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Hitting refresh: The importance of decluttering recruiting data

Staffing Stream

Hitting refresh: The importance of decluttering recruiting data

Don Tomlinson
| January 22, 2025
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“It’s like drinking from a firehose.” At this point, anyone working in staffing has run across this well-worn metaphor, usually about the deluge of candidate profiles crossing their desks every day. The rise of candidate-side AI application tools and the shrinking labor market have led to a drastic influx of job seekers. A recent study by Fortune found that job postings in 2024 saw a 31% increase in responses compared to 2023’s data.

This influx of data has created challenges for staffing professionals. Aside from choosing the ideal candidate from increasingly large talent pools, staffing teams must grapple with the tasks of storing, cataloging and parsing this flood of applicant data. Most staffing teams rely on multiple sources of applicants for the same position, and not all platforms offer the same levels of integration with their ATS. Manually transferring applicant data from various sources, like job boards and LinkedIn, introduces a significant risk of human error into the data ecosystem. These errors can compound over time, leading to inconsistencies and inaccuracies that undermine the efficiency of staffing operations. AI applications offer solutions, but their output is only as reliable as the data they work with. Without rigorous data management processes, AI-powered ATS tools may cause more problems than they solve.

Generative AI’s rapid adoption and its promised cost savings have led to pressure from leadership to implement these tools quickly. However, this rush to adopt AI often overlooks the foundational need for clean data. Without clean, reliable data, AI tools can deliver inaccurate results and exacerbate existing biases. Clean data — data that’s accurate, consistent, complete and well structured — is essential for actionable insights. For example, data should be recorded in consistent formats, free from errors and aligned with its intended use. Dirty data wreaks havoc, costing companies a staggering 12% of overall revenue, or approximately $3.1 trillion annually, according to Forbes contributor Falon Fatemi. This translates to wasted budgets and lost opportunities.

Even structured and organized data degrades over time, making it difficult to build and maintain accurate candidate profiles. HR Daily Advisor has reported that 40% of email users change their address every two years, underscoring the need for continuous maintenance. By streamlining data entry processes and focusing on collecting only necessary information such as skills, experience and qualifications, staffing teams can reduce errors and maintain consistency. Additionally, periodic purges, deduplication and updates ensure that talent acquisition teams and their AI tools operate with the most reliable and actionable data.

If this sounds like a never-ending process, that’s because it is. Data hygiene is a continuous, mission-critical function for staffing teams using AI tools. By implementing strict data hygiene processes — either manually or with tools — staffing teams can significantly enhance their operations. These tools automate data transfer, detect duplicates and ensure consistent and reliable information within ATS or CRM systems, providing a strong foundation for AI-driven insights.

As a staffing firm, your value lies in your candidate database — it’s the backbone of your operations. Clean data allows staffing teams to efficiently find qualified candidates through accurate keyword searches, skills matching and targeted sourcing campaigns. It ensures timely communication and improves candidate experiences while streamlining hiring processes to reduce time to hire and enhance talent analytics. 

Although AI is an important part of any staffing firm’s toolset, it relies on clean data to work effectively. As databases grow, keeping candidate data organized and current becomes increasingly challenging. But, by implementing rigorous data hygiene practices, firms can ensure stronger analytics, better hiring decisions and, ultimately, better hires — which is a win for everyone involved in the recruitment process.