Project schedule

A project schedule is a time-phased plan that maps activities, durations, dependencies, milestones, and dates. It guides execution and control by showing when work starts and finishes and how changes affect the overall timeline.

Key Points

  • The schedule is a model of how the project timeline will unfold, not just a calendar of tasks.
  • Critical and near-critical paths reveal where delays will directly impact the finish date.
  • Float (slack) indicates schedule flexibility and opportunities for sequencing choices.
  • Resource availability and calendars can change the critical path after leveling.
  • Regular updates with actuals enable forecasting and timely corrective actions.
  • Scenario testing (what-if, fast-tracking, crashing) supports informed trade-off decisions.

Purpose of Analysis

  • Assess feasibility of the planned finish date and major milestones.
  • Identify critical and near-critical paths and the drivers of the completion date.
  • Reveal schedule risks, long-lead items, and activities with low float.
  • Evaluate the effect of resource limits and calendars on timelines.
  • Support decision-making on compression, sequencing, and risk responses.

Method Steps

  • Validate activity list, dependencies, and calendars for complete and correct logic.
  • Confirm duration estimates and resource assignments for each activity.
  • Run critical path calculations to determine path(s) with zero or minimal float.
  • Check for over-allocation and perform resource leveling, then recalc paths and float.
  • Analyze constraints, lags, and leads; remove unnecessary hard dates and weak logic.
  • Conduct what-if analysis for compression options (fast-tracking, crashing) and risks.
  • Establish or update the schedule baseline and define the update cycle and forecasting approach.

Inputs Needed

  • Scope breakdown (WBS), activity list, and defined dependencies.
  • Duration estimates, resource assignments, and resource calendars.
  • Project calendar(s), constraints, assumptions, and milestones.
  • Risk register items that affect time (e.g., uncertainty, long-lead risks).
  • Organizational policies, tools, and scheduling method rules.
  • Actual start/finish dates and progress data for updates and forecasts.

Outputs Produced

  • Updated schedule model with dates, critical path(s), and float values.
  • Schedule baseline and milestone list with target dates.
  • Resource profiles and histograms after leveling.
  • What-if scenarios and recommended compression or sequencing changes.
  • Forecasts (revised finish date, milestone slippage) and performance indicators.
  • Assumptions and risks specific to the schedule, including buffers or contingency time.

Interpretation Tips

  • Look beyond the final date; inspect the drivers and relationships on critical and near-critical paths.
  • Check float distribution; multiple near-critical paths mean higher schedule risk.
  • After leveling, recheck which path is critical; resources can change the driver.
  • Watch for hard date constraints that hide real risk; prefer logic-driven sequencing.
  • Validate that leads/lags reflect real work, not placeholders for missing tasks.
  • Use ranges or buffers when uncertainty is high instead of single-point optimism.

Example

A mid-size project creates a network of 120 activities with resource assignments. The team runs a critical path analysis and finds two near-critical paths within three days of the critical path. After leveling resources, the critical path shifts because a key specialist is over-allocated. The team tests fast-tracking two design-review handoffs and adds a small buffer to protect a long-lead procurement. The updated schedule baseline meets the target date with identified risks and monitoring points.

Pitfalls

  • Building the schedule around fixed dates instead of sound dependency logic.
  • Ignoring resource limits, leading to unrealistic timelines that fail in execution.
  • Underestimating durations and removing all float, leaving no resilience.
  • Overusing leads/lags to mask missing detail or poor sequencing.
  • Failing to update actuals regularly, making forecasts unreliable.
  • Focusing only on the critical path and overlooking near-critical risks.
  • Using a level of detail that is too coarse or too granular to manage effectively.

PMP Example Question

The sponsor asks to pull in the delivery date by 10 days. What should the project manager do first when analyzing the project schedule?

  1. Crash all activities by 10% across the schedule.
  2. Evaluate fast-tracking and crashing options on the current critical path.
  3. Compress activities with the largest float to free up time.
  4. Extend the workweek by adding weekend work for the entire team.

Correct Answer: B — Evaluate fast-tracking and crashing options on the current critical path.

Explanation: Compression decisions should target the critical path first and be evaluated for impact and risk before implementation. Compressing noncritical work or making blanket changes may not improve the finish date and can add risk.

AI-Prompt Engineering for Strategic Leaders

Stop managing administration and start leading the future. This course is built specifically for managers and project professionals who want to automate chaos and drive strategic value using the power of artificial intelligence.

We don't teach you how to program Python; we teach you how to program productivity. You will master the AI-First Mindset and the 'AI Assistant' model to hand off repetitive work like status reports and meeting minutes so you can focus on what humans do best: empathy, negotiation, and vision.

Learn the 5 Core Prompt Elements-Role, Goal, Context, Constraints, and Output-to get high-quality results every time. You will build chained sequences for complex tasks like auditing schedules or simulating risks, while navigating ethics and privacy with human-in-the-loop safeguards.

Move from being an administrative manager to a high-value strategic leader. Future-proof your career today with practical, management-focused AI workflows that map to your real-world challenges. Enroll now and master the language of the future.



Become an AI-First Agile Leader!

HK School of Management empowers you to master AI as your most powerful co-pilot—without the complexity. Transform your agile leadership with practical, prompt-based workflows and proven strategies designed for real-world scrum challenges. For the price of lunch, you get the tools to automate mundane tasks, refine backlogs with precision, and drive unprecedented efficiency in your team. Backed by our 30-day money-back guarantee—zero risk, real impact.

Learn More