In this article, we are going to walk through the process called Monitor and Control Schedule.
We will start from the key outputs, then work backward to the inputs and the tools and techniques that get us there.
Think of this process as the way we keep the schedule honest, realistic, and aligned with what is actually happening on the project.
Let’s begin with the most important output: change requests.
Change requests are produced when our monitoring shows that the schedule, as originally planned, no longer matches reality or no longer supports the project objectives.
They are the formal mechanism to adjust the schedule, scope, resources, or approach so that the plan and reality can be brought back into alignment.
The value of change requests is that they prevent silent drift. Instead of allowing delays, new risks, or scope changes to quietly undermine the schedule, we capture them, analyze them, and route them through integrated change control for decisions. This keeps the schedule baseline meaningful and protects stakeholder expectations.
Now, to understand how we arrive at change requests, we need to look at the key inputs and the main tools that help us decide whether a change is needed.
One of the foundational inputs is the schedule management plan, which is a component of the overall project management plan.
The schedule management plan tells us how we measure schedule performance, how frequently we do it, what thresholds trigger action, how we report deviations, and how we will control changes. Its value is consistency. It ensures we are not reacting emotionally to every small delay, and that we use agreed rules and methods when deciding whether a variation is acceptable or requires a formal change.
Alongside that, we rely heavily on the schedule baseline.
The schedule baseline is the approved version of the schedule, including start and finish dates, that we measure against. Its purpose is to be the reference point for performance. The value of the schedule baseline is that it gives us a stable yardstick. Without it, we could change the schedule informally and never be able to say whether we are truly behind or ahead.
When schedule slippage or major changes in sequencing are detected, we compare the current performance to this baseline. If the deviation is significant, we prepare change requests to update the baseline.
Another important plan component is the cost baseline and, more broadly, the performance measurement baseline.
The performance measurement baseline integrates scope, schedule, and cost into a single plan for performance measurement, often using Earned Value Management. The value here is that schedule decisions are not taken in isolation. When we consider a schedule change request—like crashing a critical activity—we can see the impact on cost and possibly on scope. This supports better, more holistic decisions.
To feed these comparisons, we need actual data. That’s where work performance data and work performance information come in.
Work performance data is the raw, observed facts: actual start and finish dates, remaining duration, hours worked, completed work, and so on. In their raw form, these data points are not yet very helpful for decision-making.
Through analysis, we transform this data into work performance information. This is where we convert numbers into insights: schedule variance, schedule performance index, trends over time, and forecasts of completion dates. The value is that work performance information directly tells us whether we are on track, where we are slipping, and what that means for the overall project timeline.
The transformation from data to information, and then to potential change requests, is supported by several tools and techniques.
A central technique is earned value analysis.
Earned value analysis integrates scope, schedule, and cost to measure performance. For schedule control, we focus especially on schedule variance and the schedule performance index. The “why” behind this tool is objectivity. Rather than relying on subjective impressions of progress, we use standardized formulas. The value is that it allows us to quickly see whether the project is performing ahead or behind schedule in a quantifiable way, and to support data-driven decisions about whether change requests are needed.
Another major tool is variance analysis.
Variance analysis compares planned dates and durations with actual performance to identify differences. The purpose is to see where the schedule is deviating, how much, and in which direction. The value is early detection. The earlier we can see where activities are trending behind, the more options we have to respond, often without drastic measures.
Trend analysis is also used to understand the direction of performance over time.
Rather than just looking at a single snapshot, trend analysis examines how schedule performance is evolving. The value is predictive insight. If we see that schedule performance has been gradually declining over several reporting periods, we know that small variances are turning into a significant risk and may justify a change request before we hit a crisis.
When we suspect that a schedule change might be necessary, we often turn to what-if scenario analysis.
What-if scenario analysis lets us test different approaches: what if a resource becomes unavailable, what if a key activity is delayed by two weeks, what if we add a second team to a critical path activity? The purpose is to understand the potential impact of different decisions on the project completion date and on other constraints. The value is that we do not commit to a change blindly. We can compare alternative responses and then raise a well-justified change request that aligns with project priorities.
The critical path method plays a key role here as well.
The critical path method identifies the longest path of dependent activities through the schedule, and thus the shortest possible project duration. In schedule control, we monitor critical path activities very closely because any delay on them directly affects the project end date. The value of this method is focus. It tells us where to pay attention and where schedule compression will have the most effect.
In some environments, especially where resources are heavily constrained, we may also use the critical chain method.
