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Data Analytics in Learning Management Systems

Year after year, our reliance on digital tools and workspaces keeps increasing. Our clients interact daily with systems that can track their actions and store information about their activities. Often, and particularly in the case of a Learning Management System, this data gets stored in a huge database and then only used to produce yearly or periodic reports. But is there something more we can do with this data? Is there a way to add value to what we already have in our systems, often overlooked?

What is Data Analytics

To better understand the hidden value of data, TeamPeaks helps customers adopt Data Analytics. Data Analytics is a series of tools and procedures, which concur in the process of analyzing and then interpreting and visualizing data. Data is usually organized in large and complex datasets and the aim of Data Analysis is to use it to provide meaningful insights to help make better, informed decisions.

Our clients which possess such large databases, have in their hands an often untapped and overlooked resource. The process of extracting value from data leverages different people and procedures and usually can be broken down in these steps:

  • Data Collection: which pools offer the data we are going to use?
  • Data cleansing: prepare the dataset. This step usually includes removing duplicates, errors or incomplete data
  • Data Transformation: prepare the data for efficient analysis with operations like standardization and formatting
  • Data modeling: apply statistical models on your data
  • Data Visualization: organize the data in a visual manner through charts, tables, graphs

TeamPeaks assists its clients in all these steps:

  • by setting up appropriate business processes to help all system user generate high quality data and by assisting
  • by assisting data migrations to consolidate data sets coming from different sources or legacy systems
  • by leveraging the data modeling and data visualization solutions embedded in the SAP Analytics platform

Using Data to guide your decisions

Information gathered from data can help management make informed decisions on existing problems and situations. This case mainly relies on data analytics as a descriptive and diagnostics analysis tool. We can therefore create dashboards that help answer questions such as “What happened?” and “Why did it happen?” when analyzing a situation.

As an example, using data analysis one of our clients could spot a large number of trainings completed after the due date, highlighting a relevant compliance risk for the company.

Through data analysis we helped identify patterns and criticalities: assignment of mandatory training tended to concentrate in times of the year more critical for the normal flow of work in the business. Assignments were then shifted away from major holidays or from important business deadlines. More in detail, data could be broken down using different criteria, like business roles or geography. In other cases, we could identify trainings that were particularly difficult for certain target user groups.
Armed with this additional information, training managers can now think of different plans and measures to harmonize training processes with the business rhythm of the company.

Using Data to spot challenges and opportunities

In addition to adding context and information on existing situations, Data Analysis can also be used for prescriptive and predictive analysis, which are ways to look into the future and chart the best path forward.

Data Analytics can also used to maximize the efficiency of automatic assignments, looking at which trainings people who were promoted in certain positions completed, helping tailor curricula and learning programs fit for that specific position.

Grouping people together based on what trainings they complete is also helping to draw similarities across different groups inside the company even if they are spread over different countries and locations.

Conclusion

The quantity of data tracked by a Learning Management System is huge: information on how many trainings users choose to do or are assigned, how much time is spent in training, what are the most popular courses, and which ones are less appealing to the users—all this information can be found in the database but gets often ignored. Turning these data into business value is possible. Data Analytics can help organization in decision-making, but also highlight and uncover hidden patterns or opportunities.