2018 Microlearning Global Benchmark Report

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Carol Leaman: 

Hello, everyone. Welcome and thank you for joining us for today’s exciting webinar. Leaders and learning professionals alike are trying to determine how microlearning can help them improve employee performance in ways that traditional training and employee development tactics can’t. According to a recent study from Brandon Hall Group, organizations rank microlearning as highest priority with 54% of them looking to add microlearning programs to [inaudible 00:00:35] learning. This growing enthusiasm, though, there’s so many questions surrounding this revolutionary approach to training.

What types of companies and industries are successfully using microlearning as an application where it works better … when it’s used for training, do we still utilize test scores and completion rates to measure success?

These questions could only be answered theoretically even a few short years ago, but the quick growth and pervasive adoption of microlearning as the gold standard for training in organizations across virtually every industry mean we can move beyond applying general theory. We now answer key questions around the advocacy of microlearning using empirical data from real world applications.

I’m excited to introduce the 2018 Microlearning Global Benchmark Report. This report is designed to cut through the noise with actual substance, the evidence you need to thoughtfully apply microlearning principles in your own organization. I’m delighted with [inaudible 00:01:46] JD to be able to walk all of you through the highlights of our report. Again, welcome everybody. My name is Carol Leaman and I am the president of Axonify, and joining me for today’s conversation is JD Dillon, our Chief Learning Architect.

A little bit of housekeeping before we dig in. First, if you’re having any audio issues at all or the slides aren’t advancing, F5 to refresh your browser. Welcome your questions during today’s event. You can submit them at any time via the Q&A dropdown on the right hand side of your screen. We’ll be answering as many questions as possible in Q&A section after the main part of the agenda, but please feel free to send in your questions at any time and we’ll add them to the queue.

Please be aware that today’s session is being recorded and will be available on the Axonify website within the next week for you to review. You’ll be notified via email when the recording becomes available, and of course, we’ll be sending you the full 2018 Global Microlearning Benchmark Report as well.

Let’s get going. We have a pretty packed agenda for this next hour, and JD and I are going to go back and forth, we’re going to be tossing the conversation back and forth as we go through all the items here.

We’re going to talk about the objective of the study. Learning engagement, the anatomy of a microlearning session. JD’s going to dig into what that really looks in actual usage today. We’re going to look at the general usage of trend data. We’re going to talk about gamification and microlearning. How do those two things tie together? How they impact one another and why is gamification so important to the equation?

We’re also going to review key microlearning measurements and microlearning applications in some specific industries: retail, finance and insurance or F&I as we call it, and manufacturing and logistics. Then finally, we’re going to look ahead to 2019 and look really what’s coming down the pipe with respect to microlearning.

Let’s start. I’m just going to dive in here. We want to cut through all of the microlearning noise that’s out there and really focus on the empirical evidence. Axonify have been delivering microlearning now for over six years to a wide variety of companies and industries. During this time, we’ve had such a huge variety of implementation from single use case deployment through full scale organization wide LMS replacement, which run the gamut.

When we set out to build this report, we wanted these questions to help educate and advance the industry on microlearning using data from real world usage.

These five questions are the ones we really set out to answer. How is it being in the real world? What the experience look like for that average learner? What industries are being very successful with this approach? What are the most common applications? Is it sales? Is it safety? Is it other sorts of financial related items that show up on the ballot sheet or income statements? Do microlearning measurements look different than what we’ve all been very used to in terms of traditional metrics?

Going to toss it over to JD, and JD is going to cover a few things as we get going.


JD Dillon: 

Thanks. Hi everybody. Let me get to the study methodology. Where does this data come from? Where is the inside sourced? Who is participating in this study as it were. Within the Axonify user community, we basically took a sample from North America of 78 different organizations in different industries. Not all from particular agency, there’s a mix of industries in our presentation and in the final report. That represents about 360,000 different users or end user frontline employees who completed around four million sessions. When we breakdown what a microlearning session looks like, what were these people doing as related to microlearning.

It was four million moments within the study overall so a very large sample size of data, and our data came from last year. Calendar year 2017 is the sample size for the report that we’re breaking through today. When you [inaudible 00:06:32] high level of what did we see or what were the results from an executive summary perspective, we saw three big points. One, the universal appeal of microlearning. I think one of the big questions I hear a lot is, “Where does microlearning work? Where does it now work? Who is it good for?” Which [inaudible 00:06:47] these types of ideas, and the idea that one, we see universal appeal, especially in environments where employees can’t control a lot of how their time or their day is used, frontline and/or deskless employees.

Two, there’s considerably higher engagement with the application of microlearning principles. We’re talking about a world with people who are engaging and learning content more frequently than you may be familiar with traditional set of tactics or traditional learning technologies.

Three, that microlearning excels at building performance across a variety applications in use cases. One of the things that stands out in this data is that this is not a corner case solution. It’s not something that just works for one particular industry or particular set of topics. We [inaudible 00:07:31] application across a wide variety of use cases that are important [inaudible 00:07:36] trying to achieve results today.

One little point I think that’s very important to define as we walk through this report is, what is microlearning? This is one of those things that depending on who you ask in the industry, you tend to get a different definition, because learning and development people don’t do a great job at definitions. Every time we say microlearning, these are the principles I want everyone to keep in mind.

