M2.3 — Resources, Productivity & Schedule Optimisation

M2.3 — Resources, Productivity & Schedule Optimisation

1. Practical outcome

By the end of this section, the learner should be able to test whether a logically valid schedule is actually deliverable with the people, skills, equipment, facilities and other constrained resources available to the project. They should be able to distinguish resource demand from capacity, derive realistic activity durations from quantities and productivity, identify overloads and bottlenecks, understand the difference between smoothing and levelling, develop practical optimisation options, and explain the time, cost and risk consequences of those options.

The objective is not to produce a perfectly flat resource histogram. It is to create a delivery plan in which the schedule, resource assumptions and productivity assumptions are mutually credible. A schedule that calculates correctly but assumes the same scarce team can work in three places at once is not a credible control model.

2. Core concepts

Resources turn a logical schedule into a feasible delivery plan

M2.2 establishes whether the work is logically connected and what currently controls the important outcomes. M2.3 asks the next question: can the work actually be performed with the available capacity and at the productivity assumed? Logical feasibility and resource feasibility are different. Both are needed before the schedule can be treated as credible.

·       A schedule can have perfect logic and still be impossible to deliver because it over-allocates a scarce resource.

·       A resource-loaded schedule can look balanced and still be poor if the underlying activity logic, scope or productivity assumptions are weak.

·       The purpose of resource analysis is therefore to test and improve the delivery model, not simply to populate software fields.

What counts as a resource?

A resource is anything whose availability or productive capacity can materially affect the ability to perform planned work. Depending on the project, this may include people, specialist skills, crews, equipment, rooms or work fronts, vehicles, test facilities, temporary systems, production capacity, supplier capacity or other constrained inputs.

·       Labour resources may be modelled by individual, role, skill, crew or organisational unit depending on the level of control needed.

·       Equipment resources may include cranes, vehicles, test rigs, specialist tools or shared facilities.

·       Non-labour constraints such as access windows, room availability or limited supplier production slots can behave like resources even if the scheduling tool represents them differently.

The level of resource detail should be proportionate. A project rarely benefits from loading every named individual if management decisions are actually made at team or skill-category level.

Resource Breakdown Structure (RBS)

A Resource Breakdown Structure groups resources into meaningful categories so demand and capacity can be analysed consistently. It might distinguish project management, design, procurement, installation, testing, digital specialists, operations representatives and external suppliers. The RBS should support the questions management needs to answer, rather than merely mirror the organisational chart.

·       Use categories that are stable enough for planning and reporting.

·       Separate resources that are genuinely interchangeable from those requiring different skills, licences, experience or authority.

·       Do not aggregate scarce specialist skills into a broad category if that hides the actual constraint.

Demand, capacity and availability are not the same thing

Resource demand is what the current schedule requires. Capacity is the amount of usable resource that could be available. Availability is the capacity actually accessible to the project during a particular period after calendars, leave, other commitments, access restrictions and contractual limits are considered.

For example, an organisation may employ ten technical specialists, but if four are committed elsewhere, one is on leave and two do not hold the required competence, the project does not have ten usable specialists. Resource planning should represent effective capacity, not nominal headcount.

Productivity links work content to time and resource

Productivity describes the amount of output achieved for a given amount of resource input. It is one of the most important bridges between schedule and cost. If the amount of work is known, and realistic productivity is known, the practitioner can estimate the resource effort and duration required.

A simple relationship is:

Productivity = output / resource input

For repetitive work, a useful duration approximation is:

Duration ≈ quantity of work / (number of effective crews × productivity per crew per period)

These relationships are deliberately simple. Real work may be affected by mobilisation, learning curves, access, handovers, congestion, rework, quality checks, weather, shift patterns and other factors. The important discipline is to make the assumption visible and evidence-based.

Productivity is not a universal constant

A rate achieved in one environment should not automatically be transferred to another. The same team may perform differently depending on work complexity, work-front readiness, supervision, interfaces, repetition, fatigue and disruption. Historical data is useful only when the context is sufficiently comparable.

·       Adding people does not always increase output proportionately. Coordination and congestion can reduce marginal productivity.

·       Overtime may increase available hours while reducing productivity or quality if sustained.

·       New teams may need mobilisation and learning time before reaching expected rates.

·       A highly experienced specialist may not be interchangeable with a larger number of less experienced staff.

Effort and duration must not be confused

Effort is the amount of resource work required; duration is the elapsed working time needed to complete the activity. An activity requiring 40 person-days of effort does not automatically have a duration of 40 days. With two fully effective people it might theoretically take 20 days, but only if the work can be divided, the people can work concurrently, and no other constraint limits progress.

This distinction matters because software can automatically recalculate duration, units or effort depending on configuration. The practitioner must understand the planning assumption rather than accept the software response as inherently correct.

