Here’s something new to me: spam in the comments of this weblog. In an entry on “Globalisation (and other e-Learning) resources”, we got a totally un-related comment (twice!), plugging the commenter’s company. Since this site is interested in the business of eLearning, a relevant pointer to a company’s products and services is often welcomed. When the plug is merely to a self-serving demo and a nearly content-free PDF, the greeting is not nearly as warm and (I believe) it opens that company to the harshest criticism I can muster.

Despite an impressive-seeming Advisory Board, the commenter’s company, LearningIDEAS seems to offer as its main “solution” (I hate that word…) an electronic implementation of a really good switchboard operator.

“The Match and Route capability accurately connects individuals based on their need, skills sets, organizational profiles, time zones, and other relevant factors. Knowledge seekers can be employees, agents, or customers of an organization. Experts can be employees or a third party, contracted to provide such a service on behalf of the organization. Knowledge seekers and experts may reside wherever a network connection is available – anywhere in the world.”

In their video [Windows Media Format], they demonstrate such scenarios as an insurance adjuster needing help with a complicated case and an eLearner requiring some extra help with a section in an online course. Here’s where it gets a little silly:

Scenario 1: The adjuster logs onto his KnowledgeShare application — pre-installed and purchased by his company, or served by an ASP — and is presented a form where he can enter his request and a description of his problem. The KnowledgeShare application reads and parses the perfectly- and accurately-written request, identifies the expert in the company most capable of handling that request and immediately connects the two people in a whiteboard and vidcam enabled interface.

Scenario 2: The learner is stuck on a concept in an online course. She, too, logs onto the KnowledgeShare app — hooked into her eLearning course — and is immediately connected with a tutor who walks her through the appropriate computations, and in just seconds imparts his wisdom to her and shows her how to solve her problem.

Can you spot the myriad pitfalls in these scenarios? Here are just a few:

• One of the major selling points of this app is timely access to expert help. What happens if the adjuster is not sitting comfortably at his desk, as adjusters are often on the road? Is there a telephone interface to the system?
• The parsing mechanism depends on the user being able to input a concise, cogent and accurate description of the problem and what he needs to resolve the problem. If you’ve spent any time at all reading and participating on tech support bulletin boards, you’ll understand just how rare is this ability. (And those boards are populated by real-live humans with infinitely more capable message-parsing systems. Still, it often takes several back-and-forths to accurately identify the nature of the problem before any kind of solution can be explored.)
• What kind of skills survey is required of all people in the company to determine who might be expert in a particular topic, and how long will that survey take? What kind of pre-created taxonomy of skills is necessary for the natural-language parsing this system claims to provide? How are these skills captured? Who will be surveyed to determine their expertise on particular topics? If the adjuster has questions on a case related to cleaning materials, for example, will the system know to connect him to the janitor? Or will it connect him to the Director of Facilities and Infrastructure who might not even know the janitor’s name or what products his maid uses to clean teh floors at home?
• The expert on the other end is online, at her desk, and has nothing else on her plate which would interfere with helping this guy. Right! In any company I’ve ever worked, the experts are often the busiest people, involved in the most projects, the greatest number of meetings, and are the least likely to be waiting at their desks for a random call.
• The system takes into account time-zones, but what happens when the finely-grained expertise technology determines that the appropriate expert is offsite or is in a different time-zone where it is currently dark-thirty in the morning? How many steps will it take before the adjuster has been bumped down through the hierarchy until he is talking to the night watchman or someone’s voice-mail? What is the system’s “hit rate” for actually connecting requester with expert, and how is this taken into account in regard to claimed increases in productivity?
• Headsets and vidcams at every desk… wow! That’s a way to save money, right? Then add in the per-seat licensing for the KnowledgeShare access and we’re really saving money now!
• In the eLearning scenario, it seems like the learner is connected to a 3rd party or training-department tutor who is not only expert in the material, but is available and is a gifted teacher, rather than an outsourced script-reader currently doing 5-10 years in the Texas penitentiary. And what happens if that learner is calling after hours, as asynchronous learners are wont to do? How does this product improve on an email or IM saying, “I’ve got a question on this section of the content. Please give me a call when you’ve got a sec.”?

I could go on (and I often do!) Call me shortsighted or narrow-minded, but I don’t see this hypeware as very useful. I would go as far as to predict that in companies installing this app, a large proportion of questions, requests for advice, mentoring and tutoring will bypass this product altogether, relying instead on old-fashioned social networks to route the request to the person most likely to be able to help. As always, finding answers depends on who you know.