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You can train people all you want, but it’s nice to know if the training is working. More specifically, is it helping your company reach a business goal?
Actually, that’s not just nice. It’s something that’s very important to know. Otherwise, you may be just wasting time and money. And you may even be without a job soon if you can’t prove this.
Luckily, you can use training data from your learning management system (LMS), along with other KPI data (for example, KPIs about operations or safety), to create a compelling visual display of the positive effects of your training program. And as you know, a picture is worth a thousand words.
We’re going to give you a couple of quick examples of how to do just that in the post below.
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Your LMS will track, record, and store the required training data.
Depending on the training, this may mean attendance, activity completion, average test score, training completion percentage, job qualification rate, and so on (see this separate article for more about training-related KPIs you can track in your LMS).
For the sake of example, let’s say we’ve done two new things in our training program and we want to see if they’ve had a positive effect on training-related KPIs. Those KPIs would be:
In the next step, you’d gather data about performance at your work place, perhaps on safety, production, or quality. You could get this data from any number of sources, such as your safety tracking software, ERP system, or data historian.
To make a convincing case that the improvements in Safety, Production, and Quality all resulted from the training changes, we can create graphs that superimpose the training data and the data from Safety, Production, and Quality, respectively.
For Safety, we’ll use the Incidence Rate.
For Production, we’ll use OEE.
For Quality, we’ll use First-Pass Yield.
Of course, in real life, you might choose to use different KPIs from Training, Safety, Production, and Quality (or other departments/business units), but the method we’re describing would still be relevant.
We’ll start by getting information on a safety metric. Let’s use the Incidence Rate.
We can see from the graph above that the incidence rate took a downward plunge (which is good in this case) after March of 2015, but it’s not clear why.
Below are two graphs each showing the positive effect that training had on safety. In the first graph, we see that improved training completion is closely correlated to better safety numbers. In the second graph, we see that improved test scores are also closely correlated to better safety numbers.
The graph immediately below shows training completions (in orange) and the incidence rates (in blue). We can see that the orange line representing the percentage of training completions increased at the same time the safety incidence rates decreased.
The next graph shows improved average test scores (in orange) and the incidence rates (in blue). We can see that the average test scores increased at the same time the safety incidence rates decreased.
So now you’ve got two graphs, each giving some pretty compelling evidence that the changes in your training program had positive effects on a key safety KPI. It’s not proof that the training caused the improvement, but it’s pretty convincing data.
This information is good for you to know, but it’s also stuff you can take to management to demonstrate the value of the training department and/or the training program.
In our next example, we’re going to use a Production/Operations metric. We’ll use OEE (you can read more about OEE here).
As was true with the safety metric, the graph below shows that OEE increased (good in this case), but it’s not clear why.
Next, we’ve got two graphs each showing the positive effect that training had on OEE. In the first graph, we see that improved training completion is closely correlated to the increase in OEE. In the second graph, we see that improved test scores are also closely correlated to the improved OEE.
The graph immediately below shows training completions (in orange) and OEE (in blue). We can see that the percentage of training completions increased at the same time OEE increased.
And the next graph shows improved average test scores (in orange) and OEE (in blue). We can see that the average test scores increased at the same time OEE increased.
Again, you’ve now got some strong, compelling evidence that the changes in your training program had a positive business effect, this time on Production (as measured by OEE). As was true in the safety example, this is information that’s useful to you but can also be presented to management to show the effectiveness of your training program.
For our third example, we’ll use a quality metric-first pass yield.
As we saw with our two earlier, examples, something good happened in March of 2015 (in this case, first pass yield went up), but it’s not clear why.
Again, below we’ve got two graphs each showing the positive effect that training had on quality/first pass yield. In the first graph, we see that improved training completion is closely correlated to a higher first pass yield. In the second graph, we see that improved test scores are also closely correlated to better first pass yield.
Here’s the first graph, showing training completions and first pass yield (in blue). We can see that the percentage of training completions increased at the same time first pass yield increased.
And here’s the second graph, showing improved test scores and first pass yield (in blue). We can see that the average test scores increased at the same time first pass yield increased.
As was true with the examples for safety and production, we’ve now got two graphs correlating positive changes in the training program with positive changes in a key Quality metric.
These examples are a bit simplified, but you get the idea how you can superimpose your production data on top of your learning/training data to make a compelling demonstration of the effectiveness of your training program.
Take some training data from your LMS, collect some KPI data from other workplace sources, superimpose the two on one graph, and you’ve got a quick and easy way to visually demonstrate the positive effects of your training program.
In reality, you’d also want to control the other variables that might have caused the change in your KPIs. Read more about that in this article on Isolating the Effects of Your Training Program.
For even more articles related to measuring the impact of training programs on business goals, check out the following articles:
What about you? What do YOU do when you try to demonstrate the positive effects of your training program?
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