We live in a great era! We have amazing tech and tools at our fingertips and know almost everything about ourselves, what we eat, what we drink, number of steps, calories burned, amount of sleep and many more by just using a smart-watch and a mobile. In this ear data and analytics have allowed us to achieve the results we desire!
The same is for the business organization. They thrive on results. The results derived from various business functions, be it marketing, sales, operation, legal, administration, support and many other departments. All these departments collect the data to the best of their knowledge to prepare the plans for the next years predictions.
Do you think L&D departments are also following the same suit? May not the case…
Organizations do value learning but gauging quantifiable success for L&D initiative is difficult to achieve. I am not saying it is because of the lack of knowledge but it is the lack of actionable data that is creating the gap. This gap can be filled by data and analytics to help the L&D department track objectives and gauge success of their initiatives.
I remember an L&D partner of a middle-east bank saying, “I want more sign-ins across organization, at least 25% more from the last year. In addition, I need a 85% completion rate spread over 5000+ users. Of those 5000+ users, we must ensure XX numbers are from sales, XX from marketing, XX from retail customer service and so on.”
Such examples are a clear rarity however; it’s time we move toward objectives that are aligned to business objectives. The question is how to remove subjective oriented goals to objectives for which we can substantiate outcome with data.
Last year, I was attending a CLO meet where one of the panelists was citing the World Economic Forum report on upskilling that stated an urgent need for closing the skills gaps of resources. It’s a big opportunity for the L&D business and it can add up between $5-6.5 trillion USD to global GDP by 2030.
He was very upbeat for the share of pie that is up for grabs. There were others who felt that the learning and development function is back to the critical front and companies are feeling the need to develop organization-wide culture for learning that is based on data and analytics.
This made me start querying about two things:
During the discussions, two broad arguments surfaced…
First, the strategic importance of insights on skill transformation.
I heard one of the L&D folks commenting, “This is urgent. We need reskilling, upskilling, and new skilling programs for almost everyone and we are scouting for resources, who can help us drive this skills transformation exercise. I urgently want to roll out learning programs that emphasize what is possible to achieve with data and how to integrate data into day-to-day work.”
The second argument was on the best practices for implementing data skill transformation and toggle to a digital-first L&D function.
I assume the argument is pertinent for more than a decade. I remember my mentor suggesting learning nuggets way back in 2009 and proposed skilling programs to be digital-first by making them shorter, more interactive, and by encouraging learners to interact with the experts within the organization. We tried to follow his thoughts and designed structured training programs that are discoverable, paced, with clear and articulated learning outcomes. This created excitement around learning and we were able to harness the power of data. However, our success was limited… it was moreover scratching the skin of a new thought.
People and technology were not in pace for such Edtech disruptions.
It was a long wait till data wave hit everyone around 2015 and suddenly; everyone took data as the new fuel for Growth. In Dec 2018, I met my erstwhile Mentor over a coffee and asked him a straight question, “Do you know what data-driven learning is in the present context?”
He blinked and replied with a smile ‘Good question!
See, it’s all about using data to make digital learning more constructive and proficient by making it more precise. If you gather the right statistics on your learners’ strengths and weaknesses, and on their engagement preferences, you can tailor the learning to their needs. This will help you harness learning data to find out learner gaps and then design learning measures to fill those gaps.
He finished with a strong quote, “Just make your ID practices more strong and do not leave it to naives. Remember, the clout of naives have deep roots so, as an ID, play as tuned-in-teacher not a big brother.”
I followed with one more; I guess, I was looking at the wrong end…the data produced by the learning? Am I going wrong?
He answered looking surprised and said, “I was not expecting this from a person of experience. The ‘end of the learning’ you mention is not even the wrong end – you can use data from either end of the learning – before or after! Some people make a distinction between these using the terms ‘prescriptive learning’ and ‘diagnostic learning’. It is better to start by taking simple data like entry points for learner engagement and analyze frequency, times of most activity, top searches, failed searches, drop-off rates. Then use this information when you’re designing their learning paths and events. You look at Amazon page, which is a good place to market Amazon’s learning. It is something as simple as this – using data from online trends, preferences, and decisions can be analyzed wisely to help users learn and onboard effectively.”
I wanted to make maximum out this meeting and eager to continue.
I thanked him for the clarity and asked a follow question. So, can data help us to know learner fatigue or disinterest? Can we identify the points what learners can’t learn? Even drop off rates can tell us the point of complete disengagement. Can we use this data pragmatically to derive learning engagement?
He replied, “Yes, most definitely! The ideal would be to know what learners are really struggling with. The fact that they need to know that particular information is not going to alter, so if we could figure out what those tough points are we will know where to invest the resources and how to design the solution to meet the learning outcome. It is time to use learning analytics, like data from scans or assessments of learners’ knowledge to specify the areas they’re struggling in. Then, focus the next learning connection on that particular topic, to help the learners fill the gap. It’s all about making the learning more targeted, and precise. The best is to put together the right combination of assets – like, an interactive video, a timeline, fact sheet and a rapid fire quiz – to plug that knowledge gap in the most efficient and memorable.”
I still remember his three crucial statements or rather insights. He added three crucial insights ,
That was the last I spoke to my mentor
It was the most insightful conversation that I had till date. It helped me understand that data harvesting allows us to make learning more enjoyable and useful for the learner, and helps an organization derive a better ROI on L&D investment. It’s a win–win!
Today, data is fueling transformation in every field, from marketing to workforce management. We are making the most important business decisions on the recommendation of detailed data analysis findings. Similarly, L&D function requires as much data to be effective and successful. L&D initiatives can have significant investment and creating a system where data drives decision can easily validate the ROI. Data also gives us visibility of prevailing trends in L&D across the target audience, helping to understand the strategies, content types, and distribution platforms work best for your workforce.
The key questions that I will try to unravel in the next 6 weeks will be on:
Senior Learning Architect, Excelsoft Technologies.