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In the fast-paced world of staffing, understanding and managing the skills of candidates and the evolving needs of clients is crucial to the success of a staffing agency. A key aspect of effective skill management is recognizing the importance of context and temporality. In this blog, we will discuss why considering the context of a candidate's skills and acknowledging that both candidate experiences and client needs change over time is essential for efficient skill management in staffing agencies.

Skill management is a critical component of staffing success. However, challenges like evolving candidate skills, changing client needs, and the complexities surrounding skill definitions can make skill management a daunting task. In this blog, we will explore how candidate intelligence powered by Candidate IQ can help staffing agencies overcome these challenges and optimize their operations.

Staffing agencies often face technology challenges when managing and analyzing skill data effectively. This article will provide practical examples of technology challenges in targeted skill management and how Candidate IQ offers solutions to overcome these obstacles.

How candidate intelligence can improve the talent acquisition process for staffing agencies by automating candidate matching and providing better quality data for recruiters.

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.

Staffing agencies are tasked with finding the best talent for their clients, but the traditional approach of manually sifting through resumes and applications can be time-consuming and ineffective.

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.

As the staffing industry continues to evolve rapidly, it is more important than ever for staffing agencies to leverage technology and talent to stay ahead of the competition. In 2022, the staffing industry grew by 11%, and many firms were able to make the most of the opportunities presented to them.

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.

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.

As staffing databases continue to evolve, staffing executives must also address the challenges posed by both human and automated behaviors in managing and maintaining these databases. In this follow-up article, we'll explore some of the key challenges and share examples of how to overcome them to optimize your staffing automation processes.

In this article, we'll explore why your current ATS may not be providing the support necessary for candidate schema management and how embracing AI-driven solutions can make a significant difference in your staffing automation efforts.‍

The third pillar of Data Innovation needed to support Advantage 2.0 is Data-First applications. They take advantage of use-case specific Data Ecosystems and are different from the function-first applications we are used to and that are common in every business.

In recent years, staffing agencies have been facing increasing pressure to deliver results faster and more efficiently. One solution that has emerged as a game-changer is automation.

Achieving diversity and inclusion goals can be challenging for staffing agencies that are responsible for filling job openings with qualified candidates. That's where candidate intelligence solutions can help.

In today’s competitive job market, candidate experience has become a critical factor for both job seekers and staffing agencies.

When it comes to staffing agencies, one of the biggest challenges is identifying the right candidates for a job. While traditional semantic search can help narrow down the talent pool, it often fails to prioritize candidates with similar experiences and qualifications.

Candidate intelligence is a term that has been gaining traction in the staffing industry over the past few years. Simply put, it refers to the ability to extract meaningful insights from candidate data to improve the recruitment process. But what does that actually mean, and how does it work?

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

The main technology enabler for Data Innovation that’s needed to deliver Advantage 2.0 is the effective harnessing of AI.

Gain advantage from your data vs. talk about it by understanding the 3 pillars necessary to realize consistent innovation with data. Data innovation has been wildly successful, and frequently highlighted as a key focus for competitive advantage. In many businesses, however, it is still more of a “buzz word” discussion than a meaningful driver of strategic and operating value.

The first pillar for the Data Innovation needed to support Advantage 2.0 is the culture of the Data-Driven Enterprise.

Data Innovation is not a new concept but has not become mainstream in the corporate world. Using your data to innovate isn’t business-as-usual because the three pillars of Data Innovation are rarely embraced by enterprises, and artificial intelligence is just coming out of the lab. The pillars are:

Vettd and Icalia Labs have entered into a strategic partnership that will help bring cutting-edge, custom Data Innovation solutions to life.

In this piece, I am going to explore how companies can use AI to analyze and optimize their board composition. I was inspired to write this piece by the events at GE, which has recently announced that it will slash its dividend by 50%.

The use of Artificial intelligence (AI) in important decision-making areas continues to grow and includes such important decisions as: loan-worthiness, emergency response, medical diagnosis, job candidate selection, parole determination, criminal punishment, and educator performance. But, a critical question keeps coming up in these areas, how are the decisions being made?

Transparency in data privacy involves openness; being willing to share with users all aspects of usages of their personal data. This includes an openness on what is being collected, why it is being collected, how it is being analyzed, and how the decisions being made by AI algorithms were decided (what output parameters drove the decisions made by the AI algorithms).

