Planning for the work ahead
A schedule allocates the people available today. A demand forecast helps planners decide what capacity they may need in the coming days, weeks or months, including the skills and locations likely to be required.
Forecasts are estimates. They are most useful when planners understand the uncertainty, know which decisions they can change and have enough time to act.
This guide explains the data, methods and operating decisions involved in forecasting demand for mobile and frontline teams.
1. What is workforce demand forecasting?
Definition: Workforce demand forecasting estimates future work using service history, known commitments and relevant signals. Capacity planning then translates that work into the people, skills and time needed to deliver it.
Job volume alone is not enough. A forecast also needs to account for duration, travel, geography and qualification requirements. Two regions with the same appointment count may need very different staffing.
Scheduling uses the resulting capacity to allocate actual work. Forecasting, capacity planning and scheduling inform one another, but each answers a different operational question.
Questions a forecast should answer
Break the forecast down far enough to support a decision. A national monthly total may help with budgeting but offer little guidance for next week's regional coverage.
- Volume forecasting: How many visits, jobs or service hours are expected in each planning period? Separate confirmed work from estimated demand.
- Skill-mix forecasting: Which skills and qualifications will the work require, and how much time is needed from each group?
- Geographic distribution: Where is the work likely to occur? Include travel and local access constraints when converting volume into capacity.
- Seasonal and cyclical patterns: What recurring patterns are supported by the data? Check seasonality, recurring contracts and planned projects without assuming last year's pattern will repeat.
- Demand volatility: How far could actual demand differ from the estimate? Use that uncertainty when considering reserve capacity or alternative plans.
2. Decisions a forecast can support
Forecasts can inform hiring, training, shift coverage, territory allocation and contractor planning. Their value depends on whether the information arrives before those decisions are made.
An unexpected capacity gap does not always mean the forecast was poor. Absences, unrealistic job estimates or unavailable equipment can also reduce the work a team can complete. Investigate demand and supply separately.
Cost, service and working patterns
Capacity costs
Compare the cost of reserve capacity with the likely cost of overtime, temporary staffing or unfulfilled work. Use your service requirements and risk tolerance rather than a universal staffing percentage.
Service commitments
Assess whether expected demand can be met within the promised windows. Where it cannot, planners may need to change capacity, appointment availability or commitments before work is accepted.
Workforce stability
Earlier visibility of likely demand can support more predictable shifts and hours. Discuss proposed changes with the affected teams and review their effect; forecasting alone does not guarantee better retention.
3. Approaches to demand forecasting
The approaches below can be combined. A statistical model is not automatically better than a simple baseline; compare their accuracy and usefulness for the decision at hand.
| # | Approach | What it answers | Planning use |
|---|---|---|---|
| 1 | Respond to actual demand | What work has arrived? | Adjust capacity for known work; limited advance notice. |
| 2 | Historical reporting | What work did we receive? | Establish a baseline and examine recurring patterns. |
| 3 | Pattern-based estimate | What may recur in the next period? | Estimate demand using relevant past periods and known changes. |
| 4 | Predictive model | What demand range is likely? | Assess possible demand using a tested model and its uncertainty. |
| 5 | Scenario analysis | What responses could meet that demand? | Compare staffing, coverage and service options within the operating constraints. |
Begin with a baseline that is easy to explain and test. Compare forecasts with actual demand at the level where decisions are made, such as region, work type and week.
More complex models may help where several variables influence demand. They also require maintenance and monitoring. Retain the simpler approach if it performs as well and is easier for planners to use.
4. Data for workforce forecasting
Identify what each data source measures, how current it is and where information is missing. Completed jobs alone can understate demand when requests were declined or deferred.
Historical service data
Useful service history includes requested and completed work, date, location, work type and duration. Record cancellations, deferred requests and unserved demand separately where possible.
Skedulo Analytics can help teams examine the operational records captured in Skedulo. The available history depends on the data and workflows in use; forecasting models may require additional preparation, tools or integrations.
External signals and leading indicators
Potential signals vary by operation. Test whether a signal improves the forecast before relying on it. Examples include:
- Healthcare and community services: Referral volumes, discharge plans, recurring care commitments and relevant seasonal patterns, using appropriate data permissions.
- Field services and utilities: Weather, planned infrastructure work, maintenance schedules and inspection commitments.
- Residential and home services: Existing bookings, planned campaigns, construction activity and recurring service agreements.
- Telecommunications: Confirmed installations, network projects, customer orders and maintenance plans.
A signal can be useful without being precise. Record its limits, check whether it was available at the time of the forecast and avoid using later information when testing historical accuracy.
Workforce supply data
Compare expected work with current availability, working hours, leave, qualifications and location. Allow for travel, breaks and non-service tasks when estimating usable capacity.
Skedulo holds workforce and work information used in scheduling. Agree how those records are maintained and how planning tools receive updates; no capacity estimate stays current without those processes.
"Every time we've had an issue, Skedulo has had an answer."
Michelle McPhee — CEO, Integrated Disability Support Services
5. Using the forecast in scheduling
Agree who reviews the forecast, which decisions it informs and when a response is needed. A capacity estimate has little operational use if the team cannot adjust shifts, allocation or appointment availability in time.
The connection may be a planning review, a configured workflow or an integration. Automating it is appropriate only where the data and action rules are sufficiently clear.
An illustrative planning workflow
- A regional forecast indicates more work next Thursday than the current team can cover.
- The planner checks the expected work types, qualifications, duration and travel against available capacity.
- The team compares options such as adjusted shifts, cross-region allocation or eligible temporary staff.
- Approved changes are reflected in the schedule, and affected workers receive updated information.
- After the period, planners compare actual demand with the forecast and investigate the differences before revising assumptions.
Records from the service lifecycle help planners compare expectations with actual work. Skedulo can contribute scheduling and mobile records to that analysis; the forecast and any automated response need to be designed for the operation.
Reasons to review your forecasting process
- Recurring demand patterns are missing from the forecast.
- Overtime or temporary staffing repeatedly differs from the capacity plan.
- The team cannot explain whether a gap came from higher demand or lower workforce availability.
- Planners lack the records needed to test their assumptions.
- Forecast accuracy is measured only in aggregate, hiding regional or work-type differences.
- Forecasts arrive after the relevant staffing and scheduling decisions.
6. Planning with Skedulo data
Skedulo Analytics helps teams review the work and workforce data captured in their operation. These records can inform capacity planning and provide inputs for forecasting, alongside other business data.
- Utilization: Review how available time is allocated across teams and periods, using a consistent definition of utilization.
- Demand history: Examine recorded work by location, type and date. Include unserved demand from other sources where needed.
- Capacity comparisons: Compare expected work with available capacity using the appropriate planning tools or configured reports.
- Completion patterns: Investigate repeat visits and unfinished work where those outcomes are captured; they may affect future workload.
- Forecast review: Combine forecast and actual records to evaluate accuracy. Confirm the reporting or integration required for your model.
For broader analysis, connect relevant Skedulo records with your existing reporting environment. Confirm data access, refresh timing and the forecasting capabilities you need rather than assuming a dashboard includes a predictive model.
Skedulo customer research has reported 48% less scheduling time and 20% higher resource utilization. Those results cover customer use of Skedulo; they do not establish a separate benefit from demand forecasting.
