Trillium Insights

Thoughts and Insights from Trillium's Practice Leaders

The Art and Science of Finding Talent

The Art and Science of Finding Talent

A few of our clients recently told us that they are dismayed at how similar the resumes that they are receiving from staffing firms look, and in many cases, the candidate’s skills do not match up with their resumes.

It is often hard to determine the depth of skill that a person has when they identify a specific tool or architecture that they have experience with from their resume.   Recruiting firms use several tools to verify a candidate’s technical competence.  However, most of these tools are focused on syntax and developmental skills.

To find the best talent in this tight job market, the tools and approaches that staffing firms use can dramatically impact their success.  As we pointed out in several previous blogs, Finding Human Capital Data and What’s the Big Deal Anyways, there is both an art and a science to the recruiting process.  There are ways to leverage technology to better understand and predict a candidate’s future success, but it is the combination of a candidate’s technical capabilities plus their ability to fit into a company’s culture that ultimately determine the best fit.

Potential versus Production

Potential versus Production

Watson seems to be all over the news lately. From tax preparation IBM Watson and H&R Block, to diagnosing cancer IBM Watson Fighting Cancer, IBM’s AI product seems to be having a resurgence.  I say resurgence because over five years ago Trillium managed projects that successfully integrated Watson into predictive analytic production workflows. This healthcare Trillium Success Story describes just such a project.

In five years, not much has changed, data-wise, for healthcare organizations. Most are still drowning in data and still challenged to gain reliable, actionable insights from this information. More than 80% of the data is unstructured and in the form of physician notes, test results such as x-rays, EKG and MRIs and other medical documents. All data sources that Watson can handle. So why aren’t there more stories of success and less of them about just the potential of AI?

What still makes implementation a challenge are the human factors. While there are the tool benches and API’s to take advantage of the power of Watson to relate data and utilize Natural Language Processing techniques, without the use of proven infrastructure planning and solid project management, implementations will remain beyond reach and articles will continue to be written merely about the potential of this technology to be a valuable business tool.

 

What’s the big deal anyway?

What’s the big deal anyway?

Some people believe resume, LinkedIn and Internet sourcing is so easy that sourcing is either dying or dead or can be performed for $6/hour. After all, resume and LinkedIn sourcing appears simple and easy on the surface, however – it is deceptively difficult and complex. Anyone can find candidates because all searches "work" as long as they are syntactically correct. That doesn’t mean the searches are finding all of the best candidates.


People make assumptions when creating searches. Every time an assumption is made, there is room for error and you unknowingly miss and/or eliminate results! After all, no single search can return all potentially qualified people. Every search both includes some qualified people and excludes some qualified people. Some of the best people have resumes or social profiles that may not appear to be obvious or strong matches to your needs. People cannot effectively be reduced to and represented by a text-based document. Job seekers are NOT professional resume or LinkedIn profile writers which means people don’t create their resumes and LinkedIn profiles thinking about how you will search for them.

Most people still believe shorter and more concise resumes and social profiles are still better which means they are removing data/info from their resumes which can no longer be searched for! No one mentions every skill or responsibility they’ve had, nor describes every environment in which they’ve ever worked. There are many ways of expressing the same skills and experience, and even employers often don’t use the same job titles for the same job functions.  Not to mention that sometimes people don’t even use correct terminology.

Finally, anyone easy for you to find is easy for other recruiters to find which means there is no competitive advantage!  The work I did gathering available data has really paid off in allowing me to truely understand how the data relates.  It is really powerful.

 

Finding some people is easy… finding the best people IS NOT!

Finding some people is easy… finding the best people IS NOT!

In addition to the individuals that recruiters find while searching a system for job candidates, there are people that could be a good fit, but aren't found because of the lack of a specific keyword in a text box or missing value from a dropdown. Clues to a great candidate are hidden in the freeform cover letters and text resumes that might get ignored.  I’m guessing that a rough estimate of this class of data would be at least 50% of each data source that is searched. Using the Natural Language Processing power of Watson streamlines the search process and eliminates the need to create difficult and complex Boolean searches that rely on heavily formated data.  By also including the "intelligent search and match capabilities" of Watson ensures that a recruiter will consider other qualified candidates that might otherwise have been missed.