Workforce Planning for Hospitals: Cost, Compliance and Outcomes

Agency and overtime costs are symptoms, not causes.

When an Australian health or aged care organisation finds itself spending 15%, 20%, or 25% of its total labour budget on agency staff and overtime, the instinctive response is to tighten approval processes — require sign-off from a more senior manager before agency can be called, cap the weekly overtime ceiling, instruct roster managers to "reduce reliance on agency." These interventions generate paperwork. They rarely generate savings.

The reason is that agency and overtime aren't costs you can control at the point of consumption. They're costs that are largely determined upstream — by how the workforce is structured, how rosters are designed, how leave is managed, and how well the operational demand forecast aligns with staffing plans. By the time a roster manager is calling an agency on a Sunday morning, the structural decisions that made that call necessary were made weeks or months earlier.

This article focuses on where those upstream decisions go wrong — and what it takes to fix them.

The Scale of the Problem in Australian Health and Aged Care

Labour represents 60–70% of the operating cost base in residential aged care, and a similar proportion in hospital and community health settings. Within that labour spend, agency and overtime are among the most expensive and least productive components.

In residential aged care, agency costs vary significantly across providers — but organisations without active workforce management programmes commonly spend 8–15% of total labour spend on agency, with some in acute shortage periods spending considerably more. At average agency premium rates of 40–80% above permanent equivalent costs, even a modest reduction in agency reliance produces material financial improvement.

Overtime in health settings runs at a similar scale. In hospital wards and emergency departments operating under pressure, overtime hours representing 10–15% of total paid hours are common. For nurses on the Nurses Award or under enterprise agreements, overtime rates are typically 150% of ordinary time for the first three hours and 200% thereafter — making unplanned overtime significantly more expensive per hour than any other form of labour.

The cumulative financial impact is substantial. An aged care provider with 500 residents, a total labour spend of $20 million, and agency/overtime at 12% of spend is paying approximately $2.4 million annually for its most expensive and most unstable form of labour. The same provider with a well-structured workforce model and 5–6% agency/overtime spend would save $1.2–1.4 million annually — a transformative improvement in an environment of thin operating margins.

Root Cause 1: Structural Workforce Composition Problems

The most common underlying driver of high agency and overtime spend is a workforce composition that is misaligned with demand.

This happens in two ways.

Too few permanent hours relative to stable demand. When an organisation has a large casual workforce but insufficient permanent hours to cover its predictable, recurring staffing requirements, every absence in the casual pool becomes a gap that agency fills. Casuals have no obligation to accept shifts. When they decline — which they do at higher rates when they have multiple employers, when the shift is inconvenient, or when they're fatigued — the organisation has no internal buffer and defaults to agency.

Too many permanent full-time hours relative to variable demand. The opposite problem. An organisation that has over-committed to full-time permanent staff in excess of its minimum demand base will have those staff sitting at ordinary-time cost during quiet periods while also paying overtime to cover demand peaks that the permanent staff can't absorb without exceeding their hours. This drives both overtime at the top and inefficiency at the base.

The right composition depends on the demand variability of the specific operation. The higher the demand variability — the more the staffing requirement fluctuates between shifts, days of the week, and seasons — the more flexible hours (part-time, casual, or flex-time permanent) are needed as a proportion of the workforce. The lower the demand variability, the more permanent full-time is appropriate.

Getting the composition right requires a demand model (what is the actual variation in staffing requirement across shifts and days?) and a cost model (what does each employment type actually cost under the applicable award or enterprise agreement, including all penalties and on-costs?) Most organisations don't have both. Without them, workforce composition decisions are made on intuition.

Root Cause 2: Roster Design That Creates Avoidable Overtime

Even with the right workforce composition, a poorly designed roster can generate systematic overtime.

The most common roster design problems that drive overtime:

Misaligned shift start times. Shifts that start too early or too late relative to demand peaks create periods where overtime is needed to bridge the gap. In residential aged care, for example, the morning personal care peak is highly predictable and concentrated in a two-to-three-hour window. Shift patterns that don't align with this peak force staff to either rush the work (quality risk) or extend their shifts into overtime to complete it.

