I recently read this post about “HR Debt“, which I strongly encourage you to read.
Most startup founders are familiar with the idea of technical debt, whereby poor system design or coding builds problems over time and makes it hard to improve a piece of software. If you don’t clean up and refactor as you build, you’re left with a clunky mess that no one can (or wants to) fix.
The same thing happens if you hack your way through hiring and management.
I call this HR Debt.
Come on back when you are done.
It got me to thinking about the same notion when it comes to training. Are there situations that you are incurring training debt through poor system design? I think for many organizations there are times when that could be a yes.
1. Not offering new employee training – in a small organization, there is very little of this offered for a couple of reasons: you might be the only person that does that work and there’s no real documented processes or training to use, and there might not be anyone in charge within the organization to give that warm fuzzy orientation that larger organizations can offer.
In larger organizations there may be a nice orientation “course”, but often the connection between the vision, values, HR info that you get in an orientation and job-specific training is missing or at odds with what’s in the warm fuzzy orientation.
So you may have employees who don’t know what to do and/or you have employees who don’t know why they do it.
2. New product roll-out – launching a new product into the market without providing proper employee training could end up hurting you in the end.
3. Ignoring legislative or regulatory requirements – You might also risk an employee doing a task wrong, which could have dire circumstances for your customers, your company or even create personal liability.
4. Ignoring some employees when it comes to training – if you are focusing on groups of employees, you may be missing some people that are less obvious, but can have a big impact on the organization. For example you train employees who are customer-facing, but don’t bother training others in the organization.
5. Doing all classroom or self-paced elearning – if you don’t match the need with the method, you may end up spending more on training that isn’t really the right fit. Sometimes, connecting employees together to learn from one another is the right approach, other times it might be creating a helpful job aid.
6. Overspending on a single group, such as the executives – if your budget is limited, don’t let your ego dictate your spending choices – those leadership development programs are always expensive and may not deliver in the end.
7. Creating training and not keeping it current – this becomes not only a waste of time to provide the training, but means that the validity of the entire training solution might be called into question and not followed (can I trust that this is the right information?)
8. Treating training as a “one 0ff” – put them through a training class and then assume they are “trained”.
9. Appointing someone in your organization as the “trainer” – they may know a lot about the subject, but they may not remember what it’s like to be new, or how to sequence instruction to maximize learning. This might end up a situation where your good intentions cost you more in the end.
10. Not training customers, suppliers or others in your ecosystem about things that are critical to your business. Training is not solely for employees.
11. Waiting until a major issue, mistake or event forces you to provide training.
12. Thinking of training as a “perk” – this happens a lot when it comes to ongoing professional development – you offer a certain amount of money for ongoing learning but don’t consider how to manage this or what the implications are as you grow.
13. Tacking training on at the end of a project – this is common in systems training – training is considered when everything has already been designed (when it would have been much better to be involved during the project to understand the system and impacts on employees) or it is assumed that you will deliver this in a classroom.
Preventing Training Debt
In terms of preventing training debt – while there are times to hack together a quick and dirty training session, there are also times where that approach will come back to haunt you. Consider training as a strategic connection to your brand and your company growth. Investing is different than just spending. As you build your business plan, make sure you add in the questions: “who needs to be trained on this?” or “what training needs to be considered”. When introducing something new, don’t forget the training element. Seek out help if you need it.
What do you think? Are there areas of “training debt” that I’ve missed? What have you seen that you’d add to my list? What strategies would you offer to deal with it?
This is part 3 of my series exploring wearables in training and development. In part 1 I talked about the angle that I’m most interested in: wearables providing a trigger, feedback and data for learning and performance. In part 2, I explored it a bit further, making connections to self-reporting components, affective aspects and behaviour change.
In the next few posts, I’ll look at how wearables could play a role in different types of training situations, beginning with manufacturing organizations. I’m curious about this segment, as the majority of applications that are shown for wearables are typically busy professionals who need a watch because they can’t even take the time to look at their phone, but here’s a lot of different types of work out there, and yet the emphasis is often on the knowledge worker. There are things about manufacturing work that sets it apart from knowledge work.
- Productivity/efficiency is paramount
- Safety is a factor
- Physically demanding work
- Involves repetitive work
In manufacturing organizations, there are significant pressures to maximize efficiency (in reality, the role of humans in manufacturing operations is on the decline as more of these repetitive actions are done by robots), so there is likely a role that wearables could play to ensure this time to competency is reduced. Let’s assume that the employee is keen to reduce this time to competency and is not being pushed by a demanding employer, there are many things that could be an aid to monitoring and supporting learning. Let’s face it, having a laptop or even a tablet or handheld phone on a production floor is unwieldy and unlikely, so wearables could fit this niche.
If the employee wants to use a wearable (such as Google Glass or head mounted camera) to record portions of their work to play back and spot potential for improvement, they could use that approach to capture and review. They could “work out loud” narrating what they are doing, what they have questions about, what things they find challenging, etc. This could be reviewed by the employee and a smart system could provide short bursts of instruction after playback. Or it could be transmitted to the supervisor or expert for coaching.
