Today, HR leaders are working in an
increasingly competitive environment and face the challenge of sourcing talented job
candidates with various skill sets on a global level. Fortunately, talent
acquisition strategies have come a long way with the rise of artificial
intelligence (AI) and other data-driven automation technologies for
communicating with potential new hires and determining if they will find success within an organization. However, according to CEB only 5 percent of
HR executives feel they are effective in using talent analytics due to inaccurate
or duplicate data and a lack of understanding of analytics. The statistic is
staggering, as data analytics can mean the difference between hiring managers
making a gut decision versus a fact-driven decision.
For example, at the beginning of the
hiring funnel, organizations such as Unilever and Walmart are
using AI to pre-qualify candidates based on their resumes and other digital
responses. They then connect them with HR professionals based on scoring
and keyword categorizations. Instead of scanning candidates’ resumes for
specific words, AI software uses algorithms to analyze large data sets and
match, score and rank job candidates.
Additionally, AI is helping determine
specific skill sets that are important to an organization as well as a predicted view
into how an applicant will perform once they join a company. By constructing "identity
profiles" for candidates, AI can help predict if an individual will be a good
match for their position and within the company’s culture. This is critical, as
27 percent of employers said a bad hire has cost them more than $50,000,
according to a CareerBuilder survey.
Other companies are using a CRM-like
approach to seek out candidates and nurture them until a good fit for a
position exists. This can help foster relationships between an employer and job
seeker until a job opening arises.
Both AI and CRM approaches
illustrate that the new world of recruiting demands accurate data
regarding both candidates and open positions in order to create a good
match in an efficient manner. While a candidate might apply for multiple
positions, the HR team can leverage data-driven solutions to cleanse, consolidate,
interpret, analyze, and assess key information into a single view and ensure a
unified engagement approach based on scoring and readiness rankings for each
possible role.
The common denominator for all HR emerging
technologies is consistent, clean data and its availability in real time. When
recruiters are examining both structured (online job application) and
unstructured data (LinkedIn profile, Twitter, published articles), they need to
assimilate that information into a population of potential candidates and guarantee
they are only reviewing each candidate once. The accuracy of data is important
for ensuring that various sources about one candidate are associated with that
individual. For example, data referring to an applicant applying as James
Jones, who is also known as Jim Jones, should be linked to the same job
candidate.
Clean data drives better decision
making and can help improve recruiting metrics, but in order for organizations
to make the most of this data, various HR technologies and recruiting systems
need to be connected and rigor applied to data business processes. Also, data
from each technology should be accessible in one central location with a single
view. Otherwise, without this visibility across platforms companies could be
missing out on qualified candidates and wasting millions in lost time and
resources.
Artificial intelligence, and other
emerging technologies, can offer important insight into success of a particular
job candidate and their potential rate of success with an organization. With
insights based on real time data, HR leaders will become better equipped to
make informed recruiting decisions.
Julia Mench is senior vice president of global HCM solutions at BackOffice
Associates, a provider of information governance and data stewardship solutions
for customers worldwide.