Predictive Learning

In todays L&D landscape, the way businesses determine who should participate in what training isnt far away from some sort of conjuring act. More often than not, the result of this is a mixed bag, and many of the L&D professionals I speak to tell me that the L1 scores (based on the Kirkpatrick model) are more often than not tending towards the lower end of the spectrum.

There are typically two ways a business determines training participation. One is based on mandated training (usually related to promotion/growth), while the other is nomination by the business manager. Both of these are based on picking up from a ‘menu’ of available programs, and neither really takes into consideration the actual learning needs of the individual.

This is where the idea of predictive learning comes in. The idea here is simple … today, with the technology available to us, especially in the Big Data/Analytics domains, the data about what has worked in the past in what context is available to the organization in a large scale. This data is available based on training, HR, and operations/business data. This rich data can be leveraged to determine what is the best training solution which would likely work in a particular employee context. Like Big Data, this neednt look at the reason (or connection) between cause and effect, rather, look at the linkages as they have been seen in the past.

An important aspect of this picture is that this shifts the focus from training and learning, and from L&D to the individual learner, and makes the entire process people-centric.

One concern with this, though, could be that the outcome of the requirements could be way too granular, and too tailored to individual needs, so as to be unviable from the delivery perspective. More about this later …

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Training’s Khan Academy

Theres lot said about the way the principles of Khan Academy can be applied in the world of education. However, i see education and training as two essentially linked areas, and so, if there are lessons for education from Khan Academy, there must also be lessons for corporate training teams.

This made me think about what could be the key take-aways for a training manager from the way content is structured in Khan Academy. And an immediate answer that comes to mind is brevity.

Today, organizations are under pressure to increase productivity so that organizations are able to deliver more with the same number of employees. This means that employees need to deliver more in the same period of time. In consulting organizations, this is a euphemism for utilization pressure. Many of us would have heard those, havent we? And while L&D managers are under pressure to deliver training to enhance employee capabilities, there is also the constraint of getting participants away from their work for a few days to attend classroom sessions. There is of course e-learning, but can e-learning be an en bloc alternative for classroom or virtual education? I dont think so.

And this is where the Khan Academy concept comes in. This is something i had championed to some extent over a period of the last few years. I am talking about training modules which are a twitterized form of training. In other words, module videos which are to youtube what twitter is to blogs.

In this scenario, the fundamental idea is that people are more interested in training to enable them to do their jobs more effectively. This means that they would be more interested in short, crisp programs (not more than 5 minutes) which help them learn how to do specific tasks as part of their job. Just the things which are required for them to become more effective in their work.

Think job aids meet youtube meets twitter.


Content Search

One of the reasons that content needs taxonomy is to enable users to be able to search for content relevant to them easily. Theoretically, this is something that is quite straightforward. After all, Yahoo, Lycos, etc., have been doing this for more than a decade. And google, and now bing, have taken them to the next level of complexity when computing search results. So what are we talking about? Search is something which should be a given, and not something which should be question for discussion.

There are, though, a few things which we need to understand about search, which influence not just user interaction with content, but also the way knowledge managers look at search. To begin with, search is not the best possible option available to content or knowledge managers when they are trying to highlight content. Let me take an example to explain what i am trying to say. One of the things knowledge managers are trying to do … Highlight content which is relevant to a user so the content which users see on a portal is high impact for each user (at least thats the idea theoretically), something on the lines of personalization, the idea being that knowledge managers should be able to push relevant content to users depending on their profile of work or usage. But if there is a particular document which may be useful to users of a particular profile, how can that be highlighted to those users? Search would, after all, return a set of documents depending on what you search for, some of them relevant, and some not.

Add to this the complexity of taxonomy. This is something which is underestimated. Let me take an example to explain what i am trying to say. I was trying to search for a caller-tune. The song i was searching for is a song named Bulleya by Junoon. One of the parameters which is part of the taxonomy is language, and i searched for the song with Urdu, and with Punjabi, and couldnt find the song. Point is, with taxonomy, a user needs to understand the way the content manager would think, to be ableto find out the attribute values for specific content which the content manager would have thought up. And since i couldnt, i wasnt able to select the caller-tune. And this is where, as we know, folksonomy comes into the picture.