The idea of fitting learning experiences and training closer to the work flow. I want people to voluntarily engage, this is not something we put upon people, this is something people can build as a habit in their daily working experience. It’s the application of learning science, so how … actually learning with ideas like space and repetition. Retrieval practice, so that’s why it’s a consistent, continuous approach in engagement. [inaudible 00:08:22] Continuously to the individual, so we talk about these four million sessions, these are four million sessions that are unique to the particular needs of the end user.

Finally, the focus on a business result. It’s not training for the sake of training. This is really focused on what the business is trying to drive forward, and what an employee needs to do to help the business achieve those results.

Every time we say microlearning, keep those principles and this definition in mind as we continue our conversation today.


Carol Leaman: 

Okay. Let’s jump into the report findings. Now before we dig into the data, it’s important to provide context into what a microlearning session involves. This leads us to our first piece of data on participation and engagement. Our customers liken the Axonify microlearning experience to [inaudible 00:09:20], it’s like brushing your teeth in the morning, where it fits very easily right into the daily work flow. We, many customers, like access to their Axonify microlearning training available on things like point of sale terminals, in vehicles on the cab-on devices, and on data kiosks in the workplace.

Those, in addition to what you would expect in terms of laptops, [inaudible 00:09:49], and mobile devices. Across the four million training sessions, JD just mentioned that we analyzed, this is what participation and frequency looked like. A full three-quarters of employees participate in training every month. That is, compared to traditional training methodology, extraordinarily high. What we also know is that those participating in training do so, two to three times per week which, when you extrapolate that, works out to 106 times per year.

Again, an extraordinarily high level engagement with learning on a voluntary basis that happens when you provide microlearning in the workplace. You can imagine the vast amount of data that we capture on individual employee participation and frequency, looking at numbers like this.

Just a question for you JD, for the audience’s benefit, how do figures like these compare to other tools or approaches, and what are the types of things we can do with high with high levels of engagement like this, when it comes to tailoring the learning experience or surfacing analytics?


JD Dillon:   

Sure. I challenge anyone that says that this is meaningfully different. In my background, I’m largely an operations and enterprise learning and development professional. In my case, you know, a lot of times, training was something we have to chase people down to complete. I think that maybe from a, how many touch points do we have as learning and development, or how many times people do log in to a learning management system, was a relatively small number. We were saying things like, I had one job where I was responsible for making sure that everyone had two hours of training a year. Just two hours on something, and that was the tangible that we’re held accountable for as learning and development. I think when you go from that world to a world where, with a refined set of tactics and the implementation of these types of principles, where we have people voluntarily doing something two to three times per week.

Especially something I’d like to remind everyone that when you get to worlds like retail, we have part-time employees in this audience, we don’t have a number that identifies that in the report, but a lot of folks who are only working two to three times per week. This is potentially something that people are doing every day. I’d like to challenge everyone to think about [inaudible 00:12:14] to help people to get better at their job when you have those couple of minutes every day.

To dig in to what microlearning looks like, I think one of the big questions people often ask is, “What are people doing?”. When you have these four million sessions, what’s truly happening? What is the person participating in as part of the experience? Now, everyone’s … learning tactics and the content’s going to be different depending on what your organization’s trying to achieve, but I want to break down, very quickly, what does a … learning session look like?

When we looked at this data across last year, we found that the average session time, so when people were completing a micro session in Axonify, on average, that session was five minutes and 48 seconds. … happens in five minutes and 48 seconds that helps people do their job better.

The first portion you see on screen that represents about 35 seconds, is actually a communication consideration. When you talk about, workers who … deskless, frontline employees, retail associates, plant workers, manufacturing workers, they often are very hard to reach. We start to work backwards from the level of engagement we’re talking about and how many touch points microlearning introduces in the day, we can use those for a variety of things. In this case, we see on average about 35 seconds is spent reading messaging. Maybe from the CEO, from the management team, but it’s like getting critical timely information in front of employees. [inaudible 00:13:33] which is about 137 seconds is what you would consider traditional training experience. This is where people are potentially consuming a video, they may be completing a score module. On average, within Axonify, employees were answering four questions as part of this experience, something, it could be a reinforcement session, a session on something they’ve already received training on.

Also 60% of time, they were opting in to play a game which we’ll talk into, and about 30% of these employees opted to take extra training, so beyond what was assigned for the day. We’re at half of this session time, and we’re looking at people consuming new information, completing a learning experience, the formal training experience. What’s happening in the other half?

Now we’re looking at the motivation rewards consideration for the next piece of the pie. Where people are checking on rewards status. We use a rewards engine for motivational tactics within Axonify. People are checking how could they potentially use their points that they’ve earned in Axonify with game mechanics for a tangible reward for their efforts. Checking up on the activity of their peers, looking at the social component and seeing what the news feed looks like.

The last chunk of this five minutes and 48 seconds, we’re looking at people basically checking on their progress. This is where they’re looking at their report card to see how they’re progressing in topics over time, looking at the leaderboard to see how they stack up against their peers. Whether it be from a competitive perspective or to just understand how they’re progressing on the job as compared to the other folks that they’re working with.

When we break apart … a microlearning session looks like and how people are spending that five or so minutes per day, you can see a lot of voluntary activity wrapped around the training experience. People engaging in different ways based on where they find value, again, very focused in a very short period of time on training experiences that target helping them do their job. I hope this provides context around what people are doing when we say they’re completing a microlearning session. On average, this is how that time is being spent.


