Hiring or staffing is probably the most important function of any corporate entity as it directly feeds the lifeline of the enterprise – the people. Over time, we have seen technology change and immensely impact a lot of aspects of the way any enterprise thinks, works and optimizes resources to streamline execution. But strangely, hiring, which is the most important of all these functions has not seen any radical changes over a long time. AI is all set to change that sooner than you think.
Yes, we have had the odd database and workflow automation happening and being adopted, but nothing that compliments and improves this critical function. But this is all set to change in a very big way and AI or Artificial intelligence is going to bring in a much needed change that will change the way enterprises hire and retain talent.
Let us first look at how hiring happens today to understand why a change is needed and how AI will step in and make things better. When an organization is need of a human resource, a sourcing request is initiated and the HR department gets the request through the workflow. In the earlier days, newspapers were the preferred medium for getting the word out. Once the ad for the position was published, people responded to it and these were collated and processed. When the medium was print based, the responses were in the hundreds or maybe a thousand per opening. But with the advent of the internet and the arrival of job portals, these postings went online and the number of responses went up exponentially so where there used to be hundreds of responses, there are now easily thousands and thousands of responses.
This is further complicated by the fact that there are multiple portals and people sign in across portals and apply to multiple openings on all of them. The amount of incoming data that a recruiter now has to deal with is nothing short of a deluge. While dealing with this massive amount of data, the recruiters are then prone to rely on personal bias and discretion to sort through the applications and shortlist some of them for the next stage off hiring – The Interview.
The interview then is face-to-face or over a video conference. By definition, the interview is totally dependent on human discretion as a selection criteria. When people have to go through hundreds of candidates to select one or a few, there are things like fatigue and bias that come in. The sheer number of people being handled also makes the process of interview based grading very error prone, people tend to grade candidates or very hazy or patchy recollections of the interaction they had. Add to this the fact that there is no way to store, analyse and re-use the interview interaction for analytical and decision making purposes.
This brings in a lot of points of failure into the whole process. There are cases where a deserving, qualified and senior candidate is overlooked due to a gap in employment due to valid reasons, there might be cases where a candidate looks like a perfect fit but is actually a flight risk. The organization structure also adds some complexities to the equation. The hiring manager and the reporting manager may be two different people and the HR team will have a complicated communication matrix to manage in these type of cases and there might be a lag or delay in communication that might result in time and revenue costs for the company.
Now think of this improved and better scenario. There is a requirement of N resources for a new project and the request is entered into the system. The system is capable of analysing and understanding the requirement criteria at a granular level and translating it into actual search and match actions which are more than just a dictionary match. The system then looks into the internal bench with a fine contextual comb and identifies some resources that are readily available to be repurposed. There is also a hiring alert that is sent out to job boards both internal and external. If there are internal references and external matches that are available, the system is capable of analysing all sources of data in all formats and grading them in order of relevance and fit. The hiring manager and the initiator of the sourcing request are sent the relevant notifications. The stake-holders then shortlist the ones they want to interview. The system then schedules a meeting on a mutually agreed upon time slot and notifies all the parties involved. The system also goes one step ahead and actually records and analyses the actual interview.
Note here that the system we are talking about has the ability to add context and apply complex machine learning and cognitive logic to artefacts and data. Now the interview happens and post the meeting, the system then reads the data from various sources like social media and other online channels among others to come up with supporting data that can aid the final hire decision.
After that is done, the human stake-holders can take an informed decision. The system then continues to engage with the candidate who is now a hire and manages the performance analysis, job progression and other related data.
Now what a system like the one we discussed will do very well is to remove bias, fatigue and related issues from the important function of hiring. Additionally, the inclusion of context into the process adds immense value and improved ROI to the hiring process. The additional benefits of abstraction acting as a layer of security are also important to note.
So it is very clear that the next big wave of innovation and value addition to the hiring function is going to come from the AI stables. The addition of machine learning and context with the elimination of bias and reduction of errors, ROI will be better and the enterprise will be better served by the hiring function.
Before you start thinking that the system that we discussed above does not exist in reality and may come around only in the future, let me tell you that such a system exists and can actually start working for your enterprise. While there are a few players who are working on solutions like this, Bangalore based Spire Technologies is having a product called Spire TalentSHIP that does this and more. The solution has a mobile front end that makes all the above described steps and flow points relatively easy to implement and manage for all the stake holders.