There could be RFID chips or near field communications in the machinery, the product, or on their clothing to track activity, pacing, speed, weight, etc. Perhaps it’s using motion tracking to provide insights on their physical performance. This might ensure not only high productivity, but also provide feedback on techniques that may prevent repetitive strain injuries. There might also be sensors that provide insight on their physical responses – heart rate, blood pressure, body temperature, etc. There are also gadgets that capture data and transmit wirelessly via bluetooth, which generates data and could provide an opportunity for trend analysis.
Smart watches or arm bands could also provide a visual cue in a potentially noisy environment. A vibration might alert you to look at the screen giving you a message to adjust your actions, access a piece of performance support or capture that moment in time for data collection.
Wearables could offer a training “mode” in manufacturing environments, where feedback is provided during real work (not simulation) that gives coaching and corrective input to ensure that the employee is learning IN the work environment, with actual feedback on their real performance. This would be a real benefit for learning in situ, blending real time feedback with performance support. One organization is even pitching gloves that will shape your muscle memory.
And there is also the potential for virtual reality to provide a simulated workplace for training purposes. This is likely too costly for most manufacturing operations, however the potential exists.
What do YOU think? Have I highlighted the things that are most relevant to manufacturing? Do you have insights to share about wearables in manufacturing? Share them in the comments below! Next time we’ll look at wearables in service industries.
You might want to check out David Kelly’s blog, he’s written and collected insights about wearables as well.
This post is Part 2 in the series that I’ve started on Wearables for Learning + Development.
I am a huge fan of BJ Fogg’s work and find his behavior model such a useful way of thinking about training. As I reflect on the idea of wearables for feedback and monitoring of learning, it seems to me that it provides a great opportunity on the “trigger” side of his model that helps to convert activity into habit. I think it applies to learning situations as well, as we are hoping to convert learning into memory or at least develop behaviours that will provide scaffolding for learning.
Interestingly enough, I saw this today: This app tells you which of your friends stress you out, make you happy – the app provides you the opportunity to self-report about how you are feeling. In fact, after stumbling on the story, I did some searching and there are many mood tracking apps, such as:
- Emotion Sense – developed by Cambridge University
- Mood Meter developed by: Yale University
- Gotta Feeling
- And more here: http://www.wellocracy.com/mobile-mood-apps/
- and a bunch here that lump habit and mood trackers together: http://tech.co/best-habit-and-mood-tracking-apps-2013-08
When you consider the possibility of using apps to trigger your self-reporting or reflection, you open up some powerful insights to your own patterns and behaviours. Having the app on a wearable as opposed to just an app on your phone means you have the potential to incorporate physiological aspects, such as heart rate to the mix, which might give you additional insights that support your self-reporting or not! But that focus on how you are feeling or what your state of mind is might just give you a better view to what’s going on for you, holistically.
Imagine how this would impact your own learning:
- you decide you are going to learn something
- you sign up for training, let’s assume it’s e-learning
- you track your progress through testing, which is sent to you electronically AND you also self-report what’s going on in the environment
- your smart progress meter collects this data and begins to create a picture of how your learning is impacted by what’s going on around you, or within you (physically or emotionally)
- your smart progress meter provides you with tips on which times work best for you to study or practice as well as gives you reminders on where to find things.
- you refine your approach to maximize the learning
What about at an organizational level?
- you enroll employees/students in a course
- you choose to use a drip campaign or serialize your learning
- you develop an app that not only provides content, but also provides opportunities to practice (maybe it’s a form of gamification) and a self-reporting component
- you provide a personalized experience for each employee based not just on how they score on tests, but also on the kind of environmental data that your smart progress meter collects and analyzes
- now you have a ton of useful data about the efficacy of your training program.
We tend to treat learning as a completely cognitive event, but approaching it from this perspective means we look at learning (and delivering training) on a more systemic level. That is interesting to me. There are of course tons of privacy, security, ethical implications, especially on the organizational side, but it’s interesting to think about how wearables, the internet of things (IoT), data and the quantified self movement might provide for learning.
What are your impressions? Do you have ideas to share? I’d be curious to know what others think of this emerging area and the impact on learning.
There’s a fair bit of hype around wearables – smart watches, bands, rings, belts (!) and the list could go on. As a trend, it’s still a few years from actual impact (according to the Gartner Hype Cycle). I am curious about the possibilities for application to training or learning situations. So far, we have naturally gravitated towards examples like Google Glass or Oculus Rift, which hold potential for delivering instant information or training.
How would wearables apply to training/learning?
I’m equally curious about wearables for monitoring and feedback on your learning and in gadgets to deliver training or support. In a recent #chat2lrn, there was some brief conversation around this as a trend it got me thinking about some potential blog posts. I can see several scenarios worth exploring:
- Manufacturing training
- Service training
- Knowledge workers
- Health education
- Creative work
In the November issue of HBR, the feature article (“How Smart, Connected Products are Transforming Competition“), identifies there are three aspects to consider:
Physical components comprise the product’s mechanical and electrical parts. In a car, for example, these include the engine block, tires, and batteries.
