Recently I was in an MES bootcamp and in interesting debate started among representatives from two companies working in two different domains.
The debate started around relative complexity of Production tracking solutions and Inventory tracking solutions.
To understand the problem it is important to have some basic understanding of the meaning of these two terms in the context that people were using it:
Production tracking is recording the information about activities performed in a plant to make a product or deliver a service. for example the number of tonnes passed through a washing machine can be a production figure.
On the other hand, Inventory tracking is trying to provide information about quantity and quality of materials in a plant or more precisely in storage locations. going back to the washing machine example, the amount of material before and after the washing machine work-cell would be an inventory information.

by my example it sounds like the inventory tracking is a more advanced and challenging task, especially because we know that we can 'infer' the production tonnes if we know the inventories over time.

This is like trying to compare Derivatives and Integrals in calculus. It is probably a useless argument anyway. We know in some industries like food or high-tech, the production process is very complex while little or of little value inventory is maintained.
In contrast, going to bulk material processes, usually the production processes are very simple, but the value of the inventory is of more interest.

This may sound a simple and easy resolution, but in reality things are never that easy!
In projects that I have worked in, although theoretically these two sets of data could be inferred from each other, but as a matter of fact they tend to live independently and most of the time in an inconsistent manner.
It is a good practice to think why this happens and how we can marry these two data sets. Is it even possible and wise?