By: Brian J. Stewart
Content Management is about more than simply ‘managing content’ and replacing traditional file shares with new content repositories. Before designing a taxonomy, organizations need to clearly identify business objectives and the problems that an organization hopes to resolve with the new content management system. It is best to center taxonomy design around eliminating common content management challenges such as compliance risks, quality issues, safety concerns, data issues, and business process inefficiencies. Too often taxonomy design is constrained by ‘legacy system syndrome’ where the new system is designed similar to the old system, rather than around current tangible business objectives.
Too often taxonomy design is constrained by ‘legacy system syndrome’ where the new system is designed similar to the old system, rather than around current tangible business objectives.
Beyond designing a taxonomy around clear business objectives and measurable Return on Investment (ROI), there are five critical success factors of an effective taxonomy and metadata model design:
Success Factor #1: Terminology Consistency
An effective taxonomy ensures terminology consistency across the taxonomy itself, but also enterprise systems. Terms should have the same meaning across systems. A consistent naming convention should be followed for attribute or property names. For example, ‘Product’ should not mean ‘Product Code’ in one system and ‘Product Name’ in another system. Also as another example, a multi-valued attribute/property should not be plural (i.e. Keywords) in one case and singular in another (i.e. Author). In addition to attribute or property names, object type or content type names should also be consistent, and singular names are always best for content or object type names.
Beyond naming conventions, it is important to also have consistency with the granularity of object types or content types. Specifically, an object type name shouldn’t be general in some cases (i.e. Training Material) but granular in others (i.e. Work Instruction). And always, careful attention should be made to grouping or hierarchy of object types or content types.
Success Factor #2: Data Consistency Across Repositories
Organizations need to look at data not through the prism of a single system, but rather through the spectrum of the entire business process which often spans many systems.
Organizations need to look at data not through the prism of a single system, but rather through the spectrum of the entire business process which often spans many systems. An effective taxonomy leverages a Master Data Management (MDM) to facilitate enterprise application integration and business intelligence. Organizations should invest in MDM despite the significant complexities, challenges, and implementation costs. Throughout the past several decades, organizations invested significantly in enterprise content management solutions. Each solution aimed at automating specific business processes. This created significant volumes of inconsistent data which cripples enterprise application integrations and impacts data quality. It also makes MDM adoption a significant challenge for most large organizations. Adopting MDM means existing systems need to be modified and existing data mapped to a consistent global dictionary. This data mapping requires extensive manual effort.
With new systems, architects and system analysts should ask “from where can I get this data list?” before creating any new dictionary that organizations must maintain. Very few data lists or dictionaries are truly “unique” to a single system.
Success Factor #3: Facilitates Operational Efficiencies and Business Intelligence
An effective taxonomy should be centered around driving operational efficiencies and business intelligence. In the global and hyper competitive business environment, organizations need to continually improve employee productivity and decision making.
It is important when designing a taxonomy to remember that for each attribute or property a user must enter the data for each and every record that is created. Large numbers of attributes or properties often lead to confusion of what values to enter and undoubtedly leads to ‘bad data’.
It is important when designing a taxonomy to remember that for each attribute or property a user must enter the data for each and every record that is created. Large numbers of attributes or properties often lead to confusion of what values to enter and undoubtedly leads to ‘bad data’. For these reasons, it is important to clearly weigh the needs and benefits of adding each and every attribute or property. This scrutiny ensures that systems and taxonomies improve operational efficiencies rather than create hurdles and obstacles.
Equally important is to design a taxonomy to facilitate business intelligence upon system implementation. Too often business intelligence is an afterthought, “how can we derive insights from our existing data”, rather than “what data can we capture to drive efficiencies and insights”. Automating the capturing of metrics and data throughout a business process will enable organizations to draw competitive insights and optimize business processes.
Success Factor #4: Improves Discoverability of Information
An effective taxonomy ensures that consumers of information can easily and quickly locate content. A common frustrating user experience is repeatedly performing a search while trying to locate content that is known to exist.
To facilitate the discoverability of information, the taxonomy design should ensure:
- Inclusion of all necessary properties and attributes for various content consumers
- Expected data values for properties and attributes through unambiguous, consistent, and precise data dictionaries
- Identification of appropriate required fields for all object types or content types
- Data consistency through an intuitive metadata model (users should intuitively know what values to select for all properties or attributes, rather than leave to chance or leave blank)
Success Factor #5: Sustainable model for growth
Finally, the taxonomy design needs to be sustainable. A sustainable taxonomy design is:
- Flexible to support additional object types or sub types
- Intuitive for end user consumption and creation of electronic records
- Adaptable for enterprise applications integrations and business process automation
- Streamlined design which supports easy and consistent creation and maintenance of accurate metadata
- Lightweight design which is not burdensome for content producers and consumers
- Leverages common terminology across enterprise
- Leverages common dictionaries for data consistency
- Scalable for data storage and retrieval (it’s important to understand the internal constraints and design of the underlying enterprise document management platform)
The taxonomy and metadata model design should not be rushed or developed in a vacuum.
Although existing legacy data and the mapping of the existing data is an important consideration, the taxonomy design should be primarily forward looking.
Although existing legacy data and the mapping of the existing data is an important consideration, the taxonomy design should be primarily forward looking. The following are the key success factors for an effective taxonomy and metadata model design:
|Data consistency across repositories|
|Facilitation operational efficiencies and business intelligence|
|Discoverability of information|
|Sustainable model for growth|