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Building Learnable Products - Managing Knowledge Effectively

After a long hiatus, I've realize it's time to resurrect my blog, with my renewed experience from all the years I was away. Its been a fascinating journey with so many challenges personally, professionally, and just overall that I was overwhelmed at first about what to write about. During this time I transitioned multiple roles from an eLearning instructional designer to a curriculum developer for instructor-led training, to delivering a train-the-trainer to instructors and consultants at Oracle University, to graduating as a technical writer. I was fascinated by the vision of the convergence of applications, user interfaces, and training into a amalgamation in the modern era of mobile technologies and machine learning. It's beautiful to watch this evolution in a short period of just 6-7 years. Notably the evolution began well before it but became significantly visible in the last few years. 

This gives me a segway to my topic, Learnable Products, which I have diligently promoted during the transition of applications to the modern era. From Get Started guidance to first time users, to intrinsic UI information that drives how users quickly learn and use applications, it all fascinates me. Coming from a learning and design background, I like to call this product 'Learnable'. Users install applications and figure out how to accomplish their basic tasks with a 'separate' channel to train or read documents. 'Learnable products' are a boon in the fast-moving business world where people have limited time to train themselves, but expect applications to tell them how to be used. As an added layer to that machine learning changes the game by saving further time by ensuring the information people see to be 'relevant' to the goal they're trying to accomplish. 
'Learnable Products' are applications that incorporate user experience and content seamlessly so that users can 'learn' and 'use' them at the same time, and save on formal training time, thus accomplishing their goals with no or minimal training or documentation.
This takes me back to a post I wrote in in 2010, Future of Organizational Learning: Some questions. A lot of this has happened and a lot more than it actually by 2019! Today, machine learning shows great potential with its 'prediction' capabilities to make our lives better and help us do our jobs with greater ease. I see applications in the knowledge management space in addition to the more obvious applications in the use of an application itself. Knowledge workers can gain an advantage by better prediction and relevant information being pushed to them, especially in very large companies where standards, guidelines, and policies overwhelm workers. Knowledge workers spend a lot of time just figuring out what's 'relevant' in the current context of their jobs.

Building more learnable products can greatly increase the productivity of employees by leveraging the 'knowledge' of a network of people over individuals reaching out to other individuals by chance to find to get information on their current tasks. This approach eliminates knowledge silos with individuals and empowers new and older employees perform at par with each other. Google has already broken these barriers with their powerful search engine, but now machine learning adds the prediction layer and increases information 'relevance' to a great extent. This could potentially on-board new hires very quickly and make them productive in a short span of time thus making organizations more profitable through transitions.

I see a lot of promise and avenues to make lives better and drive innovation in a vast majority of areas. I'm glad to have started blogging again and look forward to writing down my thoughts and growing.












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