Learning technologies are a hot topic today, especially given the recent erosion of the conventional “office space” and subsequent dispersal of the workforce. On top of that, we already live in an age where it’s easy to feel buried under a sea of information. But this latter phenomenon didn’t begin with the advent of the iPhone or the internet. It’s been with us since the dawn of the printing press. That’s over one-half a millennium ago for those who are counting. Information transformed seemingly overnight from something only the privileged few had the “right” to access into a common feature of everyday life. Today, businesses reap the benefits of the ever-expanding pools of knowledge immediately at our disposal. This access enables them to make more prudent decisions, streamline processes and revolutionize industries. However, as with most things in life, there’s a downside.
The sheer volume of new learning technologies available now is staggering. It’s no wonder organizations often struggle with discerning what new systems and applications might have real long-term value. It can be full-on anxiety inducing. But the key to resolving this dilemma is to recognize one thing: that information overload is not the problem; it’s simply a fact. Once leaders accept this reality, they can begin moving forward and uncover solutions that will help silence some of the noise, solutions that can help filter out much of the excess info being hurled at us from every direction. The result? Leaders feel more confident in making better informed decisions.
The immediate question at this point is this: What criteria can help leaders determine whether or not new learning technologies have the inherent ability to improve work effectiveness while mitigating work impediment? This question matters because implementing new tech is a considerable investment, not only of money but also of time and energy to prepare the company culture for the impending changes. Failing to apply the right criteria to the search and selection of learning technologies will at best result in analysis paralysis and at worst, the implementation of a costly failure.
The Technological Litmus Test
To help determine whether a new technology is worth integrating, here are the top three characteristics to look out for.
1. It must be simple. This characteristic alone takes most systems out of the equation. Referring to a technology’s ability to get you to your end goal efficiently, simplicity primarily focuses on user experience. It’s often used interchangeably with intuitiveness. Consider the host of apps available today. We can immediately start using some of them with little to no orientation. These are the ones we tend to use most often and assign the greatest value. However, many apps fail to place the user experience first. We usually struggle to make sense of the platform and how to best use it, which leads to user frustration. And the more complicated they are, the less useful they seem. All we see are mounting roadblocks and reduced productivity. In the end, these are the apps that usually get sidelined or deleted.
This analogy holds firm in business as well. If we’re careful and, with simplicity in mind, test our technology toolset options before adoption, we’re more likely to integrate those that yield the greatest value, offering the least resistance and improving workflow. That is, we have a much better chance of creating a technology ecosystem that is really useful.
2. It must be learner-centric. Like point number one above, the learner-centric model is often tough to come by. And it’s best understood by way of contrast with its more conventional content-centric counterpart. The content-centric approach, which learning management systems (LMSs) adopt, includes creating, uploading, assigning and assessing content. In other words, it measures the learner’s success on the grounds of information retention and regurgitation, to put it crudely. The problem here is the facilitation gap regarding the learning process — that is, content-centric systems neglect opportunities that would enable learners to receive feedback on their execution of the content.
Meanwhile, the learner-centric approach used by the aptly named learning experience platforms (LXPs) prioritize application of learning and the growth-centered feedback needed for improvement. These dynamic systems not only house content and offer intuitive suggestions based on the learner’s specific needs and interests, but they also facilitate both system-generated and human feedback. In a sales training context, for instance, the sales professional could hypothetically practice in a recorded, AI-supported sales simulation and then submit that recording for asynchronous evaluation by managers and coaches.
When gauging the value of new learning technology, the learner-centric model is an absolute must. It goes well beyond low-level memorization and understanding and challenges learners to execute new knowledge creatively in various contexts.
3. It must be adaptable. The final of the three characteristics, adaptability refers to a tech system’s responsiveness to individual usage and needs as well as changing circumstances. This is where machine learning (ML) comes into play, where the tech itself adjusts to what the learner is trying to accomplish. If it’s working well, the platform should provide insights and offerings based on learner inputs and cues, such as searches, likes and completed tasks.
Users should also be able to creatively apply the learning technology in ways that adhere to and support the business’ goals and strategy. Additionally, to achieve high impact, the application’s expansive user predictions must evolve with the learner. Learning technology that can do that becomes increasingly accurate and useful over time. It continually provides new information, fresh perspectives and the much needed feedback that enables professionals to learn and grow. Those are the crucial components that sustain long-term learner engagement.
Simple. Learner-centric. Adaptable. This three-word litmus test allows organizations to easily decide what has value and what can be discarded. It ultimately prevents them from getting bogged down by the near infinite array of tech options available today. And this can have a huge payoff beyond improved workflow and productivity. As employees become more efficient in their processes and thrive, engagement and satisfaction increase. That spells good news for employers because it usually translates to better retention.
