Corporate Strategy and Learning Center

What is AI?

The term Artificial Intelligence (AI) might invoke futuristic images, but it’s actually part of our present day and more approachable than you’d think. The fathers of the AI field, Minsky and McCarthy, described artificial intelligence as any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task. AI can find patterns in big data to learn and show information to deliver solutions to complex problems.

This is part of our ongoing series, Interviews with Learning Leaders.

Kevin M. Yates, Learning Technology Manager at McDonald's, uses his expertise to answer the question, “Did training work?” with facts, evidence, and data. Kevin's work spans the globe and industries, and he is a sought-after subject matter expert and international speaker. His experience reaches across training, learning, and talent development, having served in roles for facilitation, instructional design, learning solutions, learning technology, program management, operations, strategy, measurement, and analytics.

Kevin's guiding principle is, “Find one thing about a person's behavior or performance you can attribute to training or learning, and let that lead to the facts about impact.”

In a recent blog, we pointed out strategies to increase learning retention by using what we know about human memory, but what about after the training event is over? How do we make sure it sticks?

In many organizations, learning is seen as a one-time event, often in a different location from the job site, and once it's over, the learning on that content is over. But in order to reinforce the application of the learning and identify the actual retention, we need to think of training as a continual process and extend it beyond the one event.

There are several practical ways to ensure knowledge transfer, and implementing these can improve the investment your organization has made in training employees.

When learning & development organizations successfully prove that they aren’t merely cost centers—that they reliably and verifiably deliver positive results to the bottom line of the enterprise—they inevitably gain stature and influence with business leaders. By establishing a solid metrics and measurement program, underpinned by a learning analytics process, learning leaders gain access to the evidence that illustrate their team's everyday impact.

Analytics turns learning metrics and measurement into insights that enable informed decisions and actions. Learning insights may include process efficiency, alignment of employee skills to business needs, and the impact of learning on key organizational metrics like staff turnover and leadership development capabilities. When analytics are leveraged effectively, they can influence not just how courses are designed or how the L&D function is staffed, but also larger decisions such as hiring and competency development.

The benefits of structured and consistent development and communication of learning analytics may extend to all levels of the organization.

It’s been a long time coming, but we’re finally starting to see more learning leaders taking a serious look at implementing meaningful metrics and measurement. As a result, relationships and conversations between the learning & development organization and business stakeholders have begun changing for the better.

That said, there are times that learning leaders need to root themselves in some foundational principles of learning metrics. We get so caught up in new thinking, models, and frameworks that we tend to lose focus on the fundamentals of how to run our L&D business.

No matter what model, framework, system, tool, methodology, or new approach we want to adapt, adopt, and deploy, there are at least three fundamentals that we should never lose sight of—principles that should be applied to all learning metrics.

A learning and development organization that lacks effective metrics and measurement is going to have a difficult time proving its business value to the enterprise. Having comprehensive learning metrics in place is a key reason that successful learning leaders have the respect of business leaders and are able to get their talent development initiatives funded.

When taking the first steps toward implementing a measurement process, try not to overthink it. While collecting effective metrics and determining the ROI of learning takes planning and strategizing, it doesn't have to be a terribly complex process.

There are four key areas to focus on in the measurement journey, and they all tie back to business results. By measuring intent, knowledge, performance, and impact, learning leaders achieve insight into how to improve learning solutions—and just as importantly, they'll be able to prove that value to the business.

Your organization has identified a need for learning surrounding a broad topic like on-the-job coaching or business acumen training. As a learning leader, your first inkling might be to just peruse the internet and sift through the many off-the-shelf offerings from dozens of training providers. But this approach comes with obvious, potentially crippling downsides.

This challenging question is known as the build vs. buy scenario, and it’s one that learning leaders deal with frequently. Should you go the easy route and purchase a ready-made learning product—one that will necessarily lack key specifics about your organization and industry—or build a customized training program that will meet your learning needs precisely, but which may be more time-consuming and expensive?

How should learning leaders weigh the pros and cons of such a straightforward transactional purchase with the larger, longer-term needs of the organization?

When considering the value of metrics to a learning & development organization, it's instructive to think about the statistician's dream world that is team sports.

Sports fans are famously obsessed with statistics, yet regardless of how impressive a player's individual stats might be, players are ultimately evaluated in the larger context of team success—even the best player in the league is unlikely to win a Most Valuable Player award if the team has a losing record. This evaluation of the metrics that correlate to success has given rise in recent years to "advanced stats," in which number crunchers attempt to identify the metrics that directly impact wins and losses.

In L&D, the shift toward meaningful metrics is gaining traction, albeit slowly... but the principle nonetheless still applies. If learning leaders want the credit they deserve for shaping their organizations' MVPs, they need to identify, quantify, and track the metrics that go into achieving organizational objectives and bottom-line success.

This time last year, we at Caveo Learning were optimistic that 2015 would be the year that the learning & development industry "got it"—that there would be a mass realization that L&D needs to deliver real business value, above all else.

The good news is that the wave is building—more and more learning leaders are figuring out that the best way to gain influence, budget, and that proverbial seat at the table is by aligning the learning function with the business and becoming a true organizational partner. The bad news is that the wave has a long way to go yet before it crests, and we'll have to defer our optimism for the industry to 2016.

Case in point: much of the discussion at the Fall CLO Symposium remained stuck in that outdated way of thinking that has kept L&D ensconced in a bubble, oblivious to business needs or realities. I share the dismay of Dave Vance, executive director of the Center for Talent Reporting, who was incredulous that so many learning leaders continue to place employee engagement, not alignment to business goals, at the apex of the L&D mission.

Learning professionals have a tendency to overcomplicate things. There’s no better example of this than our industry’s fraught approach to ROI analysis.

Believe it or not, ROI is much easier to estimate and capture than most learning leaders believe. Far too often, we hear the pessimistic cries that it’s impossible to quantify ROI from L&D programs, based on a whole host of unsound excuses. Among the most common copouts:

• “There’s not enough data available.”
• “We can’t get a control group set up.”
• “Other initiatives are already taking credit.”
• “One can’t ‘prove’ the outcome.”
• “There are too many outside variables for the data to be reliable.”

Not to say that these concerns are never legitimate, but let’s be real—capturing ROI is not rocket science. Other functional areas of the business do it all the time. So why does this struggle seem to be so particularly acute among learning leaders?