A corporation’s Learning and Development department often acts as a funnel. Learning content is generated from the L&D function in a model where bottlenecking occurs as different departments vie for L&D’s resources, reducing productivity and compromising desired business results. An emerging model for L&D is that of information filter where valuable information is collected and filtered from the very beginning of the project lifecycle.
Let’s imagine that a large corporation has moved up its launch date for a new product, a first-to-market super widget that the company anticipates will be a strong source of revenue. All company employees, partners, and customers need their own specific training on the widget right away. Will L&D have the bandwidth to add this new training to an already full training plan? Can the company wait six weeks to six months for formal learning solutions? How much will this new training cost and can it fit into L&D’s budget? Will the developers of the product and other employees have time to serve as SMEs while training is being developed?
Even a well-organized company’s race to market with a new product or service can catch many departments off guard. L&D now has at its fingertips the tools to accommodate these initiatives while also facilitating information flow for all stakeholders and end users from the very beginning of the project.
Traditional L&D
In the traditional role for a learning and development department, formal learning content is created and then widely distributed to end users. Producing high-quality formal training can be expensive and time-consuming, and given these constraints, L&D may not be able to integrate end-user input into the formal learning programs for the new widget. Many insights that are shared informally along the project lifecycle are often not included in the formal training, and so by the time the formal training is completed and delivered, it’s often stale on arrival or constrained to widget fundamentals. Productivity and desired business results may have been compromised and learning opportunities may have been lost.
The Filter Model
An emerging model for L&D is that of information filter, where L&D builds community around the new widget at the beginning of the project lifecycle and then collects and filters valuable information as the widget is being developed and tested. L&D then disseminates critical pieces of that information informally and in a timely manner while concurrently using it to develop formal training.
In the filter model, content generation begins before the widget is manufactured. Engineers and developers blog about the widget; testers film one-minute videos of the perceived benefits and uses of the widget; and sales people can post questions about the widget and get quick responses from the engineers or product managers. L&D initiates and monitors these discussion areas, which then inform the formal learning that is produced. By leveraging the available expertise early in the process, L&D can do more with less and get the entire organization up to speed much faster.
These results positively impact the bottom line. Once the formal learning events have been released and after the widget has been launched, L&D provides follow-up activities and communities of learning and communities of practice that will continue to capture valuable learner insights and provide informal job aids and performance support tools, helping to improve productivity, awareness and the bottom line.
Implementing the Filter Model
The filter model requires that L&D work with clearly defined learning goals and objectives to assess existing platforms and architectures in determining technology needs, obstacles and culture change considerations. A company SharePoint framework, for instance, may provide a heavily integrated set of content management tools, but over time, the integration of other technologies along with unaddressed server provisioning may have caused slower load times or other accessibility issues that hinder and even discourage the use of informal updates, video uploads, discussions or collaboration.
More and more, companies are turning to cloud-based SaaS solutions that offer SCORM-compliant, socially driven environments which foster creativity and problem solving while providing the governance and security controls required by the corporation. Next-generation LMSs – like Wisetail, Topyx and offerings by Expertus One – give L&D the ability to manage the learning path, monitor performance and drive discussion while leveraging commonly used social tools. What’s more, metrics can now be derived from social interactions.
With the rollout of the Tin Can API – the new and improved SCORM – next-generation LMSs and authoring tools are able to address the tracking and reporting of social metrics collected in these new environments. Essentially, content is no longer limited to SCOs (Sharable Content Objects), which for years have been at the heart of SCORM. Content has now become part of a larger “superset” that the developers of Tin Can call “activities.” With Tin Can, content (or activities) live outside the LMS until they’re completed by the learner. This allows for a cross-domain approach to SCORM: next-generation learning environments can co-exist on separate servers and still report back to the LMS. News flash: The C-suite can now have all of the social learning metrics they’ve been asking for!
When implementing the filter model, organizations should create informal environments at the beginning stages of product development or the project lifecycle. Whether developing proprietary environments or dusting off pre-existing ones, or implementing hosted SaaS solutions, L&D at the outset should provide the means for all stakeholders to share insights. These informal environments should be monitored so that important insights can be gleaned for concurrently developed formal learning solutions.
