Content Transformation for Intelligent Content
As content demands scale, so too does it need automation, cross departmental collaboration and, at the same time, the quality and consistency to ensure accurate information—all of this means we need to make content intelligent.
Taking existing content and turning it into intelligent content requires a content transformation strategy. Content transformation expert, Val Swisher, of Content Rules, shared with me how to embark on this journey using a component content management system (CCMS).
Arpita: Val, can you share some thoughts about what content transformation is and how to start this journey?
Val: Content transformation allows organizations to adopt a structured approach to how they create, store, manage, publish, and sunset content. This approach starts preparing content and organizations for digital transformation and the future.
There are many ways to divide the tasks needed to transform existing content for structure, but I think these three are essential:
- Define content architecture
- Curate existing (legacy) content
- Transform the content for the new architecture
Step 1: Define Content Architecture
- Content models
- Reuse strategy
- Taxonomy and metadata
- Workflow
- Governance
- How to walk the dog
- How to feed the canine
- How to groom the pooch
- How to train the hound
- Creating
- Writing
- Retrieving
- Tagging
- Reviewing
- Checking in
- Publishing
- Sunsetting
Step 2: Curate Legacy Content
Step 3: Transform the content for the new architecture
- Write in small chunks. The longer your chunk of content is, the less likely it will be reusable. On the other hand, shorter and more focused chunks of content are easier to reuse in a variety of settings.
- Standardize terminology. It is so important that I want to repeat it here. In order to make content reusable, we must use the same words to describe the same thing.
- Avoid dependent language. Because each chunk of content must stand on its own, you need to stay far away from dependent language. Dependent language includes:
- A chunk of content that refers to another chunk of content
- A chunk of content that requires users to read another chunk to understand this one
- Words that anchor the content in time or space