In-home aged care providers hold commitments to clients and workers that they cannot easily walk back, against thin margins. Much of the effort to protect those margins goes into day-to-day decisions. But the limit on what those decisions can achieve is set earlier, by structural choices made long before: how wide service visit windows are, how many carers a client is promised, and how shifts are permitted to be constructed.

Providers set these parameters deliberately. Few can say what they cost. A commitment to a small, consistent care team carries a price in travel time, utilisation and cost per hour of care, and providers rarely quantify it before committing. As a provider grows, the same decisions compound.

Using advanced optimisation algorithms, we model how key decisions affect performance across a representative fortnight of service delivery, drawing on de-identified datasets from Australian providers in metropolitan and regional service areas. For each set of rules, we considered the best schedule achievable, rather than reproducing what a provider’s current process would produce. Our modelling accounts for travel time, award and enterprise agreement conditions, qualifications, client preferences and carer familiarity, and the scenarios tested reflect policies in use today. Outcomes are measured in cost, coverage, and the experience of clients and care workers.

We report findings on three levers.

• Service visit window flexibility. Widening scheduling windows reduces travel time and improves utilisation. We quantify the effect on cost and coverage across the range of window widths providers use.
• Care team size commitments. We present the trade-off curve between coverage and disruption, and what each additional carer admitted to a client’s team costs or saves.
• Shift construction constraints. Limits on broken shifts, minimum engagement periods and the daily volume of domestic assistance shape how attractive shifts are to care workers. We report what tightening each beyond its award minimum costs, and where thresholds can be tightened cheaply.

Benchmark results are reported separately for metropolitan and regional service areas.

Attendees will leave with reference points for judging what their own structural commitments cost.