A context diagram shows a system (or product) at the centre and illustrates how it interacts with the external entities — users, other systems, organisations — that surround it. It does not show the internal workings of the system; it shows only the boundary between the system and its environment and the flows between them.

Context diagrams are used in requirements gathering to scope the system being built — defining what is inside the project's boundary and what is outside. The flows on the diagram (arrows) represent data, materials or signals that cross the boundary in each direction.

What it shows: The system under development is the centre box. Each oval is an external entity (actor or system) that interacts with it. Arrows show flows — data or materials — crossing the system boundary. The diagram deliberately excludes internal system details.

The WBS is a hierarchical decomposition of the total project scope into progressively smaller work components, ending at work packages — the lowest level of decomposition at which cost and schedule can be estimated and managed. The WBS is a deliverable-oriented hierarchy — it organises work by what will be produced, not by the activities needed to produce it.

The WBS is part of the scope baseline (alongside the scope statement and WBS dictionary). Every element of project scope must be in the WBS. If it is not in the WBS, it is not in the project — this is the 100% rule.

WBS dictionary: Each WBS element has a corresponding WBS dictionary entry that describes the work in detail — scope of work, deliverables, acceptance criteria, responsible organisation, resources required, cost estimate and schedule dates. The WBS dictionary prevents ambiguity about what each work package includes.

The Probability and Impact Matrix is used in qualitative risk analysis to prioritise risks by plotting each identified risk according to its probability of occurrence (vertical axis) and its impact on project objectives if it occurs (horizontal axis). The resulting position in the matrix determines the risk's overall priority and the urgency of the risk response.

How to read it: Risks in the top-right (high probability, high impact) are the highest priority — they need active response strategies. Risks in the bottom-left are low priority — they may be accepted with monitoring. Risks near the diagonal need judgement about whether their probability or impact warrants active management.

A tornado diagram is used in quantitative risk analysis — specifically in sensitivity analysis — to show which individual risks or uncertainties have the greatest impact on the project outcome. It is a horizontal bar chart where each bar represents one risk variable. The bars are sorted from longest (most impactful) at the top to shortest (least impactful) at the bottom — creating the tornado shape.

Each bar extends to the right and left of a central baseline value, showing the range of outcomes when that variable is at its highest and lowest plausible values.

A decision tree is a diagram that maps out a decision and its possible consequences, including chance outcomes and costs. It calculates the Expected Monetary Value (EMV) of each decision path by multiplying the probability of each outcome by its monetary impact and summing across all branches. The PM chooses the path with the highest (or least negative) EMV.

Decision trees are used in Perform Quantitative Risk Analysis when choosing between alternative courses of action, such as whether to build or buy, whether to add contingency reserve, or which risk response strategy to choose.

The cause-and-effect diagram (named after Kaoru Ishikawa) maps the potential causes of a problem or quality defect back to their root sources. The problem sits at the right (the "head" of the fish), and the causes branch off to the left along the "bones." Causes are typically organised into categories — the classic 6Ms framework: Man (people), Machine (equipment), Method (process), Material, Measurement, and Milieu (environment).

A control chart tracks a quality metric over time and compares it against statistically calculated Upper Control Limit (UCL) and Lower Control Limit (LCL), which are typically set at ±3 standard deviations from the mean. It distinguishes between normal process variation (common cause) and unusual variation that requires investigation (special cause).

The Rule of Seven: Seven consecutive data points on the same side of the mean line — even if all within control limits — indicates a non-random pattern (special cause variation) that requires investigation. This is the most tested rule about control charts on the PMP exam.

A Pareto chart combines a bar chart (showing defect frequency by category, sorted from most to least frequent) with a cumulative line chart showing the running total as a percentage. The Pareto principle states that roughly 80% of defects come from 20% of causes — the chart makes this visible and helps quality teams prioritise which causes to fix first for maximum impact.

The chart is read by finding the cumulative percentage line at 80% and looking down to the x-axis — all categories to the left of that point are the "vital few" causes responsible for 80% of problems. These are where quality improvement effort should be focused.

A scatter diagram plots two variables against each other to investigate whether a relationship (correlation) exists between them. Each dot represents one observation. If the dots form an upward-sloping cluster, there is positive correlation. If they slope downward, negative correlation. If they scatter randomly, no correlation exists.

