How many startups and corporations do you know that take a data-driven approach to hack growth or build products? The answer is likely to be “plenty.” How many of these organisations use data to boost their hiring process? The answer is likely “not many.”
Data utilisation technology has disrupted product, marketing, sales and every other department to collect, interpret and distil information and make better decisions. Yet, it still hasn’t touched talent acquisition. At least not up to its potential. Organisations still depend on interviews and resume to recruit employees, rather than harnessing data and automation.
Hiring Data: Untapped Goldmine To Make Better Decisions
Oftentimes, talent acquisition is based on gut feelings rather than facts, which is not an ideal scenario, especially given that so much valuable data is available. Data that can act as guideposts to evaluate whether a potential candidate will turn out to be a quality hire or not. This is where data utilisation technologies come into play.
How Do Data Utilisation Technology Help in Hiring?
They use tangible metrics and statistics to support hiring decisions, right from shortlisting candidates to onboarding them. The approach goes beyond using data to make the process more efficient and into measuring how well a candidate will fit a role.
It’s why recruiting teams that use data are more productive, objective, and operate with lower costs. One scenario where data-backed hiring lends efficiency is tracking the email back and forth between the recruitment team and candidates. Then pinpointing stages where the process can be sped up.
Data utilisation technology can also reveal hiring problems and benchmark the process. For instance, by reviewing the conversion rate of the application form, recruits can analyse if they need to alter the question or, even, completely redesign it. Another hiring issue that data-driven recruiting can bring to the surface is diversity and inclusion and if the organisation is unknowingly practising it.
A real example of data improving talent acquisition is IBM. The tech giant applied artificial intelligence to the occupational data of 40 million employees, from applications to managers, to identify the best personality trait in salespeople. Using keywords and phrases, they concluded that persistence is the aptitude necessary for salespeople.
Let’s unpack how data utilisation technologies can further boost hiring processes.
1. From gut-based evaluations to a better quality of hire
If the process used is traditional, intuition and luck play a significant role in hiring the right talent. It is not only competence that determines whether a person lands the job but also confidence and charisma, which is why many new hires turn out to be ineffective or, worse, fail at their roles, leading to weak teams. For this reason, quality of hire (QoH) has become a crucial KPI for companies of all sizes, as it measures the value a new employee brings to the organisation’s table.
To measure the quality of hire, teams need to track the complete employee lifecycle. However, the current process is siloed. There is a break between talent acquisition and employee performance. Since the feedback loop is incomplete, there is no reliable data. Recruiting teams cannot judge if the skills and traits they are assessing lead to high-performing and effective employees or not.
According to a survey by LinkedIn, 40-45% of companies keep QoH as a priority because it tells them if the employee will be productive at their tasks, improve their work, and consequently contribute to the long-term success of the business.
To measure the quality of hire, teams need to track the complete employee lifecycle. However, the current process is siloed. There is a break between talent acquisition and employee performance. Since the feedback loop is incomplete, there is no reliable data. Recruiting teams cannot judge if the skills and traits they are assessing lead to high-performing and effective employees or not.
Data utilisation technologies help connect those dots by breaking information silos and digging deep into the right metrics. Some of the data they track includes turnovers and resignations, characteristics of top talent, the performance of hire and what was the lead source, etc.
For example, Xerox used data to detect candidate behaviour to reduce attrition in its call centre by 20%. By tracking performance and using test data, the company identified that the probability of retaining “creative” people was higher than that of “inquisitive” or “empathetic” people. Xerox could also determine that the proximity of the workplace and residence played a major role in attrition.
2. Match-making potentials with top performers
One of the best ways to boost hiring outcomes is to juxtapose candidates with the top talent in that particular position in the organisation. This necessitates collecting and evaluating data such as:
- Matching the candidate’s skills with top talent
- Contrasting the candidate’s previous accomplishments or work with that of top talent
- Capturing the tenure, engagement, and performance ratings of the top talent.
This data can be manually gathered and measured, but it takes time and resources that teams can barely afford. On the other hand, data utilisation technologies that use advanced artificial intelligence and machine learning can do it automatically and in a fraction of the time. They use the data to filter actionable insights, such as what skills or experience to look for in future candidates. Furthermore, such a tech solution can compare each applicant to the best employee to find better fits.
3. Fine balancing recruiting capacity
Talent acquisition walks a tightrope. Over-hire and it becomes a financial cost. Under-hire and it becomes a productivity cost. Data utilisation technologies can factor in the current state of the organisation by tapping into real-time and consolidated data. Combining this with forecasts based on historical data on hiring success, turnover, and internal team movements, tech can enable recruiting teams to make hiring plans that exactly mirror the needs of the company.
Data-driven recruitment planning has the added advantage of spending wisely. Since technologies use people analytics, they get an HD image of the spend, which gives a better understanding if they are not effectively using the recruitment budget. Teams can compare the costs of activities to make economical decisions. One example is tracking different hiring sources and determining which one brings in the most qualified candidates. Then allocating more budget towards it.
Data utilisation technologies can factor in the current state of the organisation by tapping into real-time and consolidated data. Combining this with forecasts based on historical data on hiring success, turnover, and internal team movements, tech can enable recruiting teams to make hiring plans that exactly mirror the needs of the company.
The Future Of Data In Hiring
Building the right teams is a science. So, shouldn’t choosing the talent for the team be one, too? It’s this thought that has evolved the hiring process and given organisations the impetus to adopt AI in recruitment.
Currently, only a small number of recruitment teams rely on AI and other data utilisation technologies to increase efficiencies, conveniences, and productivity. But as geographical boundaries disappear with remote working and employer branding gets more emphasis, more organisations will embrace Big Data and automation in hiring. Not only to help find the right people for the right position and improve job satisfaction but also to completely disrupt the way talent is acquired and retained.