Insufficient overlap at handover. Handover shifts that are under-resourced relative to the clinical or care complexity at that time of day generate overtime as outgoing staff stay back to complete tasks.

Consecutive days accumulation. Rosters that regularly place staff in positions where they've worked six consecutive days before the weekend create overtime exposure as soon as any additional hours are required. Better spread of rest days across the roster cycle reduces this structural vulnerability.

Split shift design in community care. In home and community care, split shifts that require carers to make multiple trips create travel time that exceeds the productive care hours worked — driving overtime on total hours and kilometre reimbursements. Route optimisation and clustering of service visits by geography significantly reduces this.

Root Cause 3: Leave Management Failure

Unplanned absence is the biggest single trigger for agency calls. But in most health and aged care organisations, the majority of leave is not genuinely unplanned — it's leave that was predictable but not built into the forward roster.

Annual leave accumulation is a universal problem. Staff who have accumulated large leave balances are a latent liability: when they eventually take leave (or when the organisation requires them to reduce their balance), it creates gaps in the roster that weren't anticipated in the staffing model. An organisation with 200 FTE nursing and care staff carrying an average of four weeks of accrued leave is managing a latent liability equivalent to 16 FTE — the equivalent of a small ward.

Planned leave that isn't built into the tactical roster creates a forecasting error that manifests as an agency call. If a roster manager builds a forward roster based on full establishment, and two staff have already approved leave for the same weekend, the gap on that weekend was entirely predictable. It became an agency call because the leave wasn't integrated into the roster at planning time.

The fix is straightforward in principle: forward leave planning, integrated into the tactical roster at the point of roster construction, not added retrospectively. In practice it requires discipline — a leave management cadence that locks in planned absences at a defined planning horizon (typically four to six weeks forward) and treats those absences as fixed inputs to the roster, not variables to be managed later.

Root Cause 4: Absence of a Casualisation Strategy

Many health and aged care organisations use a large casual workforce as an unmanaged buffer — calling whoever is available rather than maintaining a structured pool with predictable availability.

The problem with unmanaged casualisation is that it combines high unit cost with low reliability. Casuals who work across multiple providers have no particular commitment to any one of them. Their availability at short notice is unpredictable. Training and orientation costs are absorbed every time a new casual works at a facility for the first time. Care continuity — a meaningful quality outcome — is compromised every time a resident or patient receives care from someone who doesn't know them.

A structured casual strategy addresses this differently. It defines a target casual pool size, maintains relationships with a defined group of known workers, provides preferred casual hours to the most reliable pool members in exchange for commitment to a minimum availability level, and manages the pool as a genuine workforce segment rather than an on-demand external resource. Done well, it improves availability, reduces agency dependency, and improves care quality without increasing cost.

Root Cause 5: No Agency Governance Framework

Even where agency use is genuinely unavoidable — in acute shortage situations, in specialised clinical roles where the internal casual pool can't provide coverage — the absence of an agency governance framework means agencies are called without benchmarking, approved without costing, and managed without data.

An effective agency governance framework includes: a preferred agency panel with agreed rates and response time commitments; a defined approval process that ensures agency calls are costed before they're approved; a cap on agency expenditure as a percentage of total labour budget (typically with a hard cap and a secondary approval requirement above it); a system for tracking agency hours and spend by ward, facility, or business unit; and a regular review of agency usage patterns to identify structural drivers that can be addressed.

This doesn't eliminate agency. It ensures that agency is used deliberately, procured competitively, and managed as a monitored cost rather than an uncontrolled variable.

What Good Looks Like

Organisations that manage agency and overtime well share some common characteristics.

They have a demand model — a forward projection of staffing requirements by shift, based on actual operational drivers rather than last week's pattern. They build the roster against that demand model, with leave integrated. They have a structured casual pool with predictable availability. They run an escalation protocol that sequences responses to shortfalls in a defined order. They track agency and overtime weekly, by unit, against a target. And they treat variance from target as a management issue that triggers investigation, not just approval.

