According to Gartner, “quiet hiring is when an organization acquires new skills without actually hiring new full-time employees.”
Sometimes, organizations will bring on short-term contractors for this work, but it usually means more responsibilities beyond their current roles. In other words, it is an opportunity to upskill/reskill. It’s up to the organization to structure this as an opportunity for internal mobility.
Of course, this is not new and has been happening for decades. Nonetheless, a new workplace model is rising from this: the Skills-based Internal Marketplace Model. In order for this model to work, there has to be a “marriage” of behavioral science and data science, with all stakeholders who are buying in. There’s a methodology behind this, and it will disrupt the existing HR structure.
So, leadership, employees, and administrators must be on the same page, and this data needs to be structured and shared appropriately.
What is a skills-based model?
The most basic definition of a skills-based hiring model is that it’s an approach that screens for specific competencies. Skills-based hiring applies to existing employees, as well as candidates, and goes far beyond majors and what’s on someone’s resume.
It focuses on the employee/candidate’s soft and hard skills applicable to what the position actually requires. Skilled-based hiring is a very dynamic process and can completely change the way organizations and individuals see each other. People have a lot of potential, and this model allows the organization (and individual) to have a qualitative and quantitative system in place to not only, in many cases, predict performance but also to outline a career path.
There’s a lack of line of sight between talent management systems, decision-making, and critical organizational outcomes, such as organizational performance and improved operational effectiveness. Existing HR systems (job boards, applicant tracking systems, recruitment process outsourcing/recruiting agencies) look for keywords on an application/resume and can’t go beyond that basic descriptive data.
Resumes can be unreliable due to the common practice of embellishment. Don’t worry, employees and candidates – this doesn’t mean you’re bad! You are great at some things, just not everything!
These systems and methodologies have been around for decades and often have an adverse effect on both candidate and employee experiences. The emerging combination of soft and hard skills and how to qualify and quantify is the future and will replace these existing systems.
The Impact (on organizations and individuals):
Many candidates are rejected due to this keyword match model. Another issue is internal, where the hire may have been a mistake, but there’s no data on why or how to fix it (lack of correlation/causation data). Furthermore, there is also no data on how to reskill/upskill existing employees over time, which would create a culture of talent mobility within the organization.
This leads to considerable strain on management and the entire team. Workplace morale will deteriorate over time, and this is where the employer brand deteriorates. We see this manifest first in turnover but also in long interview processes and poor candidate/employee experience.
There is another issue: high costs caused by, for example, the purchase of many independent (often unnecessary) technologies and the purchase of assessments lacking scientific foundations. It is worth noting that often these costs are “hidden” in the form of having to get employees up to speed on systems they don’t want to adopt (e.g., lack of buy-in, Campion and Campion, 2021), reductions in employee and leadership morale, or producing new hires that were the wrong choice. These costs can also be evident in the form of litigation from those who should have been hired (Cappelli & Holmes, 2019).
The Resolution / Solution:
Organizations usually don’t have quantifiable data that can be predictive and prescriptive on existing employees, much less candidates. First, this has to be created internally, and it has to be an “All-In” approach. Second, there has to be a documented approach to “data trust,” where this information is shared transparently and used ethically. Once you have the skills library in place, a system to process and report this data, and an all-in internal process, you will dramatically improve time to hire, productivity and retention, internal talent mobility, and overall employer brand.
Our technology uses advanced ML/NLP to create a skills-based internal talent marketplace for each organization, combining team culture/work style/performance review (soft skills) data with hard skills data to show skills transferability and correlation for each individual and in each opportunity. This creates a constantly evolving intelligent model that gives the entire team predictive and prescriptive insights.
Outcomes are plentiful, including:
10%+ net revenue increase.
- Effective team optimization/workforce change management.
- Reduced costs for talent management processes.
- Shorter times for hiring and internal human capital change.
- Aligned and connected talent management practices and human capital decision-making.
- Increased retention rates for talent.
- Hire internal/external talent that can “hit the ground running.”
- Upskilling/reskilling of employees and leaders.
Brandon Stevens, founder and CEO of AI talent management platform, Scoutr, has over 20 years of experience in sales, sales management, business development, business analytics, and recruiting. At Scoutr, we have combined the worlds of Data Science and Behavior Science. Quiet Hiring and ‘The Great Stay’ are two of the most common workplace trends as we head into 2024. Due to the economic times, many employees are starting to stay versus trying to go elsewhere, which has also led to the quiet hiring trend. For more information on workplace trends, check out: www.scoutr.com.