Learning Debt (and Forecasting)

The hidden reason transformations succeed or struggle

One of the most uncomfortable truths in any transformation is that people are often the last part to genuinely up-skill. Technology gets deployed, processes get re-written, governance gets tightened… but the people using those systems are still catching up. There’s always going to be a lag!

And that gap between what people need to know and what they actually know is what creates learning debt.

What is learning debt (in plain English)

Learning debt is the gap between what people need to know to thrive in a new system and what they’ve actually learned.

Here’s a real-life example:

• An agent attends a one-day training on a newly deployed cloud platform.
• The following week, the agent is juggling customer calls, but can’t remember how to transfer a call to another queue.
• Instead of raising a ticket, this agent creates their own sticky-note (…sort of a quick workaround).
• Soon, half the team copies the agent’s method. By month two, supervisors are fixing dropped calls daily.

That’s learning debt in action, and it spreads faster than leaders realise.

How learning debt snowballs

Within the context of financial institutions, banks are uniquely vulnerable to learning debt because:

• teams juggle BAU, regulatory deadlines, and transformation at the same time (the ratio of teams to projects is often 1:many!)
• staff often don’t have breathing space to learn deeply
• different business units have different levels of change maturity
• people fear making mistakes that could create compliance or audit issues
• legacy systems stay in place for years, causing mental overload
• new tools often overlap with old ones, creating confusion
• staff turnover wipes out pockets of knowledge
• leaders underestimate how much they themselves need to learn…

Nobody wants to admit they’re behind, which means learning debt grows silently until it becomes too big to ignore.

Here’s another example of how it compounds:

1. First week: Agents forget 60% of the training content on a certain cloud platform.
2. Second week: Workarounds spread (‘just log out and back in if routing fails’).
3. First month: Supervisors lose trust in dashboards because metrics look off.
4. Three months: Leadership wonders why call handle times haven’t improved.
5. Six months: Adoption plateaus. Benefits promised in the business case vanish.

In most of the scenarios, it’s not a training issue (if tailored training was made available), it’s a credibility issue.

Why learning debt forecasting works

It forces us to ask honest questions upfront:

• What skills will people actually need to survive the ‘new world’?
• Who is furthest behind today?
• Who will struggle the most tomorrow?
• What is the cost of not upskilling them?
• What will break if people don’t learn fast enough?

When done early, forecasting catches risks before they explode.

Recommendations for a more sustainable uplift

Keeping a pragmatic approach to befit the organisation’s unique challenges helps with understanding the course of actions. Some of the most basic ones are to…

> Create a learning debt ledger. Just like finance tracks liabilities, log every recurring skill gap, e.g. ‘Agents still can’t locate call recordings.’

> Create a network of champions. Tailor the change (and learning) to the context of each business area… in their language.

> Train supervisors deep-dive. One bank I worked with gave supervisors extra deep-dive training. Within a month, helpdesk tickets dropped because supervisors solved issues on the floor.

> Organise literacy sessions for leaders. Help leaders bridge their own learnings to be able to role model the same for their teams.

> Include micro-learning in the flow of work. Replace bulky PDFs with short videos or clickable walk-throughs, and easily accessible support materials.

> Tie hypercare-exit to learning KPIs. Don’t exit hypercare until basics are mastered, e.g.‘<5% of tickets are about audio settings’.

Celebrate competence. Shifting the story from ‘we went live’ to ‘95% of people are now confidently using the new system’ builds trust and morale.

Reflection…

Most transformation initiatives run the risk of struggling because learning debt was never forecasted, monitored, or owned by anyone.

It acknowledges something everyone feels: people need time, space, clarity, and support to adapt. This isn’t about unwillingness to learn; it’s a predictable gap that grows over time if left unaddressed.

When organisations embrace this honestly, transformations stop being so painful and start being more empowering.

References

These links provide the context and case studies that validate the patterns brought up in this article:

• AWS Financial Services Cloud Transformation Paper https://aws.amazon.com/financial-services/transformation
• Gartner Research on Digital Workplace Change Management https://www.gartner.com/en/information-technology/glossary/digital-workplace
• RBA Payments System Modernisation Research https://www.rba.gov.au/payments-and-infrastructure/