The MES Solutions designed for the food, beverage and the pharmaceutical industries need to cover few extra requirements to be used along with eBRS systems. These requirements are mainly driven by regulatory requirements about how process data should be stored and protected to be able to be used as part of batch records.

The US FDA’s CFR 21 Part 11 has become the baseline requirement for MES system used in these industry even outside the US.

http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?CFRPart=11

An important section of this regulation is the requirement for linking records and signatures :

Electronic signatures and handwritten signatures executed to electronic records shall be linked to their respective electronic records to ensure that the signatures cannot be excised, copied, or otherwise transferred to falsify an electronic record by ordinary means  

MES Systems generally use Encryption Algorithms for Digital Signatures to satisfy this requirement. This means anyone who does not have the ‘Private’ key, will not be able to forge the signature and it is assumed that having access to the Primary Key is not considered ‘ordinary’.

While not explicitly said, using Database level security is not usually considered enough protection against ordinary tempering of the signature and that is mostly because of the preventable but prevalent loose security in DB level in industries.

Engineers frequently ask for and successfully acquire higher access rights that they needed for commissioning, maintenance and debugging systems. By having the access rights to add/update/delete records,  a user can easily clone signature data if they are not digitally signed. 

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?