In a previous post, I looked at the Operations Management model of processes, with a view to comparing to the process of documenting artefacts in a museum.
In a factory, process calculations are fairly straightforward. Items and processes are standardised, and so a standard items takes a predictable amount of time to be processed on a standard machine. Factories know pretty accurately how many items they want to process, so it’s easy to work out how long it will take to complete the tasks.
If there are N items, and each one takes t minutes, then it takes Nt minutes to process them all. So the expression for total time, T, is:
Museums are not so straightforward.
The information that is recorded about each item can vary from museum to museum, although standards have been proposed. Some museums are happy with a minimal amount of information, but others prefer to complete a full research account of the item’s provenance, context etc. This makes it difficult to give an estimate for t, the amount of time required to process and document a single item, since it will depend on the amount of work required to generate an item’s documentation. Depending on local practices, each museum may be able to come up with a rough estimate of its own working value of t, at least for the minimum amount of information needed to identify and locate an item.
Next, we must count how many things need to be catalogued, N. Does every button in a box of buttons need to be uniquely identified, or is it sufficient to document the box and its contents as one item? Or each and every card in a collection of cigarette cards? Or every gold ring in a treasure trove? So, counting how many items need to be catalogued depends on the precision of the cataloguing task, which may depend on the uniqueness and value of the items.
So, although factories have clear ideas of how long it takes to process an item, and how many there are, museums do not share this precision. It would not be impossible to model mathematically the impact of a range of documentation times for articles of greater or lesser value and uniqueness, but I’m not going to do that here. Instead, we’ll work for now with averages and estimates, because that’s a good place to start.Back to top of article