A unique matching algorithm enables a process that both identifies and creates relationships between elements from two or more sets of data. Unique matching algorithms are used to find an optimal pairing between certain elements according to search settings. What makes a unique matching algorithm different is that it looks for only one matching pair. As the technology matures, it will affect HR functions in various ways.
You’ve Been Using Algorithms the Whole Time
We are already applying matching algorithms in everyday life. For instance, question-answer apps and user-item shopping platforms take your search terms and link them to data that has been tagged accordingly.
Plus, if you are involved in learning and development, you may have used a platform such as Growthspace. It relies on an expert matching algorithm to connect workplace course elements to relevant training experts, with the final choice of coach, mentor, and trainer left up to the L&D team.Â
But sometimes, only one result is desirable for certain types of research. Unique matching algorithms come into play in situations such as:
- Data refinement – eliminating repeated and redundant records in a database
- Biometrics – identifying unique patterns or characteristics in biometric data in applications that include fingerprinting, iris scans, and facial recognition
- Preference matching – also known as the stable marriage problem, algorithms can be used to link a set of priorities to parameters (for instance, if someone wants a job that has X, Y, and Z, an algorithm can boil all the possibilities down to one selection)
The Benefits of Unique Matching Algorithms for HR Teams
Preference matching in particular has opened the door for numerous human resource applications based on algorithms. Especially in large companies, sifting through massive amounts of data is time-consuming. And, when you need to make HR-type decisions for thousands of employees, a unique matching algorithm enables all kinds of choices to be reduced to a single answer.
Another advantage of leveraging algorithms is that it tends to eliminate human error and bias. Overworked HR staff might not catch some of the important details that go into making certain decisions, but the technology won’t. In addition, during these days of DEIB programs, even unconscious bias is under scrutiny. Unique matching algorithms lend a form of credibility to any HR process that could be influenced by the human aspect of the activity.
However, no process is ever perfect. Even when the computer does its job, it still requires the input of people. So, if an employee doesn’t like a talent development program because they end up disliking the commitment, the overall situation is still problematic. But, perhaps ironically, such mismatches can be solved by quick HR intervention that puts the employee back on the correct path.
HR-Specific Uses for Unique Matching Algorithms
Here are a few of the emerging uses of unique matching algorithms for HR professionals:
Resume Screening
When a company receives a large number of resumes for a position, a matching algorithm can be used to automate the initial screening process. The algorithm scans the resumes for specific keywords, qualifications, and relevant experience. It also filters out resumes that do not meet the predetermined criteria. This saves time and effort for HR professionals who would otherwise have to manually review each resume. Note that this is also an application used in workforce analytics processes.
Job Matching
When employers have job openings, they can utilize matching algorithms to compare the qualifications, skills, experience, and preferences of job applicants to the requirements of the job. The algorithm analyzes the data provided by both parties and identifies the best possible matches. This helps employers narrow down their candidate pool and focus on those individuals who are most likely to succeed in the role.
Tools
Matching algorithms can be implemented through HR tools, such as applicant tracking systems (ATS), job boards, or online recruitment platforms. These algorithms improve the overall candidate experience by ensuring that applicants are considered fairly and efficiently.
Team Building
Matching algorithms can aid in assembling effective and diverse teams within an organization. By considering factors such as skills, personality traits, work styles, and team dynamics, the algorithm can recommend optimal team compositions that enhance collaboration, productivity, and overall performance.
Skill Matching
Matching algorithms can be leveraged to match employees with suitable training programs, development opportunities, or internal job openings within an organization. By analyzing employee skills, performance data, career development program features, and organizational needs, the algorithm can suggest the most appropriate opportunities for growth and advancement.
Growthspace Is already There
The ultimate effect of AI and unique matching algorithms on HR employees and activities is unknown. But what is known are the capabilities that Growthspace provides to human resource and L&D teams around the world today.
Growthspace’s algorithm has proven itself as a tool that can match employees looking for personalized talent development and experts with top credentials. Through a comprehensive taxonomy but simple interface, HR staffers can search for coaches, mentors, and trainers to deliver highly granular skills. So if you are looking forward to the benefits of matching algorithms for L&D initiatives, the future is already here.
