According to a recent article by Josh Bersin, while the global learning and development (L&D) industry is worth $200 billion, many learning professionals believe that half of this money is wasted. In Learning Analytics, John Mattox II et al. cite research on waste being even higher — between 60 percent to 90 percent.
The challenge of measuring the effectiveness and ROI of L&D has long been debated. In Strategic Analytics, Alec Levenson explains that L&D programs are usually a number of steps removed from any clear and direct impact on business outcomes, which in his view means it is very difficult to measure and quantify ROI.
Until recently, talk of people analytics in the L&D domain has largely been restricted to debates on how to overcome this challenge and more closely link L&D programs and the needs of employees, managers and businesses.
Fortunately, the continued growth of people analytics, the consequent shift to a more data-driven approach and the emergence of artificial intelligence in the HR domain is helping to revolutionize L&D and significantly increase its value to employees and the business.
I recently spoke with Trish Uhl, founder of Owl’s Ledge and an expert on both L&D and people analytics, to discuss key trends and how this shift is radically changing how L&D programs are designed, delivered and measured.
One of the key challenges we’re facing in the L&D space is that we’re having trouble moving beyond our past, and people analytics is helping to break that orbit and give us some escape velocity.
As with any emerging profession, we come by our past honestly. Training and development — the predecessor to learning, development and performance, or L&D — has traditionally had a reputation as an operating cost vs. an investment.
As you know, costs do not usually have an expected return. Until recently, training and development (T&D) wasn’t expected to have a return, either. Born of the Industrial Age, T&D focused on tangible assets like courses, training materials, number of people trained, number of classes delivered — Industrial Age metrics that were always subject to cost control.
At one time, it made sense. In a stable world of work and a routine workplace, those physical assets were worth something — think of McDonald’s binders full of proprietary systems training — and had long life cycles.
Then the world, workplace, work, workforce and workers dramatically flipped.
Administrative T&D gave way to strategic L&D in the 1990s, and the field has been on a maturity curve since. Progress, to some, has felt slow, but there have been pockets of progress featuring quantifiable leaps forward.
For example, people analytics applied to L&D is actually a mature discipline, put into practice by such early pioneers as Jac Fitz-enz, Dave Basarab, Gene Pease and Jenny Dearborn.
Fitz-enz is credited as the creator of one of the earliest methods for measuring ROI for people investments; Basarab introduced predictive analytics to Motorola University in the early 1990s; Pease founded Vestrics in 2005, which was one of the first human-capital predictive analytics Software as a Service (SaaS) platforms on the market; and Jenny Dearborn, CLO of SAP, used her Prescriptive Action Model (PAM) to radically change SAP’s global sales organization.
They’ve been early adopters in a world that now competes on intangible assets, having moved beyond metrics of efficiency to metrics of efficacy.
Yes, we’ve had advanced analytics in L&D for more than a decade; what we haven’t had is widespread adoption. Until now. That’s what the growth of people analytics is doing to help L&D overcome its challenges — to break free from the ghosts of the past.
I led my first L&D team to success with predictive analytics in 2015. Back then, employee experience wasn’t a key driver or phrase, but we were able to make measurable positive people impact and produce quantifiable business results.
It was a “soft skills” development program — developing personal resilience to improve employee health & well-being in an environment experiencing a steady rise in stress-related sickness absence.
Shortly after the program started, the situation was compounded further by industry deregulation. In response, the company crafted a new people-centric strategic plan focusing on customer retention and acquisition, which required dramatic changes to employee-performance KPIs.
The pressure was intense. People needed real coping strategies that could provide some relief, and the organization needed a fit and ready workforce capable of navigating this and future upheavals.
Under the leadership of then-Head of People Development Pam James and the expertise of personal resilience expert Roddy Herbert at Koru International, we were able to take Koru’s body of work and transform it into a data-enabled, responsive resilience learning system. (Cheers here to teammates Sarah Archer and Jack Butler for their hard work, as well!)
The bespoke learning system was embedded with assessments and a predictive algorithm developed by evaluation expert Ken Phillips, inserted at a key milestone so we could measure and take preventative action at the individual delegate, business unit and organizational levels.
In just over two years, we were able to provide evidence for making sustainable positive impact on employee engagement, and leading indicators showed interim progress toward the long-term goal of decreasing stress-related sickness absence.
We were able to equip the L&D executive and management team with data and insights that provided evidence-based recommendations for investment of targeted resources — for example, one-on-one coaching for individuals in need. Best yet, individual people were measurably more resilient having personally benefited from the program.
That makes me happy! I believe true success in achieving organizational outcomes comes from both driving business results and making positive people impact.