Resource loading and resource profiles

Resource loading assigns resource demand to scheduled activities and time-phases that demand according to the schedule. Aggregating those assignments produces a resource profile or histogram showing how much capacity is required over time.

·       Peaks may reveal short-term overloads.

·       Long periods of low utilisation may reveal inefficient sequencing or an unrealistic assumption about when resources can be released.

·       A smooth profile is not automatically a good profile. Some work genuinely requires mobilisation peaks or specialist bursts of activity.

Resource smoothing and resource levelling

Terminology varies slightly between organisations and software products, so the practitioner should understand the purpose rather than rely only on the label. A useful distinction is:

·       Resource smoothing uses available float or flexibility to reduce peaks while preserving required completion dates where possible.

·       Resource levelling resolves resource over-allocation even when doing so changes activity dates, criticality or project completion.

In both cases, the calculation is only the beginning. The practitioner must review whether the resulting sequence is operationally sensible and whether the algorithm has created undesirable fragmentation, handovers or new risk.

Time-constrained and resource-constrained planning

A time-constrained plan starts from a date requirement and asks what resources or interventions are needed to achieve it. A resource-constrained plan starts from limited capacity and asks when the work can realistically be completed. Many projects contain both conditions: the public opening date may be fixed, while specialist commissioning capacity is limited. The resulting management problem is a trade-off, not a purely mathematical scheduling exercise.

Resource constraints can change the controlling path

The critical path calculated from precedence logic may not remain the controlling sequence once scarce resources are considered. Two activities with float may compete for the same specialist team; delaying one to resolve the conflict can consume float, create a new near-critical path or shift the completion driver entirely. Resource optimisation therefore needs to be considered alongside the M2.2 analysis, not separately from it.

The practitioner should re-check critical and near-critical paths after significant levelling or resequencing. The key question is still: what now controls the important outcome, and why?

Optimisation is a trade-off between time, cost, resource and risk

There is rarely one universally optimal schedule. Additional resources may shorten duration but increase cost, mobilisation complexity or coordination risk. Resequencing may avoid overtime but consume float. Outsourcing may add capacity but introduce commercial or quality risk. A good optimisation decision therefore compares the consequences of different options rather than selecting the schedule with the earliest finish or smoothest histogram.

·       Time: does the option protect or improve important milestone dates?

·       Cost: what additional or avoided cost results?

·       Resource: is the required capacity genuinely obtainable?

·       Risk: does the option create new dependencies, quality risk, fatigue, mobilisation risk or contractual exposure?

·       Practicality: can the delivery organisation actually work in the proposed sequence?

3. Step-by-step method — how to test and optimise resource feasibility

1. Start with a credible schedule. Confirm that the scope, activities, calendars and logic are sufficiently sound for resource analysis. Do not use resource levelling to compensate for a schedule that is fundamentally incomplete or poorly linked.

2. Identify resource-sensitive work. Focus first on activities whose duration, sequencing or feasibility depends materially on scarce people, specialist skills, equipment, access, work fronts or supplier capacity. Not every activity needs the same level of loading detail.

3. Define the resource categories and units. Establish the Resource Breakdown Structure (RBS) or equivalent categories, the unit of measure for each resource, and which resources are genuinely interchangeable.

4. Establish calendars and effective availability. Define working patterns, shifts, leave, other commitments, access windows, supplier calendars and any limits on when the resource can work. Use effective capacity, not theoretical headcount.

5. Quantify the work content where possible. Identify quantities, outputs, deliverables or measurable units that drive the work. If the work is non-repetitive, estimate effort using comparable experience, expert judgement or a documented estimating basis.

6. Establish productivity assumptions. Use relevant historical performance, benchmarks, supplier evidence or trial information. Record the basis, range and conditions under which the rate is expected to apply.

7. Convert work content into effort and duration. Calculate the implied resource effort and activity duration, then sense-check whether the result is operationally plausible. Distinguish effort from elapsed duration.

8. Assign resources to the schedule at the level needed for control. Avoid false precision. If management controls installation by two-person crews, model crews rather than individual names unless individual availability is the actual constraint.

9. Time-phase the demand. Use the current schedule to see when each resource is required and aggregate demand by day, week or month at a frequency appropriate to the work.

10. Compare demand with effective capacity. Identify periods of over-allocation, under-utilisation, impossible concurrent assignments, access conflicts and supplier-capacity conflicts.

11. Classify the conflict. Determine whether the issue is caused by scarce capacity, poor sequencing, unrealistic productivity, an incorrect calendar, too much planned concurrency, a work-front constraint, or some combination of these.

12. Examine criticality and float before changing the plan. Identify which overloaded activities are critical, near-critical or have usable float. Do not move activities simply because software suggests it without understanding the schedule consequence.

