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I worked in a DC for one of the supermarkets and the pick rate is closer to 200 cartons per hour. Cartons contain multiple units and can be pretty heavy depending on the product. It's not for everyone, even with incentive paid on top of a healthy union wage, most people would quit after a few months. The good pickers made it look easy. Some had been working there 10, 20 years.
If these tools are necessary to conduct business and they are so worried about being able to support it, why don't they use proper software for that process?
A lot of people who make these bloated spreadsheets are people with no education in computing, and don't think about the basics of how to store data that is easy to analyse later. If they are building a weekly report, they build the report and enter the data directly into the report structure, which then makes it almost impossible to analyse later. Next week they just copy the file, rename it and update the data. If you want to analyse that same data over a year, good luck! You can't even count on the data being in the same place over the 52 weeks, since they would have added and removed data points over time.
Once I got the process down in a jupyter notebook, handling all the oddities with the data coming from whichever website, CSV file, data warehouse report I need, I can just save it as a .py file and run it as a scheduled task on a virtual computer forever. The data is kept in a format that can be appended to with each update, and can be easily analysed later.
The most amazing thing with replacing excel with python is you don't need to manually perform the update process yourself. Which means it doesn't cost anything to run the process more often. Weekly reports can become daily, or even hourly email updates that are only sent when something interesting happens. People can start reacting to things shortly after they happen, rather than having to remember what happened a week or a month ago. The iteration on improving becomes so much faster. People spend more of their time discussing how to fix problems, rather than spending time building problem finders. You can even start to automate the fixing of the problem in python and people don't even have to spend time on that thing at all, ever again.
As someone else mentioned, if they are quieter than the diesel equivalent, you may be able to start delivering to supermarkets in areas where they have curfews on deliveries after a certain time because of the noise.
I think an electric car the size of a Toyota Yaris / Honda Jazz would be a big hit in Australia, since that category has been popular for decades. Whereas I think the only popular sedan nowadays would be the Camry, and they are mainly used for taxis. Family cars tend to be SUVs with underpowered petrol or diesel engines to try and get the fuel economy, even if it struggles to climb hills.
Another big seller I think would be a plug in hybrid ute similar to a Hilux, since they are the main vehicles used by tradies. If you could get maybe 100 - 200km of travel using electric only and then petrol for the rest, I think that would be suitable for people who mainly work in metropolitan areas. You could also use the battery instead of carrying a petrol generator.
Another tricky problem I thought of would be a double trailer that can be side loaded would take a single dock, but a double trailer that has to be rear unloaded would take two docks. Also zoning docks so a refrigerated truck can't dock at a dry goods dock, or customers may want to make sure certain suppliers use the dock closest to where they need the goods. As in you wouldn't want to unload the truck and then have to move the pallets hundreds of metres to the storage location.