Carol Leaman: 

Thank you very much, JD. Now, let’s look at some general trends that surfaced with the research. Where you’re using it for onboarding, [inaudible 00:15:47] are growing and sustaining critical knowledge to drive on the job performance, the data tells us that microlearning has universal appeal across virtually every industry. The largest concentration of adoption though exists in three key sectors, and they’re retail, finance and insurance, and manufacturing and logistics [inaudible 00:16:10] at the outset. What’s a common thread between all of these three industries, is this idea of the deskless worker. The worker needs training when the deskless environment, in particular, that fits seamlessly into their busy work flow. Whether they’re on the floor dealing with customers or working remotely to sell complex financial products, they’ll be in the field as a sales rep, or the on the road transporting product to an end consumer, they need to have something that fits very seamlessly into the work flow. Which is very different than a desked worker.

As you can see from the graph, from a global distribution and usage point of view, this is being delivered in almost 200 countries in over 40 languages. There really are no barriers in terms of geographic or language or those sorts of, types of barriers that one might think would exist. It isn’t the case that it is only happening in North America, it is, in fact, a global movement.


JD Dillon: 

… about reaching out to the deskless workforce, so folks who again don’t have a ton of control over their day, maybe don’t work in front of a device of some type, how do we reach that audience? If anyone here is looking to [inaudible 00:17:40] the value of mobile technology or to break down the wall for bring your own device strategies and things like that, I think here’s an interesting stat in report, that we definitively see when mobile devices are permitted within microlearning experience, we teach training frequency increase quite heavily. Who have more access, again, whether it’s their own device or a mobile device they’re using as part of their job, engage more frequently and it’s again, not because they’re being told to do it, it’s because they have an opportunity to access something that’s going to help them do their job. Again, it’s a great point for anyone who’s trying to make the case for the use of mobile technologies to support continuous learning and microlearning.

Carol already mentioned, we’re going to talk a little about gamification because we want to complete buzzword bingo as part of this webinar. When we talk microlearning … said, not a well-defined concept we’re trying to break through that noise, we also would like to do the same thing around game mechanics. There’s been conversations for 10+ years at this point around, “Do game mechanics work? Is it just a buzzy idea? Is training supposed to be fun?” What we [inaudible 00:18:45] are two things. One, this is an opportunity to break through the rhetoric and help people more fully understand the value of gamification. Two, it’s a critical part of the experience we’re discussing today.

When we talk about the level of engagement, the level of participation we’re seeing in microlearning, talk about the motivational side, why are people coming back, is an important part of the puzzle, so we need to make sure that we address it as part of the conversation today.


Carol Leaman: 

To continue with what JD was [inaudible 00:19:14] path of there, the whole concept of gamification is one that has caused a lot of confusion in the learning space. People don’t fully understand what the varieties of gamification can mean, and what we know is that two specific game mechanics are highly effective at driving voluntary participation, when combined with learning. They don’t have to be heavy scenario based or quest … games. [inaudible 00:19:49] gaming, so these are games like Angry Birds or brain teaser style games, that really are short and fun and mimic things that an individual learner might play in their space time. Those are the games that really stimulate the brain to free it of distractions so that when learning happens, the brain can focus on the key learning point, and optimize knowledge acquisition. It works extremely well, and there are lots of written pieces about how that works now.

The second thing are, what everybody would … familiar with, things like [inaudible 00:20:30], the words JD just mentioned, challenges, competitive spirit that you can build within your workforce. Those things, the points, the rewards, the challenges really do motivate employees dramatically to engage in the daily learning experience. Each of these things, when combined with learning, can have a dramatic impact on increasing knowledge which ultimately changes behavior.


JD Dillon:

[inaudible 00:21:03] a significant percentage of the individuals completing a microlearning session included gameplay as part of that experience. This stat is particularly interesting to me because it’s particularly not interesting at all. There’s potentially a myth out there that says games are for certain types of people, and what we’ve want to drive home and use some of our data to validate, is that games don’t discriminate, especially based on gender. When … data apart, we see that games are equally applicable and equally interesting between users identified as male or as female. Also, I urge everyone to think about this is terms of other ways that we categorize individuals of the workplace. If you’re looking to make the case around the use of gameplay and gamification within your organization, our data shows that it’s equally applicable regardless of the makeup of your workforce.

When we go down another layer, we do see the different types of games that we offer, they’re selected and engaged with at different rates. We see things like brain teasers actually being more popular overall than sports games, which might be slightly counter intuitive given the popularity of certain games in everyday life. We do see some variation between users who identify as male and female in terms of the [inaudible 00:22:13] game selection. It’s not about gameplay overall and who wants to have fun and doesn’t want to have fun as part of training, and how that focus is achieved. We do see some variation in terms of selection, which again, doesn’t mean you’re program in a particular way and use games in a certain way based on the makeup of your [inaudible 00:22:31]. I think it’s just something interesting to point out because it is a highlight within the data that we present today.


Carol Leaman:

Continuing on that theme, the impact of casual gameplay on things that are important to the organization. Participation, extra training, knowledge acquisition, are pretty dramatic. What the data shows us is employees who do choose to play casual games during their daily training show 52% higher overall participation in those daily training sessions. Advising participation is the first step in the equation to get employees and learners more knowledgeable, doing the right things in the workplace. It also turns out that employees who select to play a game during the day are 100% more likely … voluntarily take a little bit of extra training if you make it available to them.

