This customer has lots of shops across several Nordic countries. Their retail business consists of selling flowers. Items are constantly moved around the shop, numerous promotions are being run, and orders vary from week to week drastically. Therefore, M3’s standard set up of locations is not flexible enough when it comes to picklist handling and picklist reporting. The app is all based on standard M3, so there are no modifications within the software, but we have developed a way to use M3 customize tables (CUGEX1-CUGX3) as a “layer on top” of standard M3. Because of this, we can keep track of customer orders that are ready for picking (status 44). Moreover, in the app, you can plan how to print out and do the picklist across customer orders. This enables the shop manager to plan the pick and pack in a way that proves the most efficient. The application is “workflow-based”, which means there are different steps to follow in the application itself. The application runs within M3’s H5 client due to the close relation to the users which exist in M3. So, the setup of users in M3’s MNS150 is vital for when displaying shop/users. The application is also responsive, so you can run it on handheld devices. We use several list transactions configured in M3’s CMS010/015 to create CMS100MI APIs. The application is using M3 rest APIs for both updates and lists of M3 information. No SQL is used to retrieve data. The application is installed via the H5 admin tool and you can start the app as an H5 favorite.
Some examples from the different steps are shown below.
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Here you choose which orders to print on a special picking list. CUGEX3 is taking care of the picklist lines – with a “unique” picklist number saved in the table. The document is printed with barcodes and as a PDF.
After the picklist is reported and packed, the customer order in M3 gets status 66. From there, it is sent to a transportation system that takes care of printing out the label for delivery. We are working on a rest api interface for this application as of now in Q1 – 2020.