The financial outcomes are consistent. Australian health and aged care providers that move from unmanaged to managed workforce models typically reduce agency spend by 20–40% within 12 months and reduce overtime by 15–25% — without compromising care standards or service levels. In some cases, the improvements are larger.

How Trace Consultants Can Help

Reducing agency and overtime costs in health and aged care requires a systematic diagnosis of the root causes, not a blanket instruction to use less agency.

Trace Consultants works with hospitals, aged care providers, and community health organisations to identify where agency and overtime spend is structurally driven, design the workforce and rostering interventions that address root causes, and implement the governance frameworks that sustain the improvement.

Diagnostic. We analyse your workforce composition, roster patterns, leave data, and agency usage to identify the key cost drivers and quantify the improvement opportunity.

Roster and workforce redesign. We design the shift patterns, workforce mix, and leave management processes that reduce structural overtime and agency dependency.

Governance and performance management. We implement the reporting frameworks, escalation protocols, and management cadences that sustain cost discipline over time.

Technology configuration. Where rostering or workforce management technology is in place, we work to ensure it is configured to support demand-driven rostering and award-compliant scheduling.

Explore our Workforce Planning services →Explore our Health & Aged Care sector work →Speak to an expert at Trace →

‍

The static roster is one of the most expensive and least examined costs in service-heavy industries.

It works like this: a standard shift pattern is set — typically based on historical precedent, negotiated conditions, or a manager's judgement about what the team needs — and then repeated, week after week, with minor adjustments for leave and the occasional last-minute scramble when someone calls in sick. The roster is fixed. Demand is not.

The result is a workforce that is simultaneously overstaffed during quiet periods and understaffed during peaks. Overtime accumulates at the margins. Agency or casual labour is called to fill gaps that should have been anticipated. Staff who are over-rostered become disengaged; staff who are under-rostered become unsafe. And the manager responsible spends an inordinate amount of time on last-minute scheduling rather than on the work that actually drives performance.

Demand-driven rostering breaks this pattern. It starts with a forecast of when work will arise — and at what volume, complexity, and required skill level — and builds the roster from that demand picture, rather than from a fixed template. The approach is more complex to design than a static schedule. The operational and financial returns are consistently worth it.

Why Static Rosters Are So Persistent

If demand-driven rostering is better, why do most organisations still run static schedules?

The answer is a combination of inertia, industrial complexity, and data limitations.

Inertia. Static rosters are easier to administer. Once set, they run automatically. The short-term management cost of building and maintaining a dynamic roster is higher than repeating last week's schedule with minor edits.

Industrial complexity. In health, aged care, and other award-covered environments, rostering involves navigating shift penalty rates, overtime thresholds, minimum rest periods, consecutive days limits, and skills-based assignment rules simultaneously. Under the Aged Care Award (MA000018), for example, ordinary hours must sit within a defined span for day workers, and shift penalties vary significantly across evenings, nights, weekends, and public holidays. Getting the roster right requires award literacy as well as scheduling capability. Many rostering managers default to static patterns precisely because they reduce the risk of payroll errors.

Data limitations. Demand-driven rostering requires a demand forecast — and many organisations don't have the data infrastructure to produce one. Without reliable, granular data on patient acuity, order volumes, call arrivals, or service visit schedules, the demand side of the equation is guesswork.

These barriers are real. They're also solvable, and the case for solving them has become substantially stronger as labour costs have risen, compliance requirements have tightened, and the penalty for poor staffing decisions — in quality, safety, and financial terms — has increased.

The Three Horizons of Demand-Driven Rostering

Effective demand-driven rostering operates across three time horizons, each with a different purpose and a different level of granularity.

Strategic (Monthly to Quarterly)

At the strategic horizon, the question is: what workforce structure — the mix of full-time, part-time, casual, and permanent roles, and the distribution of hours across shifts, days, and skill levels — best matches your expected demand pattern over the coming months?