An extra minute to three minutes is actually taken to reinforce key learning or to learn something new. Again, not something that we would typically see in a traditional learning environment. Finally, employees who have the option to play, have a knowledge level driven 20% higher than those who simply go on and do their daily training sessions. It gets back to what I mentioned earlier, which is that, the brain when playing a game, frees itself of distractions, the whole dopamine effect kicks in, and it gives a very ripe environment for the brain to acquire knowledge and retain it longer. That again, is proven here by the data.


JD Dillon: 

There’s one additional point I could drive home as well when it comes to the gamification consideration with things … more familiar like points, leader boards, and whatnot. It’s, how do the mechanics and how do the motivators translate into some type of tangible or real world value? I think there’s a variety of ways we can go in that conversation. In this particular case, we’re actually using tangible rewards. When you earn points within the microlearning experience, you can use them and translate them into some type of an item, maybe it’s an option experience or purchasing experience in a marketplace, and what [inaudible 00:24:57] are that participation is considerably higher, so 200% higher, when rewards are provided as compared to when they are not. [inaudible 00:25:07] are very open in using tangible rewards to reward the effort for people voluntarily engaging in microlearning, and some aren’t quite sure, but we see huge participation spikes when rewards are offered. We also see that [inaudible 00:25:22] regularly visit the rewards page exhibit higher training frequencies than those who don’t.

Even in an environment where rewards are offered, not everyone’s necessarily going to be engaged in that consideration, but those who are come back more frequently, train more frequently, and to connect it to what Carol just said, have higher levels of knowledge, because of that level of engagement and the fact that they’re coming back and continuously reinforcing that knowledge.

I know when I was the learning and development professional, it was an interesting conversation to go to the executive team and talk about physically rewarding people for training, because it’s a relatively new idea. But, why not reward the effort? Especially when it’s something that people are spending limited time on every day as part of their job. Huge changes in participation when there’s an outcome and a reward in addition to the overall learning and job improvement that we expect from training at work.

As we jump out of the gamification consideration, goes back into the details of the data. Get into really the crux of the report when it comes to the measurement, applications, industry application, and finally the benchmarks and the measurements we pulled from the data from last year when it came to the microlearning sessions. I think it’s important first to take a high level look at the types of metrics that we’re using. Because we mentioned earlier, that microlearning helps us get beyond the traditional completion, test score, you took a test once in training six months ago, but we don’t quite know where you are now, because traditional training doesn’t have that continuous component. Microlearning gives that ability to continuously measure where people are in terms of both their knowledge and their confidence in applying that knowledge.

You look at the data on screen, these are actually the summarized data points from the sample size that year. [inaudible 00:27:00] everything from baseline knowledge, the first time someone gauged, the first we asked them a question to assess where the knowledge was. 73%, so they knew 73% of the information presented, over the course of the year, that lifted by 12% to get to a sustained knowledge level of 85%. Their self-assessed confidence, so how confident are you in this information, how likely are you to use it on the job, was measured at a 8.2 out of 10. A high level of confidence overall in the sample size across all of the jobs we’re talking about today. We already talked about engagement measures, but again, overall participation last year was 74% of people engaging at least once per month, and on average, they were engaging about 8.7 times or two to three times per week throughout the course of last year.

Those are the metrics that you’re going to see throughout the report. We’ll give you a little bit of a high level summary of some of the highlights jump out as we work our way through the different sessions of the report.


Carol Leaman: 

Speaking of highlights, what is clear based on the global exposure that microlearning is now getting, what we know is it is being used ubiquitously across the globe to build employee performance, deliver business results for lots of organizations. Here, we want to take a look at the most common applications and the subjects that companies are in, at a practical level training their people on. Then we’re going to further break down the numbers within specific industries to serve as benchmarks for what your peers are doing, and help you set your priorities for the future.

If you take a look at the findings on the top of the chart, what you see here is that product knowledge is by far and away the number one topic that companies are training their people on. This isn’t necessarily unexpected. Products today, just the way the world is, change frequently, particularly in certain industries. If you’re in the retail beauty industry for example, every week, there are new beauty products being launched, and your associates need to be on top of how to effectively sell everything new coming in. If you’re a pharmaceutical sales rep, the number of regulations, competitive products, the efficacy of products, all of those things are highly complex, constantly evolving and require diligence on the part of the learner or employee to stay on top of what they need to know, in order to effectively work, and effectively deliver results for the organization.

From top line revenue perspective, product knowledge sales, customer service, experience related training, comprised three of the top five applications. [inaudible 00:30:00] that top line revenue is critically important for organizations. Safety, on the expense side of the equation, safety is the second most popular application. This really is incredibly helpful in instilling that safety first culture to first line employees who are putting themselves at risk in warehouses, in other logistics types operations, driving trucks, you name it. The number of safety concerns in organizations today is, again, unprecedented. Having employees be on top of all that is critically important to the business.

JD, is there any contrast between the applications we see here, versus what organizations typically train their people on using more traditional [inaudible 00:30:56] modalities? In other words, I’m asking, would this chart the look the same if we were to take a sample from an LMS tool for example?