Leveraging Existing L&D Resources and Tools
A typical L&D team for developing formal training might look like this: Manager, Project Manager, IDs, development personnel and graphic artists. Let’s call it the formal team. The new filter model includes an informal team as well, one that operates concurrently on the same learning initiative as the formal team. The project manager coordinates the efforts of both teams.
The informal team is made up of an ID and a social learning manager, someone who can apply their knowledge of the company’s current social tools and who can assess the need for and make recommendations on any new social tools that should be deployed for informal learning purposes. The role of the informal team is to establish the appropriate social environments; seed them with informal learning nuggets (like webcam videos, documents, schematics, recorded hangouts and chat threads, and other social objects); build community; and facilitate discussions among all relevant groups at each stage of the learning initiative.
As the formal team develops the structured learning pieces – practiced-based solutions, simulations, performance support tools, in-depth resources and job aids – they are now informed not only by SME and key stakeholder input, but also by valuable learner insights gathered by the informal team.
With the filter model, the learning initiative – and the learning – doesn’t end when the formal solution is delivered. Communities of learning and communities of practice remain available and are supported, moderated and facilitated by the social learning manager.
Building Community
The greatest challenge to any informal initiative is building community, particularly for companies who are embarking on social learning initiatives for the first time. Driving community and keeping it engaged requires an artful blend of culture change, useful “only found here” content, incentives and rewards.
It also requires community, which doesn’t exist until you have, well, community. The social learning manager’s greatest task initially is to seed new social environments with useful content that, by its very informal nature, is not found anywhere else, content that is important for successful learning outcomes.
Whenever possible, a gamification layer should be added to encourage engagement. Not only will the number of users grow, but data shows the quality of user-generated content will improve as well. Even proprietary frameworks can integrate behavior platforms like Badgeville to track, motivate and reward learner behavior and to provide deep and granular behavior analytics.
Learn more
When someone needs to know something, they look for answers, and they want them quickly. With the filter model, learners who seek information find the right answers when and where they need them.
We’ll be speaking in more detail on the filter model, the social learning manager and community building this week at George Mason University’s “Innovations In E-learning Symposium,” June 5 – 7, 2012. I’ll post the slides here after the presentation. If you’d like to learn more, please get in touch!
UPDATE: Here are the slides from our presentation.
{ 2 comments… read them below or add one }
You said, “Whenever possible, a gamification layer should be added to encourage engagement. Not only will the number of users grow, but data shows the quality of user-generated content will improve as well.”
I have to admit, I’m a bit skeptical of the idea that gamification tacked on as an additional layer will actually improve the quality of content as you say, especially as an across-the-board recommendation regardless of the audience or context. You also seem to be talking about gamification as badges and leaderboards, which is basically the most shallow way to look at games.
There’s plenty of evidence that extrinsic motivation like badges and leaderboards can be detrimental to tasks that require creative or critical thinking. I’d be very interested to see the data supporting your claim. Can you please provide a citation?
Thanks for your comment, Christy. You’re right, badges and leaderboards can be detrimental to tasks that require creative or critical thinking, which is why I’m still a big advocate of formal learning. It sounds like you’re familiar with Karl Kapp. In the filter model, I’m suggesting the use of informal environments for the generation of learning nuggets that can inform the structured solution.
Also, I’m speaking of gamification and not games – to quote Kapp, “using game-based mechanics … and game thinking to engage people, motivate action, promote learning and solve problems.” Badges and leaderboards do have their place in some informal learning environments, though personally I’m not motivated by them. In an informal work context, they begin to take on an almost caricatured quality – shallow, as you say. The mention of Badgeville is not intended to imply the use of badges, but rather the benefits of its comprehensive Behavior Engine and engagement mechanics.
As for data to support my claim that gamification improves user-generated content, well, darn. I failed to bookmark what I had read. It was linked to from either Badgeville’s site or on the Gamification Blog, but I can’t find it.