HKSM

Curated schedule data, metrics, and reports used to assess progress and guide control actions. It aggregates actuals, forecasts, and performance indicators into insights for timely schedule decisions. Effective use enables early variance detection and targeted corrective or preventive measures.

Key Points

• Combines baseline, current schedule, actual progress, and performance metrics into a single decision-ready view.
• Includes dashboards, status reports, variance and trend analyses, critical path views, and look-ahead plans.
• Supports both predictive and adaptive approaches, from Gantt variance to burndown and cumulative flow.
• Updated on a defined cadence to align with decision points and governance meetings.
• Visualizes risked activities, float consumption, and dependencies affecting milestones.
• Designed for traceability so each metric can be tied back to source data and assumptions.
• Facilitates scenario testing to evaluate options like fast-tracking, crashing, or resequencing.

Purpose of Analysis

• Spot schedule variances early and assess severity and trend.
• Forecast milestone dates and overall completion with confidence ranges.
• Identify drivers on the critical path and near-critical paths.
• Validate feasibility against resource calendars and constraints.
• Support change control with evidence-based impact assessments.
• Communicate clear, action-oriented status to stakeholders.

Method Steps

• Define cadence and decision needs for monitoring (e.g., weekly, per sprint, monthly gate).
• Select metrics and visuals: SPI/SV, milestone trend, critical path variance, look-ahead, burndown, throughput, WIP.
• Configure tools and data sources, including integrations for timesheets, boards, and resource calendars.
• Collect and validate data for completeness, timeliness, and consistency with the baseline and assumptions.
• Analyze variances and trends, focusing on critical/near-critical activities and float burn.
• Forecast outcomes and test scenarios such as crashing, parallelization, or scope deferral.
• Formulate corrective and preventive actions, quantify impacts, and prepare recommendations.
• Present findings via concise dashboards and briefings; capture decisions and update repositories.

Inputs Needed

• Approved schedule baseline and current schedule model with logic ties and constraints.
• Actual start/finish dates, percent complete, and remaining duration estimates.
• Resource calendars, allocations, and availability updates.
• Change log, approved changes, and pending change requests with schedule implications.
• Risk register and issue log entries affecting time, including response plans.
• Backlog, board metrics, and sprint/iteration data for agile or hybrid teams.
• Assumptions, constraints, and external dependency status from vendors or partners.

Outputs Produced

• Schedule status reports and dashboards highlighting variance and trend.
• Critical path and float analysis with prioritized delay drivers.
• Forecasted milestone and completion dates with confidence levels.
• Recommended corrective or preventive actions with quantified time impact.
• Change requests for schedule adjustments, sequencing changes, or resource plans.
• Updated schedule data, calendars, and backlog ordering where applicable.
• Stakeholder communications and meeting minutes capturing decisions and next steps.

Interpretation Tips

• Focus on activities with zero or low float; small slips there have outsized impact.
• Use trend lines rather than single data points; a slowly declining SPI can be more concerning than one bad week.
• Correlate schedule slippage with resource constraints and dependency delays before choosing actions.
• In agile contexts, compare throughput and cycle time trends to backlog burn to gauge finish predictability.
• Watch for calendar effects and seasonality; align forecasts with real availability windows.
• Validate “percent complete” with remaining duration and tangible deliverable acceptance.

Example

A multi-team release shows two consecutive weeks of negative milestone trend and SPI at 0.92. Critical path analysis highlights a vendor API dependency and a testing bottleneck. The team uses the information to model options: fast-track testing, add a contract tester, or resequence lower-risk stories. Management approves a short-term tester addition and resequencing, recovering five days on the critical path and updating the forecasted release date.

Pitfalls

• Using vanity metrics that look good but do not inform decisions.
• Allowing stale baselines or calendars to invalidate variance calculations.
• Relying on unverified data from timesheets or boards without reconciliation.
• Overreacting to noise and missing underlying trends or systemic constraints.
• Ignoring near-critical paths where float is rapidly burning.
• Confusing capacity with productivity and misreading throughput improvements.
• Presenting dense reports without clear actions or owner assignments.

PMP Example Question

During schedule control, the sponsor asks whether a one-week slip on a non-critical work package is significant. What should the project manager review first using project management information?

1. The SPI for the entire project to see if it is above 1.0.
2. The critical and near-critical path view to assess float consumption and path impact.
3. The cost EAC to determine if funds can accelerate work.
4. The team’s overtime policy to add more hours.

Correct Answer: B — The critical and near-critical path view to assess float consumption and path impact.

Explanation: Impact is driven by path criticality and float, not by overall averages. Reviewing path status shows whether the slip threatens milestones and what corrective actions are needed.