This is the workforce composition question. Getting it right reduces structural overtime (hours rostered at penalty rates because the mix of permanent and casual hours doesn't match demand variability) and reduces agency dependency (called because there aren't enough casual hours available in the internal workforce when demand spikes).

In a residential aged care facility, for example, the strategic horizon question is whether your current mix of full-time registered nurses, part-time personal care workers, and casual staff appropriately covers your expected occupancy and acuity levels — including weekend and night shift requirements — without relying on agency to plug routine gaps.

Tactical (Weekly to Monthly)

At the tactical horizon, the question is: given the specific demand forecast for the coming weeks, how should available hours be allocated across shifts, days, and roles?

This is where the actual roster is built. Tactical rostering translates a demand forecast — patient admissions projected by day, orders expected by shift, service visits scheduled by geography — into a staffing plan that covers demand, stays within budget, and complies with industrial conditions.

The key discipline at this horizon is roster freeze — the point at which the forward roster is locked and subsequent changes are tracked as variance. A roster that changes continuously up to the last minute is a roster that can't be evaluated against a baseline. Locking the roster at seven to ten days forward, and tracking changes and their cost against that baseline, is a basic operational discipline that most organisations haven't formalised.

Operational (Daily to Shift)

At the operational horizon, the question is: given what we know today — about actual demand, actual staff availability, and actual service requirements — how do we adjust the roster in real time?

This is the short-interval control problem. Even a well-built tactical roster will require daily adjustments: unplanned absences, demand spikes, equipment failures, and patient or resident acuity changes are part of the operating environment. The operational horizon is about having a clear, fast protocol for making those adjustments — in a defined order of preference (redeployment before overtime, overtime before agency) — without defaulting to the most expensive option by default.

The three horizons need to be designed as an integrated system. A well-structured strategic roster reduces the volume and cost of tactical changes. A well-managed tactical process reduces operational fire-fighting. Without the strategic foundation, tactical and operational rostering will always be reactive.

Building the Demand Forecast

The most important input to demand-driven rostering is a reliable demand forecast — and this is where most organisations have significant headroom to improve.

The demand forecast answers the question: when, and in what volume, will work arise? The specific inputs depend on the sector:

In residential aged care: occupancy levels, resident acuity scores (under the AN-ACC funding model, acuity directly determines care minute requirements), behavioural support needs, clinical risk classifications, allied health schedules, and the predictable rhythm of high-demand activities — medication rounds, personal care, mealtimes, activities programmes.

In a hospital ward: bed occupancy, patient acuity (ADDS scores, ICU dependency), admission and discharge patterns by day of week and time of day, procedure schedules, and the ratio of high-acuity to low-acuity patients in the ward mix.

In community and home care: scheduled service visits by package level, geographic clustering, historical dwell time variability by service type, carer travel time between visits, and seasonal illness patterns.

In a distribution centre or logistics operation: order volumes by day and shift, cut-off times, SKU complexity, value-added service requirements, and seasonal peaks from promotional events, holidays, or sales cycles.

In all of these environments, the demand pattern has predictable structure — days of the week, times of day, seasonal rhythms — that can be extracted from historical data and used to build a demand model. The goal is not perfect forecast accuracy; it's a demand picture that is materially better than last week's schedule as a basis for planning.

Designing the Roster Against Demand

Once you have a demand forecast, the roster design process has five key elements:

Baseline staffing. Define the minimum staffing required at each point in time to safely and compliantly deliver the service. In health and aged care, this is partly set by regulatory requirements — care minute mandates, safe staffing ratios. In other sectors, it's set by service level targets and operational capacity constraints.

Shift pattern design. Design shift patterns — start times, durations, break structures — that align with demand peaks and troughs. This doesn't mean designing a different shift for every day of the week; it means ensuring that the available shift patterns can be combined to cover demand efficiently. Common interventions include: introducing split shifts or short "swing" shifts that cover high-demand transition periods; adjusting shift start times by 30 to 60 minutes to align with demand peaks; and introducing overlap shifts that provide surge capacity at predictable high-demand points without adding net hours.