13. Develop practical optimisation options. Consider resequencing within float, splitting work, changing work fronts, adjusting crew size, adding shifts, using overtime, mobilising additional resources, outsourcing, changing methods, changing procurement strategy or revising milestone expectations.

14. Model each credible option. Recalculate the schedule, resource profile and affected costs. Check whether the option creates new peaks, broken logic, excessive handovers, fragmented work or new risk.

15. Compare time, cost and risk consequences. Avoid selecting an option solely because it gives the earliest completion. Assess affordability, resource availability, quality, safety, fatigue, commercial impacts and delivery practicality.

16. Select and document the preferred resource plan. Record the chosen assumptions, the capacity commitment required, rejected alternatives where material, and the management decisions needed to secure the resources.

17. Re-check schedule paths and baseline coherence. After significant optimisation, reassess critical and near-critical paths, milestone confidence, time-phased cost and any risk assumptions affected by the resource decision.

18. Monitor productivity and capacity during delivery. Compare actual output and resource use with the assumptions used in the plan. If productivity changes, update remaining duration and forecasts rather than preserving an obsolete assumption.

4. Worked Reference Project example

The Community & Learning Centre provides a useful neutral example because several workstreams need the same limited specialist resources at different times. The purpose is not to teach construction or technology delivery; it is to show how resource assumptions affect a project-controls model.

Example 1: technology installation capacity

The Digital & Technology Systems workstream has four zones ready for installation at slightly different times. The initial schedule assumes three installation crews can work concurrently during a two-week peak. The supplier, however, has committed only two suitably qualified crews to the project.

·       Scheduled demand during the peak = 3 crews.

·       Confirmed effective capacity = 2 crews.

·       The schedule is therefore over-allocated by 1 crew during that period.

The first response should not be to press the software levelling button. The planner should identify which activities use the crews, how much float each activity has, which zone feeds the earliest testing milestone, and whether the installation sequence can be changed without creating a new completion risk.

Example 2: turning quantity and productivity into duration

Assume the team must install and configure 1,200 standard technology points across the centre. A fully effective installation crew has demonstrated an average sustainable output of 20 points per working day once mobilised. Two crews are available.

Ignoring zone-release constraints for the moment:

Duration ≈ 1,200 / (2 crews × 20 points per crew-day) = 30 working days

This 30-day result is not automatically the activity duration. The learner must then test whether both crews can access productive work continuously for those 30 days, whether testing follows immediately, whether there is a learning or mobilisation period, and whether rework or handover restrictions should be allowed for. The calculation creates a transparent starting assumption; professional judgement makes it a credible plan.

Example 3: capacity profile and work-front readiness

Suppose the building team releases the four installation zones sequentially. Zone A is available first, followed by B, C and D. If only one zone is available during the first week, two installation crews cannot both achieve full planned productivity even though both crews are technically available. The constraint is the work front, not labour capacity.

This is important because the wrong diagnosis produces the wrong solution. Hiring a third crew would not help while only one productive work front is available. The better intervention may be to accelerate area handover, change the installation sequence or divide the available work differently.

Example 4: compare optimisation options

The resource conflict threatens the planned start of integrated testing. Management considers three options:

·       Option A - smooth the schedule using available float. Move the lowest-priority zone later, retain two crews and preserve the public opening date. This has minimal additional cost but consumes most of that zone's float.

·       Option B - mobilise a temporary third crew for the peak period. This protects float and testing dates but increases cost and introduces mobilisation, competence and supervision risk.

·       Option C - use sustained overtime with the existing crews. This appears cheaper than a third crew but may reduce productivity and quality if maintained, so the apparent capacity increase should not be assumed at face value.

A good project-controls recommendation would compare the modelled schedule impact, incremental cost, confidence that the resource can actually be secured, and any new risk. If Option A preserves the fixed opening date with acceptable residual float, it may be preferable even though it does not produce the flattest or earliest theoretical schedule.

Example 5: productivity deterioration during delivery

Later in the project, actual installation productivity averages 16 points per crew-day rather than the planned 20. With 480 points remaining and two crews available, the old assumption implies 12 working days remaining; the observed productivity implies approximately 15 working days. The remaining duration should therefore be challenged and the effect on testing and handover assessed.

This is where M2.3 connects directly with M2.4 Progress Updating & Schedule Control and M2.5 Schedule Forecasting & Analysis. Resource and productivity assumptions are not one-time planning inputs; they are forecast drivers that need to be updated as evidence changes.

5. Interpretation and professional judgement

Resource optimisation requires judgement because the data is rarely perfect and the mathematically neat solution is not necessarily the operationally best solution. The practitioner should understand both the numerical model and the practical delivery environment.

Do not confuse availability with usability

A person may be technically available but not productive on the required work because they lack the right skill, access, induction, information, equipment or work front. Similarly, supplier capacity may exist in principle but not be contractually committed to the project. Use capacity that management can reasonably rely upon.

