by Kate Libbie | November 17, 2020 1:52 pm
In recent years, the market of Human Resource Software has been advancing at an exponential pace. It is an effective way to organize the search for candidates and reduce the time to perform routine tasks. However, a lot of Recruitment Software still struggles to deliver its designed capabilities. What prevents this type of software from being more robust and competitive on the market? In this article, we tried to find a reason.
A clear understanding of the purpose and ultimate value of recruitment software is the paramount key to developing software that hires well. For talent acquisition systems (ATS) or human resources management (HRM) software, this purpose is narrowly focused – to facilitate recruitment processes. For achieving this goal, the software can be composed of a variety of techniques that automate manual tasks.
From posting job positions, and reviewing hundreds of applications and CVs to sending offer letters, previously recruiters had to do much paperwork. Recruitment software, in turn, transforms old mechanisms of the search for needed specialists. Bringing all requirement tasks into one place, they leave staffing agencies to perform only those tasks, which requires human factors. All this saves time tremendously.
Recruiter software is an end-to-end hiring solution that should perform the following tasks:
Since we live in progressive times of cutting-edge technologies, it is impossible to develop competitive recruitment software without Artificial Intelligence (AI). Like for any other software, AI intelligently automates the manual tasks allowing us to do more with less. Thanks to machine learning algorithms, recruitment software can learn from past behavior and perform time-consuming, repetitive tasks such as screening resumes or scheduling interviews with candidates.
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There are several ways to use Artificial Intelligence for recruitment software. All of them are based on training machine learning algorithms, which is a solid base of AI. For this, you need to define what repetitive cases you plan to automate. Then, it is necessary to collect data on these cases and let ML-algorithms learn from them. The more data you provide, the more accurate results you will get. For instance, for accurate screening resumes, you need to analyze and extract insights from thousands of resumes for a specific role.
Another approach to involve AI in HR software is integrating chatbots into hiring processes. Just like in the previous case, for this, you need to find the most used scenarios and make the chatbot act according to it to provide real-time interaction to candidates. Apart from this, Recruitment automation with AI allows facilitating the performance of other tasks like posting job ads, candidate scoring and evaluation, and more. Besides, you can set AI-based recommendations systems, etc.
Given a large selection of recruitment software on the market, recruiters will probably choose those that work flawlessly and have no bugs. What are the bugs in the recruitment software? These would be even the most primitive errors with registration, bad performance, delays in sending offers, and more. One more negative case is when software works fine on one device but shows different scenarios on another. To prevent these and other mistakes in HR solutions, it is recommended to conduct these types of testing:
Neglecting software testing for recruitment projects, you risk to face bugs that will be too expensive to be fixed later after production.
To push recruitment software to the market may be a risky endeavor. But keeping in mind several factors, you have more chances to beat your competitors on the market and win customers’ hearts. These factors are: 1) Involving Artificial Intelligence to form recommendation systems, automating manual tasks, integrating chatbots for regular replies; 2) to care about recruitment software testing, and check it before release to avoid all possible bugs.
Source URL: https://blog.qatestlab.com/2020/11/17/recruitment-software/
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