Smart components comprise the sensors, microprocessors, data storage, controls, software, and typically, an embedded operating system and enhanced user interface. In a car, for example, smart components include the engine control unit, anti-lock braking system, rain-sensing windshields with automated wipers, and touch screen displays. In many products software replaces some hardware components or enables a single physical device to perform at a variety of levels.
Connectivity components comprise the ports, antaennae, and protocols enabling wired or wireless connections with the product. Connectivity takes three forms, which can be present together:
- One-to-one: An individual product connects to the user, the manufacturer, or another product through a port or other interface –for example, when a car is hooked up to a diagnostic machine.
- One-t0-many: A central system is continuously or intermittently connected to many products simultaneously. For example, many Tesla automobiles are connected to a single manufacturer system that monitors performance and accomplishes remote service and upgrades.
- Many-to-many: Multiple products connect to many other types of products and often also to external data sources. An array of types of farm equipment are connected to one another, and to geolocation data, to coordinate and optimize the farm system. For example. automated tillers inject nitrogen fertilizer at precise depths and intervals, and seeders follow, placing corn seeds directly in the fertilized soil.
So in a series of posts, I’ll explore wearables and training/learning for these situations, and also look at the role of the xAPI (here’s an awesome post on “Getting Started” by Aaron Silvers). If you have suggestions or examples, please pass them on!
Wow! Serials are really trending. The most popular example is “Serial” – a podcast that is delivered as a serial (shocking I know) – it’s a fabulous model for learning. People who are captivated by the story and the approach are creating their own “study” groups to discuss and analyze the new findings. It provides a great example of learning that is pushed out to an audience, but additional learning is pulled from the accompanying web resources (and the study groups). It’s fascinating. It’s compelling storytelling so it might be successful because it’s done well. Good pacing, moody background music, great interviewing. Plus, everyone loves a mystery.
Over the past few months, I’ve also seen some courses or modules being delivered by via email on some kind of schedule (serial) sometimes called:
- Drip Campaigns – more a marketing slant and training is one
- Educational Drip Campaigns – this shows how this type of learning can be a great Minimum Viable Product – MVP, which is a great insight and could even be a way for learning professionals to get a course out the door quickly. You could even build it as you go, adapting each week based on feedback or analytics.
- Subscription Learning – Dr. Will Thalheimer has a whole blog with examples
- Learning Campaigns – I noticed that all the big e-learning companies in the UK seem to offer this as part of their services now -not sure if these are courses broken into smaller pieces and delivered piecemeal (serialized), but struck me as interesting.
Email newsletters have been around forever, but these take the notion further, it’s not just a grab bag of interesting content, but content with instructional goals, delivered with intent to teach something. There’s something anticipatory about waiting for your installment. The examples I’ve referred to below are not stories, but that would be a very interesting approach.
Here’s a couple of examples:
This Explains Everything (how could you NOT sign up for this?) – this is a course that features a range of experts and provides you insights on product psychology. It’s more of a curated list, but each week in your inbox a new module is sent about social psychology, brain science or design thinking.
“Creative instructional design lessons” can be delivered to your inbox from Ever Learning. The topics include “Use Learner Personas to design learning experiences” and “Digital technology is like a bicycle for the mind”. The lessons aren’t long, and it’s the kind of email that you like to open because you are going to learn something.
If you want to create your own – you might want to check out: How to create a self-paced email course. The part I like about this explanation is it establishes a way to set autoresponders to send the next lesson when the current one is marked as finished, so you can automate it, but also match the pace of the person taking the course. Which may not make it serialized, but still a subscription.
What do you think? Are these a viable option or a fad that will quickly fade? Got any great examples to share – leave a comment.
I saw a tweet quite awhile back that was said something like “smart societies don’t polarize, they synthesize”, which I thought could be applied to many things. Take the learning industry for an example. There can be some times when it feels polarizing. If you deliver courses you are a luddite who is a throwback to the 20th century. Or, if you use rapid e-learning tools, you are responsible for the creation of bad e-learning and ruining the industry. I’m not sure if it’s just me, but sometimes I think we are not helping ourselves in the grand scheme: the zero sum approach only makes winners and losers.
The way I see it, the solution is only a solution that makes sense in the context of the problem, the business drivers for the solution (time or budget for example) and the culture of the environment. But as an industry we tend to judge the solution based on what we see, and we actually don’t know what’s going on beneath the surface, what lead to that or what criteria was considered. Instead we point out what it isn’t. It’s not mobile-first. It’s got a next button. It’s a course.
I think we would serve our industry better if we didn’t look for ways to identify how others do it wrong (in our opinion) or polarize things. I think we’d do more good if we looked to synthesize or bring polarizing positions together. You can still try to educate people that a course isn’t the only solution without polarizing. You can still urge vendors to innovate their tools without browbeating those that use the rapid tools. Think about it the next time you tweet something about the “wrong-ness” of something. Are you just contributing to a polarizing discussion? Can you do something different?
[Note: It wrote this draft post here on the blog and let it sit here for awhile. I’ve been finding time to write blog posts again lately and thought this quote still had merit.]