Mix optimisation. Determine the optimal mix of permanent full-time, part-time, and casual staff to cover the demand pattern. The goal is to provide permanent hours that cover the predictable, stable base demand — the hours that are needed every week with high certainty — and casual or flexible hours that cover the variable demand above that base. Over-reliance on permanent full-time staff to cover variable demand drives structural overtime. Over-reliance on casual staff to cover stable demand drives higher unit costs and lower service continuity.

Leave and training integration. Build leave and training into the forward roster at the tactical horizon rather than managing them as surprises at the operational horizon. Predictable leave consumption, applied to the roster at planning time, produces a much more accurate staffing picture than rostering to establishment and then absorbing leave as it is taken.

Escalation protocols. Define the sequence of responses when planned staffing falls short — in a specified order: redeployment of existing staff, extension of hours to ordinary-time limits, overtime for existing staff, known casual pool, agency or external labour. The escalation protocol ensures that the most expensive options are reserved for genuine shortfalls, not reached by default.

The Industrial Framework: Rostering Under Australian Awards

In health, aged care, community services, and many parts of retail and logistics, rostering must be managed within the requirements of modern awards or enterprise agreements. This adds complexity but also provides structure that, used intelligently, can reduce cost.

Key provisions that rostering managers need to understand:

Penalty rates. Shifts worked outside ordinary span hours, on weekends, or on public holidays attract penalty loadings that significantly increase the unit cost of labour at those times. Designing the permanent roster to minimise exposure to penalty rates — while still covering service requirements — is a material cost lever. For direct care workers in aged care, Saturday and Sunday penalty rates and evening/night shift penalties can increase the effective hourly cost by 25–50% over ordinary day-shift rates.

Overtime thresholds. Overtime is triggered at different thresholds under different awards — daily, weekly, or by roster cycle. Understanding exactly when overtime is triggered for each employment category in your workforce is fundamental to roster design. A part-time worker whose ordinary hours are 20 per week doesn't attract overtime until they exceed their contracted hours; a casual worker's overtime trigger is different again. Roster patterns that accidentally push workers over overtime thresholds drive cost that is avoidable with better design.

Minimum engagement periods. Under the Aged Care Award, full-time employees have a minimum four-hour shift; casuals and part-time workers have a two-hour minimum. Rostering shifts shorter than these minimums creates payroll obligations that exceed the actual hours worked — a common source of waste in organisations that roster casuals for very short shifts.

Rest requirements. Minimum rest periods between shifts vary by award and by employment type. Inadvertently rostering someone with insufficient break time between shifts creates both a compliance risk and a fatigue and safety risk.

Award-compliant, cost-efficient rostering requires these provisions to be understood and actively managed — not just administered reactively. Technology that automates award interpretation reduces both compliance risk and rostering administration time significantly.

Measuring Rostering Performance

You can't manage what you don't measure. The core metrics for rostering performance are:

Overtime as a percentage of paid hours. The single most useful measure of roster design quality. Structural overtime — overtime that recurs week after week in predictable patterns — is a signal that the roster design is misaligned with demand. Target: below 5% for well-managed operations; 8–12% is common in unoptimised environments.

Agency and casual pool usage. Measured as both hours and cost. Track agency usage as a percentage of total paid hours, and separately track the cost premium over equivalent permanent hours. Reducing avoidable agency usage is typically one of the highest-ROI interventions available. In aged care and health, agency premiums of 40–80% over permanent equivalent rates are common — and in tight labour markets, availability is not guaranteed even at premium rates.

Roster change frequency. The number of roster changes made after the freeze point, and the cost of those changes. High change frequency indicates that the tactical forecast is unreliable or that the operational environment is being managed without clear protocols.

Coverage against demand. For shift-based operations, the percentage of demand periods where actual staffing met the planned minimum. Tracking both over-coverage (waste) and under-coverage (risk) by shift and day gives a precise picture of where the roster is working and where it isn't.

