Top
1.800.628.2783
1.800.628.2783
November 2020
Issue Map
Feature5_November2020_TD.jpg
TD Magazine

Among Disruption, New Opportunities

Embrace these learning technology disruptors and trends.

It's been a disruptive year. There's a global pandemic, rising action against racial inequality, and related effects of both that may not be fully realized for years to come. Though some 2020 events are unique, disruption and the feelings of uncertainty it creates are perpetual. But in that disruption are new opportunities talent development professionals can use in support of learners.

Advertisement

In February, I presented on the topic of embracing learning technology disruptors and trends at the Association for Talent Development's TechKnowledge conference, and the concepts I shared then are even more important today. There's no definitive list of disruptors and trends that affect all organizations equally. However, as you consider the thought-starter list that follows, determine whether each area poses an opportunity for your organization and whether there are others you should also address with the presented frameworks.

Distributed Learning 2.0

The COVID-19 pandemic didn't introduce working and learning remotely, but it accelerated adoption faster and more broadly than expected. Fortunately, many people adapted quickly—but efforts to digitize and virtualize en masse revealed industry-wide shortcomings in the ability to engage participants. Fatigue became a popular suffix for describing virtual experiences as learners who may otherwise spend hours engaged in online streaming, gaming, or social media struggled through valiant attempts to hold their interest. You may have responded temporarily to an unplanned catalyst, but long-term success depends on much more.

The need and appetite for digital and virtual learning has never been greater, and there are important decisions to make. Should digital and virtual solutions complement or supplement in-person experiences? Which design, development, and deployment capabilities should organizations provide in-house versus source externally? How should the scope of offerings flex to include connectivity, culture, and other elements that co-located experiences afford incidentally?

Even after travel and the ability to congregate in large numbers return, expectations about what learners can and should experience through distributed channels versus in person will have shifted. Now is a golden opportunity to learn from new approaches and behaviors and incorporate them going forward instead of reverting to old methods when co-location is easier.

Bespoke ecosystems

A comprehensive ecosystem road map and data management strategy are imperative for organizations seeking to maximize learning impact and retain employee trust. As part of that work, some companies recognize a need for greater flexibility and extensibility than their legacy learning management systems afford, so they are configuring their own ecosystems of specialized platforms to unleash the full potential of engagement and analytics.

For example, learning experience platforms aggregate content from internal and external sources and offer user experiences more extensible than the average LMS. Learning record stores track and report wide ranges of activity and integrate with internal data warehouses to enable robust analytics and personalization. And learning content management systems handle object-level content and enable rapid asset development and maintenance.

The short-term pain of conversion may deter some organizations from developing their own ecosystems, but the long-term benefits are enough for others to embrace them. Integration with people systems, however, will require thoughtful attention to matters of personal data and privacy. How much individual performance data can and should you track to enable personalization? Will artificial intelligence bias make inappropriate or even offensive recommendations? How openly will people engage in "safe" learning when the company captures and uses their data in ways that aren't transparent? To be successful, the strategy and road map must account for both technology and people considerations.

Expertise management

In an increasingly complex and nuanced world, managing talent expertise has become an essential function to maximize performance and mitigate risk. It is traditionally associated with highly regulated fields, but organizations now recognize that capability ambiguity at any level can compromise performance and cascade risk across an enterprise.

Managing expertise requires a framework for markers and technology to scale implementation. Expertise markers—such as affiliations, credentialed skills, and credentialed multiskill approaches—must include how employees demonstrate their capabilities, how companies define proficiency levels, and how employers should or should not use different markers when deploying talent. Additionally, technology needs to provide opportunities to demonstrate capabilities, track and update proficiencies, and integrate credentialing across all systems where talent data drives value.

It's impractical to define and manage expertise for every possible action that people can perform, so organizations need to prioritize what's most critical, define the mix of learning and on-the-job performance required for evidence of proficiency, and determine who's qualified to evaluate candidates and oversee the system. Unless you expect the future to be less complex with fewer risks than the present, a rigorous expertise management capability is imperative.

Automation conundrum

Automation pervades everyone's lives in ways seen and unseen, presenting challenges and opportunities apparent and subtle. Companies are piloting autonomous vehicle transportation and drone package deliveries that will likely become mainstream, social robots dispense medication and provide comfort support, and advanced surgical technologies enable individual doctors to perform complex procedures. It's an amazing time to be alive, but beyond learning how to use new technologies, we must mitigate the unintended consequences that some introduce.

For example, aspiring surgeons assist on a set number of procedures in their training, often performing a percentage of the operation themselves. Assistive technologies enable lead surgeons to do more independently, leaving medical students to do less. Extend that circumstance over multiple fields and roles, and an intriguing problem emerges: How do healthcare workers benefit from learn-by-doing when technology is increasingly performing the doing?

Automation also frees time for other things, and TD professionals want to capitalize on that. But when you're in a ride share again (which will be an autonomous vehicle someday), notice how you spend the time. Do you check email, browse social media, play an online game, or engage in digital learning? It will always be difficult competing for engagement against consumer-grade alternatives, which is why our attention to learning relevance and value must be even sharper than it is today.

Feature5chart1.jpg

Integrated learning

One reason people may not choose digital learning in the previous scenario is it doesn't integrate well with their lives. Adults want targeted help when needed, and legacy learning is often packaged densely in formats that are difficult to access. Advanced connectivity, smart device expansion, and artificial intelligence can change that—if we rise to the experience design opportunity.