JD Dillon: 

Actually, I’d be shocked if anyone whose with us today or watching our recording looks at this list and says, “This is radically different than my prioritization as a learning and development professional,” because again, I think we’re talking about the things that are high level priorities, critical priorities for business, especially when we talk about things like product knowledge, customer service, these types of ideas.

What it says to me, in terms of, [inaudible 00:31:27] start to connect this data anecdotally to some of the stories of organizations that we know are applying microlearning principles, start to speak to the idea of applying a new method to do the things we’re all trying to achieve, but do them better. To finally to break through some of the barriers or walls, or barriers, limitations, in terms of our ability to support employees. I’m going to use product knowledge as an example, I like [inaudible 00:31:49], I think is a great example for this as well, because when certain companies release a new phone, they don’t give the information to the provider until maybe a day or two prior to the phone releasing. You, as a sales person, happen to know just as much as the person who’s really into phones, who’s been doing research on this thing for months, and they’re coming to get that new phone.

The speed with which that business can now respond because we have this idea of continuous learning embedded into the day, allows us to be much more proactive and less reactive. I think another great example is safety … organization’s safety training is something that’s done in onboarding, and now everyone’s been trained, so now they’re going to be safe. That’s not what happens, people can develop bad behaviors, bad habits as they go, and that type of activity’s what ultimately gets someone hurt. This allows us to be more proactive and get there before there’s a challenge by reinforcing the right things, breaking those bad habits, and really instilling a culture of knowledge around topics that are critical for the business.

I think there’s an alignment in terms of prioritization. I think those organizations are addressing those considerations differently, because of the agility that’s really fostered around microlearning and this idea of continuous daily learning.


Carol Leaman:

Perfect segue into the next slide JD, it is really is about the agile business, and what that means is that changes to business happen all the time. When you employ microlearning, they can be changes that are rapid, and if you chunk them down into their individual concepts, they can be absorbed by the business, because they’re small and it does enable the business to be very nimble and adapt rapidly to the changing business environment right in the moment. Such continuous cycle really means there’s no start and end to learning, which is one of the things that really goes against what we’ve historically done. It’s always been that [inaudible 00:33:52] as JD just mentioned, where you train on safety and then you expect people to be safe.

Continuous learning is very much supported by microlearning, which again supports the business with all of the changes and keeps it [inaudible 00:34:11]. Coincidentally, this concept also really describes the philosophy behind microlearning, because as … previous slide demonstrates, businesses are adopting this to respond to product changes, just changes generally in the information in the workforce that matter to that business. All businesses are different. There is no one size fits all. Be able to do it quickly and easily is absolutely essential in the competitive global marketplace that we live today.

JD, I’m curious to hear about how the concept of microlearning and the topic of business agility have become part of the same discussion over the past few years. Is this more a line of business conversation within organizations? Does it now blend into learning? Because learning has been the domain of human resources and learning and development organizations historically.


JD Dillon:   

You’d have heard the word agility a lot more used on the line of business side of conversation … several years now. The word agility is erupting in a lot of different publications and a lot of different blogs and a lot of different presentation topics today, across things like instructional design, learning strategies, these types of ideas. I know for me personally, coming out of a corporate learning environment, it was always, again, one of my biggest challenges and why I started to get interested and naturally evolve into the application of these types of principles. The idea of daily learning, the idea of shifting away from a net based mentally, to something that was closer to the what people are doing every day and where and when they were spending time on the job.

It was because I was always trying to keep up. The business was constantly changing, trying not to get disrupted, trying not to fall behind, and as a result, me as the L&D guy, I’m responsible for trying to keep employees up to speed with the decisions the business is making. Microlearning is a natural evolution based on the realities of business, and I think that we’re starting to see the same types of conversations take place within learning and development. I think this data echoes that evolution in the fact that, we’re trying to keep up and do our jobs as best we can, and I think these principles are helping us do it as long as we’re able to imagine what it’s like to provide training experiences inside of the workplace.

As we dig a little bit deeper, I’m not going to go deep into the data because again, we’ve only got 20 minutes or so, and you’re going to have the full report of you when we’re done today. A couple things to just quickly highlight as we start to break down each of the individual industries that we’re focused on in this version of the report. When you look at these graphs, you see that we’re measuring again knowledge growth over the course of last year within our sample size, and also changes in confidence. One thing that may stand out if this type of data and this type of report is new to you, is that you’re not seeing zero to 100% knowledge growth. People didn’t start with a baseline of nothing and then go up to 100% last year, because that’s simply unrealistic in terms of how people learn.

Two, everyone was at a different place last year within the sample size. Some employees are brand new to this experience and new to the organization, but sample size also includes employees who’ve been doing this for 40 years, or have been part of the organization forever, and while microlearning is maybe new to them, their knowledge has been there for a while. We’re measuring not just new knowledge, people who have received training for the first time, but driving that sustainment of knowledge and that retention over time because the reality is with traditional learning, if you graph these same types of numbers, you see declines over the course of the year. Because people forget, people develop bad habits, if you test people at the beginning of the year and the end of the year, it’s not necessarily always going to be a growth.

One thing is to point out that we’re [inaudible 00:38:04] new and sustained knowledge within the reporting. Two, that’s small increments in knowledge growth. You see the safety graph as an example says, if we went 79.3 to 89.4, so about 10 point growth in terms of sample size knowledge for these particular topics, that 10 points can be very meaningful when you think about the types of decisions people are making on the job and how people trying to keep themselves and their peers safe.

