Content Rationalization

An Automated Content Rationalization approach for Transforming Learning Experience

Executive Summary

Rationalize: to apply the principles of scientific management to (as an industry or its operations) for a desired result (as increased efficiency). - Merriam-Webster

As the learning industry shifts its focus to a personalized learning requirement, the existing learning systems need actionable strategies to help them meet new cost and quality goals. Rationalization—whereby a system centralizes or co-locates similar content within a given domain—is one such strategy. With the right framework in place, rationalization can position a learning system to avoid duplication of content, ensure content is delivered in the optimal setting, and reduce the overall cost of learning.

What is Content Rationalization?

Content rationalization is the process enables content to be organized, tagged and available to the appropriate target audience. This can improve future search results - if learners cannot find content it has little chance of being effective or successful.  Moreover, cleanup of content benefits multiple learning stakeholders.

Why Content Rationalization?

Content rationalization extends the value of training by determining which courses to consolidate, promote, invest in or sustain. Based on Cognitive reviews of content and metadata, coupled with analysis by Learning SMEs, content will be categorized for recommended action as follows:

∙ Consolidate: Combine or eliminate due to overlapping or duplicate content. Sunset or archive content due to underutilization or outdated content.
∙ Promote: Raise awareness and promote relevant content that is underutilized. Ensure clear communications, accessibility, mapping to target audience, etc.
∙ Invest: Update, convert or create new content.
∙ Sustain: Maintain as is, with no recommended changes. (Identify timing for maintenance/review intervals going forward).

How to adopt Content Rationalization for your organization

• Confirm a inventory template
• Defining the Scope of Rationalization

• Identify and tag different types of mat
• Tag learning material by Language, File Type
• Provide count of learning objects

• Automate the Clean-up process

• Remove duplicates (ex: By matching content title)
• Remove duplicates (content to content match) (should include all file types)
• Display existing meta-data for content
• Curate content further based on existing meta-data (year of publication for instance)
• Provide fresh count of the objects

Recommendations

The amount and depth of recommendations will depend on the completeness of content analyzed and further examination by the learning team and SMEs. These areas may be flagged for deeper analysis.