Why your learning data is key to create a positive learning experience
Imagine you’re about to buy new shoes. About 2 billion of us (õver 25% of the earths population) are expected to buy online in 2019 (source). We love to shop online as it is convenient, allows us to visit a massive collections of shoes in many different webshop, and often it is cheaper as well.
Now suppose you have found the perfect shoe webshop and eagerly start to search for black leather shoes size us 9. You go to the top right search box and enter “Black leather size 9” to search in the catalogue of shoes. Only to find that the site does not give you any search results. Same when you’re trying to search on “Black Leather”, and then “Leather” shoes only. Again, the same result: none. You are getting a bit annoyed for not finding anything and normally you would leave, but the webshop was highly recommended by a friend, so you try a different method.
You decide to browse for those perfect black leather shoes. You go to the browsing section, have a first go at the filter on color and opens the filter pane, only to realize that browsing for color is not possible. The colors specified are actually all the colors that are available rather than individual colors. So you will find “black_brown_dark-blue” or “black_navy-blue_white” for a somewhat less traditional brand, and “Pink_Yellow_Orange” for a series of kids shoes. You even find “Zwart_Bruin” there, which is Dutch for Black and Brown, a language you are not familiar with at all. Again, most people would by now give up and go to a different webshop, but your friend was really persuasive. So you try again.
You’re heading to the material browsing section and notice that there is a browsing section called “account manager” and with a bit of a smile you think by yourself what it is doing there, not really relevant right? Finally you arrives at the materials section and you look at the options. You find “Leater”, obviously a typo, “soft_leather”, “leather-linen” and “italian-leather”….but no simple “leather”.
Now ask yourself, would you consider this a enjoyable experience? Would you proceed to find your pair of black leather shoes, size us9? Or would you simply leave and go to an online shop where you can actually find what you are looking for?
In addition, if by sheer luck you do find what you are looking for, would you place your order?
Or would you have that nagging thought at the back of your mind that if the website is such a mess, the payments and delivery of your shoes will also be a troublesome experience? That if the experience of trying to buy your perfect shoes is such a hassle, the quality of the shoes most likely also would be as bad as the experience.
Finally, would you think such a site would be economically viable? Do you think it will still be around a few months later? Or do you think it will simply stop to exist because its potential customers much prefer to go to a website that offers a much more pleasant and better quality experience, one where you can easily find the exact shoes you are looking for.
My worst online learning experience ever
Chances are very likely that your answers to the questions asked in the previous chapter are, (1) No, I would not continue to try finding shoes on the online shop, (2) No, i would not buy them, even if I could find them, and (3) No, i do not think the webshop will survive long.
If the above are your answers, I would completely agree with you. But then think for a minute. If we both agree that this is the worst shopping experience ever, why on earth are we as learning and development professionals creating similar (or even worse) bad experiences for our learners? In the majority of cases i worked on learning data management, I have encountered situations where little or no attention was given the to put accurate, consistent and meaningful data into the learning management system. The list of examples is endless:
- Course durations provided in both minutes and hours (in one instance, i came across a course duration that was in the tens of millions of minutes, causing the yearly cumulative time spend on training for the entire company to be off by a staggering 25% while only 11 people completed the course,)
- Incorrect or missing languages
- Many naming conventions in course titles, preferable using underscores
- Meaningless abbreviations in course titles
- Vague and way too long, or too short course descriptions
- Duplication of data that is also not aligned
- Taxonomy structures that represent the organizational structure of l&d and are completely meaningless for anybody outside l&d
And i’m afraid I could go on for a while…..
Imagine for a moment that your LMS is the webshop described in the previous chapter, and your training catalogue is the catalogue of shoes. Then put yourself in the position of the employee who would like to continue develop himself coming to your webshop and have that horrible experience of not being able to find anything.
It takes little imagination to realize that in that case it makes perfect sense that employees will be disappointed with their online experience in the LMs, that chances are very likely that they will find their development opportunities elsewhere and only come to your lms for mandatory training. And that your high investment in all sorts of great online courses are not giving you the return you expect.
If this sounds familiar, please stop blaming your LMS, or the search engine of your LMS.
Instead you should start considering the state of the data in the LMS that you put in yourself. Most likely it is in such a bad shape that not even the best LMS or LXP could make any sense of it, let along your learners. Fortunately there is something you can do about it; develop a strategy and approach to manage your learning data and keep improving it over time. It is one of the foundations of creating valuable learning experiences and leverage all the nice things that are coming to us, like artificial intelligence.