What it means
A grocer may offer customers a choice of delivery windows, and each window has limited driver, vehicle and route capacity, so utilisation shows how much of that offered capacity customers take. Start by defining the unit, because one "slot" can mean a customer appointment, a capacity unit on a route or a one-hour time window.
A ratio of booked slots to offered slots is meaningless if one slot can hold very different orders. In a simple illustration, 720 booked capacity units out of 900 offered units gives 80% booking utilisation, which says nothing about whether all 720 deliveries were completed.
Failed deliveries are not a success simply because a slot was booked, so track failures, cancellations and completed stops separately, since a no-answer attempt may consume driver time without finishing the service. Cancellation timing matters too, because an early cancellation frees capacity for reuse while one after route planning may leave a gap.
Capacity may differ by zone and by order, since a van can complete several nearby stops in an hour but fewer widely separated ones, and a single small grocery bag and a large furniture order should not necessarily consume one identical unit. Use weighted capacity units when the operation requires them.
Research on attended home delivery treats routing and delivery-window demand as linked decisions, so capacity is not simply empty calendar space and a new booking has to fit a feasible route. Evening windows may fill faster than midday windows, and a weekly average can hide evening shortages and idle midday capacity, so show day, hour and area before deciding to buy another van.
A very low booked share can indicate excess offered capacity, unattractive times or a website that fails to present relevant slots, whereas a very high share can leave customers with no convenient choice. Track next available slot and failed slot searches along with utilisation.
Managers may offer price differences or incentives for less busy times and test them against actual routing cost and customer fairness, because lower fees can shift demand while a longer detour could erase the benefit. A wider window can give a route planner flexibility but is less convenient for the customer, so do not improve an internal ratio at the expense of unreliable promises.
Capacity forecasts should include driver hours, vehicle availability and loading time, since store picking delays can make a nominal slot unusable, and outsourced capacity should match the carrier's confirmed allocation. Record offered, booked, cancelled and completed units in the same period and add on-time rate and cost per delivery, so one chart shows whether fuller windows improve service and economics.
Compare similar periods or label unusual events such as holiday weeks, weather or promotions. Avoid a universal "good" target such as 80% for every business, since the best range depends on variability, urgent-order needs, service promise and route density.
In practice
Real-world examples.
Example
An invented grocer books 720 of 900 offered capacity units in a week, for 80% booking utilisation. The planner then checks how many of those bookings were completed before deciding whether to add a van.
Example
A furniture retailer compares bulky-order capacity separately from small-package appointments. A sofa takes four capacity units while a cushion box takes one, so a single count of appointments would hide the difference.
Example
A retailer keeps some same-day slots unbooked until later for urgent orders. Reported booking utilisation looks lower, but the unused slots are a deliberate service reserve rather than wasted capacity.
Formula
Calculation
Booking utilisation = Booked capacity units / Offered capacity units x 100
Worked example. A fictional grocer offers 900 capacity units in a week and customers book 720.
- Booking utilisation = 720 / 900 x 100 = 80%.
A completed-delivery view is different. If 36 booked units are cancelled too late to reuse and 24 deliveries fail, completed units are 720 - 36 - 24 = 660, and completed utilisation is 660 / 900 x 100 = 73.3%. Use consistent units and track both measures.Case study
Seen in the real world.
This entirely fictional case follows Fresh Basket Grocery, an invented online grocer. Midday slots were rarely chosen while evening slots filled early. The team compared booking, completion and route costs by area, then tested a midday incentive. No improved utilisation or avoided vehicle purchase is claimed.
At the start, midday booking utilisation averaged 40% while evening slots were close to 100%, so the weekly average of about 70% looked healthy. Splitting the data by time and area showed that customers in two suburbs could not find any evening slot, and several tried again the next day. The grocer widened a few midday windows and tracked next available slot alongside utilisation, so it could see whether the change helped customers as well as the ratio.
Watch out
Common mistakes.
- Using a weekly average that hides peak-hour shortages.
- Counting booked appointments as completed deliveries.
- Offering more windows than the real route and driver capacity can support.
Questions
People also ask.
What is a good utilisation rate?
There is no universal target. Balance booking demand with service reliability, customer choice and disruption capacity.
How can demand shift to quieter windows?
Test suitable fees or incentives, wider windows and clearer choice, while measuring route cost and customer response.
Should every slot have the same capacity?
Not necessarily. Route location, order size and available drivers can make capacity vary.
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