The Concept Of Intelligent Tracking of Training Intervention

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Tracking Training Intervention

First a small story:  David is an ace Learning Manager.  He has spent weeks identifying a mobile training partner, did a deep evaluation and conducted multiple meetings to deploy it perfectly. Finally, he went live with a gleaming new mobile training initiative. However, David soon found out, while tracking training intervention, that it is not working as expected. Most of the employees were not spending enough time reading the content. What went wrong?

If the above story sounds familiar, OR if you are afraid you might run into something similar, read on…

Mobile training is new, and there is no dearth of training vendors touting feature after feature. From AI to blockchain to AR and even VR, we have vendors claiming fancy new tools to train people.  However, like most things in life, the eventual success boils down to some very basic fundamental principles. Getting the basics wrong will throw off the most cutting edge technology one deploys, while getting the basics right will lead to dramatically high training completion.

HandyTrain has over 90% training completion rate across 45000 employees in 7 sectors.
We know a thing or two about the basics 🙂

Understanding the Employee Base and Their Habits

First, you need to understand your employee base very well. Basis the education background, their online habits, their engagement with mobile phone, and other uses of mobile in their work life – all play an important role in defining the success of the mobile training initiative. A detailed view of user psychology is a separate topic and we will cover it in a separate blog. For now, suffice it to say that field agents prefer not to read reams of text. Similarly, senior management would not like a series of animations for higher learning. Yes, its as basic as that.

Training needs and business value.

One needs to make the training content directly related to the goals of the employees. In case the relation is not obvious, you should clarify the benefits of the training early in the program. Encouraging the employees to start and complete the training is a science in itself, and we have covered a part of it in a previous blog. In a nutshell, if the training is not going to help the employees, they do not have enough reason to learn it.

Intelligence and Tracking Training Intervention

And finally to the holy grail. While one does everything right, it is important to know that our thoughts and reality could be very very different. One needs to track the training intervention very deeply to understand what is working. However, it is even more important to track why some things are working and why some things are not. This requires very deep level tracking by the mobile training vendor. Additionally, most of us are not exactly data scientists. Therefore, the vendor must also provide an easy way to pull out and visualise data. Finally, many of us have decent excel skills, so the vendor must allow us to download this data and evaluate it as we please.

So far, we were talking theories. Now to business.

HandyTrain has recently released a Training Intelligence tool as part of the standard offering. The tool tracks over 45 behavioural metrics of each user. These include, but are not limited to, the first time access, the last time access, the daily reading averages etc, and can be filtered down by users and the user segments. You will be able to answer questions like:

  1. Does the Sales Team in East region learn optimally?
  2. How are people reporting to managers who joined in last quarter learning?
  3. For people who opened the app last week, how many actually spent over 20 minutes learning?
  4. And so on ….

How Tracking Training Intervention Really Works

HandyTrain tracks every single movement the user makes. That is the easy bit. The innovation lies in joining these individual events and pulling out behavioural data. Our internally developed Intelligence System, aptly nicknamed Solomon, makes the data associations in real time. Once the data is grouped together, it is further mined. For example, a user may have opened the app for 2 minutes, and then repeated this 3 times in a day. Solomon would mine this to compute the total usage time as 6 minutes, and mark the user as active for the day. In addition to this, Solomon adds a lot of metadata to the users behaviour including the type of content read, the user’s department, reporting manager, region etc. This will allow you to identify which users are learning and how.

Epilogue

The goal is pretty simple – you have spent a lot of time and effort to get the initiative live. The least you deserve are some deep answers to understand WHY some users are not learning, and whether there is a pattern that you can leverage for greater success. Granted that this is not how L&T has traditionally functioned. However, the right mobile vendor will enable you to function in a whole new way with minimal effort.

No prizes for guessing who that great mobile training vendor is 🙂

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