Of course, today, we find that the network can bring up content which may be relevant to you as a user. Of course, this depends on the quality and density of your network (ok, so i dont really know what density means, but what i am thinking is that since noone leads unidimensional lives, the network is based on a number of dimensions, and the knowledge a network would throw up along a particular dimension would depend upon the density of the network along this dimension, there should be some attribute of the network which can define this behaviour of the network, and maybe density is a term which is as apt as another). But as i have written before, the network would enable users to discover more easily the content which they find relevant, though search would still play an important role. This is because search is about pull. More like DIY.

An aspect which not many folks look at is that for a lot of contexts, its not always possible to classify content into specific, discrete values as defined by a content management team. An example for this is the song search that i mentioned. Any document resides at the intersection of specific values for a large number of attributes, and this is made more complicated by the fact that different people may look at the same document being at different intersections of values.

Add to this the idea that the easier you want to make it for users, the more you will probably make it complex for anyone who would try to contribute a document. All in all, a complex scenario. But if we try to see how users look at content, we can make it just a little simpler for users to search for documents. Thing is, different people have different ways or perspectives for looking at the same content, which means that you can only go so far as meeting user requirements for search. While this is where folksonomy comes in, i believe folksonomy cannot totally replace taxonomy for the structure of taxonomy does add to the usability of the repository.


Formal And Informal …

My friend, Subash Thyagarajan recently shared an interesting diagram over at the K-Community site. I am posting this here, thanks to him …

This picture gives quite an interesting representation of the various initiatives which together make up for KM. I agree that i dont quite understand some of the terms he has mentioned here, but even so … This shows that knowledge sharing has to be a convergence of informal and formal means. For over a decade, we have been looking at the right part of the picture, which is about the sharing of content in terms of documents, or means of learning like formal training. The left part, on the other hand, refers to the informal means of learning which are emerging as the next set of tools available to the organization for knowledge sharing.
The important point, though, is that these are to converge into a single set of tools, driving the entire idea of knowledge sharing. Which means that conversations, for example, which, within the organizational context, revolve around topics, could bring into their fold documents, learning content, and other formal means of learning, and documents could be managed in a way that lends them to be leveraged more easily to conversations. This is something we are seeing. So today, there could be tag-clouds for documents, just as they are for blogs, and people could reference documents they have written, or read on their profiles.
This is a picture which i have in mind when it comes to social networking, within the organizational context. That all people in the organization have their own profile, and they should be able to connect with others based on topics, as well as based on documents, and formal means. So, for example, if you are interested in a particular topic, you might like to see who are the people who have attended the training on that topic which happened some time ago. Or, who are people who are writing documents, or reading documents on that topic from the corporate content repository.
While these are just examples (and i would look forward to more such examples from you to add to this picture), these do make a point, that the KM strategy of the organization must be inclusive to these varied forms of knowledge-sharing.

KM … Nothing New

A very encouraging post by Dave Snowden … titled We just forgot it for a while … encouraging because this affirms something i have been thinking about for some time now. I wrote about it, too … and i quite agree with Mr. Srinivasan that KM, with the new aspects of technology, and the entire gamut of tools which are at our disposal, has changed the scope of knowledge interactions.

Something that i have been thinking about … the basic nature of human interactions doesnt change. Sure, it changes in terms of its form, but not really in terms of substance. What really changes is the mechanics of these interactions, and this change is facilitated by the changes in technology which are coming in. And, to that extent, i agree with Dave, that social computing has simpy changed the scope for human interactions, by enabling people to interact with each other across barriers and boundaries. Before the advent of modern management as we know it today, there was conversation. And today, we are again emphasizing conversation as the mainstay of knowledge interactions. Somewhere in between, the focus shifted to documentation as a means of abstracting meaning from personal knowledge and making it more generically relevant.

Lets not get carried away, though. We need to understand that both documentation, as a form of content which can deliver generic content to an audience with widely varied contexts, as well as the conversation, which today accompanies this document, both make up an integral part of the “conversation” in the context of today’s technology-enabled business scenario. While it can be argued that blogs and wikis, for example, also represent documents, i dont quite like to look at it this way. This is because these are tools, and tools, as such, re dependant on their usage by someone. So, its dependant on the user to decide whether to use these as tools for creating documents, or conversation. The difference being the reference to the context, with the conversation being highly context-rich.


