One of the more important tools in eLearning for business training purposes is what’s known as a Learning Management System (LMS), which is a software that deploys and tracks online training initiatives. In short, there are two main groups of users for this type of software: learners who can login to the system and receive training remotely and management who disperses information and analyzes the data collected by the LMS on the learning process.

LMS data and LMS analytics, which can determine the time needed for learners to complete tasks, tasks that are most often abandoned, and learning retention, helps management improve upon e-learning effectiveness. As MIT studies have shown, organizations that put an emphasis on data-driven decision making, have management tend to enjoy 6% higher profits and 4% higher productivity than organizations who simply “wing it” with employee training metrics and have no L&D strategy.

A winning combination for any company that wants to see productivity and profits increase is pairing LMS data with key performance indicators, which shows the return on investment of your L&D strategy. Here are five ways to make better business decisions with LMS data.

1. Make the connection between training and improved sales. Salespeople with more training in sales and who know their product inside and out bring more profit to the company. This means that better training equals more sales. This is probably the easiest step to implement.

2. Track compliance training and connect it to incidents and essential daily business metrics. This step can set a baseline for the company’s daily business operations which can then be adjusted for maximum efficacy.

3. Measure course completions to track the effectiveness of business initiatives. Does the coursework assigned to employees and learners correspond and contribute to the business objectives of the company? Coursework can be fine-tuned to correlate with unique, specific objectives such as KPIs.

4. Find the most effective and efficient mix of employees at a given location.  How many team members are required for optimal sales performance? What type of team works best for certain stores’ overall performance? Which employees are most efficient when it comes to sales, production, and training? This information can be essential in streamlining operations and increasing profit. 

5. Track what times of day users access learning content. With this information, the L&D team can build and fine-tune eLearning effectiveness so that employees can complete online training as painlessly as possible.

At first glance, the possibilities of eLearning analytics—and just the concept in general—may seem overwhelming. How do you implement data-driven decision making? And where do LMS data and data analytics come into play? Here are four steps that explain the process of data-based decisions.

1. Formulate key questions. Good solutions come from good questions. Ambiguous or ill-defined questions lead to answers that aren’t useful. What information is critical to improve training? What concepts can be prioritized? What is essential? Questions must be specific, relevant to the goals of the company and, most importantly, the answers must be measurable. For example, a factory that wants to improve productivity might ask the following questions:

1. 1. How much does it cost when production lines shut down and mechanics are called in to deal with troubleshooting?
   2. Which mechanical troubleshooting training modules have the highest completion rates?
   3. By how many units does production increase when machine operators are given bi-weekly paid training on mechanical troubleshooting?

All three questions lead to answers that can be measured, and the questions are relevant to the company’s goal of increasing output and profitability.

2. Collect and analyze LMS data. Most LMS software collects and analyzes the data for you, but the information gathered must be useful for and relevant to your pre-established objectives. As the saying goes, make sure that the LMS software of your company can do what you need it to do. It may be worthwhile to get an LMS that’s xAPI-compliant.

In other words, it must answer the questions established in the previous step. As with the example above, the LMS data may indicate that all of the training modules have a high completion rate, but that the morning shift workers have a lower completion rate. Other data collected from the production lines may show that following completion of training, productivity increases significantly in the evening, but not in the morning. One can infer that the training modules are indeed effective. But in the case of the morning shift, something must be adjusted to increase training completion rates.

3. Communicate results to decision-makers. Formulate recommendations based on the facts delivered by the LMS data and analysis. Present your LMS data analytics, other results, and recommendations to the decision-makers in your company through the appropriate channels. For example, via a PowerPoint presentation, one could recommend an investigation into the lower training completion rates of the morning shift, or recommend more training for the evening shift to increase production even more.

4. Refine processes. Recommendations of the previous step are applied. In the productivity example mentioned above, the process could start again with targeted questions about why morning shift training is not successful. Ultimately, the goal is to get data, use it, become better, and do it all over again with something else that could be improved.

Data-based decision making is not a one-off event: The cycle of four steps is repeated often to provide continuous improvement. Even when things are going well, they can always be made even better. A business that lasts the test of time is the one that adapts to new technology and new situations nimbly and without missing a beat.

Using LMS data and data-driven decision making in education and business leads to tangible advantages: productivity and profits increase by significant percentages when they are implemented. This is why data-driven decision making is important. They ultimately affect a company’s bottom line. However, it’s necessary to keep in mind an old locksmith’s saying when it comes to LMS software and data analysis: “the best lock in the world won’t save you from robbers if you leave your door open”.

In other words, just having the software won’t do anything unless you use it and learn what your software can do.

Learn what data is available in your LMS, think critically to use it most effectively, and watch your business grow.