Personalization for Knowledge Workers

This is the 2nd in a 3 part series addressing the impact of personalization in the education and training markets. In the first post, I addressed the application of personalization in K12. In this post I address use cases that apply to a high-skilled knowledge workforce.

Personalization for the high-skill knowledge worker

Personalized learning has different applications for different audiences. In the previous post, I discussed how personalization is a key plank in the educational reform movement.

Personalization in the K12 context is used to enable each student to learn at his or her own pace, and the curriculum is tailored on-the-fly to the meet the unfolding needs.

The subject of this post is a vision of personalized learning in the 2013 workplace.  To start, let’s look at the profile of a high skilled worker and view personalization through this lens.

The Collaborative, High-Skill Worker

The 2013 high-skill knowledge worker is connected, mobile, global, dispersed and relies the new breed of communication, and collaboration technologies to do business.

This describes myself, and most of my friends and colleagues in the post dot.bomb shake out.  Almost everyone I know has changed jobs several times in the past ten years. When the bubble popped, it caused creative destruction and spurned a new, and sustainable business model: one built from the ground up to be distributed and virtual.

This is the story of Xyleme. We’ve adopted a philosophy of hiring the talent where it is, promote hard work and high quality of life, and have cultivated a virtual culture of global collaboration and communication. I work in teams with my colleagues in the US, Europe, Central America, Czech Republic, Russia, and the UK – many of whom I’ve met only on conference calls.

 Our work model is indicative of a trend in both small and large companies. Our employees, like those in other distributed organizations, are highly adaptable, responsive and must continually acquire new skills and competencies. In our virtual workplace, we assume our employees to be self-starters, who take upon themselves the responsibility for their personal learning and development.

The flip side of working in a virtual workplace is the loss of the opportunities for tried and true methods of informal learning: those acquired by osmosis over the water cooler, or by shadowing more experienced colleagues.

Personalization in the Ad Hoc Workplace:  Matching No More, No Less

So what is the appropriate modality for learning in this type of work environment?  The answer, I believe, lies at the intersection between performance support, personalization, and collaboration.

 Personalization in the corporate context must support an ad-hoc modality of learning.

The objective is to help the employee cut through the corporate knowledge repository and match the content with the unique needs of each employee.  Each user will have a “living” learner profile that captures and tracks who the employee is, what they responsibilities they have, and their learning requirements.  With this knowledge about each user, the personalized performance support solution matches the users with the most relevant content – wherever they are, when they need it, on the device they have.

 While the learners’ needs and the nature of the content may vary by business and profession, the fundamental personalized learning use case in the corporate context is to match each user with the specific corporate resources needed to be effective in the work they do.

It is a user-aware system that provides opportunities to learn, and build skills – as they are needed. A next-gen, user-aware performance support solution will support an ad-hoc modality that lets people learn at the moment they can best absorb and retain it – when they need to use it.

Perpetual Content Improvement 

Personalization is only as good as the content that is available. If no content matches the user’s needs, the solution will be rejected. Those companies that have existing classroom, or eLearning products can quickly realize value by simply disaggregating materials into their constituent parts.


When content is broken into discrete learning objects – rather than buried in large courses – I believe users will willingly access specific lessons, assessments, topics, procedures, and videos – as they are needed. Because the modularized content is enriched with descriptive metadata that correlates it to the company’s knowledge domain, it makes it possible to programmatically match it to the needs of the learner. For example, a products company may tag their content with metadata that describes the products or services to which it pertains; the competencies or skills to which it relates; and the geography to which it applies.  With this information tagged on the content, the system can precisely suggest content appropriate for a sales rep selling a specific product line, within a specific geography.

 Social commenting, ratings, and analytics on the granular bits of content provides the curators of the content (the training development teams) with the business intelligence to drive a continual improvement process.  It engenders a “living” repository where problems are fixed as soon as they are identified, and gaps filled as they become apparent.

User generated content will increasingly become a key part of a living repository. In a sense, this will be the virtual return of “over-the-shoulder,” informal learning. Employees, with smartphones, can turn a camera on themselves to describe or demonstrate areas of expertise.  Shared with their peers – who can comment, and rate it. This exchange has the potential to fuel and enrich the iterative, training development process.

Corporate Learning Use Cases

There are as many use cases as there are unique businesses. Here are just a couple of examples.

  •  Professional Certifications & Test Prep For employees that must maintain professional certifications, personalization is similar to the academic use case. The system can track the set of competencies the covered within the certification exam, and provide assessments to benchmark cognition levels. With the gaps identified, the personalization engine can recommend a set of resources tailored to fill the gaps.
  •  Product and Service Support For employees that support a company’s products and services, the system can track the responsibilities of the employees and match them with the appropriate product or services content.
  •  Regulated Industries and Audits In regulated industries, such as Pharma, the system can know who is responsible for what products. When there are changes to rules, or procedures, the system can identify affected individuals, and push updates to them, track receipt, and even test comprehension.  This provides a means to keep affected employees up-to-date, and provides a clear audit trail.
  • XML Learning Objects:  The Foundation for Next Generation Corporate Learning Systems Personalization is underpinned by granular, semantically rich content. So how do we get there? A good place to start is by mining existing learning materials entombed in the 3-ring binders, and monolithic eLearning courses and disaggregate them into their usable parts. For some organizations this will relatively easy, for others it may be more difficult due to the way the content was created and formatted.

Moving forward with new content development, organizations will have to adopt content strategies that support personalization. As I’ve said many times in previous posts – this must be done using XML. XML is rich with semantics, can be easily modularized, and flexibly published to meet the needs of each user.

It is clear to me that the delivery channel, too, must evolve. The LMS-centric model of monolithic courses is out of step with the way professionals want to learn. For this modality of learning to be affective on the corporate front, the access to content must be instantaneous and available on the devices we use.

Personalized Performance Support has the power and potential to provide high skilled knowledge workers the responsiveness and flexibility to learn what they need to learn, when they need to learn it. The ability to profile employees by their responsibilities and learning requirements presents rich opportunities to personalize, and optimize the value of, the enterprise learning resources.  Quick access to the most relevant, expert resources will, I envision, enhance both the employee organization’s ability to thrive.

Xyleme is on a development path to enable this very vision. The LCMS provides a development environment for the development of modular, semantically rich XML that can be flexibly published. This content can be deployed to Bravais – the Cloud-based delivery system from which end users can access and comment on the content. Bravais is aware of a user’s needs and can programmatically match those needs with the base of learning content. Our customers are already using this platform to create pioneering, first-generation personalized performance support applications.