Navigate the “Now Normal” of Remote Work with Data Science

Categories
AI Buyers COVID-19 data science staffing WFH

Predictive data science. Predictive analytics. Predictive AI. You’ve probably seen or heard these terms used, but aren’t quite sure how they might apply to the industry or to the role you’re trying to fill right now. Well, here’s what predictive AI can do for you.

Say you’re hiring a software engineer. Typically, you hire out of the San Francisco tech hub for this type of role, but is that really the best option? With predictive data science, the job description can be automatically parsed and analyzed, and you may see that this particular position is benchmarked as requiring low collaboration vs. other engineering jobs and could be staffed fully remotely. In real time, your data science insights prioritizes Columbus, Ohio, as a target market given its strong supply of high-quality data engineers.

As a less competitive market, the cost of talent is also 25% lower. Beyond the lower salary cost, you would not have to pay for the candidate’s relocation, commuting, office space, or travel expenses. Predictive AI can also highlight that candidates in Columbus will be more likely open to new job opportunities, cutting down on recruiting costs and speeding up the hiring cycle.

WFH Experiment. I’m writing from my house in Charleston, SC.  No surprise given we’re still in the “world’s largest work-from-home experiment.”  But my team’s “experiment” in remote work has actually been going on for years — my colleagues work from home in San Francisco, Minneapolis, San Antonio, Jacksonville and Orlando.

Like our company has experienced, many organizations are realizing the benefits of remote flexibility – lower travel, office, and salary costs, greater workforce scalability, employee retention, and more.

Organizations – especially in tech – have fundamentally transformed their workforce management approaches as a result. Facebook expects 50% of its workforce to be remote and plans to make salary adjustments based on location-specific cost of living. Twitter went so far as to announce a permanent work-from-home option.

But, as the workforce fundamentally changes, not all jobs are ready; some still require high levels of collaboration and onsite work. And, some organizations will just want to go back to their pre-pandemic status.  Regardless, with work-from-home the “now normal,” and employees awaiting word on what’s next, how can employers effectively decide which jobs and employees go where as they get back to work?  How can they ensure they get the best talent pool at the lowest possible cost?

Predictive data science. These are the types of questions best answered via predictive data science.  That’s why we asked our internal data science team to leverage our proprietary database of 100 million professional profiles to create talent location optimization algorithms.  What does this mean? It’s  giving hiring managers access to skill-specific global benchmarks to make better, faster, and less costly hiring decisions for their unique job postings.  Our data science team did just that by developing three new patent-pending workflows to identify:

  • The level of collaboration typically required for a similar type role based on insights from the Role Collaboration IndexSM.
  • Whether an open position would be best staffed onsite, near remote (with commuting access to an existing office location), or in a fully remote arrangement. The Remote Role RecommenderSM considers the employer’s corporate culture, role requirements, and industry and similar role benchmarks.
  • The best places to source and staff talent, given the job description and other employer-specific requirements. Suggestions from the Geo-Selection EngineSM are based on market-specific talent supply and demand gaps, salary profiles, a candidate’s willingness to engage with the company, local commuting patterns, and more.

PREMIUM CONTENT: Staffing and Workforce Solutions Mergers and Acquisitions

Competitive Advantages. Using this data science enables hiring managers to understand how their talent location decisions impact quality and costs before an offer is made.  These are the types of strategic and forward-looking insights that give organizations a competitive advantage and enable workforce management leaders to plan effectively and create value for their organizations using data science.

Even as some organizations transition employees back to the office, there’s a clear shift to remote work, and employers need to be ready. Predictive workforce management can help make data-driven decisions that expand the talent pool, drive cost savings, and successfully navigate evolving market dynamics.

For a tongue-and-cheek look at our response to helping hiring managers locate the best talent in the “now normal” of remote work, check out our new video.  I assure you, it’s the only workforce management video that features Batman, Robin and Batgirl!