Fill rate. The percentage of shifts filled as planned, without changes. A low fill rate indicates either a supply problem (not enough people available) or a design problem (shifts designed in a way that people don't want to work them).

How Trace Consultants Can Help

Demand-driven rostering is both a design problem and a change management problem. Getting the analysis right is necessary. Getting the organisation to change how it plans and manages shifts is often the harder part.

Trace Consultants helps Australian health, aged care, logistics, and service organisations move from static schedules to demand-driven rostering models that reduce labour cost, improve service reliability, and work within the industrial framework.

Demand modelling. We build demand forecasting models from your operational data — acuity scores, occupancy, order volumes, service schedules — that produce actionable, shift-level demand forecasts.

Roster design. We design shift patterns, mix structures, and leave frameworks that align with your demand profile and comply with your award or enterprise agreement obligations.

Cost analysis. We quantify the current cost of structural overtime, agency usage, and under-staffing, and model the financial impact of the redesigned roster.

Implementation and uplift. We support the transition to the new roster model — including manager capability building, technology configuration, and the governance framework for ongoing roster management.

Explore our Workforce Planning services →Speak to an expert at Trace →

Related reading: Workforce Planning for Aged Care Australia · Planning & Operations · How to Build a Workforce Planning Model from Scratch

‍

Most organisations know they need a workforce plan. Far fewer have one that actually works.

What passes for workforce planning in many Australian businesses is a combination of last year's headcount, a few assumptions about growth, and a spreadsheet that someone in HR updates annually and nobody uses to make decisions. It describes the workforce you have. It doesn't tell you what you need, when you'll need it, or what it will cost to bridge the gap.

A real workforce planning model is different. It connects demand — the work that needs to be done — to supply — the people available to do it — and surfaces the gaps between them clearly enough that management can act. Built well, it becomes one of the most commercially useful tools in an organisation. Built poorly, it becomes another document that sits in a shared drive.

This guide explains how to build a workforce planning model that actually earns a place in your planning cycle.

What a Workforce Planning Model Is — and Isn't

Before building anything, it's worth being precise about what you're trying to produce.

A workforce planning model is an analytical tool that projects workforce demand and workforce supply over a defined horizon — typically one to three years — and identifies the capacity, capability, and cost gaps between them. It should answer three core questions:

• How many people, in what roles, with what skills, do we need to deliver our operational plan?
• How many people, in what roles, with what skills, do we have — and how will that change through natural attrition, retirement, and current hiring?
• What is the gap, and what are our options for closing it?

What it is not: a headcount budget, an organisation chart, a HR strategy document, or a rostering system. These are related tools — and a good workforce plan connects to all of them — but they're not the model itself.

The model lives between strategy and operations. Its inputs come from both. Its outputs should drive both.

Step 1: Agree the Planning Horizon and Granularity

The first decision in building a workforce planning model is scope: what time horizon are you planning for, and at what level of granularity?

Horizon. Strategic workforce planning typically operates over a one to five year horizon. Operational workforce planning — connecting demand to rosters and shifts — operates over weeks to months. Most organisations need both, but they're different tools. For a strategic model, a three-year horizon with annual milestones is a practical starting point for most Australian organisations. In fast-changing environments (health, technology, defence), a five-year horizon with quarterly reviews is more appropriate.

Granularity. You can model workforce at the level of the organisation, business unit, function, role family, or individual role. The right level depends on your purpose. If you're planning for an enterprise-wide transformation, role family level is usually sufficient. If you're planning for a specific operational area — a hospital ward, a distribution centre, a contact centre — role-level granularity is necessary.

Starting too granular creates a model so complex that it can't be maintained. Starting too coarse creates a model so aggregated that it can't be acted on. Most organisations benefit from a tiered approach: enterprise-level for strategic decisions, function-level for workforce investment decisions, role-level for operational planning.

Step 2: Build the Demand Side

Demand modelling is the part most workforce plans get wrong. They start with last year's headcount and adjust for growth. That's supply modelling — it tells you how your existing workforce might change. Demand modelling starts somewhere different: with the work.