Critical chain scheduling takes resource limitations into account and uses buffers to protect the project’s completion date. During monitor and control, we track buffer consumption to understand whether we are using up schedule protection faster than planned. The value is that it gives us an early warning when resource-related delays are threatening the final delivery date, which may then trigger change requests or corrective actions.
If analysis shows that we are likely to miss key dates, schedule compression techniques come into play.
The two main compression techniques are crashing and fast tracking. Crashing means adding resources to critical path activities, while fast tracking means doing activities in parallel that were originally planned in sequence. These techniques are used when we need to bring a delayed schedule back on track without changing project scope. Their value is the ability to recover lost time, at the cost of higher risk or higher expenditure. The results of these decisions often become part of change requests for approval.
To support all of this analysis and recalculation, we rely on the project management information system, or PMIS.
The PMIS includes scheduling software and related tools that store the schedule model, track actuals, and automatically recalculate dates when changes are made. The value of the PMIS is efficiency and accuracy. It allows us to model changes quickly, maintain a single source of truth for the schedule, and generate reports that can accompany change requests and stakeholder communications.
Now, let’s move to another key set of outputs: project management plan updates and project document updates.
As we monitor and control the schedule, we often need to adjust the schedule management plan, the schedule baseline, and sometimes the cost baseline and performance measurement baseline.
Updates to the schedule management plan occur when we realize that our existing rules for measurement, reporting, or thresholds are not adequate. For example, we might decide to change the frequency of schedule reporting or tighten the variance thresholds that trigger escalation. The value of these updates is improved control. We learn from experience and refine our management approach over the life of the project.
When approved changes alter key dates or sequencing, we update the schedule baseline.
Updating the schedule baseline ensures that future performance comparisons are made against the latest approved plan, not against obsolete dates. The value is alignment. Everyone works off the same, current commitment, and future status reporting remains meaningful.
Changes that significantly affect timing often have cost implications as well.
In those cases, we may need to update the cost baseline and the integrated performance measurement baseline. This keeps scope, schedule, and cost synchronized. The value of doing this is integrated control: decision-makers and stakeholders always see a coherent, up-to-date picture of the project.
Beyond the plan components, we frequently update several project documents as a result of this process.
The project schedule itself is a primary document that gets updated.
As we record actual start and finish dates, remaining durations, and any resequencing, the project schedule evolves from a pure plan into a living model. The value of keeping it updated is that it remains a reliable tool for forecasting and coordination. Team members and stakeholders can trust it to reflect current expectations.
Schedule data is also updated.
Schedule data includes detailed information such as dependencies, leads and lags, assumptions about durations, constraints, and sometimes alternative paths. Updating schedule data ensures that the logic behind the schedule is accurate after changes. The value is transparency: when someone looks behind the dates, they can understand why the schedule behaves the way it does.
We also update schedule forecasts.
Schedule forecasts are projections of future milestones, release dates, or the overall completion date based on current performance trends. Their purpose is to look ahead: if we continue as we are, when will we finish? The value of these forecasts is proactive management. Stakeholders can adjust their expectations and plans early, and the project team can prioritize corrective actions.
The assumption log may be updated as well.
During schedule control, we often discover that some assumptions about resource availability, productivity, or external dependencies were incorrect. We record these changes to assumptions and their impact. The value is learning and traceability: future decisions, and even future projects, can understand which assumptions were risky and how they played out.
The basis of estimates can also change.
If actual performance shows that our original effort or duration estimates were optimistic or pessimistic, we may adjust the basis of estimates. This document explains how we arrived at our estimates—what data we used, what methods we applied. Updating it improves the credibility of future estimates and provides a better foundation for similar projects.
The lessons learned register is another important document that benefits from this process.
Whenever schedule issues arise—such as recurring delays on a certain type of activity—and whenever we find successful corrective actions, we capture those insights in the lessons learned register. The value is continuous improvement. We are not just fighting fires; we are building knowledge that can improve schedule performance later in the project and on future initiatives.
The risk register is also closely linked to schedule control.
Monitoring the schedule often reveals new schedule risks or changes in existing risks. For example, repeated delays on a vendor delivery might escalate a known risk from low to high probability. We update the risk register to reflect these changes, including any new response plans. The value is that risk and schedule management stay aligned. Schedule decisions are informed by the latest understanding of risk exposure.
Resource calendars and project calendars are updated when there are changes in availability, holidays, or working patterns.
These calendars define when people and equipment can work. If new public holidays are added, or key team members become unavailable, we update the calendars. The value is realism. The schedule remains grounded in actual, available capacity, which improves the accuracy of future plans and forecasts.
Now, let’s talk about the inputs related to risks, data, and agile practices that we have not yet emphasized.
