Leveraging Talent Analytics Today: How It Matters
November 08, 2022
Pretty much every recruiter has at some point asked themselves the question — how can our company hire better? The challenge of attracting and keeping the top industry talent is one that companies everywhere face, especially in an uncertain post-COVID world.
The answer to it is both straightforward and highly profound — talent analytics. A company that invests in talent analytics and implements strategies based on it can benefit from some of the best and most loyal teams of employees.
Here, we offer you a quick guide to leveraging talent analytics in ways in which it can benefit your company. Let us begin:
Simply put, talent analytics is a data-based approach to people management. It employs sophisticated analytical techniques to solve challenges related to recruitment, team leadership, collaboration, recruitment, promotion, and so on.
It allows managers to make systematic, scientific decisions about their team rather than using their gut instincts. This enables the formation and retention of a skilled, motivated team where everyone is doing the role they are best suited for.
Talent management analytics might sound like something new-age, but it has, in fact, been around for a long time. Other terms by which it goes in the industry include workforce analytics, human resource analytics, people analytics, and human capital analytics.
Earlier, it was only significant for big companies like Google or Microsoft that hired thousands of people globally and needed to find the best way to engage them.
However, today, companies of all sizes recognize the importance of proper hiring to ensure optimal business results. As such, even a startup with four or five team members needs to think about how they can utilize analytics in talent acquisition.
If the word “talent analytics” is unfamiliar to you, think about Moneyball, the iconic film starring Brad Pitt, based on the real-life story of how Billy Beane and Peter Brand introduced sabermetrics to the process of recruiting players for baseball teams.
It involves using empirical analysis statistics to measure a player’s in-game activity and thus predict their performance in future games. Sabermetrics was a significant change from the earlier convention of scouting and gut instinct to pick players and was, in fact, laughed at when people first heard of it.
However, now every Major League team uses it to fill their teams. This is a classic example of how going by the numbers is a reliable way to pick the best people who will shine in one project and continue to shine in subsequent projects. It gets you optimum results while ensuring that everyone is doing what they are best at.
Talent analytics can be classified into three broad components:
This involves studying hiring metrics such as cost per hire and time to fill each new position to make the recruitment process more efficient.
By understanding in numerical terms how well the company is attracting and retaining top talent, hiring costs can be brought down, and better hires can be drawn based on data, not subjective preference.
A big part of this is automated resume screening, a type of software that delivers insights to the recruiter about a candidate’s skills and aptitudes based on the resume they have uploaded. This is faster and more accurate than manual scanning.
This involves obtaining real-time insights about the current workforce from ongoing feedback data. It gives the talent manager quick insights into how well teams are performing and who the outstanding contributors are and suggestions on where employees who are not doing as well might flourish better. This allows managers to put the right talent in the right places and accurately identify where talent gaps exist.
This combines the data and insights from hiring analytics and ongoing feedback analytics to help a company design robust processes that enable maximum productivity and people retention. It covers multiple aspects, including the nature of the hiring process, feedback mechanisms, performance evaluations, and training requirements.
Getting the top management on board with investing in talent acquisition analytics can be challenging, especially if they are used to a more subjective way of doing things or simply doubt the financial benefit of the investment.
The best way of convincing them is by demonstrating examples of companies that have seen significant benefits from talent management analytics. Some prominent ones include:
One of the iconic entertainment brands of Las Vegas and Atlantic City had long been seeing promising results with data analytics for its client base and decided to try the same technique with its employees.
Analytics helped them understand what optimal working conditions would look like and how many employees would need to be stationed at each of their service points.
Perhaps most significantly, data analytics gave the brand better insight into how well its health and wellness programs were working, as a result of which preventive care checkups at their in-house clinics have gone up, and urgent care costs to the tune of millions of dollars have been avoided.
The famous shoe retailer conducted some studies to determine the link between employee engagement and financial performance. Their studies determined that there was an optimum team size for performance and that how long a store manager stayed at a particular store could indicate performance quite accurately.
Accordingly, Clarks implemented a strategy that placed top performers at each of their retail outlets and launched engagement ‘toolkits’ to improve motivation and performance.
The computer hardware giant recognized that performance reviews are only as effective as the people on the receiving end. Accordingly, before rolling out a proposed change, the company asked for feedback via the internal social network.
Based on the responses, one specific portion of the new idea was dropped. The use of talent analytics enabled this to happen in real-time before the actual rollout.
They already send out employee feedback services twice a year, but recently they shared an open-ended survey with a subset of their workforce for real-time feedback. This helped identify pain points and rectify them early, rather than waiting for the next semi-annual review.
Eschewing conventional resume requirements that prefer candidates with excellent academic records, Google and AT&T decided to follow data that demonstrated that candidates who can take the initiative would make for the strongest hires. This helped to boost employee performance and reduce attrition rates.
