Influence Diagrams Under Uncertainty: Ranges and Probability Distributions

PMBOK v8 Definition

An influence diagram is a graphical representation of situations used when making decisions under uncertainty. It shows causal influences, time ordering of events, and other relationships among variables and outcomes. Where an element in the influence diagram is uncertain as a result of the existence of individual project risks or other sources of uncertainty, this can be represented in the influence diagram using ranges or probability distributions. The influence diagram is then evaluated using a simulation technique, such as Monte Carlo analysis, to indicate which elements have the greatest influence on key outcomes. Outputs from an influence diagram are similar to other quantitative risk analysis methods, including S-curve diagrams and tornado diagrams.

Why It Matters for the Exam

This concept appears frequently in Quantitative Risk Analysis questions on the PMI exam. You will encounter it in scenario-based questions where the project manager must model uncertainty from individual risks or other sources. The exam tests your ability to identify when to use ranges/probability distributions in an influence diagram and what technique evaluates the diagram (Monte Carlo analysis). It also tests the distinction between influence diagrams and other risk visualization tools like tornado diagrams.

Key Points to Remember (for the exam)

Core Purpose: Influence diagrams show causal influences, time ordering of events, and relationships among variables and outcomes under uncertainty.
Representing Uncertainty: When an element is uncertain due to individual project risks or other sources of uncertainty, use ranges or probability distributions (not single-point estimates).
Evaluation Technique: The influence diagram is evaluated using Monte Carlo analysis (simulation technique).
Key Outputs: Similar to other quantitative risk analysis methods, outputs include S-curve diagrams and tornado diagrams.
Common Confusion: Influence diagrams are NOT the same as tornado diagrams. Influence diagrams are the input model; tornado diagrams are one of the outputs showing which elements have the greatest influence.
Decision Context: Used specifically "when making decisions under uncertainty" – this is a critical exam trigger phrase.
Elements Shown: Entities, outcomes, influences, relationships, and effects among them – all within a project or project situation.

Typical PMI Exam Example

A project manager is analyzing schedule risks for a construction project. Several tasks have uncertain durations due to weather risks and supplier delays. The PM creates an influence diagram showing how weather impacts supplier delivery, which impacts task duration, which impacts project completion date. For the uncertain weather element, the PM represents this using probability distributions and evaluates the diagram using Monte Carlo analysis to identify which elements most influence the completion date.

PMI Exam Traps

Trap: Confusing influence diagrams with tornado diagrams → Reality: Influence diagrams are the graphical model showing causal relationships; tornado diagrams are an output from evaluating that model.
Trap: Thinking influence diagrams only show individual project risks → Reality: They show uncertainty from individual project risks OR other sources of uncertainty (e.g., inherent variability).
Trap: Using single-point estimates for uncertain elements → Reality: Uncertain elements must use ranges or probability distributions, not fixed values.
Trap: Confusing influence diagrams with decision trees → Reality: Influence diagrams show causal influences and time ordering; decision trees show sequential decision points and outcomes.

Important PMI Connections

Related Concept	Relationship Type	Exam Attention Point
Monte Carlo Analysis	Evaluation technique	Monte Carlo is the simulation technique used to evaluate the influence diagram
S-curve Diagrams	Output	Influence diagram evaluation produces S-curves showing cumulative probability distributions
Tornado Diagrams	Output	Tornado diagrams show which elements have the greatest influence on key outcomes
Individual Project Risks	Input source	Individual risks are a source of uncertainty represented in the diagram
Quantitative Risk Analysis	Process area	Influence diagrams are a tool/technique within Quantitative Risk Analysis

Quick Review Questions

When an element in an influence diagram is uncertain due to individual project risks, how should it be represented?
What simulation technique is used to evaluate an influence diagram?
Name two types of diagrams that are outputs from evaluating an influence diagram.
What three types of relationships does an influence diagram show?
Is an influence diagram used for decisions under certainty or under uncertainty?

PMBOK v8 Reference

Section 11.4 - Perform Quantitative Risk Analysis (Tool: Influence Diagrams)