I Wasted $40 Million on Skills Strategies. Let Me Save You the Trouble.

At Reejig, we’re obsessed with workforce transformation. But before we nailed the formula, we made plenty of mistakes—$40 million worth of them, to be exact. My journey was an expensive education in what doesn’t work when building skills strategies in HCM tech. Here's the reality check you need to avoid the same pitfalls.

The Costly Mistakes Organizations Are Making

Despite the best intentions, many organizations fall into these traps.

• Poor Data Quality: Extracting or inferring skills from job descriptions and adverts led to irrelevant and misleading insights, as these sources don’t reflect the actual work being done.
• Inconsistent and Messy Data: Skills extracted from multiple systems created a chaotic, ever-changing dataset, made worse when AI dynamically updates records and pushes them into systems like Workday or SuccessFactors without proper governance.
• Flawed Data Sources: Job adverts are one of the worst data sources for inferring skills, with the same job appearing in multiple locations, skewing demand signals and creating false insights about "emerging skills."
• Unharmonized Data: Different platforms and teams use their own language for skills, resulting in fragmented datasets and a lack of alignment across the business. This creates confusion and inefficiencies as each system operates in silos.
• Large Language Models (LLMs) Issues: LLMs provided inconsistent and unreliable outputs, offering different recommendations for the same job depending on how it was described.
• Rigid Job Architectures: Using job architecture frameworks to match work was ineffective. They were rigid, out of date by the time projects were completed, and didn’t align with the way businesses actually describe or think about work.
• No Skills Governance: Without governance, duplications, inaccuracies, and inconsistencies compromised data quality and made it impossible to maintain a reliable skills dataset.
• AI Automates Tasks, Not Skills: AI and automation are designed to handle specific tasks, like analyzing data or generating reports. They don’t “have skills” in the way humans do. Recognizing that AI is task-driven enables more effective integration with human workers.

Trust me—I tried all of this, and none of it worked. If you want a better outcome, you need a smarter approach.

What Works and Lessons Learned

1. Focus on the Work Being Done: Most organizations don’t have a clear view of the actual work being done. That’s why we built 23 Industry Work Ontologies™ to fill in the gaps and uncover real insights.
2. People Have Skills > Jobs Have Tasks > Tasks Need Skills: Once you see work this way, you can’t go back.
3. Create One Common Language of Work: HR and the business need to agree on a unified framework. Start with the work being done, then layer in skills. This reduces friction and helps get buy-in for transformation.
4. Harmonize Your Data: Pick one system to standardize skills across all use cases—hiring, learning, mobility, and more. This ensures consistency and better alignment across the business.
5. Put a Governance Layer in Place: Don’t allow your skills system to constantly update and change jobs live in your HCM. Agree on a governance timeline to approve updates.
6. Build Strong Data Foundations: A reliable dataset on your people’s skills and the work being done is critical. This allows you to solve real problems and do meaningful strategy work.
7. Match Work to Workers Based on Real Insights: Go beyond job titles to understand the tasks being done and align people with what they’re best at.

Why This Matters:

The old methods don’t just waste money—they prevent you from unlocking your team’s potential. Here’s how our approach helps you stay competitive:

• Uncover AI opportunities and build clear roadmaps.
• Eliminate inefficiencies with precise task mapping.
• Design meaningful career pathways that engage your workforce.
• Create a marketplace of opportunity, fueled by accurate data.
•  

Take Action—Book a Skills Masterclass

We’ve learned the hard way so you don’t have to. If you’re serious about future-proofing your workforce strategy, let us show you how to get it right.

👉 Book Your Masterclass Now

Transformation starts with the right data. Together, we can create a future where there’s Zero Wasted Potential—in your people, your business, and society.