PSK I Practice Exam — PSK I : Professional Scrum with Kanban™

This question assesses core PSK I (Professional Scrum with Kanban Level I) knowledge of flow metrics and their appropriate use cases. The scenario requires forecasting completion for a single, already started Sprint Backlog item, rather than aggregate system-level performance. Per PSK I curriculum, forecasts for individual in-progress work items depend on tracking the elapsed time the item has spent active in the workflow, compared to historical cycle time performance data for the team's process. The Work Item Aging Chart is explicitly designed for this specific use case, as it focuses on individual active items rather than aggregated system-wide metrics. Option Analysis:
A. Work Item Aging Chart: Correct. Per PSK I content, the Work Item Aging Chart plots each active in-progress work item against the number of days it has been in the workflow, with overlaid historical cycle time percentiles (typically 50th, 85th, 95th) for the team's established process. For the specific started Sprint Backlog item in the question, you can cross-reference its current age against these percentiles to generate a probabilistic forecast of when it will complete, which directly addresses the scenario requirement.
B. Throughput Run Chart: Incorrect. Throughput is an aggregate metric that measures the total number of work items completed per fixed time period (e.g., per day, per Sprint). A Throughput Run Chart tracks this aggregate count over time to forecast how many total items the team can complete in a future period, but it provides no data on individual in-progress items, so it cannot be used to predict when a specific started item will finish.
C. Control chart: Incorrect. The cycle time Control Chart referenced in PSK I tracks historical cycle times of already completed work items to identify process stability, common cause variation, and special cause variation. It only uses data from finished items and does not track the current age of in-progress individual items, so it cannot generate a completion forecast for the specific started Sprint Backlog item in the question.
D. Cumulative Flow diagram (CFD): Incorrect. The CFD is an aggregate system-level chart that shows the count of items in each workflow state over time. It can be used to calculate average system cycle time, WIP levels, and throughput for the entire workflow, but it does not track individual work items. There is no way to isolate data for a single started Sprint Backlog item on a standard CFD, so it cannot answer the question of when that specific item will finish. Key Concepts:
1. Work Item Age: This is a core Kanban flow metric defined as the elapsed time from when a work item enters the "in progress" segment of the workflow to the current point in time. Per PSK I content, it is the only flow metric designed to forecast completion for individual active work items.
2. Probabilistic Forecasting with Cycle Time Percentiles: PSK I emphasizes using historical cycle time percentiles rather than average cycle times for reliable, realistic forecasts. Work Item Aging Charts overlay these percentiles to give teams clear, data-backed estimates of the likelihood an in-progress item will complete within a given timeframe.
3. Aggregate vs Individual Flow Metrics: PSK I distinguishes between system-level aggregate metrics (throughput, average cycle time from CFD, control chart cycle time) that forecast overall team performance, and individual item metrics (work item age) that forecast outcomes for single work items, ensuring teams select the right metric for the specific question they are answering. References:
Kanban Guide for Scrum Teams, Professional Scrum with Kanban (PSK) Learning Resources, https://www.scrum.org/professional-scrum-kanban-psk

This question assesses core knowledge of applying Kanban practices in Scrum Teams as covered in the Professional Scrum with Kanban Level I (PSK I) certification domain. PSK I guidance emphasizes that Kanban systems for Scrum Teams center on visualizing all work-related elements, flow states, and governing policies to improve transparency, identify flow bottlenecks, and optimize delivery efficiency. The three correct options represent valid, commonly visualized elements for Scrum Teams using Kanban, while the incorrect option refers to a Scrum event that is not part of work flow tracking.

Option Analysis:
A. The Product Backlog. Correct. PSK guidance confirms Scrum Teams often visualize the Product Backlog as the upstream portion of their Kanban system, with states such as Ready for Refinement, Refined, and Ready for Sprint Planning. This visualization creates transparency around incoming work, helps identify bottlenecks in backlog refinement, and ensures a consistent pipeline of work ready for selection in Sprint Planning.
B. The Sprint Backlog. Correct. Visualizing the Sprint Backlog is a foundational Kanban practice for Scrum Teams, as covered in PSK I content. Teams track Sprint Backlog items across flow states (e.g., Selected, In Progress, In Review, Done) on their Kanban board to monitor progress toward the Sprint Goal, surface blockers, measure cycle time, and enforce work in progress (WIP) limits during the Sprint.
C. The Definition of Done. Correct. The Definition of Done (DoD) is a core quality policy that is frequently visualized alongside or embedded into a Scrum Team's Kanban system. Teams may list DoD criteria as exit requirements for each Kanban board column or post the full DoD adjacent to the board to ensure shared clarity on quality standards, reduce rework, and enforce consistent rules for moving work between flow states, a key requirement outlined in PSK guidance.
D. The Sprint Retrospective. Incorrect. The Sprint Retrospective is a formal Scrum event focused on continuous process improvement, not a work artifact, work item, or quality policy that is tracked as part of work flow on a Kanban board. While action items generated during a Sprint Retrospective may be added to the Product Backlog or Sprint Backlog and visualized, the event itself is not a candidate for Kanban visualization.

