Trillium Insights

Thoughts and Insights from Trillium's Practice Leaders

Finding Human Capital Data

Finding Human Capital Data

Unlike the skills needed in finding the answers to trivia questions, when it comes to finding and identifying qualified and talented people based on their resumes and social media profiles and updates, the information is often incomplete, and in many cases, critical bits of identifying data are simply not present. For example, how do you find someone with "Spring MVC" experience when many people don’t mention it on their resume, nor on LinkedIn, Twitter, blogs, etc.?

There is an entire world of Human Capital Data in LinkedIn – direct keyword, title, and even concept/relational search methods, used by humans or algorithms, that can only retrieve results based on existing text. Quite simply – if the text isn’t there to be retrieved or analyzed, a semantic search/NLP algorithm can’t do anything with it. There is much more to high-level sourcing than keyword and title search/match. Good recruiters really do “read between the lines” of both the job description and requirements as well as the human capital data they are searching for and analyzing.


There have been semantic solutions on the market for quite some time that can do keyword, title and concept matching reasonably well (as well as some that claim to, but don’t). The issue with those solutions that no one seems to (or wants to) realize is that they have limitations – they find some matches, exclude some, and bury others. The real question is who, how, and why are some matches found and ranked highly, while others are excluded, and others ranked lowly but actually represent the best talent?

Likability Matters More

Likability Matters More

I was debriefing with a client recently to understand their thought process for choosing a Project Manager to lead one of their strategic initiatives, and my takeaway was a reminder that "People do business with people they like".

The consultant we presented for the role was imminently qualified.  She has managed over two dozen implementations like the one our client was looking to have managed.  Our consultant has all of the skills and competence to enable our client to address the time sensitive implementation.  During the client interview, our consultant identified risk areas and missing artifacts in the current project and how she could get the project back on track, which emphasized her skills and abilities to do the role.

In my debrief, the client acknowledged that our consultant had better skills and had more experience than the consultant that they ultimately chose, but they felt that the other candidate had a “can do” attitude and focused on how to achieve success.  Relying on your skills will only get you so far.  Culture and likability are key to closing your next opportunity.

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.