In quality management, scatter diagrams test whether a suspected cause is actually correlated with a quality outcome — for example, whether testing time correlates with defect detection rate, or whether developer experience correlates with defect introduction rate.

A histogram is a bar chart that shows the frequency distribution of a dataset — how often values fall within each range (bin). Unlike a Pareto chart, the bars in a histogram are not sorted by frequency — they are ordered along the x-axis by value range. The shape of the distribution reveals whether the data is normally distributed, skewed, bimodal (two peaks) or has other patterns that indicate quality issues.

In project management, histograms are used to visualise resource utilisation distributions, defect frequency distributions and schedule or cost estimate distributions. A bimodal histogram (two distinct peaks) suggests the data comes from two different processes or populations and should be investigated.

A run chart plots data points in time order, showing how a metric changes over time — the trend. Unlike a control chart, a run chart does not have statistically calculated control limits. It is used earlier in a quality monitoring process to identify patterns, trends and shifts before enough data exists to calculate control limits.

Key patterns on run charts: A consistent upward or downward trend (7+ consecutive points trending in one direction) signals a systematic change. A shift (7+ points above or below the median) indicates the process has moved to a new level. These patterns trigger investigation even without control limits.

The Power/Interest Grid plots stakeholders on a 2×2 matrix based on their power (ability to influence the project) and interest (level of concern about the project's outcome). Each quadrant determines the engagement strategy for stakeholders in that segment.

The Stakeholder Engagement Assessment Matrix maps each stakeholder against the five engagement levels — Unaware, Resistant, Neutral, Supportive, Leading — and marks both their current (C) and desired (D) engagement level. The gap between C and D reveals what engagement work needs to happen.

The RACI chart maps project activities to team members using four assignment types: R — Responsible (does the work), A — Accountable (owns the outcome, final authority, only one per task), C — Consulted (provides input, two-way communication), I — Informed (receives updates, one-way communication).

A burndown chart tracks remaining work over time. The x-axis is time (days in a sprint or sprints in a release), the y-axis is remaining work (story points or tasks). An ideal burndown line descends from the total work at day 1 to zero at the sprint end. The actual burndown line shows real progress — if it is above the ideal line, the team is behind; below means ahead.

The Cumulative Flow Diagram tracks the number of work items in each stage of the workflow over time using stacked area bands — one band per workflow stage (e.g. To Do, In Progress, In Review, Done). The width of each band at any point in time shows how many items are currently in that stage. A widening band means work is accumulating — a bottleneck.

The CFD is the primary flow metric tool for Kanban teams and is increasingly used in hybrid environments. It reveals: lead time (how long items take from start to done), throughput (how many items complete per period), and work in progress (WIP) levels across workflow stages.

The network diagram shows project tasks as nodes connected by dependency arrows, illustrating the logical sequence of activities. It is the foundation for critical path method (CPM) calculations — the forward pass and backward pass that determine ES, EF, LS, LF and float for every task. The path from start to end with zero float is the critical path.

PMBOK recognises two formats: Activity on Node (AON) — the modern standard where boxes represent activities and arrows represent dependencies; and Activity on Arrow (AOA) — the older method where arrows represent activities. The PMP exam primarily tests AON format.

The Gantt chart is the most widely used schedule visualisation — a bar chart where each task is a horizontal bar plotted against a timeline. The length of the bar shows the duration. Dependencies are shown with arrows between bars. Resource assignments, milestone markers and baseline vs actual comparisons can all be layered on.

Gantt charts are excellent for communicating schedule status to stakeholders but are less useful for analysing dependencies than network diagrams. For large projects, they can become visually complex — rolling wave views (showing only the next 2–4 weeks in detail) are often more practical for day-to-day monitoring.

The S-curve plots cumulative cost or work against time and typically shows three lines: the Planned Value (PV) baseline curve (the budgeted cost of scheduled work over time), the Earned Value (EV) curve (the budgeted cost of work actually completed), and the Actual Cost (AC) curve (what was actually spent). The curves form an S-shape because spending is slow at the start, accelerates in the middle, and tapers off at project completion.

Reading the S-curve: If EV is below PV — the project is behind schedule. If AC is above EV — the project is over budget. The horizontal gap between PV and EV shows schedule variance in time terms. The vertical gap between EV and AC shows cost variance.