Everybody’s talking about big data these days. The popular buzzword has been subject to a variety of interpretations, but no matter how you define it, one thing is certain: To obtain the best insights for impacting business results, organizations need to have the right data in the first place. However, the reality is that most organizations haven’t collected the right kind of big data when it comes to corporate learning.
For decades, learning leaders have tracked things like course completions, test scores, training satisfaction rates, hours spent on learning and more. While these metrics are important to L&D, they aren’t important to the business. These metrics just don’t showcase if learning has actually helped to increase revenue or decrease costs. And that’s what business leaders care about.
What kind of big corporate learning data do organizations need?
The only way organizations can truly measure business impact from corporate learning initiatives is by collecting data that tracks employee knowledge and associated behaviors over time. If you think about it, knowledge is at the center of every organization. What an employee knows or doesn’t know impacts the way they perform every task, which can have a marked impact on business outcomes. After all, it’s one thing to give someone information. It’s another thing to have him/her digest it, remember it, and use it in the appropriate ways on the job.
In a sales situation, for example, if employees don’t know the product or service inside and out, or they don’t know good selling techniques or the competitive landscape, they’re not going to get the intended result (a sale) and this can have a negative impact on revenue.
Why new data is essential for measuring the business impact of learning
Historically, corporate learning departments have checked the “done” box when they’ve sat somebody in a classroom in front of a video and played it all the way through. They’ve considered the person “trained” when, in fact, they typically have no idea if the person actually digested any of the video content. Maybe the person wasn’t really watching the video at all. Perhaps he/she was thinking about dinner or all the things on their to-do list. The reality is that most human beings simply don’t acquire knowledge that way. People forget most of what they learn unless it is repeated over time and they use it in their daily lives. On top of this, just because they know a fact, doesn’t mean they can apply it on the job, so it is important to not only assess knowledge, but also if it is applied correctly at work.
So, to really figure out how to increase revenue or decrease costs, it’s critical that organizations start tracking new types of big corporate learning data—concentrated on employee knowledge and behavior. This will allow organizations to analyze employee patterns in the workplace and uncover trends en masse that lead to more strategic decision-making. How do you do this? It can’t be accomplished through traditional e-learning tools, like a LMS. But, today’s advanced corporate learning technology makes it possible.
How technology makes it possible to collect and analyze big corporate learning data
When you deliver learning content through an advanced learning technology platform, you can collect and analyze data on employee knowledge growth as well as behavior on the job. The system can test employees on learning content using a Q&A format to gather data on what they know and don’t know. Then, as the system continues to expose employees to the content over time, the technology can keep tracking their knowledge growth. This allows organizations to not only get granular, person-by-person data that can be used to identify areas of expertise as well as coaching opportunities, but also analyze patterns and trends across departments, divisions, locations or the organization as a whole that allow executives to reach bigger conclusions. On top of this, by observing behavior on the job and inputting whether or not employees perform job actions correctly, the technology can assess if employees are actually applying what they’ve learned in the correct way. If not, the system can identify where the gaps are, on an individual as well as a grand scale, so leaders can determine what needs to be changed.
For example, if you can confirm that what an employee knows is deficient because you’ve been able collect this data, and you know across an entire population that employees keep falling down in terms of demonstrating that knowledge, then you know there’s actually something wrong with the training content—the information you need employees to have. In a safety situation, perhaps employees understand certain safety policies, but they don’t know how to use a ladder properly and continue to have accidents. If you have big corporate learning data in volume, advanced learning technology can actually start to, not only identify problematic areas, but tie the data together and statistically correlate it to predict behavioral outcomes that will impact the business. In the case of ladder safety, the organization might be able to predict a 75 percent chance a ladder accident will occur based on this kind of data. To mitigate ladder accidents and reduce costs, the organization might then determine employees are receiving training on the wrong things and the content needs to change to address the specifics of proper ladder use.
Instead of employees continuing to make the same mistakes repeatedly, the right kind of big corporate learning data allows organizations to proactively address issues rapidly and adjust training to truly impact the business in a positive way. Without this kind of learning data, this simply can’t be done.