Search Or Communities …

No, i dont think they are mutually exclusive. Interesting post by Nirmala … where she is posing the question … about what is it that lets your choose between google and wikipedia? to my mind, not much … or, to put it differently, when i search on google, more often than not, wikipedia results are among the first few to appear.

Now, this is interesting. Nirmala mentions someone being of the opinion that the rise of social networking would spell the end of search. While, on the face of it, this sounds like a tempting assumption, this is probably a bit of an oversimplification. Let me put it this way … if i am looking for something, i search. If someone on my network has found something, and i find it useful, i go through it. The opinion here seems to be a bit too much of a stretch, if you ask me.

Lets look at it this way … social networking is about knowing who you know, and this leads to (more often than not) knowing what you know. And the two, to my mind, are related, but different things. What could happen (and this is something i have been looking at, for some time now …) is that search could change … in the way tools enable users to interact with them. One of the possibilities is the availability of aggregators, or the possibility of searching for opinions.

In other words, and this is something i have been chatting about on the KM India Forum as well (as i am sure, my friend Sumeet Anand would agree …), that “collaboration”, and what i like to call “codification” are complementary, and not competitive in terms of the value they can add to the larger KM initiatives, and stressing on one, to the deteiment of the other, is not something which is nice. And if we agree with this, we would also tend to agree with the idea that content is an integral part of the knowledge inventory of the organization, and as long as this is so, search (in some form or the other), must also be around.

Where, then, does this bring social networking? To my mind, social networking is about bringing value which was not possible with the “KM 1.0” paradigm of the 90s. This is more about bringing the people aspect into the entire way of doing things, which was lacking. Now, one could argue that documents originate from people, and hence, looking at the people aspect should be enough to enable us to not look at the “codification” aspect, but the point remains that its not possible for you to know everyone in the organization (even if you are working in a mid-sized organization), and hence, to some extent, it is imperative to abstract knowledge, and this is where the content, and the search aspects come in.


Shelflife …

A rather interesting post by Darcy Lemons over at APQC about the shelflife of knowledge … or, how long should we retain knowledge? Interesting question. This is a question which frequently comes up whenever there is a discussion about a content management system. People usually come up with the question of how old is too old. Especially if you talk to technology firms, this question becomes even more pertinent, because a particular solution which would work with a particular release of a software would, in all probability, not work in a newer release.

My take on this … its not the age, rather, the relevance of knowledge which matters. Again, lets take an example … or rather, lets extend the earlier example. While the solution which worked on an earlier version of the software may not work in the newer version, if you are supporting the older version of the software, this knowledge is important for you. In other words, this knowledge may not be useful for implementation projects, but quite useful for sustenance projects. Hence, its not about the age, but about relevance … or, shall we say usage? Because, in a content management system, for example, relevance can be determined by usage. If people are using some knowledge elements, then they are in all probability still relevant, even if they are dated. Lets take the example Darcy has taken … if tomorrow we decide to do away with cars and trucks, and decide to go back to horse drawn carriages, there are still parts of Delhi where the expertise is alive and kicking. More on that later …

The issue here is, the people who generated the knowledge in the first place, may ot longer be around. How, then, do we attempt to recreate something which, in all probability, has already been created. This is an area where the entire idea of social computing can be quite useful. Lets illustrate this … a lot of people, when writing books about history, or topics about which not much knowledge exists today, refer to papers, documents, plaques, photographs, archaeological remains, etc., of the topic they are writing about. For example, I just completed reading a book titled In the Shadow of the Great Game … by Narendra Singh Sarila (though i have no idea how some folks get the idea that this is a partisan book … its anything but that, but then, thats my opinion … you are free to have your own) … and here, the author has extensively quoted sources, including official archives, personal papers, etc. … Personal diaries, for example, are a description of the then current events … as such, they become a valuable source of information about things that were happening, as well as the opinions of people (stakeholders?) about these. Somewhat similar to blogs?

From this description, we could go on to the possibility that blogs, discussion fora, and other, similar platforms could be a good way of preserving the thoughts of people about contemporary events … whether outside, or within the organization.