We are experiencing an unprecedented rate of change in workplace environments and job skill requirements. This is clearly reflected in a recent Global Sentiment Survey, where reskilling/upskilling was the most popular answer to the question, “What will be hot in L&D (learning and development) in 2021?” So long as the economic climate reflects change as the only constant, learning and performance professionals will be critical players in Agile business development and infrastructure. There are several essential skills L&D professionals need to be high performers. However, those skills alone will not prepare L&D pros for the future of learning.
Understanding data and analytics, specifically the ability to use big learning data to inform the design, delivery and impact of learning initiatives, will be the dividing line between good and great L&D talent. Unfortunately, low confidence and capability in data and analytics has been cited by the Learning and Performance Institute as a serious problem in the L&D industry. If reskilling/upskilling is a current priority in L&D, then L&D professionals themselves should prioritize their upskilling efforts on data and analytics.
Before taking our data and analytics conversation further, let’s clarify a few important definitions. Elliot Masie, author of “Big Learning Data,” offers the following descriptions:
Big Data: Having vast amounts of data from a myriad of sources with access to data at volume (think hundreds or thousands of people versus one or a few people).
Learning Data: Data from learning systems and products, such as learning management platforms, video hosting platforms, performance management systems or learning record stores (LRSs).
Data Analytics: Organizing data, interpreting insights from the data and displaying data insights for the benefit of others (i.e., learners, leaders, learning designers, etc.).
Why Data and Analytics?
Using big data to make informed business decisions is not a new concept. Corporations have been using big data for decades. Amazon, Apple, Google and Netflix to name a few. However, the ability to use big data is predicated on having the proper systems in place to collect the right data and analyze it accurately to produce valuable insights. In the L&D industry, few organizations have systems in place to collect the right data, analyze it accurately and share insights with any member of the organization who may need it.
Why are data and analytics skills essential for the future of learning? The answer lies in the benefits of big learning data. Have you ever wondered how economists predict when the stock market or housing market may crash? They use big data to explore historical trends and those trends become indicators of the future. The same can be true for L&D. When the right data are collected and analyzed systematically, we can track important trends in real time. These timely insights help to: Understand learning in the flow of work, improve the effectiveness of learning initiatives and resources, enhance personalization of existing programs and ultimately design learning that aligns with workplace environments of the future and not the past.
Case Study
Before beginning an upskilling journey, we must know what our skill levels are today. In that spirit, take a moment to brainstorm how you would approach the following case study. After writing your ideas, ask yourself:
- How easy was it to come up with a solution?
- How confident am I that I described the right approach?
Let’s say you wanted to identify the people or groups within your organization who are a training priority. How would you go about doing that?
- What data would you collect?
- Where would you go to obtain the data?
- How would you analyze the data to obtain critical insights?
- How would you display the critical insights and share with those who need it?
Resources
What data would you collect?
One thing to keep in mind when using big data is that not all data is valued equally. Keep your approach to data collection focused on the goal at hand. If you want to identify the people or groups who are a training priority, first learn from business leaders how prioritizing people or groups to train would impact the business mission or bottom line. Only after understanding the business impact can you determine what data is needed to clarify your training priorities.
Where would you go to obtain the data?
Bonnie Beresford, director of performance and learning analytics at GP Strategies, writes that learning professionals will be forever challenged if they rely exclusively on data provided by the training department. L&D professionals have an unfortunate habit of leaning on data that doesn’t actually demonstrate the impact of learning, such as the cost of production, number of participants, satisfaction ratings and net promoter scores. Telling the learning value story with quantitative data is a common challenge in L&D. To address it, we must collaborate with other departments and executive leaders to identify the key performance metrics that training initiatives should influence. Only then can we create a coordinated systematic approach to data collection, or data sharing with metrics that are already being collected.
How would you analyze the data to obtain critical insights?
Elliot Masie suggests we adopt an anthropological way of thinking in our approach to data analysis. I wish we could say that learning initiatives alone cause an impact on performance. In reality, learning is only one influence on behavior among many. Furthermore, there are many other factors (both environmental and interpersonal) that influence how humans learn. When analyzing data, we must incorporate important environmental and interpersonal factors that may influence learning and performance alongside the comparison of leading indicators of performance, key performance metrics, and learning engagement data to tell the true learning impact story.
How would you display the critical insights and share with those who need it?
Ideally, the platform or tool used to collect and analyze data is the same tool that displays and shares data insights with anyone who needs them. However, in many cases data on learner engagement, leading performance indicators and key performance metrics are housed in different platforms and are managed by different departments. Therefore, learning professionals may benefit from employing automated workflows or robotic process automation to push data from various platforms into one central location (that could be another platform or simply a spreadsheet). Once data is being pushed into one central location, analytics can be computed and shared using a business intelligence platform or data analytics dashboard.
If you are in the L&D industry because you love learning yourself — the time is now to expand your knowledge of data and analytics. The future of learning depends on it!