Numbers may look a little bit different than you’re used to, maybe you’re always looking for 90% and above, passing scores and things like that. Try to remember the types of data we’re measuring, and the context in which it’s being measured, and it’s about growing and sustaining that knowledge over the course of a year. When you take that into consideration, these numbers are particularly impressive in my opinion.


Carol Leaman: 

Turning to the industries that we focus on as part of this report. Retail represented the largest cluster of usage across the sample. In terms of key performance indicators, a couple I want to call out here across the industries covered in the report, retail boasted highest current knowledge and confidence. 84% from a knowledge perspective, current knowledge, and 8.4 out of 10 from a confidence perspective, respectively. Very high degrees of knowledge growth, confidence in the retail sector.

When you look at the retail applications, what are they delivering in terms of knowledge, what are those topic areas that are most important? What we see is, as I mentioned a few moments ago, heavy focus on product knowledge, and that actually crosses all types of retailers, but they also have a very heavy emphasis on [inaudible 00:39:59] in the workplace and customer service. How to engender loyalty, how to increase basket size, all of those things that really result from great customer service. They’re critical to those frontline associates, transforming particularly brick and mortar customer experiences to provide extra revenue in the retail world.

JD, how does that line up with conversations you have with a ring of business leaders in retail?


JD Dillon: 

I think one, as we’ve already said, there’s a consistency in terms of prioritization. Things like safety as an example, may jump out, because safety in a retail environment may not ping in people’s minds as a top priority as compared to things like product knowledge and customer service. I think we see a relative consistency there. At the jump in terms of things like marketing, [inaudible 00:40:49], asset protection, again, speaks to timely business priorities that are maybe not unique, but more important in this type of an environment. The other thing I think stands out is the breadth of topics, again, we’re only looking at the top selection each of the use cases we’re talking.

In a lot of cases, you can bogged down with specifically focusing most of your time on just product knowledge and maybe never get to continuous safety training and these types of ideas. Or, [inaudible 00:41:13] training and never really get to that marketing promotions or asset protection story. I think it really speaks to the breadth of knowledge and the breadth of topics that can be addressed when we’re talking about something that people are doing every day and reinforcing right topics for them. You can cover more ground because different people are at different points in their career and have different needs.

Yeah, I see a larger list here of active work than I traditionally see in terms of the limited scope and limited resources learning and development teams may have, especially in a hard to reach retail environment. You then break it down to see what does growth and confidence growth look like. I think it’s important to note, one, the noticeably high levels of knowledge that these organizations are getting to, with again, a retail environment with [inaudible 00:41:58] that in traditional environments may not ever get training. Maybe these are folks with their first job, they’re new to this company, new to this type of product.

I know in a lot of retail environments, we’re shifting from a world where a retail associate folds clothes and just checks people out at the cash register, to where you’re expecting them to be a style assistant and help put together the perfect outfit for this particular customer. The high levels of knowledge coupled with that reality, and especially the high levels of confidence, speak to … this approach, the fact that they’re always getting support, is making them more ready to use their knowledge than maybe traditional experiences where they just get training when they’re onboarded and they’ve got to figure it out themselves from there.


Carol Leaman: 

JD, the second industry that we want to focus on is finance and insurance. Here, we’re talking about banks, we’re talking about insurance companies that sell complex insurance products or banking products. What you can see as far as the KPI’s go, is that this industry had the highest level of knowledge lift. That increase from baseline knowledge, the first time through content, to the average current knowledge after microlearning training. Yet interestingly, this industry boasts the lowest current knowledge overall. I think that this is largely the result of the type of knowledge they’re expected to know, heavily regulated and very complex. JD, what do you think about that?


JD Dillon:   

Yeah, I think if you compare this graph to the previous or the overall story within the report, process leaps forward. If you’re in finance and insurance, you’re in banking, you understand the regulatory considerations that are surrounding you, I think in a lot of cases, that can be, not an excuse, but it can be a distraction from getting to the things that are going to really help people sell more effectively, support customers more effectively, because you’re in a highly regulated environment, but it’s not the only thing, but it tends to be the most important thing. Without that, big trouble tends to happen. I think you see that focus enable here from a microlearning, continuous learning approach, but not dominating the other things that I think are equally important when it comes to helping people do their jobs when they’re working with or selling very complicated products. You see a huge prioritization of process, but it doesn’t overwhelm the other things that are going to help people do their jobs more effectively in this use case.


Carol Leaman:

If you look at the top applications in terms of knowledge and confidence, similar to what we’ve just been talking about, we saw the highest jump in knowledge lift in the F&I industry versus the other industries, at 13%. Why does it grow at a faster rate in F&I than other industries? Part of the reason for that is, that the entire world of finance moves at a very fast clip. Competition is fierce. As a financial advisor, if you tune out for a second, a regulation changed, stock market shifted, and you really do need to be on top of your game, so that you are the advisor that has the best chance of closing that next deal.

Why the lowest knowledge levels then? It’s not easy, as we’ve been talking about. The topics are extremely complicated and think about things like, they have to know how to properly calculate a return on an annuity or how to asses risk with a customer, and dealing with topics that involve, for example, personal wealth or life insurance or just money in general, the stakes can be extremely high.