The advantages to investing in talent management analytics and benefitting from objective data may seem obvious, but a surprising number of companies are reluctant to go ahead with it.
Much of it is a general suspicion of anything new that could potentially displace human jobs, but there are more concrete grounds for uncertainty for some. In most cases, the challenges to winning top management over include:
The best talent analytics platforms on the market will undoubtedly cost a fair amount, which could dissuade many from taking the step. This is particularly likely in legacy organizations that do not use too many tools in general or companies that have previously invested in software that did not deliver the promised results.
Even if managers agree in theory about the importance of talent acquisition analytics, they may not be comfortable figuring the ropes out in practice. This largely revolves around not knowing how to decide upon and keep track of suitable metrics.
Many top managers may be accustomed to doing things independently based on their instincts and decision-making abilities. When they cannot ‘see’ what is going on in the software’s mind, the notion of a software presenting decisions is unpalatable.
The impact that talent analytics can have on hiring and retaining the best employees is phenomenal. The cost of a bad hire can be immense, as can the cost of a dissatisfied workforce.
Any objections that top managers may have to invest in analytics can be countered by the overwhelming benefits that the investment will offer, including:
Talent management analytics programs can rapidly examine the candidate’s background as shared through resumes and compare it against the specific skill requirements for the job to shortlist the most suitable ones.
By automatically keeping track of metrics like the cost to hire or time to hire, the analytics platform frees up managers to focus on broader business requirements.
Talent analytics enables the collection of real-time insights on what skills employees currently have, what they need to fulfill their roles, and whether they would be better off in other roles, including leadership. This can also be used in a predictive fashion to determine how to attract and hone future talent.
Analytically finding talent gives access to critical insights on what prospective and current employees need to be suitably empowered. For instance, feedback may reveal that certain stages in the recruitment process were not well-received or that current employees desire particular types of training opportunities.
Talent acquisition analytics gives clear insights into how much the workforce is being paid versus what the output is and thus helps identify whether there are any patterns in overtime or irregularities in payroll. This ensures that the workforce is put to productive and profitable use.
Talent analytics can provide granular reports, all the way down to the individual employee versus their team or their role expectations. This gives the employee clear visibility on what they need to do to improve.
Multiple times, it has been demonstrated that diverse teams are more creative, more agile, and more productive. Talent management analytics can assess teams for diversity based on agreed-upon diversity metrics (race, gender, age, background, or others), thus providing necessary information for diverse hiring initiatives.
Talent analytics allows hiring decisions based on demonstrable skills and numerical predictions of how a candidate will do on the job, rather than the interviewer’s personal impression of them. This goes a long way in removing unconscious bias from recruitment.
For those new to talent analytics, getting started can certainly seem daunting. That is why we have laid out a quick roadmap for you to get started:
If you are transitioning out of a system driven by gut instinct, moving away from that thought process and creating a culture of using data is essential. This means having sufficient knowledge of data analysis. Organize training programs for your HR team and host open discussions on how best to incorporate data into decision-making.
Not every metric may require immediate attention. Choose areas you would like as the focal point of your talent analytics initiative, such as lowering the attrition rate or adding talent to a specific department.
Based on the current employee data you have, build an ideal candidate persona that covers aspects such as what skills and background they have, what languages they can communicate in, what values they possess, and their long-term career motivations.
Once you have a persona in mind, tailor your online communications and profiles to appeal to that candidate. If you are looking for more diversity, for instance, ensure that your language is sufficiently inclusive.
Talent management analytics data only works if the overarching HR infrastructure can support it. Work with the IT team to ensure that you have the right HR technology in place for the entire employee lifecycle.
This is a simple way to ease into talent management analytics and one that will immediately save you a lot of time. AI-based resume screening tools can quickly scan resumes to filter out candidates with the most desirable skills and traits, letting you focus on just them.
This is an ideal way to get a data-based picture of a candidate’s true abilities and reduce bias. Examples include aptitude tests, situational judgment tests, personality, culture fit tests, and programming tests.
Using a tool like Adaface, you can screen the best talent and ensure a scalable, efficient, and quick hiring process that reduces your time to hire by up to 80%.
At the end of the day, one must acknowledge that employees are people, not names on a list. There is, of course, a human component to every interaction, be it recruitment or performance evaluation, and managers need to take that into account when making their decisions.
What talent analytics does is offer concrete data points on which to base those decisions, rather than relying simply on gut instinct or “what has been done before.”
This removes ambiguity from the process and demonstrates to employees that they are being hired on merit and potential and nothing else.
For companies of any size, therefore, the best thing talent managers can do is to employ reliable data — as delivered by talent analytics solutions — in making decisions for the betterment of their team.
Asavari is an EiR at Adaface. She has made it her mission to help recruiters deploy candidate-friendly skill tests instead of trick-question based tests. When taking a break, she obsesses over art.