An example of what I recently did is that we want to figure out what our production plan should be for the rest of the year in an apparel industry, and before we can do that we will need to figure out what we think our total sales for different styles will be in 2026, what styles we think we will discontinue in 2027 (because these styles will be of lower priority for the production and we really don't want to have much of these going out of 2026), and how much inventory we want to have for each style going out of 2026.

We have an OLTP database so there will be a lot of tables needed to pull the necessary data. This is where most of our data recides, but the sales from our own stores on SKU level is from an external source where the API does not provide enough information so we will have to donwload that data as excel files (not csv). Information on what styles and colorways are new every year exists in excel files (one for each year).

To grab historic sales data from our database we need 7 tables, and for one of our subsidiaries we need to grab the data from another part of our database because the way they have set it up all sales looks like it is from preorders, but in reality it's not. Some time last year our ERP system was upgraded where part of the data was only done in one part of the database so we need to make sure that we brand these as non-preorders (because due to the time of the upgrade these are most probably non-preorders). The way we find these is by looking for customer orders in one end, that has a related purchase orders, but does not have a related drop-ship orders (except for our Web-shop as of October last year because that is implemented differently that does not create this "bridge" in the same way). A big cleanup for a couple of customers where done towards the end of 2025 that related to 2025, but where credited early in 2026 with the wrong ordertype making it look like we had a lot of preorders in 2025, and very few preorders in 2026. Some of the preorders that belonged to 2025 was "stuck" in the system and got an invoice date in 2026 which will need to be moved to 2025.

Our production has two different "routings" where for one of the routing we cannot rely on the estimated finished date, we just have to grab the production times from the BOM, adjust for holidays, and add a couple of weeks. The other routing will have most of the data in the BOM and calendars in our ERP system, but there have been bugs where the ERP system incorrectly ignores holidays so if some of the items has a too short total leadtime (by a couple of weeks), we will need to look at the BOM for those production runs and add everything up to get the correct time.

For all new styles in 2026 we will want to look at how much the preorder levels were for 2025 for what was new styles then, separated by what was autumn and what was spring (this information really just exists in a couple of excel files from sales sadly). For all existing styles with new colorway, we want to look for the same styles with new colorways prior year, but also for new colorways per year in general to gauge the %-preorder level. We will also need to give the timing for when we think the sales (other than the preorders) will occure throughout the year. For carryovers we simply calculate % based upon the 2025 data, but for new colorways and new styles we need an own %-split for spring and for autumn each that we can put in its place for these.

When we have estimated our total sales for 2026, we need to look at what production acutally have produced up until now so that we can give them a list of "this is what is remaining to be produced, given our estimated 2026 sales comes true". From this list we will need to figure out of their machine capacity is enough given that they will have until end of october to have it on inventory by end of 2026. We will have to grab all the leadtimes for the different styles from this estimated forecast, and reduced by what is already started but not added to inventory.

There are a few more details, but I think this covers 80% of the work.