of Quality Problems in Building Construction Workers Rebar workers Concrete workers Carpenters Mortar workers Frequency 10 15 20 5 Topics Problem Diagnosis Pareto Analysis Fishbone Diagram Scatterplots Systems Thinking and System Dynamics Causal Loop Diagrams System Dynamics Fishbone ("Cause and Effect") Diagram Help identify the drivers of given performance problems, by providing a format with which managers can easily understand cause and effect relationships. The causes for a given performance problem are analyzed by initially defining the problem and then channelling possible causal relations on the defined problem into predetermined (proj.-specfic)categories Subcauses shown as progressively refined branches Fishbone Diagram Example: Delay in concrete pouring Controllable Causes Workers Lack of Experience Hiring Temporary Workers Low Productivity Use of Inefficient Concrete Pump Late Arrival of Concrete Pump on the 1st Day Equipment Schedule Delay Rains in the Morning of the 3rd Day Uncontrollable Causes LEGEND Effects Categories 2nd Cause 3rd Cause 1st Cause Topics Problem Diagnosis Pareto Analysis Fishbone Diagram Scatterplots Systems Thinking and System Dynamics Causal Loop Diagrams System Dynamics Scatter Diagram Help predict the trend of future performance by showing the correlation between different variables. The data set used in a scatter diagram consists of an independent variable and a dependent variable Representing the independent variable on the horizontal axis and the dependent variable on the vertical axis, a scatter diagram can plot the correlation between two variables Scatter Diagram Different types of correlations Scatter Diagram Disadvantages Correlation does not necessitate a causal linkage Many potential directions of causal chains could explain a given correlation E.g. suppose A is correlated with B Possible Causal linkages A B B A A B A C B Topics Problem Diagnosis Pareto Analysis Fishbone Diagram Scatterplots Systems Thinking and System Dynamics Causal Loop Diagrams System Dynamics Systems Thinking and System Dynamics Systems thinking focuses on Conceptualizing problems in broader context Emphasizes interconnections rather than reductionist reasoning Internal rather than internal factors Feedback structure of system as primary determinant of behavior Common manifestations Qualitative: Causal loop diagrams Quantitative: System dynamics Systems Thinking and Project Management Primary critique: Traditional methods too Fragmented Restrictive in assumptions Local in attention to implications of changes Hesitant regarding representation of "soft" factors Too dependent on people link components Too willing to ignore important "side effects" Seen as potentially major contributor in project Learning (model captures institutional knowledge) Planning (identify robust decision rules, leverage pts) Control (how to best handle deviations) Consider traditional discrete methods Critique of Fragmentation CPM, Resource algs, time/cost tradeoffs, productivity considerations, manual check of global Activities analyzed in isolation (local impact of delaying activity or extending activity duration) Productivities, resource use, quality, cost all linked Delay/extension of activity influences resources, morale, productivity, etc. Takes people from other activities, idles others May affect customer relations, allocation of labor to project Makes overtime, concurrency more likely ( lower quality) Requires reconsidering subcontractor, material procurement Typical schedulers do not think through all implications Plans is always changing, being updated Causal Loop Diagram Like fishbone diagram, focus on causation Contrast with correlation focus of scatterplot More general, expressive than fishbone Cyclic: Focus on capturing feedback effects Indicate sign of causal impact (+ vs. ) x +y indicates y x -y indicates x > 0 y <0 x Causal Loop Diagram An arrow with a positive sign (+): "all else remaining equal, an increase (decrease) in the first variable increases (decreases) the second variable above (below) what it would otherwise have been." An arrow with a negative sign (-): "all else remaining equal, an increase (decrease) in the first variable decreases (increases) the second variable below (above) what it otherwise would have been." Reasoning about Link Polarity Easy to get confused regarding link polarity in the context of a causal chain Tips for reasoning about link polarity for XY Reason about this link in isolation do not be concerned about links preceding X or following Y Ask "if X were to INCREASE, would Y increase or decrease"? Increase in Y implies "+", Decrease in Y implies "-" If answer is not clear or depends on value of X, need to think about representing several paths between X and Y Ambiguous Link Ambiguous Link: Sometimes +, sometimes Overtime Productivity Replace this by disaggregating causal pathways by showing multiple links Fatigue + Overtime + Longer Hours Productivity + Feedback Loops Loops in a causal loop diagram indicate feedback in the system being represented Qualitatively speaking, this indicates that a given change kicks off a set of changes that cascade through other factors so as to either amplify ("reinforce") or damp ("balance") original change Loop classification: product of signs in loop Balancing loop: Product of signs negative Reinforcing loop: Product of signs positive Simple Causal Loops Remaining Work + Change Requests + Project Duration + Worker Productivity Perceived Slack + Target Completion Date - - Perceived Completion Date Job Rhythm Changes to Schedule Willingness of Project Participants to share info with PM - + Aggregate Productivity Estimated Design Costs beyond Target Budget Target Budget + - Design Scope Overbearing PM Management Style + PM Suspicion Elaborating Causal Loops 1 Estimated Design Costs beyond Target Budget Target Budget + + Estimated Design Costs beyond Target Budget + Design Scope Target Budget - Design Scope Elaborating Causal Loops 2 Work Pressure + + Work Remaining Productivity Work