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Ten Common Mistakes When Developing a Taxonomy

During the course of our consulting engagements over the years we have seen businesses make all kinds of mistakes when developing taxonomies. We see these common errors whether the taxonomy is to be used for content management, document management, or search development. In some cases, taxonomies are used as master data and reference data for ERP systems. These gotchas still apply.  

  1. Mistaking taxonomy for navigation.
  2. Trying to use an “out of the box” or pre-built taxonomy.
  3. Creating an overly granular taxonomy.
  4. Not maintaining the taxonomy.
  5. Taking an academic approach.
  6. Incorrect implementation.
  7. Improper technology.
  8. Inadequate tagging of legacy content.
  9. Lack of tagging compliance for new content.
  10. Incorrect auto-tagging set up.

1. Mistaking taxonomy for navigation.

For some time many design firms and information architects referred to navigational structures as “taxonomy”. This is one possible application of taxonomy and we do have navigational hierarchies. But taxonomy is not the same as navigation. We need to consider classification as opposed to navigation. We can then create multiple navigational structures from a single classification mechanism (this will contain multiple “facets” or trees)

2. Trying to use an “out of the box” or pre-built taxonomy.

There may be standards that can be leveraged for creating a taxonomy, but starting with a generic industry vocabulary or a very large term set can lead to additional work and take the project down the incorrect path.

3. Creating an overly granular taxonomy.

Many efforts lead to taxonomies that are at too fine a level of detail to be practical. Taxonomy design can make or break a customer experience.

4. Not maintaining the taxonomy.

A taxonomy is a living, changing entity. Some organizations spend adequate time on development but then do not have the correct resources and processes in place to maintain the taxonomy after it is deployed.

5. Taking an academic approach.

There have been projects that have employed librarians that were not well versed in the practical application of taxonomy. The end result was a taxonomy that was “correct” in theory, but not practical for the business.

6. Incorrect implementation.

Some organizations have handed off the taxonomy to the development organization without a close partnership with the developer of the taxonomy. That has led to “bolting” the taxonomy on to the application as a navigational structure as opposed to integrating into the core architecture.

7. Improper technology.

The correct technology needs to be available to leverage taxonomies - especially the so called “associative” relationships from a thesaurus structure. Ontologies for ecommerce goes beyond taxonomy.

8. Inadequate tagging of legacy content.

If the taxonomy is not applied to content that already exists in the system, the benefits of the taxonomy will not be fully realized.

9. Lack of tagging compliance for new content.

New content needs to be correctly tagged by content curators. There are a number of considerations here but at the least there needs to be a quality metric to ensure that tags are appropriately applied. How to get people to tag documents.

10. Incorrect auto-tagging set up.

Automatic (rules based or statistical) classifiers can be incorrectly configured which will lead to poor results.

We minimize the risks of these by adhering to the correct methodology but also applying judgment and experience to the process. This means not adhering to the process blindly, but taking into consideration exceptions and validating assumptions and choices with user experience data.

For a deeper dive into our approach to improving the customer experience through data models, taxonomy, and attributes, read our whitepaper: Attribute-Driven Framework for Unified Commerce.

Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

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