There’s a lot happening fast! To put it into context and make it a bit more digestible, I’ve organized how we can leverage AI & ML in L&D into three categories:
Do It Yourself (DIY) – Back in 2015, though our analytical approach was pretty forward-thinking, our data-management and analysis tools were pretty old-school. Today, that’s all changed. We can now process, analyze and model all of the data we collect using AI/ML on a SaaS platform such as Amazon AWS, Microsoft Azure or IBM Watson. These technologies give us the additional choice of outsourcing data science and statistics to a platform vs. a person.
Do It With You (DIWY) – Other modern AI-powered tools, such as Amazon QuickSights, simplify and automate the application of AI/ML to workplace learning analytics projects even further, often going from information to insights within seconds.
Do It For You (DIFY) – As the name suggests, these are the turnkey solutions that fully automate individual areas of L&D. These are the L&D industry disruptors.
Each solution represents a single application and use case, but like most AI, they are exceptionally powerful in their narrow focus. Training materials that used to take months to create can now be AI-generated — with interactivity, assessment and instructional integrity — in minutes. It’s all natively cross-platform and voice-controlled, too. AI chatbots located in workflow — like on Slack — are now available to handle things like personalizing new-employee onboarding experiences. You can also set up some of these digital docents to automatically curate resources on topics of interest, resources that become more contextualized and relevant as the AI learns more about you. And we can use AI to offer one-on-one, adaptive, 24/7 coaching, training delivery and tutoring services.
But the big one? The true disruptive L&D solution is a learning ecosystem integrated with an AI/ML-enabled data river that collects data from multiple input devices (e.g. VR, e-learning, AR) as delegates advance through a development program and provides real-time statistics, insights and recommendations on individual delegate, cohort and program performance via visual dashboards and voice controlled devices. This is the L&D solution from a New Zealand-based company called Skilitics.
Far too much detail to fit into this wee space, but Skilitics and virtual reality strategic partner CerebralFix were successful in solving an Emirates Airlines challenge to reduce crew-training costs by 50 percent within nine weeks, while participating in 2017’s Dubai Future Accelerators.
Skilitics and CerebralFix together were one of 46 companies selected out of 1,100 to participate in the third DFA cohort. I was on-site with them at the DFA innovation space in Dubai when the Skilitics and CerebralFix team were preparing to deliver a personal presentation to His Highness Sheikh Mohammed bin Rashid Al Maktoum, vice president and prime minister of the UAE, ruler of Dubai. Talk about priority stakeholder — you don’t get much higher than that. (More detail on the DFA program, cohort three and the Emirates Airlines challenge can be found on the DFA website here.)
Ensure you have a strong sponsor champion when you are ready to put analytics into practice in your learning function. This is culture change. Culture change requires both commitment from the executive team and buy-in from the front line.
We get to choose where we want to be in proximity to the turnkey AI solutions. We can either be wielding them or in front of them, flinching. These tools are not only revolutionizing L&D, they’re democratizing workplace learning. They enable just about anyone to use them — with great effectiveness. Think about how you can disrupt your practice before someone shows up to do it for you.
I don’t have to tell anyone that these are challenging times with intense pressure. We’ve invested so much time and resources into developing people’s skills and knowledge that we have neglected to help them develop their inner, affective, states, too. People analytics applied to soft skills can make significant inroads here, and there’s no better time than the present.
And that’s all we’ve ever really wanted to do, right? Make positive people impact and contribute to business results. Use these modern tools wisely — together we can create a world that works better.
The publications below were either mentioned in this article or provide related reading on the use of people analytics and AI in the L&D domain:
Bailie, Ian, Butler, Megan Marie: The impact of AI in HR (2018)
Basarab, Dave, et al: Using Predictive Evaluation to Design, Evaluate, and Improve Training for Polio Volunteers (2017)
Bersin, Josh: AI in HR, a real killer app (2018)
Bersin, Josh: A New Paradigm For Corporate Training: Learning In The Flow of Work (2018)
Dearborn, Jenny: Data Driven: How Performance Analytics Delivers Extraordinary Sales Results (2015)
Dubai Future Accelerators (DFA) Cohort 3 Results: October – November 2017
Fitz-enz, Jac, Pease, Gene: Human Capital Analytics: How to Harness the Potential of Your Organization’s Greatest Asset (2012)
Herbert, Roddy, Uhl, Trish: Improving Organisational Performance and Individual
Wellbeing Through Evidence-Based Development in Personal Resilience (2017)
Lawton, George: How AI and machine learning help in upskilling employees (2018)
Levenson, Alec: Strategic Analytics (2015)
Mattox II, John, van Buren, Mark, Martin, Jean: Learning Analytics (2016)
Phillips, Ken: Predictive Learning Analytics™: New Rules, New Tools for Increasing Training Transfer (2017)
Uhl, Trish: Are you ready to start the workplace learning analytics journey? (2018)