Organizations are increasingly relying on data and analytics to inform criticalÂ talent decisions.
By Marta Chmielowicz
Necessity breeds innovation, and as the COVID-19Â pandemic disrupted the business world, companiesÂ responded with new ways of working. AccordingÂ to Mercerâs Global Talent Trends 2020-2021 report,Â executives met the challenges of 2020 by doublingÂ down on strategic partnerships (40%), usingÂ more variable talent pools (39%), and investing inÂ automation (34%).
Data science has become a critical element of theÂ talent strategy, with organizations leveragingÂ analytics, artificial intelligence (AI), and machineÂ learning to enable decision-making. In fact, 61% ofÂ executives say that of any current talent trends, usingÂ talent analytics has delivered the biggest impact toÂ their business.
COVID-19 drove a data explosion, with companiesÂ collecting data on remote working, location, andÂ health. The Mercer research shows that HR hasÂ quadrupled its use of predictive analytics from 10%Â in 2016 to 39% last year. Now, the challenge is usingÂ that data to inform forward-looking insightsâand HRÂ leaders seem to be stepping up, with more than halfÂ reporting that they are able to answer executivesâ topÂ talent questions, up from a third in 2019.
However, the way that companies are relying onÂ analytics is changing. Before the pandemic, HR wasÂ making headway on operationally-oriented analytics,Â such as data related to recruitment, selection, orÂ identifying flight risks. These have become less of aÂ priority, with employers instead choosing to focus onÂ strategic analytics that inform foundational decisionsÂ around workforce management, such as the relianceÂ on homegrown talent versus hiring from outside.
The fastest-growing analytics include:
- finding pay equities by gender and race/ethnicityÂ (52%);
- identifying why one team is performing well andÂ another is struggling (52%);
- learning how total rewards programs are beingÂ utilized by employees (46%);
- leveraging data to better manage healthcare spendÂ (41%); and
- correcting inequities and preventing them fromÂ reemerging (12%).
Organizations are also harnessing workforce scienceÂ for hiring, identifying high potentials, and makingÂ promotion decisions. Technical skills assessments areÂ the most prevalent (98%), followed by situationalÂ judgment tests (75%), role play-based assessmentsÂ (73%), and realistic job previews with digitalÂ personas (72%). In general, organizations tend toÂ use psychometric tests for external hires, cultureÂ assessments for internal promotions, and technicalÂ assessments to identify high potentials. However, manyÂ continue to rely on experience (87%), interviews (75%),Â and education (63%) to hire talent, with only 27%Â using online assessments and only 11% using onlineÂ simulations.
With the increase in volume and types of dataÂ collected comes a greater responsibility to useÂ data safely. To date, more than a quarter (29%) ofÂ organizations have revised their policies on accessÂ to employee data and developed ethical practiceÂ guidelines. Organizations are also taking care toÂ ensure that their AI solutions donât perpetuateÂ inequities, with 69% reporting confidence in theirÂ ability to intervene when technologies find unethicalÂ patterns and 67% feeling confident that they canÂ ensure their AI technology doesnât institutionalize bias.
As organizations combine business data with humanÂ intuition to identify and solve business problems,Â they will need to update guidelines and assessmentsÂ to ensure their technologies are delivering fair andÂ equitable outcomes.