The question is: what does your operational plan require in terms of human effort, by role, over the planning horizon?

There are three primary approaches to demand modelling, and the right choice depends on your industry and data availability.

Driver-based modelling. Connect workforce demand to the operational drivers that cause it. In a hospital, demand drivers include bed occupancy, patient acuity, procedure volumes, and outpatient attendances. In a distribution centre, they're order volume, SKU complexity, and despatch frequency. In a contact centre, they're call volume, average handle time, and service level targets. Build a model that translates operational drivers into FTE requirements by role — and you have a demand forecast that updates automatically when the operating plan changes.

Ratio-based modelling. Use established ratios of workforce to output as a starting point — staff-to-patient ratios in health, covers-per-staff in hospitality, cases-per-picker in logistics. These are faster to build than driver-based models but less sensitive to operational change. They're a useful starting point or a cross-check, not a substitute for driver-based modelling in complex environments.

Activity-based modelling. Map the activities that each role performs, estimate the time each activity takes, and multiply by projected activity volumes to get FTE demand. This is the most granular approach and the most powerful for identifying where work is being done inefficiently — but it requires significant data collection and is harder to maintain.

For most Australian organisations building a workforce plan for the first time, a driver-based model at role family level, cross-checked against ratios, is the right starting point. It's buildable in a reasonable timeframe, updatable without heroic effort, and directly connected to the operational plan.

Step 3: Build the Supply Side

Supply modelling answers the question: what workforce do you have now, and how will it change over time if you make no deliberate interventions?

The supply model starts with a current state snapshot — headcount by role, employment type (full-time, part-time, casual), age, tenure, location, and any skills or qualification data you hold. Then it projects that workforce forward using three variables:

Attrition. How many people will leave in each period, by role? Attrition has voluntary and involuntary components. Voluntary attrition (resignation, retirement) can be estimated from historical data, segmented by age band, role, and tenure. In health and aged care, where workforce shortages are acute and turnover is structurally high, voluntary attrition rates of 20–30% in some care worker cohorts are not unusual. In professional services, rates in the 10–15% range are more common. Involuntary attrition (performance exits, redundancy) is usually smaller and more manageable.

Internal mobility. How will people move within the organisation — through promotion, lateral transfer, reskilling, or deployment? An organisation with active talent development programmes will have higher internal mobility than one that fills roles primarily externally. Internal mobility reduces recruitment cost and supports retention, but it needs to be modelled explicitly to understand its effect on supply in different role pools.

Current pipeline. What recruiting, training, and development activity is already in progress, and what headcount will it deliver, when? Graduates and trainees already enrolled, internal development programmes underway, and approved recruitment in progress should all be factored into the base supply projection.

The output of the supply model is a projected workforce profile — by role, over the planning horizon — assuming no new interventions.

Step 4: Identify and Quantify the Gaps

With demand and supply modelled, the gap analysis is straightforward in principle: subtract supply from demand, by role, by period.

In practice, the gap analysis has four dimensions that need to be considered separately:

Capacity gaps. Do you have enough people? A simple numerical difference between demand and supply. A positive gap means you're short; a negative gap means you're over-resourced.

Capability gaps. Do you have people with the right skills? A capacity analysis that shows sufficient headcount can still mask a serious capability problem if the skills required have changed — through technology adoption, regulatory change, or service model evolution — and your existing workforce hasn't kept pace.

Location gaps. Are your people in the right places? In organisations with geographically distributed operations — health networks, retail chains, government agencies — the aggregate workforce picture can look balanced while specific locations or regions face critical shortfalls.

Cost gaps. Can you afford the workforce you need? A workforce plan that identifies the right headcount and skills profile but is unaffordable is not a plan — it's a wish list. The cost model needs to run in parallel with the demand and supply model, translating FTE requirements into salary and on-cost projections that can be tested against the budget.

