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In what seemed like an instant, the COVID-19 pandemic sent the U.S. job market crashing, and with that, record-low unemployment numbers shot to unbelievable highs.

It has become an employers’ market.

Even so, the forces weighing on companies have multiplied, making hiring and maintaining appropriate workforces more of a challenge. The unpredictability of COVID-19 is forcing companies to adopt new tactics and strategies to manage their workers, whether they are contingent or permanent. Companies must now negotiate new safety issues, worker uncertainty, a greater need to control costs, and locating and managing mostly remote workers.

There is no way to know what the “new normal” will look like once the pandemic has subsided. So how can companies find ways to adapt to meet such unpredictable, rapidly changing workforce needs while finding success in this atmosphere?

Adopting technology powered by artificial intelligence (AI) offers employers data-driven answers to many of these questions. Before COVID-19, the available AI solutions tended to be used for talent acquisition and retention — if they were used at all. Now, some AI applications provide data that can be used to determine everything from how to hire (remote, near remote or onsite) to which workers will likely leave.

The power of AI and data

Companies are finding that a remote, or mostly remote, workforce can actually give them more flexibility. Without the need to engage local workers, organizations are finding talent in previously untapped markets and at more competitive costs. Remote workforces can also be scaled up and down faster in response to changing demands.

Solutions powered by AI allow users to stop being reactive and become predictive, looking at current and future states to make optimal workforce planning decisions. And solutions providers like Workforce Logiq are making the investments to bring these tools to market. In 2019, Workforce Logiq acquired ENGAGE Talent, bringing the predictive analytics and artificial intelligence software company’s AI capabilities in-house.

With its own staff of data scientists, talent economists and business intelligence experts, the global workforce solutions provider offers proprietary workflows and tools capable of incorporating hundreds of millions of data points so users can address questions of recruiting, retention and management. Data insights are gleaned from internal and external sources, allowing for broader comparisons to competitor data and market data. And data-powered decisions can mean better hiring and retention outcomes.

Predicting the workforce future

Procurement and HR teams often have different but connected workforce management functions, and they are facing tough situations. No one has a clear idea of what the next few months or years will look like. These fluctuating circumstances raise many questions around:

  • Adding or removing staff
  • Hiring contingent or permanent workers
  • Timing of hires and rehires
  • Best worker location based on need (remote, near remote or onsite)
  • Geography of workers
  • Hours estimated to complete projects
  • Skill levels
  • Diversity and inclusion

AI-based solutions can parse out the underlying components of a project, offering what Workforce Logiq calls Total Talent Intelligence.

Relying on those same millions of data points, users can uncover answers surrounding time, cost savings, compliance and many other factors affecting hiring decisions. This actionable intelligence isn’t to be confused with “total talent management,” a concept that has yet to manifest in any realistic way from a single solution provider. The Total Talent Intelligence approach applies data-science-driven decision making to the total workforce lifecycle. From talent discovery and recruiting through engagement and retention, that data helps companies remove uncertainty and strategically accommodate evolving workforce needs.

The current situation for remote workers can be especially fraught. Workers may be scared, frustrated and reticent in the current job market. They may not feel secure at their present jobs, but not confident of prospects. Through Workforce Logiq’s AI tools, companies gain a competitive edge. They can identify and recruit workers who are more likely to make a career change based on assigned individual and company employment volatility scores.

While being able to analyze and contextualize data at those levels sounds like the plot of a science-fiction movie, it is available now. Workforce Logiq’s patent-pending predictive recruiting and retention algorithms, including its IQ Location Optimizer, can judge the sentiment of companies and workers, matching highly interested prospects with organizations looking for their specific skill sets. The tool can also recommend where the position should be located and track the retention risk of that worker over the tenure of the engagement.

The IQ Location Optimizer can run algorithms to generate recommendations that help users make faster, sharper recruiting decisions as quickly as the environment is changing. Workforce decisions can be more data-driven and based on where the deepest pool of relevant talent is located. It can also determine which passive candidates are most likely to be open to an unsolicited recruiter call. That means faster time-to-fill with quality, cost-competitive workers.

In a recent Spend Matters article, the technology was reviewed and found to have distinct advantages. Recruiters and hiring managers “can begin with a job requisition and game out the options for where a specific role could be sourced. … It also ‘recommends’ the best options based on job requirements, salary/rate, cost of physical location, commutability and other factors.”

Harvard Business Review, in its 2019 research, looked at the potential of “using big data and machine-learning algorithms to develop a turnover propensity index for individuals — a real-time indicator of who is likely thinking about quitting.” Over a three-month period, individuals identified as “most likely” to be receptive to new job opportunities were twice as receptive to unsolicited recruitment messages and 63% more likely to change jobs, as compared to those who were predicted “unlikely” to be receptive.

Using publicly available data and Workforce Logiq’s technology, the researchers wanted to find out if big data and AI can accurately predict a person’s chances of leaving a job. They investigated two common reasons people quit a job: major change events like a new CEO or acquisition and little connection to their organization. After working with about 2,000 participants, their research showed that by “using big data, firms can track indicators of turnover propensity and identify employees who may be at an elevated risk of leaving the organization.”

Diversity and inclusion

In response to heightened market and customer demands, Workforce Logiq is developing AI technology to help users improve their diversity and inclusion performance. In the past, workforce management diversity matters often focused on supplier diversity, but now companies can directly address talent diversity.

The Workforce Logiq AI tool IQ Talent Diversity assesses where a company can improve its diversity (i.e., by geographic location, skill set, job level, etc.), looking at elements like race, gender and ethnicity. To create a more diverse workforce, each company can look at its overall employee base, then compare themselves against peers within their industry and by geography. Simply having the tools to more clearly understand their situations can lead to positive change. Real-time predictive insights help create recruiting pipelines that include under-represented groups, giving organizations the ability to improve their diversity and inclusion efforts.

In the next installment in the series, Spend Matters will talk with William T. Rolack Sr., Workforce Logiq’s Vice President of Diversity and Inclusion, to discover real-world examples of how an expert advisory managed service provider, AI-powered tools, and predictive analytics drive real diversity and inclusion benefits.

This Brand Studio post was written with Workforce Logiq.



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