The evolution of recruitment strategy is an interesting process. What started with newspaper ads and bulletin boards, later became online job boards and advertisements. However, more than two decades after the 1990s, the recruitment industry realized that there has been a lot of data archived from the recruitment procedure when done online.
This big data can be used to a company’s advantage with the help of new technologies that allow users to analyze big data and bring out useful information from it.
There are limitations to using data for recruitment needs. Data of candidates from CV and early experience is mostly very subjective as it is about a person’s character and them fitting into the company culture. Hence, using data to analyze this might not turn out to be as effective. You need to figure out a way to do both to optimize your results.
How do you switch to a data-driven recruitment strategy?
The most important factor in creating a data-driven hiring process is maintaining records. A detailed list of activities during an interview, which includes the process flow, the leads and executives at each stage, the number of positions to be filled, total number of candidates sourced, screened and interviewed to fill the positions. The following process can be automated using an applicant tracking system (ATS). The market offers multiple variants of AI-driven ATS that helps deriving conclusions and better aligning our hiring process. The AI-driven approach helps in understanding the flaw in the procedure and helps you make corrections.
For the implementation of the ATS, you require complete data. Incomplete data will not let you take proper recruitment decisions as the decisions will be made by only partially analyzing the candidate data. After this is done, you can engage in data analytics which will ideally make your recruitment process far easier and optimum.
It is very important to have scorecards. The standardized scoring mechanism and review system makes the process more complicated to follow and makes the activity more person dependent over process dependent. To retrieve data from the vaguely created notes and points is a purposeless task.
Steps to create a scorecard:
- Create very specific features and skills the candidate will be tested
- Describe this feature and what character comes under it
- Each of this feature should be given a particular percentage of weightage
Giving points to characteristic traits can be a very effective way to make intangible features tangible. A detailed description of what each feature entails will make sure that bias and subjective rating is avoided.
Measure hiring speed
Identify the time taken by each candidate in each of your interview stages. You can create a pattern out of it, showing you which stage takes the least time and what makes the most amount of time. This data can be of immense help as identifying the most time-consuming step allows you to work on that particular step to speed up the whole interview process.
Determine the value of each candidate sourcing channel
The quality of your sourced candidate can be found by using the same data provided by other channels. Measure the number and quality of candidates provided by each of the different channels to get the overall quality of the candidate you picked.
If you want to gather comparable data or any data for that matter, your interviews need to be structured. Without the structuring of data, it is almost impossible to generate usable data. Here, the goal is to have comparable data so that every candidate can be compared and before the final stages of the interview, the recruiter will have an idea of who will perform the best.
Here are a few steps that can be implemented to create structured interviews.
Define the traits you want in the candidate:
Identify 5 or 6 traits that describe an ideal candidate fit for the job you are looking to fill. This is more personality traits rather than the technical skills needed to do the job. It can be characteristics like being a fast learner, good decision making, good team player, and more. Make sure these traits are independent of each other.
How to measure:
Create questions and answers for it to analyze these traits. Decide what answer gives 5 points, which gives a 3 and so on. Also, decide what total score a candidate has to get in order to bag the job. Also, implement a minimum threshold to clear for each trait.
Make sure the traits your mention is detailed. The order in which you ask the questions should be predefined and stick to it. Apart from this, make detailed notes for future references.
Feedback within 24 hours of the interview is ideal. This can be hard to achieve if there are a lot of people you have to get back to, but only so much can be remembered after 24 hours of an interview. Hence, the sooner you write the feedback, the better detailed it will be including all aspects there is.
After you have figured out who gets through the required score of bagging the job, waste no time. Offer them the job immediately even if it is one of the first people you interview. The candidate you interview might have other interviews and other offers pending so the more you delay, the more the chance they will find someplace else.
To check if all these worked, you can simply compare your recruitment data with that of performance data to see if the characteristics of high performing ones do align with the ones you chose. Incorporate an ATS that has an Artificial Intelligence and Machine Learning enabled into this same format and you will have a much easier time recruiting individuals and generally take your recruitment process to the next level.