The Hidden ROI of Learning and Development: What the Numbers Don't Show
Replacing one employee can cost nearly $50,000 in lost productivity. Training one costs a fraction of that. Three APAC talent leaders break down how to diagnose the real cause behind training requests, build the business case for L&D investment, and capture the ROI that never shows up on a P&L.
Most organizations treat learning and development (L&D) as a cost to manage, rather than a strategic workforce investment. But that changes when leadership commits to ensuring every dollar spent has a material impact on the bottom line.
At our recent event in Singapore, "The ROI of Learning: Turning Cost Centers into Performance Engines," three APAC talent leaders — Eng-Sing Soon (Vice President, Group People & Sustainability at Singtel, a Visier customer), Cherie Tang (Regional L&OD Lead at ENGIE), and Mujibor de Graaf (CEO at Fellow Digitals) — explored what it takes to reframe L&D from a cost center to a strategic driver of business performance.
As moderator, I walked away with more than a few insights worth sharing.
How to diagnose the real cause behind every training request
Reframing L&D as a strategic investment starts with a simple but often overlooked question: are you measuring the right things?
Soon observed that most HR teams collect metrics the way people wear smartwatches — compulsively, and without a clear sense of what to do with the numbers.
"Many of us actually don't question the use of having all these vitals in our palm," he said.
Having vitals, he noted, is not the same as having answers.
A 3-Step Approach to Talent Insight from Eng-Sing Soon, Vice President, Group People & Sustainability at Singtel |
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1. Know your objective |
3. Ask the right question |
In practice, that meant starting with one big strategic question—"what is our leadership optionality?"—then identifying the specific metrics that would give clues, whether mobility rate or pipeline strength. "We took the approach of telling the talent insight and story instead of just presenting a dashboard or report," Soon said.
Tang’s experience at a previous organization illustrates exactly why. She recalled an incident where 80% of managers requested communications training.
But when she dug deeper—asking what questions led them to identify it as a communication issue— she found the real problem was difficulty managing people, not communication skills.
Managers had attributed the friction to how people spoke to each other, when the actual issue was something else. “When you have different data points from different perspectives, that’s where it grows the entire picture for you.” The root cause? “It's the conflict management that’s usually weak when it comes to leadership,” she explained, “because we are always uncomfortable to have those difficult conversations with others.”
What you can do: Start with the business question, not the data. When managers request training, dig deeper through one-on-one conversations to uncover the root cause before designing a solution.
Why internal knowledge sharing beats external training
"The problem is knowledge sharing," de Graaf argued. "L&D just provides the training but forgets that the knowledge is already in this organization." His advice is to train leaders to ask their people to share what they know, provide positive feedback to all those involved, and create a content verification process to ensure what is shared is accurate.
Today, it's possible to speed up this process by using AI to extract and package that knowledge into microlearnings rather than commissioning costly external agencies.
But as De Graaf's pointed out: AI cannot replace the need for us to learn from each other. This point in particular resonated with me. Instead of defaulting to the top-down approach, L&D should concentrate on tapping the knowledge already within their people and using AI as a co-pilot to get it there faster and more efficiently.
What you can do: Before purchasing external training, audit what expertise already exists within your organization. Train leaders to actively solicit knowledge from their teams. Use AI tools to help subject matter experts package their knowledge into microlearnings.
Don't swim in the data for too long
Soon also described an onboarding paradox he’s witnessed: new hires gave glowing feedback on their first 90 days, yet attrition among new employees was higher than among tenured staff. Within the same employee demographic, two reports gave two completely different stories.
When data contradicts itself, it is HR's job, Soon clarified, to apply human judgment and curiosity.
When we only look at one report, we’re like a person touching a wall and assuming that’s the whole reality: that wall is actually just one part of a much larger elephant. Zooming out and connecting multiple, seemingly contradictory data points uncovers the full picture that a single source can never reveal on its own.
If you get conflicting data, don't be afraid to tackle it from a human perspective, or you risk falling into a spiral of analysis paralysis.
His advice is to get the insight and take action. The data pool can wait.
What you can do: Don't let conflicting reports paralyze you. Combine AI-driven data analysis with human judgment. In this specific scenario, that would mean conducting structured check-ins at 30, 60, and 90 days post-onboarding to get a fuller picture beyond the initial satisfactory feedback data. Then, when insights surface, set a deadline to act.
The ROI you can’t see on a spreadsheet
Tang posed a question to the panel: "If we are spending X amount of money, how do you ensure that we reap the benefits from it — that we really see an increase in sales, our BDs getting in numbers?".
Her answer is to tie training to learning outcomes, then trace those outcomes back to business goals.
If the target is 20% to 30% profit growth, the training needs to directly support those goals.
When selected employees complete the training, they need to share what they learned with their team members and apply it to their everyday work because the returns aren’t always immediate or visible in the P&L.
But there must also be recognition that some results won’t be immediately visible in the P&L. Tang stressed that the unseen ROI is real: teams are more motivated and managers leading more effectively. As she said, "Employees bring in knowledge, sharing it in their teams. They have better working relationships with each other. I think that's the win."
What you can do: Send selected employees for training, then require them to share key learnings with peers who didn't attend. Track both hard and soft indicators. Collect data on the revenue impact of course, but also the impacts to team motivation, manager effectiveness, and absenteeism rates.
Why replacing an employee costs more than training one
Tang put a number on what most organizations overlook. Using Singapore's median salary of $5,500, she calculated that inducting a single new hire costs roughly $33,000 in the employee's own time, plus another $16,500 for the colleague who spends half their time teaching them.
"In totality, you're spending almost $50,000 when there's a new person on board," she said.
Multiply that across 10 new hires, and you're looking at nearly $500,000 in productivity loss.
"Even if it's $10,000 to send someone for training, I'm essentially saving $490,000," she said. When the trained employee returns and shares what they've learned, the savings compound.
Speed to readiness, as Tang's numbers show, is ROI in its own right.
I put the same question to de Graaf: how do organizations speed up their learning pace? With competitors operating globally and time to market shrinking, he noted, "If you can manage to get this knowledge out faster through peer-to-peer interaction, then you have won a lot."
He suggested a practical solution to speed up learning:"Don't just throw everything at people. Put it in little ‘snacks’—maybe each week—and then people learn faster and they just remember more."
What you can do: Calculate your real induction costs to validate L&D costs. Include not just the new hire's salary but also the time existing employees spend onboarding them. Use AI-powered tools to design snackable microlearnings employees can easily and quickly consume.
From business expense to strategic investment
Traditional L&D is often seen as a slow, expensive overhead expense. But what I took away from this conversation is that learning only creates value when it changes behavior.
Soon put it plainly: “We are in a constant transformation phase.” The workforce needs to pivot, adapt new systems and integrate AI — not someday, but now.
Tang was even more direct: If organizations don't get their people AI-savvy, they risk being replaced not just by AI but by the younger generation.
The time pressure is real.
I truly believe that any training program has zero impact if there’s no change in behavior at the end of the day. Start with one question worth answering. Close the gap between what’s being spent and what’s actually changing. The discipline to follow through will take care of the rest.
