Real-World Learning Analytics: Applied Industrial Technologies [Pt. 1]

This week, we're spotlighting Andy Webb, director of training at Applied Industrial Technologies. In this post, Andy shares his experience and professional learning and development insights when it comes to the first steps to build and maintain a successful L&D program with learning analytics.

Gather Your L&D Data

Before approaching the technical steps, how you get data is through people. While directors and VPs hold the keys for permissions and grant access, it pays to be extra friendly to database administrators (DBAs) and business intelligence (BI) staff. Sometimes those little favors lead to key breakthroughs.

Unless a learning record store (LRS) makes the enterprise priority list (someday, it could happen), there’s a perception the amount of information technology (IT) and BI assistance needed makes it a daunting request.

An LRS is something new that many data professionals are not yet comfortable with (nor are many learning professionals—yet). Furthermore, BI teams are used to creating reports, not supplying data feeds.

For instance, during many LRS conversations, business leaders told us they wanted to send us monthly reports. But we needed the actual data sources. It was a process to get from receiving spreadsheets to receiving data directly from the source. There are some ways you can position yourself and your team to get the data you need, and it starts with basic people skills.

1) Foster relationships.

As a learning professional, you are dipping your toes in ponds where ownership might already be territorial. It’s a delicate tap dance until you are able to build trust.

The secret ingredient to obtaining corporate data is relationship-building skills. Make sure your entire team understands the organization's politics and is sensitive to needs, culture, and processes already in place.

2) Raise your hand.

As corporate initiatives come and go, I’m surprised by how many people (in other departments, of course) want to just check in and check out.

Being part of cross-departmental teams and taking some extra responsibility provides visibility for your team and opportunities to work with new people, which means you can learn more about how they perceive (and measure) the organization.

Ask to observe some of their data sessions to learn what is critical for success. Furthermore, some of these relationships will become important resources for your future endeavors and vice versa.

3) Pay it forward.

Provide help to other teams that may need assistance on training or data services you create. If you build the LRS right, the questions that emerge from results will actually increase interest in the tools and reports the BI/IT teams already support. Offer to connect (and promote) their existing reports as part of your project.

4) Internal customers can lobby for new data.

To obtain more data sources, consider asking your internal customers for assistance. Whenever you approach a new project, share your LRS vision with leadership and try to find metrics that are important to them.

Embed those metrics into the scope of your project so leadership will have a vested interest in lobbying for the data.

Sometimes, a new project presents a different key performance indicator (KPI) and becomes an opportunity. If senior leaders are invested in project outcomes, making a small IT request for a data feed becomes much easier—rather than requesting a large-scale database project. These small data feed additions can make your collection invaluable.

To ensure your initiative is in line with the organization, you should always be asking yourself:

  • What metrics or impacts does the prospect hope to move?
  • What is the single most important metric for the prospect? (Yes, you can only pick one.)
  • What are the biggest pain points on the issue, and how are they measured?
  • How can you track performance now and moving forward?

What’s the value of an LRS or learning analytics platform in your organization?

Most of the data we’ve accumulated from our enterprise resource planning (ERP) efforts has resulted in push reports for which managers are accountable (e.g., specific operational/sales targets). Some managers had a difficult time understanding correlations, relational connections, or root causes from columns and rows of numbers.

As a result, combining operational metrics with related learning efforts are now visualized in charts and trend lines. That means managers get clearer pictures of problems and suggested underlying related issues (e.g., related competency gaps).

Instead of plotting learning and performance on a stoplight chart with obvious dead-end conclusions, the LRS should beg questions about associate competency and understanding gaps that need further exploration.

By pinpointing the issues in the LRS, our support staff is better equipped to review and address the biggest issues first, making remediation and improvements more efficient.

I think of the LRS as a canvas to paint big-picture stories. It doesn’t need to make the conclusions and provide drill-down specific reporting like BI does. It frames benchmark performance and suggests the color behind the issues. It provides direction on where to focus attention and raises questions for better associate support.

Know Your Choices for Aggregating Data

Build a repository database

Gathering includes building an organized collection of data. Rather than writing an API to each source, we created a repository of aggregated data.

The repository is our baseball card collection of stats and relational database extractions. As we work on different projects and interact with KPIs, our collection acquires new cards. When approaching projects, we take inventory of existing sources and how to utilize them.

Keeping the repository inside the company firewall and IT framework makes the connection process (of new data points) go quickly. We built a cloud instance of the repository and xAPI connections to the LRS.

New faces on the learning landscape

The face of the learning development team has once again changed. Somewhere in the early '90s, instructional designers started adding video and web professionals to their teams; now it’s important to consider DBAs, developers, and analysts.

Just as HR created a human resources management system (HRIS), learning professionals will need to utilize the services of outside professionals. It’s really about getting the organization to think beyond learning management system (LMS) data and focus more on performance, proficiency, and talent development.

You may want to promote staff members who have worked on LMS and related reporting, but also consider the important skillsets of outside business analysts (not necessarily schooled in the ADDIE instructional design model or SAM), developers who have more holistic organizational approaches, and those with advanced database skills.

Up Next: L&D Spotlight on Applied Industrial Technologies [Part 2]

Remember, data doesn't have much power if no one can see it. That's why getting people on board is the first step to getting good data to fuel your analytics programs.

Stay tuned for the second part of Andy's blog post, when he'll discuss the next steps to getting started with your learning analytics program. And be sure to sign up for our blog to have the next post sent straight to your inbox.

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eGuide: 5 Steps to Getting Started with Learning Analytics

Now that you understand the basics of analyzing learning experiences, it's time to start applying them in your own learning program. And it's easier than you might think. In fact, there’s a lot you can do with simple metrics and the data you have right now. We've also created the following guide to help you get started right now!

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