The gap analysis should be presented as a forward-looking picture across all four dimensions, with the gaps ranked by severity and time horizon.

Step 5: Develop and Evaluate Strategies

Gap identification is analysis. Workforce planning becomes useful when it generates strategies for closing gaps — and when those strategies are evaluated against each other.

For each material gap, there are typically four types of response:

Recruit. Hire people from the external labour market. Fast but expensive, and in tight labour markets (health, engineering, digital, logistics) constrained by supply. Recruitment strategy needs to account for lead times — in specialised roles, six to twelve months from decision to productive contribution is not unusual.

Develop. Build capability internally through training, reskilling, or upskilling. Slower than recruitment and requires investment, but builds organisational capability, supports retention, and is often less expensive than external hiring for roles where internal candidates are close to ready.

Redeploy. Move people from areas of surplus to areas of shortage. Effective where the roles are adjacent and the capability gap is manageable — less effective where the skills differential is large or the geographic movement is significant.

Restructure. Change the way work is done to reduce the workforce requirement or change its composition. Automation, process redesign, outsourcing, or changes to the operating model can all reduce or reshape demand. This is often the highest-leverage response but the slowest to implement.

Most workforce plans require a combination of all four, sequenced over the planning horizon. The model should allow you to test the sensitivity of different strategy mixes — what happens to cost and risk if you lean more heavily on recruitment vs. development? — and to track progress against the chosen strategy over time.

Step 6: Connect the Model to the Business Planning Cycle

A workforce plan that isn't connected to the budget process, the strategic plan, and operational decision-making will be ignored.

The model needs to be designed for ongoing use, not just for the project that created it. That means: data inputs that can be updated from source systems (HR, payroll, operational planning) without manual re-entry; a governance process that defines who updates the model, how often, and who reviews the outputs; and decision triggers that define when the model should be used — for new investment decisions, organisational changes, budget submissions.

In health and aged care, the model also needs to connect to compliance monitoring — tracking care minute delivery against mandated minimums, for example, requires the same underlying data as workforce planning and should be sourced from the same system.

The most common failure mode in workforce planning programmes is building a model that's accurate at the point of creation and obsolete within six months because nobody owns the update cycle. Design for maintenance from the start.

Common Mistakes

Starting with supply instead of demand. A workforce plan built from current headcount with adjustments for growth is a staffing budget. It misses the capability dimension entirely and doesn't challenge whether the current operating model is fit for purpose.

Over-engineering the model. A highly complex model with hundreds of variables is difficult to maintain and difficult to explain to the executives who need to act on it. Build for the decisions you need to make, not for theoretical completeness.

Ignoring external labour market context. A workforce gap analysis that doesn't account for the availability of the skills you need in the external market is incomplete. In tight labour markets — and Australia currently faces tight markets across health, engineering, and technology — a gap that looks closeable through recruitment may not be.

One-size-fits-all modelling. Different parts of the organisation have different workforce dynamics. Applying a uniform planning methodology across all functions misses the variation that drives meaningful insight.

How Trace Consultants Can Help

Building a workforce planning model that earns a place in your planning cycle requires both analytical rigour and deep knowledge of your sector's workforce dynamics.

Trace Consultants works with Australian organisations across health, aged care, government, retail, logistics, and infrastructure to design and implement workforce planning models that are operationally grounded, financially connected, and built to last.

Model design. We design workforce planning frameworks appropriate to your organisation's scale, sector, and data environment — driver-based, ratio-based, or activity-based as the situation warrants.

Data and analytics. We extract and structure workforce data from HR and payroll systems, develop demand projections from operational plans, and build the gap analysis and scenario modelling tools your leadership team needs.

Strategy development. We work with your leadership and HR teams to develop and sequence the strategies that close your workforce gaps — balancing recruitment, development, redeployment, and restructuring options against cost and risk.

Implementation support. We embed workforce planning as an ongoing management practice — not a one-off project — with governance structures, update cycles, and reporting that sustain the model over time.

Explore our Workforce Planning services →Speak to an expert at Trace →

‍