Skip to main content


Showing posts from March, 2020

The Limitation of "Boolean" in Talent Sourcing

I did a search on LinkedIn for a “Java Software Engineer” in New York City. I entered that job title as a keyword (under Job Titles) and LinkedIn suggested that my talent pool was 2,059 candidates. Then I added a skill and my talent pool decreased to 1,956 candidates. When I added another skill, my pool increased. This is the nature of Boolean search. Every candidate that has at least one of the requirements is brought up in the search results. If you want the skills to be additive (X and Y), you need to write a compound Boolean search string rather than just adding the skills from the LinkedIn menu. I wanted to reduce my targeted talent pool and added “years of experience” range. The pool tanked. The same happened when I added “education requirements”. It was not clear what I should do at this point. I didn’t know what to change in my search in order to maximize my pool while maintaining the quality of the candidates in my search results. Was it a specific skill or the combin

The 5 Biggest Pains When Talent Sourcing. Learn why and how to avoid them.

Ouch, Crush, Bang, Ack, Urg - Talent Sourcing can be painful - even with  today's AI tools . “This platform gives me too few candidates without all of the skills. That list is full of people who just started at a new job and probably won’t move. This site only shows senior people for this mid-level job.  Bottom line, why do the available tools bring me so many irrelevant profiles?” As talent acquisition professionals, we know we lack  time . We are super busy searching, evaluating, scheduling, and mediating with candidates. On top of this, we have to manage the hiring managers: their requirements, changing minds, interview pipelines and more. There isn’t enough time, especially for us to do what we do best: using our unique perception skills as super-connectors to relate to and interview candidates. It is often surprising to step back and think that this general pain, lack of time, is often exacerbated by the technologies that are supposed to be making our lives easier. The

The Importance Of Evaluating AI Talent Sourcing Tools Now!

Gone are those days..... when job seekers marched into offices with a printed resume in hand, when candidates were hired after completing handwritten applications in a waiting room, and when HR departments had to rely on the country club Rolodex of an industry headhunter to fill high level positions. Here are the days... when recruiters use technology to make their lives easier and more efficient. .. Online applications, search engines, scheduling assistants, applicant tracking systems, and keyword searches have become a way of life for talent acquisition managers. So why is it still so hard to find the right candidates? and, Why do you have such little time to focus on what you do best? That is, forging human connections with talent in order to woo the best and the brightest to your company. The answer is that the tools that are common place today are antiquated and inefficient. " LinkedIn and other recruiting sites rely on  Boolean  search, incomplete and outdated user gene

Talent Acquisition VPs share their secrets of choosing and operating AI Sourcing Bots

You’re ready to evolve to recruiting 3.0 with AI technology, but how will you choose and operate your sourcing solutions? Savvy executives are looking to move into the future by using technology to streamline their team’s sourcing process, but there is a lot of “noise” in the marketplace. Parsing through false promises and clunky software is a process as important as recruiting the most coveted employee on your team. After all, the right AI technology will unleash the talent of your star recruiters to do what they do best: build connections with candidates and make right decisions. So, the question begs, how should a VP evaluate and implement an AI sourcing strategy? We spoke with over 100 successful VPs responsible for Talent Acquisitions to compile the following best practice methodology: Keep testing: AI has gained some bad rep as a result of false promises from companies with 1st generation AI logic. Don’t get discouraged. AI has improved significantly in recent years. Enter tr