Data Quality in Recruitment: An Industry Perspective with Fabian Heyse, Co-founder of daidalo

The recruitment industry is awash with data, yet agencies often struggle to unlock its true value. We sat down with Fabian Heyse, co-founder of daidalo, to discuss the real challenges of leveraging candidate databases, the pitfalls of automation without solid foundations, and how agencies can future-proof their operations. ———————————- Company Spotlight: daidalo Founded: 2024 Headquarters: Ghent, Belgium Active in BeNeLux, soon UK Focus: daidalo updates and completes candidate data, so recruitment agencies can make placements faster using their existing network. Key Benefits: always clean and up-to-date data, faster placements, less dependency on external sourcing platforms, no manual data updates ———————————-

What pain point led you to start daidalo?

Fabian Heyse, co-founder daidalo: We wanted to build a software company but didn’t have a clear idea at first. Through consultancy assignments in data and AI, we landed in the recruitment sector. We quickly saw that, although there’s a huge amount of data, much of it is outdated or incomplete. This makes genuinely data-driven recruitment nearly impossible.

Why do agencies so often look outside their own databases, and what’s the real barrier to using internal data better?

Fabian: Recruitment involves thousands of candidates, each needing to be coded correctly in the ATS. It’s a time-consuming process, and the sector moves fast -often, the fastest wins. There’s rarely enough time to keep all fields updated. Even when data is entered, people’s careers and skills change rapidly, so the information becomes outdated. This leads to incomplete records and little trust in the data, so recruiters turn to external platforms like LinkedIn, which offer up-to-date information but not a real competitive advantage. Unless data quality is addressed, this dependency will remain.

What are the risks of automating processes when the data isn’t right?

Fabian: Everyone is looking at automation and AI to speed things up, but if the underlying data is poor, automation just accelerates existing problems. Sending irrelevant job offers damages your brand and frustrates candidates. Automation and AI only add value if the data foundations are solid. Bullhorn’s January Grid Report found that 36% of agency owners see poor data quality as the main barrier to extracting value from automation. I fully agree.

How does daidalo address this challenge?

Fabian: We don’t offer a new platform or interface. We work in the background of existing ATS systems, leaving the recruiter’s workflow unchanged. Our focus is on making sure the data is up-to-date and enriched (E.g. location, categories, specialities, skills). We scan candidate profiles for missing or outdated information, using sources like CVs, meeting notes, emails, and public LinkedIn data. It’s fully automated, so recruiters see immediate improvements and can make more placements from their own ATS.

How do you ensure data privacy and compliance?

Fabian: We never source private phone numbers or emails from dubious origins. Any contact details we find come directly from the candidate’s CV or meeting notes. Personal data stays in the client’s system; we just structure it for better usability. We don’t store data ourselves. For LinkedIn, we only use public information; name, employer, location. It’s fully compliant and more than enough for our process.

Can you share a client success story that illustrates the impact of better data? What KPIs should agencies track to measure this?

Fabian: One client recently made their first placement entirely from their ATS, without using LinkedIn. Previously, they’d shortlist in LinkedIn, only to find some candidates were already in their database. With well-classified skills and complete fields, they filtered for relevant candidates, sent targeted emails, and quickly secured interviews and a successful placement. This speed is impossible with cold outreach. The key KPIs are time to hire - comparing placements from the ATS versus external sources - and the proportion of placements from the ATS. After improving data quality, these numbers should rise significantly.

How is the recruitment sector evolving, especially with AI and automation?

Fabian: Many agencies claim a personal approach, but with so many tasks, true personalisation at scale is hard. Technology will automate non-value-adding tasks like data enrichment, CV formatting, and lead generation. The human element will remain vital, especially for senior roles. Automation can handle volume, but personal relationships and networks will continue to set agencies apart.

Where are you focusing geographically, and how do you see the competitive landscape?

Fabian: We’re focused on Benelux for now. There are similar products in the US and Israel, which confirms the problem is real. Staying local lets us build strong client relationships and learn from the market. We plan to expand to the UK and, eventually, the US, but only after achieving critical mass and product-market fit at home.

What advice would you give to agencies hesitant about adopting automation or AI?

Fabian: Just get started, tools will only improve. Early adoption helps you understand where they fit in your business. But remember, the impact of automation and AI depends on having solid data foundations. Without quality data, you’re just accelerating chaos. Focus on building those foundations first. ———————————- BeNeLux Recruitment Agencies: The State of ATS Databases

• Estimated number of recruitment agencies: 5,000+
• Average ATS candidate database size: 20.000+
• Percentage of placements from ATS (average): 20–40%
• Industry research suggests that up to 70% of placements could come from an agency’s ATS if the data is well maintained. (Source: Bullhorn Grid Report, 2024)

———————————- This conversation with Fabian Heyse highlights the critical importance of data quality in recruitment. While technology and automation offer exciting possibilities, their value depends on robust, well-maintained data. Agencies that invest in their own databases - rather than relying solely on external platforms - stand to gain in speed, efficiency, and competitive advantage. As the sector evolves, the agencies that blend technology with human expertise will be best positioned for long-term success.

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