Finally, the last industry that we want to look at is manufacturing and logistics. This particular sector in terms of the KPIs has current knowledge on par with finance and insurance at 83%, and only trails F&I slightly in knowledge lift at 12%. Very, very similar metrics there.


JD Dillon: 

I don’t think anyone’s going to be shocked when they look at this graph in terms of top applications and see [inaudible 00:46:20] leap forward in a manufacturing logistics environment given the equipment usage, the various hazards that people in this type of a workplace face. Again, I think it reinforces the story of organizations not just wanting to deliver safety training, but really embed a safety culture and make safety part of conversation every day at work. It’s not enough to just give people the training when they’re onboarded, tell them how to cross effectively at crosswalks, in a logistics environment, not get hit by a forklift, [inaudible 00:46:50]. It’s not just training to them that once, but it’s the idea of reinforcing that knowledge, reinforcing those habits, so that people don’t make those mistakes later. Again, I think that’s why you see microlearning lean heavily into safety applications, especially in this use case, given that it’s about reinforcing that knowledge and keeping it part of the conversation, and not allowing things to slip over time.

One thing that I think does stand, again, you’re thinking about a manufacturing logistics environment, again [inaudible 00:47:15] shouldn’t shock anyone reading this report, product knowledge however being the top item in this use case as well, surprised me when I first saw the data. Carol, I’m curious, where it comes from?


Carol Leaman: 

Where it comes from, it is surprising, I don’t think it’s the intuitive answer most people would expect. When it comes right down it, people in manufacturing and logistics, and these include manufacturers of products like medical devices for example, they really do need to be on top of product knowledge. Even if you’re a warehouse worker, you need to understand the product that your company is selling. Product knowledge becomes one of those things that everybody needs to be aware of and cognizant of to effectively to execute on your job. It’s that foundational information that you need to understand in order to deliver on whatever it is that you’re doing for the organization.

If we turn to knowledge and confidence, we see here despite a low knowledge baseline when it comes to product knowledge, so that 23.8%, microlearning helps lift those manufacturing logistics employees’ knowledge up to an incredible 91.4%, the highest mark in the most widely used application. JD, maybe you can talk a bit about the confidence lift here, and how even a small upward tick can drive significant behavior change, as an example, trying to instill that safety culture in your workplace.


JD Dillon:   

I think it’s just an important dimension of the conversation when it comes to measurement around training knowledge, and especially when it comes to what we can do with the types of data we’re collecting through microlearning. It’s not just enough to test people to know if they know, are they ready and willing to use that knowledge in the moment. When we think about a safety implementation or a manufacturing logistics environment, it’s the type of environment where you can’t default to looking something up if you don’t know or you’re not confident in your ability to apply. It’s the type of environment, again this is true in a lot of cases, but especially in this type of an environment, you need to know and you need to make the decision now in order to do the right thing, help keep you or someone else in the job safe. You can’t look it up or ask somebody when the moment arises.

I think [inaudible 00:49:47] assessing that confidence and using that information to ensure that people are ready to apply their new and their sustained knowledge is critical, and I think we see that [inaudible 00:49:56] here in terms of a high level of confidence across the most important topics in this use case, when maybe it’s a little bit lower in some of the things that, again, are not commonly applied topics, things like HR, corporate culture versus something like safety where you really need to … ready apply to it at any moment.

As just to wrap up, we’ve got about 10 minutes to go, we’ve got a lot of data, again, we’ve provided a very high level review of some of the highlights that are in the deeper report that you’ll get access to right after our presentation. You go from here, your use case in your organization, maybe you’re just exploring microlearning, maybe you’ve already gotten started, you’re looking to go a little bit deeper, what are the findings of the report, and can inform the strategy you’re trying to create in your organization.

[inaudible 00:50:41] of recommendations that come out of the insights from this data are one, critical importance of starting with the end in mind. Again, you see that organizations are leading into the types of topics and subject matter that are going to drive results for the business. Making sure that we keep the target and the end result and the focus in mind, because it’s not just about creating smaller stuff, it’s about really driving results for the business. [inaudible 00:51:05] going to generate the most impact. [inaudible 00:51:08] where do I get started, what’s the first use case, the first topic we’re going to try to address.

Hopefully the report gives you some recommendations, especially if you’re in one of the sample use cases in industries we’ve talked about. Again, it’s really about where are you going to generate the most business impact, where you’re going to help the organization make money, where you’re going to help keep people safer, what’s going to really create value for the organization and the employee. [inaudible 00:51:27] and focusing on that specific measurable result.

Nothing we talked about today was training for the sake of training. There was a lot more types of measurement, and we’ve got even more future studies that we’re doing now, but it’s really about finding that specific result, so that you can know when you’re being successful, and how microlearning is really taking effect.

Making sure you have the right technology in play. This is maybe, you got an existing [inaudible 00:51:50] mapping system, you’re looking to explore microlearning platform, something that does enable this daily experience like we talked about today, especially if you’re working with a large audience, and you have relatively limited resources, the right technology is going to be critical in helping people get continuous access to learning. We’re showing that people, when they have that access, will come, they will engage voluntarily and their knowledge will grow and sustain over time.

The casual gameplay piece. Again, I think providing some validation around the intelligent use of game mechanics and gameplay that measurably, it does increase engagement, and it does drive to improve knowledge and improve results. It’s about using it in the right way that’s going to motivate people based on what you’re trying to achieve as a business.

