Scale Versus Stickiness: The Eternal L&D Challenge

The first of the learning trends predicted for 2018 by Training Industry Magazine was “mass customization is driving learner experience.” Learners of today no longer want one-size-fits-all training. With millennials becoming a significant force in the talent pool, engaging them uniquely might well be the differentiator for employers. It is common knowledge that technology today can deliver it – but is it easy for L&D to do so?

In L&D, trade-offs between scale and stickiness are inevitable. With limited resources (time, money and people), it is almost impossible to reach everybody with great, personalized and sticky content on time, every time.

Readers who have been in the trenches supporting a new product rollout or a new software update will agree that getting the training ready and rolled out to thousands of employees in time is challenging. As content keeps evolving in these situations, getting the base version ready and out is stressful, let alone personalizing the content.

On the other hand, such contingencies have also resulted in thousands of hours of level-one content in organizations’ libraries. Many big organizations struggle to categorize, archive and search this database. Even if they spend the money to create engines to do this task, does the content really have many takers?

In the past few years, organizations have been leveraging managed learning services (MLS) to solve the scale problem effectively. MLS has been a great way to increase span without increasing cost. There are many other added benefits, such as standardizing content; centralizing training spends; addressing underserved segments of the target audience; and relieving the enterprise L&D teams from doing tactical work, helping them to focus on more strategic initiatives.

However, even as the MLS industry has been burgeoning, supporting training in the “factory mode,” a few exciting technologies have emerged. Augmented/virtual reality (AR/VR), gamification, collaboration engines, artificial intelligence (AI), machine learning, and big data are all geared toward making learning immersive and intelligent as never before.

The truth is that these technologies are still expensive, and creating a truly immersive experience takes time. The traditional models of web-based training or instructor-led training just don’t hold in these modes.

So, whither L&D?

These technologies are evolving at a fast pace. New devices, platforms and commercial models are emerging every quarter. It’s difficult to see exactly how the future is going to shape up. However, L&D can do a few things to keep them on course.

Gear Up!

Here are a few “dos” for the L&D community:

1. Do start with the paradigm shift: L&D professionals should deeply understand that the wheel has turned a full revolution. We need to take a 60,000-foot view that encompasses changing learner demographics, business realities, strategic priorities, technological advances and training philosophies to chart out a mid- to long-term blueprint. Taking some time out to kick back and carve your consciousness is a good starting point.
2. Do sell it well: Paradigm shifts need evangelists. They need visionary leadership. This is the time for L&D leaders to step up and integrate the function completely with organizational goals and create solutions that deliver results. This is an opportunity to involve the senior leadership team to envision the learning organizations of tomorrow.
3. Do work on infrastructure: In many organizations, the IT infrastructure has not kept pace with L&D aspirations. Many implementations of gamification, AR, VR and big data are hamstrung by IT limitations. L&D leaders should collaborate closely with IT to get the infrastructure up and running. It might involve upgrading the LMS. It might also mean finding a new cloud-based platform to augment the LMS. It most definitely involves investing in new devices.
4. Do collect data: While training ROI has been a raging debate for over a decade now, there has not been much headway so far to create a sustainable way of calculating it. Big data and machine learning are here to solve that problem. But it is up to L&D leaders to have the vision to create the models of ROI calculation. It might mean setting up your systems to do in-depth surveys, certifications and dip checks at various points of the learner life cycle. It might also require a data scientist to look at data differently and meaningfully.

Here are a few “don’ts”:

1. Don’t flirt with new technology: If there is anything that can set you back a couple of years in your journey, then it is piecemeal experimentation. Work with conviction. Pick the right program, which will be the best showcase to the new mode or technology that you want to implement. Think it through. Plan out the implementation properly. Create a visible campaign around it. Measure outcomes in a meaningful way. Most importantly, be involved completely, from the top down.
2. Don’t assume learning styles/preferences: “It’s not for us – our organizational culture is different” is an oft-heard refrain in the L&D community when it comes to adapting newer methods and technologies. This is a misconception. To overcome it, talk to your target audience. Understand their needs. Study their preferences. Involve them in the process. Look for insights within your organization.
3. Don’t get stuck with volume: While there is wisdom in “if it ain’t broke, don’t fix it,” the traditional approach (creating a large volume of content using rapid development tools and templates) might be keeping you from exploring newer ways of training. For example, in case of software training, the approach has been creating “show-try” simulations, classroom training and a sandbox environment. Instead, how about starting with a gamified sandbox environment in which users figure out the software for instant rewards and a place on the leaderboard? How about crowdsourcing content from SMEs and users? How about weekly virtual instructor-led trainings to debrief and clarify doubts? How about collaborative problem-solving sessions using the new software? How about finding correlations between the activity in the virtual sandbox and the success of the software implementation?

These are exciting times to be a learning professional, because our aspirations and technology are finally converging. Let’s lead the change from the front.