Key Concepts:
1. Kanban Visualization Principle: A core PSK I principle stating that all work, work states, and policies governing work flow must be made visible to the entire Scrum Team to enable effective flow management, bottleneck identification, and shared accountability for delivery.
2. Integration of Kanban with Scrum Artifacts: PSK guidance specifies that Kanban practices complement rather than replace existing Scrum framework elements, so visualization is applied to standard Scrum artifacts including the Product Backlog and Sprint Backlog, as well as Scrum quality policies like the Definition of Done.
3. Flow Policy Transparency: A key PSK I knowledge point requiring that all policies that govern work flow (such as the Definition of Done) are visible to the team, to eliminate ambiguity about work completion requirements and support consistent, predictable delivery.

References:
Professional Scrum with Kanban Guide, https://www.scrum.org/resources/professional-scrum-kanban-guide
Scrum Guide 2020, https://scrumguides.org/scrum-guide.html

The PSK I (Professional Scrum with Kanban Level I) certification validates understanding of how to integrate Kanban practices with the Scrum framework, including core flow measurement concepts. The question asks to identify which option is NOT a flow metric. Per official PSK I curriculum and the Kanban Guide for Scrum Teams, all four items listed in options A through D are standardized, widely accepted flow metrics used by Scrum Teams to measure and improve workflow efficiency, predictability, and transparency. Since none of the first four options are non-flow metrics, option E is the correct answer. Option Analysis:
A. Cycle Time is a core flow metric per PSK I standards. It measures the total time a work item spends in active workflow from the moment work starts on it to the moment it is ready for release. It is used to assess delivery speed and predict future delivery timelines, so it is a flow metric and not the correct answer to the "NOT" question.
B. Work in Progress (WIP) is a core flow metric per PSK I standards. It counts the number of work items actively moving through a team's workflow at a given point in time. It is used to identify bottlenecks, manage team capacity, and enforce WIP limits to improve flow efficiency, so it is a flow metric and not the correct answer to the "NOT" question.
C. Throughput is a core flow metric per PSK I standards. It measures the number of work items a team completes within a defined period of time. It is used to forecast how much work a team can deliver in future periods and track overall delivery output, so it is a flow metric and not the correct answer to the "NOT" question.
D. Work item age is a core flow metric per PSK I standards. It measures how long an in-progress work item has been in the team's workflow. It is used to identify blocked, stagnant, or at-risk work items that deviate from expected cycle time baselines, so it is a flow metric and not the correct answer to the "NOT" question.
E. All of the above are flow metrics is the correct answer. Since options A through D are all official flow metrics covered in the PSK I body of knowledge, no option listed is a non-flow metric, making this the right selection. Key Concepts:
1. Core Kanban Flow Metrics for Scrum Teams: The four foundational flow metrics defined for Scrum Teams using Kanban are Work in Progress, Cycle Time, Throughput, and Work Item Age. These metrics provide end-to-end visibility into workflow health and performance.
2. Flow Metric Use Cases: Each flow metric serves a distinct purpose: WIP prevents overloading the team, Cycle Time measures delivery speed, Throughput measures delivery volume, and Work Item Age proactively identifies delayed work items. Combined, they enable data-driven process improvement and forecasting.
3. Probabilistic Forecasting: A core PSK I competency is using the four flow metrics together to run probabilistic forecasting (e.g. Monte Carlo simulations) to predict future delivery outcomes with greater accuracy than traditional deterministic estimation. References:
Kanban Guide for Scrum Teams, Professional Scrum with Kanban (PSK) Learning Path, https://www.scrum.org/pathway/professional-scrum-with-kanban-psk

The Daily Scrum is a 15-minute timeboxed event for the Scrum Team to inspect progress toward the Sprint Goal, adapt the Sprint Backlog, and plan work for the next 24 hours. For this event, actionable data must support immediate, forward-looking adjustments to resolve impediments, remove bottlenecks, and keep delivery on track. Per PSK I core guidance, teams integrating Kanban with Scrum rely on metrics that enable proactive flow management, rather than historical measurements that cannot be changed. Leading indicators are uniquely suited for this use case, as they provide early signals of emerging issues before they impact delivery outcomes, while lagging indicators only report on completed past performance that is not actionable for daily work adjustments.

