Faster Filtering to Get to Your Good Content—or Not

Just when associations are getting comfortable with a role as content curators, they now must shift into a proliferation of content filtering strategies.

Or so the Institute for the Future forecasts in its knowledge and learning research for the ASAE Foundation.  This shift is from expert filtering (tell us what is important and what it means) to algorithmic, contextual, visual and crowd filtering (help us tell each other what is important and why). 

Algorithmic and contextual filtering is a smarter search that intuits what we really want to find.  Machine intelligence will keep getting better at anticipating our content needs based on our contextual patterns.  Google will get there first. Associations will have to follow quickly if they want their members to continue seeing them as a valuable resource.  Associations investing in content management, creating taxonomies and tagging content, are hastening the potential of smart search.

Visual filtering orders data in ways that help make sense of the content in ways that lists of numbers and text cannot. Infographics and visual representations of data analytics are early signals of this shift. 

Given that affiliation should be an association core competency, associations are moving quickly into social networking that encourages crowd filtering.  This can be as simple as communities of practice exchanging information and resources. Associations are also experimenting with recommendation rating systems to help members find the favorites others have found useful. I definitely use Twitter and LinkedIn for crowd filtering.  If a colleague I know through an association membership recommends an article or identifies a new issue, I know the reference will have some relevance for my work.

Associations will become adept at facilitating this proliferation of filtering strategies. For most this will be just an  incremental shift in how they help members find valuable content.  Granted this incremental shift will still require yet another generation of technology investment, even greater openness to member collaboration, and development cycles that can keep up with emerging knowledge needs.  With more ways to filter content, people will discover quickly when an association simply has nothing to offer on a vital topic.

This is why I believe IFTF should have included in its forecast an important filtering strategy of another type: consistent and systematic environmental scanning. If you are not systematically discovering what your members will need before they do, you have absolutely little chance of creating the knowledge they expect to find using these faster filtering strategies.  

You do not want your smart search engine to return the answer “no matches found”. And the last tweet you want to read in your social network is that your association is clueless about some looming change.

These new filtering strategies can deliver people faster than ever to your best content if you have it or direct them away to people and organizations that do.  Ours is not a patient age. People will not wait until the technical committee sorts out an answer or your research confirms a best practice.  These new filtering strategies will only increase member expectations and impatience.