How To Improve Performance And Compliance With Enhanced Tools For Learning Data Analysis
How crucial is compliance learning data analysis in the post-COVID world? Without in any way wishing to downplay the wreckage of lives and livelihoods wrought by the global pandemic, it can’t be denied that the tragedy had a transformative effect on learning. Almost overnight, in 2020, digital became the default means of supporting learning as the staple of face-to-face “classroom” training became untenable. Digital transformation programs were massively accelerated . Likewise, long-nurtured pet innovation projects in digital learning that had been back-burnered and sidelined for years were suddenly mainstream, urgent requirements.
Learning curves are sharp for many, and adapting to the new world has not been without pain. However, through this unpleasant necessity, we were catapulted into a place of centrality for digital learning that seemed to occupy a spot on the far horizon only months before. It is difficult to say with any certainty what the coming years might have in store, but research indicates that many of the gains made in online learning will be retained. One of these gains is a more data-rich environment for L&D since digitally supported learning necessarily produces more data than in-person activities.
Today’s organizations already are awash with data—and as L&D comes increasingly to use the common platforms of the business—such as Zoom, Teams, and Slack—it brings L&D, potentially at least, into closer alignment with the day-to-day workflow of a modern, data-fueled enterprise.
Compliance Learning Data Analysis: Tools For The Journey
Strong underlying drivers, therefore, as well as increasing demand from business leaders for a more data-driven approach, move L&D professionals into a closer relationship with learning analytics, and necessitate their having a forward-looking, sustainable learning analytics strategy. Here’s some help to do that.
We have some tips to give for how you go about shaping this strategy, but before we do let’s focus in for a moment on the area of learning analytics capability. At both an individual, team and organizational level, this is a key consideration of your learning analytics strategy, because it is the area in which L&D most often feels it is at a disadvantage. While appreciating that data is perhaps the most important area where it needs to develop capability, L&D also feels it lacks the skills and knowledge it needs to effectively implement a data analytics strategy.
It is for this reason that Learning Pool has introduced two important new additions to the L&D planning toolkit, two free, freely available resources:
● The Learning Analytics Maturity Model (LAMM)
● The Learning Analytics Canvas (LAC)
Here, it is worth just briefly talking about the significance of each for strategy planning.
Learning Analytics Maturity Model (LAMM)
Often we are held back in our efforts to advance capability by ‘unknown unknowns’. Specifically, we don’t really know how to judge our level of capability in learning analytics against that of other organizations. Are we laggards or trailblazers? Are there experiments we have undertaken in the past whose significance we are overlooking? Taking the LAMM’s questionnaire allows you to benchmark the ‘state of the art’ of learning analytics within your organization against a broad sample of similar organizations, in four functional areas.
Most likely you will find you are in a similar place to many of them, or even slightly ahead of the pack. But that knowledge is really helpful to you in moving forward.
More importantly, perhaps, the LAMM can also tell you what your next steps are, and in which particular areas you are more or less advanced. This helps you plot your path forward in developing capability and essential parts of strategy planning.
The Learning Analytics Canvas (LAC)
Based on the Business Model Canvas, which will be familiar to many, the LAC is a planning tool and checklist that can be used by anybody embarking on a project or program that is going to involve learning data, regardless of their level of data maturity.
Too often, learning analytics takes place within an organization only on a project or program-related basis. A particular initiative needs to be evaluated (usually after the fact), and the methodology to be adopted is specific to that program. The LAC allows you to use a common planning methodology for any type of analytics activity, and turn analytics planning into a regular, embedded and sustainable part of L&D activity.
The LAC also helps clear away some of the confusion that surrounds the subject of learning impact evaluation. It is easy to be baffled by the plethora of evaluation methodologies which have been thrown up in the 60 years since the four-step model known by the shorthand ‘Kirkpatrick’ was first introduced. Using the LAC will give you a sound basis on which to judge which evaluation model you would be best to use in any given circumstance.
Seven Tips For Developing A Learning Analytics Strategy
Equipped with these practical tools, you will be better able to plan a learning analytics strategy to make use of data in supporting working people as they strive to improve their knowledge and skills while making sense of a confusing, complex, fast-changing business reality. So as you move to do that planning, here are some things to keep in mind along the way.
1. Take A 360 Approach To Learning Data
You wouldn’t drive using only your rearview mirror, so don’t restrict your focus to learning evaluation (as important as it is); a more holistic approach will also give you side mirrors, dash-cam, and a clearer view of the road ahead. It’s not all about evaluation or analytics.
2. Be Proactive
If you wait for the business to ask for better data, the conspiracy of convenience theory suggests it might never happen. However, you will run the risk of irrelevance and, ultimately, obsolescence. Start today in making data a central part of your practice and educate your internal and external customers on the benefits of taking a data-led approach.
3. Make A Realistic Assessment
Evaluate your organization’s maturity using learning data as the first step in making improvements. The Learning Analytics Maturity Model (LAMM) will help you do this.
4. Start From Where You Are Using The Resources You Have At Hand
Today’s organizations are awash with data, although it might mean forging new alliances and learning new skills to get hold of it.
5. Take An Agile Approach
Start small, fail fast, learn by doing. Use the Learning Analytics Canvas as a starting point for your next compliance learning data analysis project and see how it could be driven differently when you start with data.
6. Use Multiple Data Sources
You need to evaluate and take a portfolio-of-evidence approach. Don’t expect there to be a smoking gun when it comes to evaluating impact. Chances are you will only be able to prove that you might be the reason something changed, but you can stack that deck higher with more data points.
Last but not least, the customer is always right—In order to progress the adoption of learning analytics in your business, you’ll need to convince customers that the output of your work is worth it. Once customers start asking for analytics, data from the LAMM shows, the business seems to fall in line.
Download the eBook Data And Learning: Adding Learning Analytics To Your Organization to meet your performance goals and overcome L&D obstacles. You can also join the webinar for more secrets to plan your Big Data journey.