Option Analysis:
A. Leading indicators are predictive metrics that signal potential future changes to delivery flow before outcomes are finalized. Common PSK-aligned leading indicators used in Daily Scrums include work item age for in-progress tickets, current work in progress (WIP) counts against set limits, and queue lengths for workflow stages. These metrics let the team identify delays, blockers, or bottlenecks in real time, so they can take immediate action such as reallocating capacity, removing impediments, or reprioritizing Sprint Backlog items to stay on track for the Sprint Goal. This option is correct per PSK I certification requirements.
B. Lagging indicators are outcome-focused metrics that measure performance of completed work, such as past sprint velocity, average cycle time for items finished in the prior month, or defect rates for released work products. These metrics are valuable for longer-term process improvement during Sprint Retrospectives or backlog refinement, but they reflect events that have already occurred and cannot be adjusted, so they provide no actionable data to guide daily work decisions during the Daily Scrum. This option is incorrect.

Key Concepts:
1. Flow Metric Use Cases per PSK: PSK I teaches that flow metrics are categorized as leading or lagging, with leading metrics reserved for frequent, proactive inspection events like the Daily Scrum to support real-time flow management.
2. Daily Scrum Alignment with Empiricism: The Daily Scrum leverages the Scrum pillar of adaptation, which requires forward-looking data to adjust plans before risks materialize, making leading indicators the appropriate data input.
3. Leading vs Lagging Indicator Definition: Leading indicators predict future performance and enable proactive intervention, while lagging indicators measure past results and are only useful for retrospective analysis of completed work.

References:
Professional Scrum with Kanban Guide, https://www.scrum.org/resources/professional-scrum-kanban-guide
Scrum Guide 2020, https://scrumguides.org/scrum-guide.html

This question assesses understanding of Kanban flow metric relationships as defined in the Professional Scrum with Kanban (PSK) I curriculum, specifically Little's Law and the distinction between flow metrics and effort estimation metrics. Work in Progress (WIP) refers to the count of work items actively moving through a Kanban system at a given time. As a leading indicator, WIP reliably predicts future changes to count-based flow outcomes, but it has no direct correlation to effort-based measures like story points. Story point values are assigned arbitrarily per team estimation practices and do not map to the count of work items tracked by WIP limits, so WIP provides no predictive insight into story point delivery volumes.

Option Analysis:
A. Incorrect. Per PSK I core content, WIP is a direct leading indicator for throughput, which is defined as the number of work items completed per unit of time. Little's Law establishes that changes to WIP directly impact throughput: excessively high WIP causes bottlenecks and context switching that reduce throughput, while optimized WIP levels maximize throughput. WIP trends reliably predict future throughput performance.
B. Incorrect. Cycle time, the total time a work item spends in the Kanban system from start to finish, is directly tied to WIP per Little's Law. All else being equal, higher WIP leads to longer cycle times, so WIP levels act as a leading indicator of expected cycle time outcomes, a core PSK I concept for flow optimization.
C. Incorrect. The count of completed Product Backlog Items (PBIs) per Sprint is a direct measure of throughput for the Sprint interval. Since WIP is a leading indicator for throughput, it also predicts the number of PBIs a team can finish in a given Sprint, as WIP limits ensure teams work on a manageable number of items to complete more work per interval.
D. Correct. Story points are a relative estimation unit for work effort, defined independently per team, and are not a flow metric. WIP tracks the count of work items in progress, not the sum of their estimated effort values. Two teams with identical WIP limits can deliver vastly different total story points if their PBIs are assigned different point values, so WIP provides no predictive insight into the total story points a team will deliver, making it not a leading indicator for this measure.

Key Concepts:
1. Little's Law: The foundational flow equation at the core of Kanban for Scrum, which states average Cycle Time = average Work in Progress / average Throughput. This law defines the direct causal relationship between WIP and the two core flow metrics of throughput and cycle time.
2. Leading vs Lagging Flow Indicators: PSK I defines leading indicators as metrics that predict future performance, while lagging indicators measure past outcomes. WIP is a leading flow indicator for all count-based flow outcomes, but not for effort-based output metrics that rely on team-specific estimation practices.
3. Flow Metrics vs Estimation Metrics: Flow metrics (WIP, Cycle Time, Throughput) track the movement of work items through the system regardless of their individual size or effort, while estimation metrics (story points, ideal hours) measure projected effort for individual work items and are not tied to flow dynamics.

References:
Professional Scrum with Kanban Guide, https://www.scrum.org/resources/professional-scrum-kanban-guide
Little's Law and its Application in Scrum with Kanban, https://www.scrum.org/resources/blog/littles-law-its-application-scrum-kanban