Vettd.ai college interns are gaining a unique perspective about the difference between classroom learning and real-world experience. They are being challenged to use open-source and low-cost software components to create prototype applications to compliment or compete with alternative approaches to natural language processing (NLP) solutions.

But how can you figure out which functions within your business can actually be transformed by AI? What are the quality limitations? How can you evaluate which business service companies are using AI effectively while others could be selling hyped up linear algebra? The best way to know if an AI product is right for your business is by asking the right questions.

Vettd, the leader in deep learning for Human Capital Management, launches new eBook for enterprise HR leaders

In the era of digital transformation, having the right people in the right places will make or break your organization. If you can bring together data about your people and your business and map talent to the needs of your organization, you’ll better understand how to stay ahead of your competition.

Humans will always play a critical role in the hiring process, but the consistency vs efficiency challenge exemplifies why reviewing resumes is a task better suited for modern machines than modern humans.

Job seekers and employers have access to almost any information they want these days. This raises a few important questions. Is more data truly useful? Does more information directly correlate to better jobs, better employees, and better matches? How will we measure the impact that big data has on hiring in the future?

The staffing industry is continuously evolving, with agencies seeking innovative solutions to optimize their processes and stay ahead of the competition. To help staffing agencies harness the power of artificial intelligence, we are excited to introduce Candidate IQ™, a cutting-edge AI-driven platform designed to revolutionize your staffing operations and enhance your agency's performance.

In the fast-paced staffing industry, business analysts need innovative solutions to stay ahead of the competition. That's why we're excited to introduce CandidateGPT™, a powerful AI-powered language model designed to augment the Candidate IQ experience, specifically for business analysts managing candidate databases.

We’re seeing more and more about how algorithms and machine learning are being applied behind the scenes in our digital lives. These techniques are being applied to tools used in the HR industry to the point that they are becoming old hat. So what’s next? Machine discovery.

Any job seeker or talent acquisition professional will tell you about the challenges in the digital candidate experience. On one side, exasperated candidates blanket job websites with resumes and cover letters.

No matter what industry you’re in, nearly every organization is becoming an information technology company due to the massive amount of data being gathered about their customers and workforce.

We had the privilege of being the topic of conversation in a new post from William Frierson at College Recruiter.

Talent classification is a simple concept to grasp but can be a difficult practice to adopt without the right tools. We refer to talent classification as the process of categorizing human capital according to shared qualities or characteristics. This process helps you recognize, differentiate, and understand the talent you have at your disposal. Decision-making in talent acquisition and strategic workforce planning becomes much more straightforward with this level of insight.

Higher education institutions understand the importance of maintaining strong connections with their alumni. A well-managed alumni network can contribute significantly to an institution's growth, funding, and reputation. Managing and leveraging alumni data, however, can be a complex and time-consuming task. That's where Alumni IQ™ comes in. By harnessing the power of AI-driven intelligence, Alumni IQ™ is set to revolutionize alumni management, helping higher education institutions unlock the full potential of their alumni networks.

With the completion of every merger or acquisition, the electronic ink is barely dry for the Chief of Human Resources and their staff before they are called upon to integrate 500, or 2,500 or maybe 25,000 new employees into the new entity. This is a daunting task that's part art (aka experience + luck) and part science (aka …if only there was some).

For over 20 years, I’ve been perplexed by the inability of the M&A process to properly capture, recognize and sort out all the people that are involved in the integration of two companies.

The college and university admissions process has plenty of room for improvement based on experiences of two Vettd interns who spent the summer gathering data for a large project. In this blog, the interns suggest several ways to make the admissions process more user friendly.

As part of the candidate screening process, some organizations task their recruiters with manual tagging of the resumes they review. The idea here is to increase the usability of talent databases by generating metadata manually.

In the December 7th issue of First Analysis Quarterly Insights, managing director Corey Greendale concludes that there’s a significant information gap that makes it difficult for organizations to optimize internal talent mobility.

Reviewing resumes can be the hardest and most demanding part of the entire hiring process. It’s extremely time consuming and is the first of many steps in a lengthy process. Unfortunately, it’s entirely necessary because job boards aren’t dead yet and resumes remain the primary way that candidates present themselves to companies.

You've probably read about how AI is being used in data security, financial trading, healthcare, fraud detection, or elsewhere. AI has taken hold in these industries, in part, because there is “big data” associated with each and ready-made AI solutions. But, what about the industries or use cases that don’t involve mountains of numerical data?

The manager’s dilemma: Hiring is the most important thing you’ll do, but has the least predictable outcome.