A Sustainable L&D Strategy: Why skills health matters

September 13, 2022
3 min read

TL;DR

Building a future-proof workforce requires more than just reskilling when change happens. Companies must monitor and maintain skills health—a real-time assessment of how well employee capabilities align with business needs.

  • What is skills health? A continuous check on workforce readiness, ensuring employees have the right skills at the right time.
  • Why it matters: Poor skills health can leave organisations unprepared for industry shifts, forcing costly layoffs and external hires.
  • How to use it: Move beyond outdated skill surveys and adopt real-time skills intelligence to inform L&D strategy.

This guide explains how leading companies manage skills health to drive sustainable learning and development.

The changing workforce landscape

Digital transformation is reshaping industries. Companies that once relied on traditional hiring and upskilling strategies now face a harsh reality: they must continuously align their workforce capabilities with business needs.

The cost of misalignment is high. When companies announce large layoffs and new hiring efforts at the same time, it raises a fundamental question: couldn’t some of those employees have transitioned into the new roles? Too often, the answer is no—because their skills were not the right fit.

Companies must move beyond reactive workforce planning and take a proactive approach to skills health. Just as elite athletes track their fitness daily, organisations need ongoing visibility into workforce capabilities.

What is skills health?

Skills health measures how well an organisation’s capabilities align with its current and future challenges. It can be assessed at different levels:

  • Organisation-wide: Are employees’ skills aligned with strategic business priorities?
  • Team or department: Are certain functions facing skill shortages or redundancies?
  • Individual employees: Do workers have the right skills to succeed in their current roles—or transition to new ones?

Skills health is often overlooked when business is stable but becomes a major challenge when disruption hits. Companies that monitor and improve skills health continuously are better prepared for change.

How leading companies approach skills health

Many organisations rely on manual skill surveys to track workforce capabilities. These are expensive, time-consuming, and outdated before they are even complete. That’s why companies like Unilever have shifted towards continuous capability monitoring, moving away from one-time assessments to real-time skills intelligence.

The three dimensions of skills health

1. Skill daps and deficits

Companies must measure the gap between the skills employees currently have and those needed for their roles. At an individual level, this is a skill gap—at an organisational level, it’s a skill deficit.

2. Employability

Employability assesses how adaptable an employee is within the organisation. If their role disappears, can they apply their skills elsewhere? High employability means a workforce that can shift with business needs.

3. Future-proofing skills

Are employees’ skills keeping up with industry trends? Companies that track skill evolution can ensure they are leading, keeping up, or falling behind in their market.

Why skills health should drive L&D strategy

Traditional learning and development strategies focus on closing skill gaps reactively. A skills health approach takes a broader view:

  • Proactive planning: Identify future skill needs before they become urgent.
  • Smarter hiring: Reduce external hiring costs by reskilling existing employees.
  • Targeted upskilling: Focus L&D investments on skills that will have the highest impact.

Real-world example: Strategic hiring decisions

A company looking to hire an accountant considers a junior candidate. If the team already lacks experience, hiring the junior candidate might weaken skills health. But if the team has enough senior expertise, onboarding a junior employee could be a smart decision.

How to integrate skills health into workforce planning

1. Move beyond one-time assessments

A single skills audit every few years isn’t enough. Companies need real-time skills data to make informed decisions.

2. Use AI-Driven skills intelligence

Manual surveys are inefficient. AI-powered skill inference provides a real-time, unbiased view of workforce capabilities.

3. Make skills health a core business metric

Track skills health like financial performance—ensuring leaders always have insight into workforce readiness.

The bottom line

Skills health is not just an HR concern—it’s a business imperative. Companies that continuously assess and improve workforce capabilities can:

  • Reduce reliance on external hiring.
  • Improve workforce adaptability and resilience.
  • Build a sustainable L&D strategy that prepares employees for the future.

TechWolf helps organisations achieve this with AI-powered skills intelligence.

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Using AI while interviewing at Techwolf

At TechWolf, we see generative AI as part of the modern toolkit — and we expect candidates to treat it that way too. We love it when people use AI to take their thinking to the next level, rather than to replace it.You are welcome to use tools like ChatGPT, Claude, or others during our interview process, especially in take-home assignments or technical exercises. We encourage you to bring your full toolkit — and that includes AI — as long as it reflects your own thinking, decisions and creativity.We don’t see AI as replacing your skills. Instead, we’re interested in how you use it: to brainstorm ideas, speed up iteration, validate your thinking, or unlock new ways of approaching a challenge. Great candidates show judgment in when to rely on AI, how to adapt its output, and where to go beyond it.

What we’re looking for:

Our interviews are designed to understand how you think, solve problems, and express ideas. Using AI in a way that amplifies those things — not masks them — is encouraged.

What to avoid:

We ask that you don’t submit AI-generated work without review, or present answers that you can’t fully explain. We’re not testing the model — we’re getting to know you, your skills, and your potential. If there are cases where we don’t want you to use AI for something, we’ll tell you ahead of the interview being booked.In short: use AI as you would on the job — as a smart assistant, not a stand-in.

Example: Programming with AI

In a coding challenge, you’re welcome to use generative AI to support your workflow — just like you might in a real development environment. For instance, you might use AI to quickly generate boilerplate code, look up syntax, or get a first-pass solution that you then adapt and debug collaboratively. What we’re interested in is your ability to reason through trade-offs, communicate clearly, think about complexity and iterate effectively — not whether you memorized the syntax perfectly. If using AI helps you stay in flow and focus on higher-level problem-solving, we consider that a strength. There could be some challenges where we won’t allow you to use AI - in that case we’ll tell you in advance, and will tell you why.

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