Big data is just large sets of numbers. But it’s not the size of the data that matters. It’s how you use it that counts. (I know, I know. I couldn’t resist!)

Most people new to big data assume (incorrectly) that more data is better. But without a way to analyze it, there isn’t a point to collecting a ton of data.

And if you haven’t calibrated your content correctly, the data you do collect can be inaccurate. Meaning any insights you gather from your new tracking suite could be skewed or statistically irrelevant.

You need both accurate data and an easy way to analyze it for big data tracking to be a useful investment.

Why Do We Need Big Data In Training?

Up until recently, most organizations have been using their LMS to measure training effectiveness.

The problem is most LMSs aren’t set up to track much more than pass/fail/participate. And your organization doesn’t function on just pass or fail.

Big data analytics help fill in the gaps so you see which employees are struggling, which are excelling, and where your organizational knowledge gaps are. And that data is useful for evaluating both your employees and your program’s efficacy -- not to mention planning future training initiatives.

We recently created a SlideShare presentation that goes over some of the basics of using Big Data in training, which you can check out below. This article will go into more detail on how to generate useful data, and why it matters.

How Do We Get Big Data?

Contrary to common belief, generating useful big data requires a bit more than a new tracking suite.

Remember, you don’t need data. You need useful data.

To get useful big data you need:

A large sample size. Participation is key. The more employees that take your training, the more reflective your results will be of your organization’s reality.
Content that’s been carefully crafted. Most people think big data isn’t related to content. But if you don’t write your content carefully, the results you get may be skewed. Simple writing errors can tip employees off to the right answer — and your results will reflect their ability to guess instead of their learning.
Employees to play for more than a couple minutes. To get statistically relevant data you need employees to answer a large number of questions. The more questions they answer, the better understanding you’ll have of their actual knowledge.

The basis of what I’m talking about here is engagement. And the best way to drive engagement is with game-based learning.

How Does Game-Based Learning Fit In?

Game-based learning makes learning fun by morphing boring content into a learning game. But more importantly, it turns employees from passive readers to active participants. And that will drive more participation, thereby generating useful big data.

Let’s look at how game-based learning tackles some of the challenges of generating useful big data.

Challenge #1: Increasing Sample Size

To get useful big data, you need a big enough sample size to generate statistically relevant insights. If only 100 people take your training, and you have 10,000 employees, any insights you draw aren’t going to be statistically relevant.

To generate a large enough sample size you need to increase participation rates. Game-based learning does this by making training fun, so employees are more likely to participate.

But you also need to remember to promote your training program. Otherwise, how will people know that it's (a) running and (b) a lot of fun?

Challenge #2: Crafting Content That Doesn’t Skew Results

Your content has to be calibrated for big data or the insights you do get will be skewed. Simple writing mistakes can make a huge difference in the quality of data analytics you get from your training.

The key is to make sure content is challenging — you don’t want employees to guess the right answer. You want them to know it.

Game-based learning can help ensure your training challenges employees without overwhelming them. Levels help ensure your employees learn your training content before moving on — and repeating content helps to weed out incorrect data based on a “lucky guess.”

Challenge #3: Driving Prolonged Activity

In addition to boosting participation rates, you need employees to answer enough questions (play for long enough) to get valuable insights. The more questions they answer, the more relevant your data will be.

Game-based learning helps drive prolonged activity by intrinsically motivating employees to keep learning. Employees feel accomplished when they level up or earn a reward — and they’ll keep playing (and learning) so they can feel that sense of accomplishment again.

Tracking and Analytics: What Can You Measure?

Once you’ve optimized your training content for big data you can start to measure the results.

Here are some of the things you can measure, and why they’re useful.

1. Participation

Beyond telling you who participated, big data analytics can give you more insights into things like how long they played, which content they accessed, and how long they spent in each course.

This helps you get a better sense of not only how employees used your training program, but also areas of your training that didn’t pull as much attention. You can use insights like this to improve sections of your training with low participation rates, and schedule your training reminders for times when participation rates are low.

2. Find Superstars and Slackers

Big data analytics give you granular insight into each individual learner. You can see exactly which employees are struggling — and on what. This allows you to reach out with additional training and take steps to remedy critical knowledge gaps.

In addition to finding employees that are struggling, big data can also reveal which employees consistently do well. This lets you celebrate those employees and reward their achievements.

3. Identify Knowledge Gaps

Finally, big data allows you to look at trends across your entire organization. This helps you identify greater learning trends and find knowledge gaps.

For example, one of our clients found that 75% of their employees weren’t aware of a password policy that let customers reset their passwords online. This was causing customers to make unnecessary trips to their stores and increasing frustration. Being able to find this knowledge gap allowed them to take steps to fill it — something they would never have been able to spot with simple LMS tracking.

The Bottom Line

Big data can give you insights into exactly how your training is working. You can see which employees are doing well, and which aren’t. You can even find organizational knowledge gaps and identify areas for future training.

In short, big data may be just large sets of numbers. But when used properly, it helps you see small details about your training you’d otherwise miss.