Learning and workplace systems hold many data points that can be tracked and used to build a historical landscape that help drive decisions for future learning plans.
In learning and development, the collection of good data is either a hit or miss opportunity. The data that does exist is usually collected in disparate systems that provide more of historical view of what took place rather than a measurement of transfer of learning or a return on investment related to business outcomes. If we look at where the marketing industry was 5 years ago, we get a good picture of the advances in learning today. Back then, marketing did a really good job of tracking spend data, ads or pieces of content available and contributing it to conversion rates based on readership. Now compare that to today’s marketing; targeted and customized to individual consumers; informative in building relationships; and based on dialogue happening in real-time. The industry has been transformed by the ability to show, without a doubt, its value to business outcomes. So what can learning and development take-away from the transformation of the marketing industry?
The bigger the data, the better the customization
Today as industries ride the wave generated by digital economies such as AI and machine learning, we have invariably become better enabled to capture learning data through more efficient means. With automated tracking software of activity streams, data can now be ushered to help learning professionals predict and customize learning content at a learner’s specific point of need. As seen in the marketing industry, the concept that the bigger the data, the better the customization is where learning and development must also deepen their efforts. Think about what drives the giants in customization. Amazon, Google and Netflix are all about big data and how it’s used to make decisions in producing sales results and business growth. According to a recent Ernst & Young paper How Can Big Data Lead to More Rational Decision Making, 2.5 quintillion bytes of data are created every day with 90% of the data being created in just the last 2 years alone. And with the total amount of data predicted to double every two years – that’s a lot of data!
In today’s world, the “Amazon way” of pushing products out to the customer through personalized marketing is king, but this ability didn’t happen overnight. It took years of data collection for it to mature to where it is at now. This data can now be paired with analytics and algorithms, in order to predict what naturally draws our individual attention to specific products that help customers make decisions on future purchases. This type of personalize engagement is how learning and development must drive adaptive and continuous organizational learning and business growth today. Learning functions must start using new data capture processes that track not only events that happen inside the LMS or classrooms, but out to anywhere learners are seeking information at any point and time. This real-time user generated data has the potential to draw attention to useful information when and where the learner needs it most, increasing skills and productivity in the workplace at rapid speed.
So where to begin? The first step… start collecting your data! You might be thinking – wait, doesn’t my LMS do that already? For the most part, yes. However, LMS data does not produce enough data points to feed the algorithms needed to drive real change. It’s a start, but we need to think bigger. What we need is a learning ecosystem that collects xAPI.
The Record Collector – xAPI
xAPI-based ecosystem can provide more complete data capture on activities and actions that happen before, during or outside any formal training environment. What is xAPI, or Experience Application Programming Interface? It generally refers to a library of programming functions that software developers can use to integrate two or more separate software applications. Any type of software or system that has been xAPI enabled can generate Experience API data. The really cool thing about xAPI is that it operates based on activity streams, a model that uses software to track things people do in real-time. This idea of tracking activity streams has become enormously popular via social networking sites such as Facebook, Twitter, and Google Plus.
Now let’s think about xAPI and activity stream tracking in L&D within your LMS, learning ecosystem and/or your greater workplace systems. Suddenly, without a large administrative burden, we can now track what happens outside the classroom, opening a new world of knowledge through system communication. Imagine your LMS can now communicate not just with eLearning courses, but with knowledge bases, collaboration platforms, document management systems, resource planning tools, helpdesk system, portals, talent management and many other types of workplace systems.
As systems track activities and communications with other systems, the data can now be used to create competency in the workplace. Now we can track when new hires read our sales philosophy before attending training (portal); when a sales model was accessed and reviewed (document management system); when they attended the 2 hour workshop (LMS); when they consumed micro learning (micro learning platform); when they consumed informal learning (portal); when they attended a coaching meeting with their supervisor (portal calendar); when they created a sales plan (CRM); delivered the sales plan to the customer (portal); and closed the sale (CRM). And best of all, xAPI tracked all of the activity streams while collecting data points along the way automatically. Through this powerful process, our new hire was able to learn while producing work outputs and performance results, thus, closing the cause and effect learning gap in real-time. This blend of learning that happens through instructional content and real life work is a powerful learning model. Not only has the learning been drastically impacted, but the data points created from activity streams can now be fed into automated intelligence tools that will help generate predictive learning plans. This opens up an array of new possibilities in personalized learning that will truly revolutionize the way we learn and do business.
The Evolving Data Point
Many learning functions of today do an incredibly inadequate job utilizing captured learning data, and often, the data that does exist is just too vast to process. Each year, for example, when it’s time to put together a schedule of classroom training, learning leaders feel this inadequacy more than ever. Most have no idea of how to predict demand and often default to their limited data points contained in their LMS historical data for a past course schedule to serve as a blueprint. Yet, as technology advances, no longer is this default framework necessary, or acceptable.
Typical learning and development data used to measure future competency training and decision making:
- Catalog (course and session type)
- Historical completion (they took the course therefore they have the knowledge needed to perform)
- Curriculums or certificates (groups of courses that build competency)
- Assignment (how should participants take the training)
This type of data does very little to help predict where future learning needs will be or how to deliver learning to the exact point and time of need.
Now with new and increased data points being collected from xAPI and other learning ecosystem tools, learning functions are now enabled to create more opportunities to deliver training right when the need is experienced by the learner.
Today’s preferred data points for learning and development:
- Predict how long or how many hours of learning is needed to produce performance threshold using historical data
- Track changes in knowledge both increases and decreases over time
- Measurements on how frequently an employee participates in training, uses supporting material or visits knowledge repositories and linking that to executing new skills or application of knowledge in real world
- Integration of CRM data to show increases or decreases in sales or customer interaction
- Survey data from customers/peer/managers to track development, strength or weakness in performance, and confidence in abilities
All the data generated from these preferred data points can then be filtered through automated machine learning intelligence tools to give us the prescriptive learning plans that are needed to drive training where and when learners need it most. It gives us the roadmap to identify when content is needed in a learner’s development cycle, and real time feedback on whether or not it was successful. This is the first real chance for learning functions to see how learning and development can provide a return on investment by tracking activity streams and responding to business/performance results that improve overall business growth.
The Golden Rule – Good Data Management Practice
Learning and development may not be the first department diving into digital and AI transformation within your organization, but don’t let that stop you from getting ready. As we can clearly see from the successful companies in the market place and from the evolution of the marketing industry, the key to unlocking the learning potential is through efficient data capture. This will enable machine learning to do its magic and revolutionize the learning industry. The digital age demands changes to learning and development, are you and your data ready?