High-band 5G networks transmit more data with less latency and make mission-critical Internet of Things possible. Smart devices have expanded well beyond the iPhone and iPad (which are now 13 and nine years old, respectively), including voice-controlled intelligent assistants and wearables such as smart watches and rings. Those devices can enable hands-free interaction and monitor human performance, such as biometric data. Intelligent systems can determine where people are; what they're doing (or likely doing); and what kind of support they may need based on personal past performance, others' performance, or data on current performance that's monitored in real time.

There always will be some need to offer learning in classes, courses, and programs, but organizations that create innovative ways to support people in real-world moments of need will have a strategic advantage over their peers.

Immersive learning

While intelligent, on-demand learning is optimal for supporting people in real situations, there's still a need for development prior to engaging real challenges. As expectations for learner experience increase, technologies improve, and disruptions cause organizations to rethink how they operate in uncertain conditions, the case for immersive learning becomes stronger.

Some companies have embraced digital twins—that is, virtual models of products, systems, or organizations that are simulated under different conditions to examine performance and optimize for different results. For example, city governments can build digital replicas of transportation systems to test how they can execute infrastructure projects safely and efficiently. Here the artificial boundaries between operations and learning blur.

Additionally, virtual reality has reached an important milestone with commercially available all-in-one head-mounted displays that enable six-degrees-of-freedom movement with inside-out positional tracking, eliminating the need for tethering to a computer. The effort required to engage VR has become a lot easier. Commercially available business simulation authoring tools have also advanced to the point that TD practitioners can develop low to moderate fidelity business simulations without the need for extensive development teams.

The technologies you have to work with are becoming stronger and more usable, and external forces continue providing more use cases to address. Immersive learning is ready for wide adoption. Are you prepared to use it?

Innovation labs

Research and innovation aren't limited to Silicon Valley startups, but the idea of launching an innovation lab may sound difficult. It shouldn't, however. Every organization is in a perpetual state of experimentation—including your learning organization. And formalizing an innovation lab is one way to test new ideas and shine a spotlight on the TD function's value.

Advertisement

Start small with just one or two ideas to test. Also think through goals and priorities, experiment timeframes, resourcing, impact measurement, and how you'll communicate results. Solicit ideas and volunteers, and don't be discouraged if funding isn't available right away. At the end of the quarter or year, you'll learn a lot, have interesting things to share, and likely have gained some attention.

Gradually add experiments until you're testing learning opportunities across every strategic area of your company or until capacity reaches its upper limit. Prioritize experiments that best serve the larger organization's goals, and make sure to share the results with project teams and leaders. Even if you start small and expand slowly, you're shaping your organization's future, which is difficult to argue against as a strategic endeavor.

Prioritizing where to focus

Regardless of whether many or few of the areas outlined above are relevant for your company, it's important to have a perspective on what's most pertinent and then prioritize those items for action. One framework to consider using is the importance versus urgency matrix (see Figure 1).

Determine importance by how significant or valuable an item is to achieving your strategic goals, and determine urgency by how significantly the item will affect your organization in the near term versus long term. In addition to yourself, ask others in the organization to individually plot each item on the matrix, and then discuss and debate as a group. Reach alignment on a shared view of priorities around which to focus action—most likely, it will be items that rank high on both dimensions.

Taking action to embrace

By definition, disruptions and trends involve change, which some organizations manage better than others. In both research and practice, McKinsey has found that transformations are most successful when they focus on four key actions to change mindsets and behavior. Collectively labeled the influence model, organizations can apply the following actions to embrace disruptions and trends.

Foster understanding and conviction. Craft a compelling change story that inspires others to embrace new ways of thinking and acting. Be careful of clichéd themes like "We struggled here, but we're going to fix things" or "We're already good at this, and now we're going to be great." People care more about how the change will affect and benefit them, their team, the organization, and society at large. Incorporate those elements into the story, and have several versions, because one version likely won't resonate with every population you need to inspire.

Reinforce with formal mechanisms. Ensure that related structures, processes, and systems are aligned with and support the change. Allocate budget and resources to priorities, and set clear scope and quality expectations in project charters. Address legacy mechanisms that may disincentivize target behavior, and ensure that efforts are formally evaluated against success criteria.

Develop talent and skills. Assess gaps between current and desired skills, and provide learning to address them. Separate marketing from learning, and focus the latter on skill development with ample opportunity to practice and receive feedback. Implement a long-term mix of individual and peer learning experiences with budget and resources for regular maintenance so offerings are viable throughout the entire life cycle of need.

Role-model. Identify influencers with the greatest impact and channels with the widest reach, and employ both to reinforce beliefs and actions that drive the change. Infuse naturally occurring touchpoints, such as performance reviews and status meetings, with examples of desired behavior. Spotlight groups and individuals across the organization who support the change, and highlight actions that yield tangible results.

What a difference a year makes

A year ago, no one predicted how differently the world would look today, and some organizations have embraced changes better than others. Whether you're navigating events that shock the world or just trying to shape the future in your own corner of it, having a perspective on relevant disruptions and trends—plus frameworks for addressing them—will increase your likelihood for success.


feature5chart2.jpg

Related Tags:
About the Author

John Sangimino is a senior expert with McKinsey & Company’s Learning Design and Development Center of Excellence (COE). He works with McKinsey practices to develop strategies and solutions that drive deep performance change. Sangimino also leads the COE-extended team charged with scaling the reach of quality learning design across the organization. He has more than 25 years of experience designing and developing learning, with deep interest and experience in simulation architectures and situated solutions.

Be the first to comment
Sign In to Post a Comment
Sorry! Something went wrong on our end. Please try again later.