Challenge apparent productivity improvements

If the plan assumes output doubles because crew size doubles, ask whether the work can genuinely be performed in parallel. Some tasks have a natural minimum duration or require sequential decisions, reviews or handovers. Additional people may add coordination rather than productive output.

Protect the delivery sequence, not the histogram

A completely flat resource profile may be unrealistic or undesirable. Projects mobilise, peak and demobilise. The objective is to remove avoidable overload and improve resource use without damaging the delivery strategy. The resource profile is evidence for a conversation, not a target shape in its own right.

Consider the cost and risk of acceleration

Adding shifts, overtime or additional teams can shorten work, but those interventions can also increase cost, fatigue, supervision needs, quality risk and rework. Acceleration should therefore be modelled as a management option with consequences, not treated as free schedule recovery.

Resource conflicts often reveal deeper planning problems

Repeated overload may indicate more than a shortage of people. It can reveal excessive planned concurrency, poor interface management, unrealistic milestone pressure, incomplete work-front planning, incorrect durations or an unresolved delivery-strategy decision. The practitioner should diagnose the cause before selecting the remedy.

Questions the practitioner should be able to answer

·       Which resources actually constrain the plan, and why?

·       What evidence supports the productivity rates used?

·       Where does demand exceed effective capacity?

·       Is the conflict caused by resource shortage, sequencing, work-front readiness, calendar assumptions or productivity?

·       Which overloaded activities are critical or near-critical, and which have usable float?

·       What happens to the critical path after levelling or resequencing?

·       What additional cost and risk accompany an acceleration option?

·       Can the organisation genuinely secure the capacity assumed by the preferred plan?

·       How sensitive is completion to a change in productivity?

·       What actual performance evidence will be monitored to validate or revise the resource assumptions?

6. Practice diagnostic

Use this table to challenge the quality of the approach or deliverable. The rows consolidate the most important recurring red flags and checks; they are prompts for professional judgement rather than a substitute for the method above.

7. Try-it-yourself practical exercise

Use the Community & Learning Centre Reference Project. Assume the logic network developed in M2.1 and M2.2 is credible. Focus on the Digital & Technology Systems workstream and the interface with Operational Readiness.

Exercise data

·       Four installation zones contain 240, 300, 360 and 300 standard technology points respectively.

·       A fully effective installation crew is planned to achieve 20 points per working day after mobilisation.

·       Two qualified crews are contractually committed to the project. A third may be available for a premium but is not yet secured.

·       The current schedule has a two-week period in which three zones are planned to be installed concurrently.

·       One of those zones has 10 working days of total float; one is near-critical with 3 working days of float; the third sits on the path feeding integrated testing.

·       A recent comparable project achieved only 17 points per crew-day during its first two weeks because of work-front and access issues, then improved to 21 points per crew-day.

·       The fixed public opening date remains unchanged.

Tasks

1. Calculate the theoretical installation duration for each zone using the planned productivity rate and one crew.

2. Build a simple weekly demand profile for the two committed crews and identify the period of over-allocation.

3. Explain whether the conflict can be resolved using float without changing the public opening date.

4. Develop at least three credible options, such as resequencing, a temporary third crew, overtime or a changed work-front strategy.

5. For each option, identify the likely schedule effect, incremental cost implication and at least two risks or assumptions.

6. Recalculate one scenario using 17 points per crew-day and explain what this tells you about productivity sensitivity.

7. Identify which assumptions should be recorded in the schedule basis and which management decisions are required.

8. Produce a short recommendation stating the preferred option and why it provides the best overall balance of time, cost, capacity and risk.

9. Explain what actual productivity and resource data you would collect during delivery to validate the forecast.

What good performance looks like

The learner should not simply remove the red over-allocation symbol. Good performance means diagnosing why demand exceeds capacity, understanding which work is genuinely controlling, developing feasible alternatives, quantifying the consequence of changing productivity, and recommending a delivery option that management could actually implement.

A particularly strong learner will also recognise that the lowest-cost option is not automatically best, that the fastest option is not automatically best, and that the observed productivity range may be more important to milestone confidence than the nominal number of crews available.

8. Bridge to capability

The How-to teaches how resources and productivity affect schedule feasibility. At APPLIED and above, capability assessment should test whether the practitioner can use realistic demand, capacity and work-front evidence to identify conflicts and compare practical options. Resource profiles, productivity assumptions and schedule consequences should support the recommendation. Supporting work products are illustrative and should be assessed with the practitioner’s reasoning. Sample learning questions illustrate the judgement at each recognition level; they are discussion prompts rather than validated assessment items.

Learning question: Do you understand how resource and productivity assumptions affect a feasible plan?

Capability question for APPLIED and above: Can you demonstrate an executable resource option and justify its schedule, cost and risk trade-offs?