How to Design a Digital Infrastructure for Training

EDITOR’S NOTE:  Because extended enterprise learning involves multiple disciplines and perspectives, we sometimes invite experts from learning technology companies to share their insights. Today, Ross Van Wyk of Administrate shares advice on building a digital infrastructure for training.

Organizations everywhere are stepping up to modern digital learning challenges. For most, this requires the development of a new or improved digital infrastructure for training. But what exactly does it take to build a foundation that will serve you well now and in the future? Focus on these factors…

The Human Element

No matter what your L&D team wants to achieve, your staff will always be your most valuable resource. Even if you rely on multi-million-dollar simulators that cost more than your department payroll, your team will still be the most critical component in your digital arsenal. That’s because software and equipment can’t provide the kind of unique insights and innovation that skilled learning professionals can contribute.

However, for L&D professionals to succeed, they require two things: time and decision support. Unfortunately, in many cases this just isn’t happening.

Too often, employees with diverse skill sets could be working on complex, strategic problems. But instead, they’re forced to perform low-value data entry or administrative tasks. That’s because their systems aren’t up to the task of managing modern training operations.

Usually, this issue isn’t caused by any particular piece of software. Instead, the problem comes from how an organization has built its entire tech stack. And it starts with the digital infrastructure. Here’s how learning technology often goes so wrong…

Do you want more information and analysis on the top 40 learning systems in the world? Buy our 2023 Corporate Learning Systems Market Update report – now available through the 2nd half of this year at a 50% discount!

Learning Tech: How Messy Is Your Toolkit?

Buying learning tech can be like buying tools for a home maintenance project. We may not have everything we need on-hand in our garage — although we could probably find most of the items if we look around.

However, because most garages aren’t highly organized, finding what we’re looking for can take a long time. So instead, we buy a few new tools. Then what happens? When we’re done, we toss the new tools into the existing mess. That just makes the entire garage problem worse.

Obviously, that’s not an efficient way to spend our time or money. In an ideal world, we would be more organized. We would know which tools we own and where to find something when we need it. But, as anyone who’s ever tried to clean a garage knows, trying to organize chaos is a tough task. And trying to keep all those tools organized over time is even tougher.

The Problem with Unplanned Digital Infrastructure

Learning tech stacks suffer from the same problem. As Josh Bersin pointed out in his report, “Learning Technologies and Platforms 2022 and Beyond,” the average company relies on up to 22 L&D tools and platforms. That’s 22 tools to track, sync, update, and report on.

What’s worse, those systems don’t play well together. According to a 2022 HR.com survey, only 29% of respondents said their HR tech stack components “usefully integrate with one another well or extremely well.”

Does that sound like your digital infrastructure? Is it really just a jumble of different systems — each bought as a point solution for a single problem? That kind of approach is wasting your organization’s valuable time and money:

• TIME: Because your team is constantly struggling to find what they need and forcing systems to cooperate with each other, rather than doing important strategic work.
• MONEY: Because, with a more strategic approach to your digital infrastructure, you could have access to the same functionality while spending much less on software licenses.

Success stories from companies like JLG show that it pays to build a digital infrastructure for training with intention and purpose. So, what specifically can you do to develop a strategy that works?

3 Pillars of a Digital Infrastructure for Training

How do we avoid accumulating so many point solutions that our tech stack becomes a shambles? The key is to be intentional in designing, building and maintaining a digital infrastructure for training. Keep these core principles in mind: connectivity, consolidation and data access.

1. Connectivity

Most learning technology isn’t built to connect seamlessly with other software. It is typically designed for an older paradigm of enterprise software use.

For example, think of an employee uploading spreadsheets filled with data into a system. In response, the system generates a chart, a report, or another spreadsheet. But that kind of routine forces employees to become shepherds for endless spreadsheets. And worse, it prevents them from focusing on more valuable work.

In an ideal scenario, the software automatically pulls data directly from wherever it’s stored and then pushes that data to wherever it’s needed. This kind of system-to-system connectivity depends on an aspect of software design that is too often overlooked in the learning tech space: ease of integration.

2. Consolidation

Ensuring that software offers basic connectivity capabilities is fundamental. Yet it’s a bar that many systems don’t clear. Even so, that alone isn’t enough for a healthy learning tech ecosystem. It is also essential to simplify how data moves through your digital infrastructure — and through employee workflows.

Reducing the total number of systems is one strategy. This approach is about looking beyond point solutions and investing in platform-based software.

It’s equally important to simplify the flow of information across your digital infrastructure. Directly linking each system to all others creates a tangle of integrations that must be continuously monitored and managed. An ecosystem that leverages data lakes and warehouses may require more upfront effort, but it reduces the number of moving parts and improves data access.

3. Data Access (for Humans)

Unfortunately, ensuring that people have easy access to data isn’t always a top priority among learning technology designers. Often, you’ll find a series of pre-generated reports that aren’t easy to customize or edit. What’s worse, these reports may not include some of the relevant data that’s available in your systems. This leaves key training information inaccessible.

If you’re running your system through a data lake, then you should at least make sure it’s always easy to pull data from that central repository. But even with individual systems, you’ll want to choose software that lets staff easily find the data they need without having to move to a second system. This simple, time-saving measure also saves computational resources.

Do you want more information and analysis on the top 40 learning systems in the world? Buy our 2023 Corporate Learning Systems Market Update report – now available through the 2nd half of this year at a 50% discount!

Bringing Data Together: Making It Easy to Use

At the start of this article, I stressed that skilled staff are your training team’s most important resource. That’s true. But the next most important resource is your data.

An engine might be the most important part of your car, but it won’t run without fuel. Training professionals can’t hope to create innovative content and learner experiences if they don’t know how well your L&D operations are working. What’s more, if your people spend too much time trying to access and manage learning-related data, they won’t be able to make creative or strategic decisions.

So, as you evaluate your digital infrastructure for training, focus on the flow of data. Does it move on its own, automatically? Or do humans need to move it along, manually? Does it flow through direct, easy-to-follow paths? Or is it pushed through a disorganized network? And when humans do need to look at data, how easily can they extract useful information from your system?

The future of learning technology depends on advances such as headless architecture and powerful API capabilities that help data flow as smoothly as possible across your ecosystem. So, to be sure your learning data is as useful and highly available as possible, take time now to rethink your tech stack so it functions like a carefully designed digital infrastructure for training.