Finally, doing your homework, I think you stated, by hanging out with us today, by checking out the report in detail, but really, looking at organizations who are already doing this, a lot of this has been demystified, meanwhile, a lot of the conversation still has buzz and noise around it. I think it’s important to look at the organization, the use cases, the stories that are already coming out of people who are applying microlearning principles, learning from that they’re doing, use that evidence to make your case in your organization, and then stepping into this based on evidence-based principles, not just buzz for the sake of buzz.

I think those are some of the insights that stand out for me in terms of, how you can take steps forward to apply microlearning in your organization.


Carol Leaman: 

Those were really, really insightful comments JD. Microlearning success is directly attributable to how human it is. It isn’t just about the buzz, it’s really designed around how people learn, what … like, how they apply their learning in real life scenarios, and it does treat learners like unique individuals as they are, rather than as that one size fits all, faceless homogenous group. By collecting hundreds of millions of data points that are available through microlearning, it now can prove the power and promise, it’s proving its power and promise, to take corporate learnings to completely new heights. Giving entire learning industry actually, a powerful set of big data that has been missing in history, through all of these years.

The first time, it really does enable learning and business leaders to measure the impact of turning and being strategic enablers in their business. We introduced a new product for those of you who don’t know, called Axonify Impact, which combines the vast amount of microlearning data that’s captured every day in those millions of sessions, and trying those to business results with growth and sales [inaudible 00:54:35] of expenses to truly regress those things together using machine learning, and prove the impact of training on your business. In next year’s report, we’re really excited to share those new insights with you, as all of that information gets tied together with those business metrics.

We’re going to jump to your questions in just a moment, but I wanted to take a moment to point out the full report to all of you, and some additional resources around microlearning, that you can access, including some real customer stories from the field. Doreen will be sending you a recording of this webinar, along with the full report when we wrap up.

We just have time for a couple of questions here. There were lots that came in, if you submitted a question, we will be back to you after the webinar. The first couple of questions, the first one was, is healthcare represented in the data? I’ll answer that one quickly and say yes, it was, and they actually fall under the other category in the report as you’ll see. Generally, the data applies to all industries, it’s very homogeneous across the sets of companies, but healthcare is represented there.

JD, a question for you. Referring back to the 50/50 split between learning and motivation that you showed in the anatomy of a microlearning session, the … does this experience … is this experience generally how microlearning engagement would look across microlearning providers like Axonify?


JD Dillon:   

I think the use of different tactics is going to depend on your organization, your culture, what experience you’re trying to create, what you’re trying to achieve. Even within Axonify use cases, we see variation in terms of what tactics people use. I mentioned with rewards, some organizations are using tangible rewards, some organizations are not, because they don’t it appropriate for their organization, but we have data that shows why you would want to consider doing so. [inaudible 00:56:45] that session time, if you broke it apart by a particular organization, or the use of different types of tactics and tools, you’ll see variation, but I think it gives you a solid idea of how people use their time, have the opportunity to engage continuously, and a voluntary experience where attention goes, and you can use that information to better shape the experience to drive long term knowledge, retention and growth.

I guess that’s why it’s a very useful piece of data, regardless of where you are in terms of your tools and tactics and whatnot.


Carol Leaman: 

We’ve got time for one more question JD. Actually, it’s two questions I’ll combine into one for you. How do you determine current knowledge, in other words, are these based on pre, post-test assessments, and how do you measure confidence? How do you measure current knowledge and how do you measure confidence?


JD Dillon:

Terms of knowledge, if you think about kind of the pre, post-test scenario, it tends to be very event-driven. You ask people a question before the training, you figure out if they knew it or they did not. After the training, you ask them again, did their knowledge change … they must’ve learned. If you expand that idea to say that we’re going to continuously ask you, we’re not just going to ask you a question, maybe we’ll challenge you with a scenario. We’ll do a variety of different things to basically probe at your knowledge, do you still remember? Do you know how to apply?

[inaudible 00:58:03] just do one pre-test, post-test scenario, it expands that idea, to make it about continuously engaging and asking. There is data that goes further than that in terms of observing transfer and behavior on the job, it’s simply not part of our story yet, it will be part of our story as we continue to evolve.

[inaudible 00:58:19] something that people are already doing, to make sure that it’s not just about knowledge, it about performance as well. From a confidence perspective, in this case confidence is self-assessed. Every time we ask people and challenge them to do something, to answer a question, to engage in a scenario, we’re all asking for their confidence in that knowledge. How confident are they in their answers. They’re self-assessing, they’re taking that moment to think about it, and giving us that information, because confidence is a personal internal concept.

[inaudible 00:58:45] how confident you are by watching you. I can tell if you’re doing it right or wrong, but you may be guessing. It’s another data point that we [inaudible 00:58:53], with [inaudible 00:58:54] around knowledge, behavior and business results, that helps us better understand where people are in their learning, but is a self-assessed metric in this case.


Carol Leaman: 

Thank you, JD. With one minute to go, I just want to say that, if you have submitted additional questions, we’ll be happy to answer them after the webinar is complete. You’ll get a copy of the recording and a copy of the report in the coming week.

Thank you very much from both JD and I, for your time and attention today. If you have any additional comments, questions, inquiries with respect to any of the data, please reach out, we’d be more than happy to engage and answer them for you.

Thanks again everybody, and have a great day.


JD Dillon: 

Thanks all.