Pressure + + Work Remaining Productivity + Fatigue - Evolving More Complex Diagrams Relationship with Owner Delay + Disputes with Owner - Labor Productivity + Morale + Delay - Relationship with Owner - Disputes with Owner Schedule Pressure + Labor Productivity + Morale + Disputes with Owner Delay Relationship with Owner + Labor Productivity + Morale - Concern About Cost of Delay Relationship with Owner Delay + Disputes with Owner - Causal loop example T argeting early project completion P roject scope completeness + Design change Design and construction requests from owner overlapping + Schedule p ressure + Delay + + Design + completeness Design change requests from construction workers + + Construction+ change Design change - Deadline and Milestone Control Overtime + + Increasing + resources Schedule slippage + + Work rate + Schedule delays + Productivity + Time to completion - Schedule pressure + Cutting the corner + Aggressive scheduling Work remaining + - Defects Causal Loop Structure : Dynamic Implications Each loop in a causal loop diagram is associated with qualitative dynamic behavior Most Common Single-Loop Modes of Dynamic Behavior Exponential growth Goal Seeking Adjustment Oscillation When composed, get mixture of behaviors e.g. Growth and Plateau CL Dynamics: Exponential Growth (First Order Reinforcing Loop) Example + Customers Graph for Stock Word of Mouth Sales + + Dynamic implications 20,000 15,000 10,000 5,000 0 0 10 20 30 40 50 60 Time (Month) 70 80 90 100 Stock : Current CL Dynamics: Goal Seeking (Balancing Loop) Example: Potential - Customers Word of + Mouth Sales Dynamic behavior 75 50 25 0 0 10 20 30 40 50 60 Time (Month) 70 80 90 100 Inventory : Current CL Dynamics: Oscillation (Balancing Loop with Delay) Causal Structure + Desires Inventory Inventory - Finishing + Producing Production + Starts demand vs. production Dynamic Behavior: 6,857 3,142 0 Time (year) demand : Oscil producing : Oscil tons/year tons/year 30 Growth and Plateau Loop structure: Reinforcing Loop Balancing Loop Potential - Customers Word of + Mouth Sales + + Graph for Customer 100,000 75,000 50,000 25,000 0 0 10 20 30 40 50 60 Time (Month) 70 80 90 100 + Dynamic Behavior: Customers Customer : Current Design/Construction Overlap Uncertainties Assumptions in Design Owner's Requests on Changes Overlapping between Design and Construction Oversizing Potential Design Change Impact on Construction Project Costs Project Duration Construction Processes Design Changes Overlapping Construction Work R2 Done before Upstream Completed Increase in Time Pressure Workforce R1 Estimated Project Duration Productivity R3 Construction Changes Delay Construction Phasing Overlap Uncertainties Assumptions in Design Owner's Requests on Changes Overlapping between Design and Construction Oversizing Construction Processes Overlapping R2 Time Pressure R1 Productivity Delay R3 Construction Changes Increase in Workforce Potential Design Change Impact on Construction Design Changes Construction Work Done before Upstream Completed Project Costs Project Duration Estimated Project Duration Topics Problem Diagnosis Pareto Analysis Fishbone Diagram Scatterplots Systems Thinking and System Dynamics Causal Loop Diagrams System Dynamics System Dynamics Many frameworks for project systems analysis Discrete event sim., Agent-based sim. System dynamics is most popular Greatest competitive advantage in systems that are Nonlinear Feedback rich Exhibit delays Less governed by low-level heterogeneity System Dynamics Basics Represents system as coupled series of ordinary differential equations (ODEs) Standard state-equation formulation Continuous time formulation Stochastic components permissible (special handling) Analytic solutions not possible: Numerically integrate Graphical representation for problem focus State equations as stocks Components of differentials as follows Intermediate computations as auxiliaries, table functions, etc. How a SD Model is Created Conceptualize system using causal loop diagram Convert CLD to "stock & flow" structure State variables (accumulations) as stocks Changes to state variables as flows All change in system state occurs through flows All loops include at least one stock Intermediate calculations, outputs as auxiliaries Add to equations to capture relations among vars Calibrate to historic data Run scenarios to identify effect, robust policies Example Creation of a System Dynamics Model Step 1: Map out Causal Loops Potential - Customers Word of + Mouth Sales + Customers + + Step 2: Identify state variables of interest Potential Customers Customers Step 3: Identify flows of interest Potential Customers Customers New Customers Example Creation of a System Dynamics Model Step 4: Define Supporting Variables Fraction of Customers in Population Total Population Likelihood of Potential Customer Joining Function Giving Likelihood of Potential Customer Becoming New Customer based on Fraction of Customers Potential Customers Customers New Customers Insert equations to describe linkages E.g. Total Population = Customers+Potential Customers Fraction of Customers in Population= Customers/Total Population Example Creation of a System Dynamics Model II Step 1: Map out Causal Loops Work Pressure + + Work Remaining Productivity + Fatigue Step 2: Identify state variables of interest Work Remaining Fatigue Step 3: Identify flows of interest Work Remaining Work Being Completed Fatigue Growth in Fatigue due to Schedule Pressure Recovery from Fatigue Example Creation of a System Dynamics Model Initial Work Size Normal Productivity Work Hours as a Function of Fraction of Work Fraction of Work Completed Completed Work Hours Normal Work Hours Growth in Fatigue due to Schedule Pressure Work Remaining Work Being Completed Productivity Coefficient as a Function of Direct Work Pressure Productivity Coefficient from Fatigue Productivity coeefficient from Fatigue as a Function of Fatigue Fatigue Recovery from Fatigue Mean time to Recover From Fatigue ...
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