Is your workforce prepared for digital transformation?

In just 10 years, the average lifespan for a company in the S&P 500 will be less than half as long as it was 50 years ago

In fact, 88 percent of the 1955 Fortune 500 already doesn’t exist.

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.

The irony is that with more people data available than ever — 90 percent of the data in the world was created since 2016 — almost every company still relies on mapping its talent manually, if at all.

These companies simply aren’t prepared to adapt their core workforce to constantly-evolving market conditions and business priorities.

In other words, their expiration date could be coming sooner than later.

As more data is generated, the HR industry has also become increasingly reliant on distilling people down to keywords, job titles, and numeric data. The market has felt the negative side-effects of this approach and is now trying to search for more innovative ways to maximize the value of their people data at scale.

A better way to handle people data overload is to empower your business analysts — those who know your business best — to create AI models that intelligently map people data connections to reveal insights within the context of your business. Making it easier and faster for your analysts to enlist the support of the AI models they create is essential to keeping up with transformation demands in our digital economy. When this AI relationship occurs, the value HR teams can provide to their organizations is unparalleled.

Truth 1 of 5. Download the ebook to learn all 5.

To learn more about how AI is helping modern HR and talent professionals adapt their organizations for the digital era, download our latest eBook, “The Future of AI in Five Truths.”

Free Ebook
Talent Classification Guide
for the AI Era of HR
Download Now
More Posts

You Might Also Like

Should you tag resumes manually?
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.
Oct 21, 2019
Vettd Team
4 Reasons Why Candidate Screening is Not a Human Task
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.
Oct 10, 2019
Vettd Team
Artificial Intelligence
How Talent Classification Works
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.
Sep 30, 2019
Vettd Team
Artificial Intelligence
The Transparency Problem with AI - Part 2
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).
Aug 28, 2019
Jeff Brennan
Artificial Intelligence
The Transparency Problem with AI
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?
Jul 22, 2019
Jeff Brennan
Artificial Intelligence
Unsupervised vs Supervised AI: Not all AI is created equal
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.
Jun 6, 2019
Vettd Team
Explore ALl Posts