Should departmental or organizational structures be managed as a taxonomy?
While there are advantages and limitations to organizational structure as an aspect of taxonomy, and organizational structure is a valid major facet or category within a comprehensive taxonomy, it is not an effective overall taxonomy. As an example, while:
Division > Line of Business > Department > Sub-Department
may work for some organizations' collaboration community site structure…it’s not wide enough to cover vertical content that cuts across multiple LOB departments. Things like applications, resources, policies & procedures come to mind. And, it just plain doesn’t work for some organizations where group names and job title have little to do with the actual ‘aboutness’ of a person’s avocation.
Another potential problem with using Org Structure as your only or primary taxonomy structure is that it also fails to address the difference between internally 'public facing' information that is intended for all employees or all those with a login ID (for intranets) vs. private information intended to be visible for members of departmental teams only. For many entities in the organization there may be a need for both,
When we draw up conceptual maps containing categories that will accommodate lists of terms within specific entities, content types, facets, or processes...we start to create 'MindMaps' of organizational constructs that are initially in competition with one another for attention within the 'labeling & indexing' universe where Users will think to find the bit of information that they are looking for. It is our job to connect related sets that live under different headings via associative relationships. I am not saying that a facet for 'department of origin' is not valid, in fact it is often more important that the actual Author's name in a dublin core-emulating type of classification system, and it can be used as a refiner against the search results to provide 'browse within search' capabilities.
It is important to look at these things from multiple angles that factor in holistic approach that includes both a bottom up approach (focused on content & process analysis) and a top down approach (focused on Buttons, Tabs, & Labels). This incorporates the best of Library Science type IA (taxonomy & terms from the bottom up) and Web Design type IA (navigation systems and category buckets labeling from the top down) that are both more effective when they meet somewhere in the middle. It has been my experience that for certain types of organizations that have public facing communities of practice and heavy emphasis on service to the community at large (healthcare, hospitals, public health agencies, and drug companies, for example) the Org. Chart just doesn't work as a good IA framework. The reason being, that their groups are difficult to define, they change names often, merge and morph into one another, and simply do not roll up well to discreet parent categories.
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