Winning in the Knowledge Economy

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The world’s leading pure-play analytics services firm recently received millions of dollars in funding
India’s leading FinTech startup catching up the Digital India frenzy and acquiring customers at an unprecedented pace
Global Capability Centers of world’s leading retail and CPG firms facing an exponential rise in volume of data hitting their servers
What’s common among the three?
All have been hit by the digital tsunami in the post COVID world leading to a severe shortage of skilled data professionals to help them manage, process and monetize swathes of data piling up with accelerated digital adoption by people around the world
With the market offering no help in accessing ready-to-serve talent, a rise in offer shopping and candidate ghosting, companies have had no choice but to look inward and think of options to re-skill and upskill their existing talent base.
This had put the focus back on L&D, which for long has just been a cost center with minimal focus from top management.
However, L&D has itself been struggling with its old, archaic ways of training and development with long lead times to deploy and a one-size-fits-all curriculum mindset, which works for a static academic setup but not in a dynamic, ever changing corporate environment.
With organizations demanding more productivity from each employee, the employees are left with even less time to invest in their learning. They don’t have the luxury anymore to sit through hours and hours of instructor led training. To make the matters worse, poorly designed trainings and no follow up opportunities to apply the learnings have led employees to simply forget everything they’ve learnt in a matter of days
The management on the other side has very clear goals: faster time to deploy, pin-pointed, relevant skills that make employees readily deployable.
The ever-changing tech skills landscape has made the task of L&D even more difficult
Here are the hard questions L&D is facing today:
With access to many modes of learning available (ex. MOOCs, ILTs, Leetcode portals, etc.), how do you design the best learning experience for maximum impact?
How do you engage an ever-busy employee?
How to control the falling NPS scores resulting from poor design and execution leading to a bad learner experience?
A huge and rarely addressed issue : How to bring contextual awareness into learning program design? Managers have a constant rant against L&D that all they do is teach them basics which can be learnt from anywhere but don’t really connect the skills to real business challenges faced on floor
The biggest of all challenges: How to truly measure and track an employee’s learning journey against ever evolving competencies?
The answer lies in a combination of three powerful ideas:
Experiential learning
Mentorship
Skill Ontologies
Experiential Learning has a simple proposition: Experience it to Learn it!
How do you learn to drive a car?
How do you learn to ride a bicycle?
How do you learn to swim?
It sounds pretty obvious how do we learn life skills. By trying, failing, retrying, and getting better at them. Switch to Corporate Learning and we find the “Experience” part hugely missing. Why?
Because Experiential Learning is hard to design and execute. To make it a real success, it needs the following essential ingredients:
Abstract Conceptualization: Thoughtfully crafted instruction design with drops of ambiguity and room for creative thinking makes the learning experience more enjoyable and “real world”.
Remember, real world problems are vague, abstract, and at times weird.
Active Experimentation: Traditional learning models focus on imparting all knowledge upfront without considering the capacity of the end-learner to absorb the dump of information coming through. Experiential learning starts with minimal pieces of information imparted, creates room for a lot of experimentation, and provides a platform to fail. The learning gained from a failed experiment sticks to the learner for life
Concrete Experience: Designing learning experiences out of real-world use cases executed as part of real projects done at organizations Nothing comes close to the real-world toil that an employee goes through. There is a reason the 70:20:10 model exists where 70% of learning happens in the flow of work
Reflective Observation: The most critical component of Experiential learning which provides room for the learner to reflect on their work and come up with an analysis of pros and cons. With traditional learning being too transactional with focus on cut off marks, the learner remains oblivious to his/her real performance gaps and gets no clue on what to improve. Learning stops right there
On top of the above aspects, there is one critical support system without which Experiential learning is incomplete is Mentorship.
An experienced Mentor who has been there, done that is really the best person to design, nudge and evaluate a learner for a successful experiential learning model
Well, you know you can’t simply sit on the driving seat and start driving on your own. You need someone sitting next to you with the brake pedal beneath their feet. That’s the mentor who’d make your learning experience a really fulfilling one.
Finally, Skill Ontologies, which are nothing but connected skill graph which grows with the new skill additions to a person’s job role (Think competency matrix). With technology playing a big role in delivering an immersive learning experience, it can be leveraged in designing, capturing, measuring and reporting employees’ performance quantitatively and qualitatively over time.
A true Learning Experience Platform (markedly different from a Learning Management System) of the future would be delivering seamless experiential learning augmented with nudge-based mentorship and measured via thoughtfully crafted skill ontologies all powered by technology.
Till then, Happy Learning!
Ready to Experience the Future of Data?
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