The risk register, as mentioned, tells us which events might affect the schedule and what we plan to do about them.
During monitor and control, we continuously check whether those risks are materializing and whether our responses are effective. The value is that schedule control is not just about reacting to delays; it is also about anticipating them and preparing responses in advance.
The lessons learned register, besides being updated, is also an input.
We can look back at past projects or earlier phases to see which activities tended to overrun, which mitigation strategies worked, and how schedule compression was best applied. The value of using it as an input is that we can avoid repeating known mistakes and can apply proven strategies early.
Resource calendars and project calendars, as inputs, are essential for understanding whether schedule variances are due to unrealistic assumptions about availability.
They help us interpret schedule performance correctly and decide whether changes are needed.
for example, if a team appears to be “behind,” but the calendar shows several unplanned holidays or mandatory training days, the issue may be with our assumptions rather than with team performance. The value of using calendars as inputs is that our analysis is fair and grounded in real constraints.
Work performance data, as mentioned earlier, is another critical input.
It provides the raw facts about what has actually happened: which activities have started or finished, how much effort has been spent, and how much work remains. Its value lies in its objectivity. We base our schedule control on evidence, not on wishful thinking or optimistic status reports.
Now, let’s look more closely at tools and techniques that support this process but have not yet been fully discussed.
Resource optimization is one of them.
Resource optimization techniques, such as resource leveling and resource smoothing, help us adjust the schedule to deal with resource constraints or to balance workloads. The purpose is to align the schedule with real resource availability without overloading people or creating unnecessary peaks and valleys in resource usage. The value is sustainability and feasibility. A schedule that ignores resource limits may look fine on paper but will fail in execution. Resource optimization helps transform schedule variances into realistic recovery plans instead of impossible demands.
Leads and lags are another important technique.
Leads allow a successor activity to start before its predecessor finishes, while lags introduce a delay between activities. We use leads and lags during schedule control to fine-tune relationships between tasks as we learn more about how work actually flows. The value is flexibility. Instead of redesigning the entire schedule, we can adjust timing at the relationship level to better reflect reality, sometimes recovering time without major restructuring.
Branch and bound is a more advanced optimization technique used in complex scheduling situations.
In essence, it systematically explores different scheduling options within defined constraints to find near-optimal or optimal solutions. While it is not used on every project, its purpose is to help us evaluate many possible configurations when simple adjustments are not enough. The value is that, in highly constrained or high-stakes projects, it can identify schedule structures that manual trial and error would likely miss.
In adaptive and agile environments, several specific practices help us monitor and control the schedule.
Velocity tracking, burnup and burndown charts, daily coordination meetings, sprint reviews, and backlog refinement all play a role.
Velocity gives us a measure of how much work the team completes in each iteration. Its value is realistic forecasting: by observing stable velocity over time, we can predict how many iterations will be required to deliver the remaining backlog.
Burnup and burndown charts provide visual feedback on progress.
A burndown chart shows how much work remains over time, while a burnup chart shows work completed versus total scope. The purpose is to give quick, intuitive insight into whether the team is on track to meet iteration or release goals. The value is transparency. Stakeholders can see at a glance whether the schedule for delivering a release is realistic, and the team can adjust plans early.
Daily coordination meetings, often called daily stand-ups, support very short feedback loops.
Each day, the team inspects progress, identifies impediments, and adjusts the plan for the next 24 hours. The value for schedule control is responsiveness. Issues that could cause delays are surfaced quickly, often before they show up in formal reports.
Sprint reviews and backlog refinement sessions also influence schedule control.
In sprint reviews, stakeholders see the increment of working product and can confirm or adjust priorities. In backlog refinement, the team and product owner clarify upcoming work and adjust estimates. The value of these practices is that they keep the product backlog and release plans aligned with reality. We do not rigidly follow an outdated schedule; instead, we repeatedly re-plan based on what has been learned.
Finally, the product backlog itself is both an input and a focal artifact in agile schedule control.
It represents the ordered list of work items. As we monitor progress, we may re-order the backlog, split items, or adjust scope to meet time constraints such as fixed release dates. The value is that schedule control in agile is often achieved by adjusting scope and priorities rather than by forcing dates or overloading the team.
To close this lesson, remember the big picture.
Monitor and Control Schedule is not just about tracking dates and reporting delays. It is about using data, structured analysis, and appropriate tools—both predictive and agile—to keep the schedule realistic, to anticipate problems, and to make informed changes through formal change control.
By understanding the key outputs, the inputs that feed them, and the techniques that transform raw data into actionable decisions, you can keep your project’s schedule credible, aligned with objectives, and trusted by stakeholders.
