We have an App that allows field representatives to lookup through a set of 83,000+ records of previous sales. This allows them to see what product a customer previously purchased so they can buy another product of the same type. Customers often ask to have what they had last time but cant remember the exact product as it may have been up to 5 years ago when they last purchased. This data is populated in reference data displayed in a dropdown. Searching this data, even on a powerful device, can be very slow. On testing it seems that each individual keypress on the Search bar causes an immediate scan though the data to produce a subset of the data that is further flittered for each subsequent key press. This makes entering the search very sluggish. It would be better if there was a short delay after the keypress to see if a further keypress occurs before scanning through the data.
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Hi Richard,
Understand what you're saying here. I'm wondering if, as a work-around, there's a way to split your data so you aren't having to load the complete list every time, probably using some Dependent Reference Data. Could you classify your customers list in some way (by state maybe, or city?) so that you'd select that first, then narrow down the customer list, and from there get the list of products? Something like this:
If it's not set up by customer, you could also do it by brand or category of part, but using Dependent Reference Data to narrow the list should help speed things up.
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Hi thanks for the suggestions. However, the data in the App has already been optimised. Each record in the reference data that populates the drop down, only contains a customer name and their location. I should point out that the term "customer" is really an individual Patient at a customer's location. The products are personal ear protection that has to be tracked to an individual Patient. We do have another App that holds data in separate dropdowns for location and Patient, which can be used sometimes but Patients may be deployed to different locations over the lifetime (5 years) of an ear protection product so the only certain way of finding their data is via the big dropdown.
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