Recruiting and hiring quality employees is one of the most important functions of a businesses.
Whether because of expansion or turnover, an unexpected job opening can lead hiring managers to act hastily, and make costly mistakes. This is why more and more companies are using talent analytics to help make otherwise difficult decisions.
When people make decisions under pressure, they often choose the easiest and fastest option at the expense of the best option. This is not because they want to make bad decisions, it’s simply that in the haste to meet an immediate need, it’s more convenient to rely on instinct, rather than data-driven, strategic consideration of all potential outcomes.
Finding the first person who can do the job and hiring them for the role is more likely to result in disappointment (for both parties) than taking the time to find the best candidate.
For hiring managers working on the front lines - who contend with high volumes of applicants - it’s hard to have any significant impact on quality of hire using the traditional intuition and instinct approach to the talent selection process. The complexity of the sourcing process often prevents them from focusing on the organization's larger strategic talent acquisition initiatives. Additionally, non-data-driven talent selection processes only result in employees that meet or exceed the expectations of the hiring manager around half of the time. Imagine being disappointed in fully half of your workforce!
These are hardly the results that most companies are looking for.
Incorporating Data in HR Management Decisions
Applying advanced analytics to HR management decisions solves the problem of guesswork by using thousands of data points, gathered through statistically predictive assessments, to determine whether or not your candidate is the right fit for a company.
In fact, the number of companies that implemented data-driven projects increased by 125% in 2015, and for good reason. When big data is used to assess talent, the workplace becomes more efficient.
Data Analytics in Action: Increased Customer Satisfaction
In spaces like telecommunications, the ability to form a bond with customers is essential in fostering satisfaction and ultimately, loyalty. And as most businesses know, one bad interaction can lead to the loss of not only a customer, but potentially disappointing reviews about the company, which can be hard to recover from.
Customer satisfaction is a leading indicator of consumers’ likelihood to repurchase a product or service and remain loyal to a company. Without representatives capable of fostering good customer relationships, the business suffers.
One telecommunications organization that worked with FurstPerson struggled to connect effectively with customers.
Through a combination of consultation and data science, a customized pre-hire assessment solution was designed that identified applicants capable of being persuasive, performing the technical aspects of the job well, and creating an emotional bond with customers. Instead of using the traditional process, pre-hire assessments allowed the company to identify top talent quickly during the hiring process.
Through the power of data analytics, the organization experienced a positive impact on customer satisfaction, and the shift carried over to other important customer outcomes.
The implementation of pre-hire assessments resulted in:
- 36% higher performance
- 31% reduction in 90-day attrition
- 25% better training scores
- 29% higher technical scores
- 8% higher quality scores
Hiring analytics helps employers to figure out what makes an employee thrive in a role and identify candidates based on specific criteria – even down to very human aspects of the job, like persuasion and relationship-building.
Relying on data to streamline the hiring process and optimize a workforce makes good sense to business leaders and investors operating in a technologically-advanced, results-oriented world.
This doesn’t necessarily there’s no room for the human element of hiring. It means those in leadership can shift more of their time, resources, and focus to where they are best-suited: achieving the company’s workforce vision, direction, and strategy. The algorithms used in data analytics are all about minimizing the labor of human thought. And when it comes to hiring on a massive scale, there are few places where this is more appreciated.
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