Not every order requires the same amount of work from the delivery team. A small box and a large set of panels may both count as one order, but need different amounts of loading space and preparation. To use Checkout & Delivery for heavy baskets, first decide on a useful measure of planning capacity. The right question is what practical workload the shop can substantiate, not how many orders a calendar can technically display.
Start with two clearly different orders
In a fictional webshop, one order contains two light accessories and another contains twelve large worktops. Ask the planning team what constrains each order. It might be loading space, unloading time, lifting assistance or preparation. Then choose a small number of recognisable order types. A simple classification that employees can explain is often more useful than a precise calculation based on product data that is not maintained reliably.
Involve the warehouse too. Large items might only be prepared later in the day, or certain combinations might not be loadable together. The relevant constraint must be reflected in the data and working agreement before it can drive the calendar. The existing Yindle delivery component includes capacity in planning. That does not establish a general automatic calculation of volume, weight or staffing requirements as a standard feature; this needs a separate design.
Choose a limited rule for the pilot
An initial implementation can distinguish regular orders from large orders requiring assessment. Clearly describe which product groups or quantities require an extra check. Avoid an invisible threshold that customers only discover after payment. When manual planning is needed, checkout should explain what happens next with the request. A provisional day must not suggest a confirmed appointment while the team still needs to assess practical feasibility.
Record who maintains the classification and what happens when product data is missing. An unknown weight does not necessarily mean an item is light. Have the shop deliberately choose a route for incomplete information. Use a clear message for the employee assessing the order. The operational value comes from getting a heavy basket to the right person early, with the context they need to discuss a feasible time.
Test a changing basket
Use fictional items to create a standard order, a clearly large order and a borderline case. Then increase a quantity during checkout and check that the explanation still fits the revised order. Next, remove a large item. The selected route should follow the current contents. Also examine the planning order view: can employees see why an extra assessment is needed without reopening every product page?
Also check that employees can still recognise an order type when a product name changes. The practical classification should rely on the intended product characteristic and maintained data, so a wording correction does not acquire a new meaning for planning.
After a few trial cases, assess whether the classification works. Unloading time might prove more important than order value, or one product group might consistently differ. Update the rule based on concrete findings like these. You can discuss the transfer of data to planning through Yindle Connect; for special calculations or assessment screens, consider custom software as an option. The result is a planning choice that better matches the practical size of an order, with a clear human follow-up for exceptions.