Blog

At Vettd, we stand at the crossroads of technology and human expertise. We're constantly scanning the horizon, anticipating future needs and addressing them head-on. Our vision is one where Candidate IQ enables a transformative leap, igniting a new era in staffing, where efficiency, precision, and data-first decision-making are the norm.

As we navigate the dynamic landscape of the staffing industry, one thing remains clear - the enormous untapped potential that lies within our candidate databases. With each profile, a wealth of data resides, often going unnoticed or underutilized. But what if we could harness this data, transforming our decision-making process and amplifying the efficiency of our recruitment operations?

Today's recruitment landscape is ever-changing, with new roles emerging, old ones evolving, and the skills required for these roles in constant flux. This makes maintaining an up-to-date, organized, and efficient candidate database a challenge. Let's dive into how Candidate IQ can help you sustain these efficiencies and stay ahead in this dynamic recruitment environment.

One of the most untapped resources in the staffing and recruitment industry is the existing candidate database. Many staffing firms possess vast databases containing tens or even hundreds of thousands of candidate profiles. But despite this wealth of data, these databases are often underutilized, with recruiters preferring to look for fresh candidates on platforms like LinkedIn, Indeed, or Zip Recruiter.

A universal candidate schema can provide staffing agencies with a structured and standardized representation of candidate data, making talent management more effective and efficient. However, building a universal candidate schema in-house can be a daunting task for staffing agencies.

In today's rapidly evolving job market, skill identification and management have become increasingly crucial for businesses to stay competitive and agile. The right tech stack can make all the difference in effectively identifying, tracking, and managing organizational skills. In this blog, we will explore the best tech stack for skill identification and management, focusing on the key components that drive success in this critical area of workforce development.

In the world of mountain climbing, having a well-organized base camp is crucial to the success of any expedition. The same can be said for staffing agencies striving to reach the peak of staffing automation. Just as climbers need a strong foundation before ascending, agencies must have well-organized candidate data to fully harness the power of staffing automation. In this blog, we'll explore the importance of organized candidate data and how it can help your staffing agency reach new heights in automation, utilizing insights from Bullhorn.

As a partner supporting staffing agencies, we understand the persistent challenge of managing candidate data. The large volume of data, the dynamic nature of candidate profiles, and the need for integration with multiple systems are just a few of the obstacles that staffing agencies face. However, Vettd's Candidate Intelligence Platform provides the solution that can help staffing agencies to improve their recruitment processes and gain a competitive edge.

In the fast-paced world of staffing and recruitment, staffing executives are constantly seeking innovative ways to automate their processes and stay ahead of the competition. However, one critical aspect is often overlooked: the candidate schema. In this blog, we'll explore what a candidate schema is, why it's essential for building reliable staffing automation, and how it can revolutionize your agency's efficiency and effectiveness.

In today's staffing industry, candidate intelligence has become an essential tool for recruiters. However, what many recruiters fail to realize is that the effectiveness of candidate intelligence relies heavily on the quality of data being used.

The second pillar for the Data Innovation needed to support Advantage 2.0 is the creation of use-case specific Data Ecosystems.