3 New Patent Filings: Location-Based Talent Tools to Help You Navigate the ‘Now Normal’ of Remote Work

Wednesday, June 17, 2020

Remote work will be the most significant business shift to come out of the COVID-19 pandemic. After successfully undertaking the “world’s largest work-from-home experiment,” many employers are realizing the benefits of remote flexibility – lower travel, real estate, and salary costs, greater workforce scalability, employee retention, and more.

Many organizations – especially in tech – have fundamentally transformed their workforce management approaches as a result. Facebook expects 50% of its workforce to be remote in the long term, and plans to make salary adjustments based on the new cost of living for remote employees. Twitter went so far as to announce a permanent work-from-home option.

But as the workforce fundamentally changes, not all professional jobs are ready for it. Some jobs still require high levels of team collaboration and onsite work. With work-from-home the “now normal,” and millions of employees awaiting word on what’s next, how do employers quickly and effectively decide which jobs and employees go where? And how do they ensure they get the best talent pool, at the lowest possible cost?

Getting smart about going back to work.

Workforce Logiq is strategically expanding its predictive analytics portfolio to help clients navigate this new world of work and make data-driven talent location and remote work decisions. Our new IQ Location OptimizerSM solution, which includes three patent-pending algorithms, will recommend:

  • The best places to source and staff talent, given the job description and other employer-specific requirements. The suggestions from the Geo-Selection EngineSM will be 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.
  • Whether open positions 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 will consider the employer’s corporate culture, role requirements, and industry and similar role benchmarks.
  • The level of collaboration typically required for a similar type role based on insights from the Role Collaboration IndexSM.

For employers, predictive, actionable insights are critical for navigating one of the most uncertain labor markets we have ever seen. To build and sustain talent pipeline, organizations need to quickly decide who they hire for a given role, at what cost, and how — whether in a contingent, part-time, or full-time capacity, and whether through suppliers or direct sourcing. Employers also need to decide on where they staff talent, whether in the office or in a remote arrangement.

Of course, these decisions must be made against a backdrop of pandemic-driven financial uncertainty – where revenues and profits can shift overnight. Our new tool is designed to help employers understand how location decisions impact talent quality and costs — before they make an offer.

Optimized recommendations for faster, cost-effective workforce decisions.

Let’s say you need to hire a data engineer, and typically hire out of your home city of San Francisco, or the New York area, given both are hubs for tech talent. The algorithms show you, however, that Columbus, Ohio has a strong supply of high-quality data engineers, and given it is a less competitive market, the cost of talent is 25% lower. The AI will also predict that candidates in Columbus will be more likely to engage, which will cut down on recruiting costs and speed the hiring cycle.

After vetting candidates in the Columbus market, you find the best, most qualified engineer for the job. The algorithms will also show that based on the job requirements, this particular role requires a lower level of collaboration than other engineering jobs and would be best staffed fully remotely. Beyond the lower salary cost, you also would not have to pay for the candidate’s relocation, commuting, office space, or travel expenses.

Before you make the final hiring decision, you can project how much staffing the role in San Francisco vs. New York vs. Columbus would cost, and the quality of talent you would attract with each option. These are the types of strategic and forward-looking insights that give organizations a competitive advantage and enable workforce management leaders to create value.

Now is the time to refine remote workforce strategies.

According to a new survey from The Conference Board, 83% of organizations expect an increase in the number of full-time professional and office workers that work remotely at least three days a week. Before the global health crisis, three-quarters indicated less than 10% of their employees worked primarily from home.

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

Learn more about today’s “now normal” and how we’re helping employers navigate the shift to a remote workforce in our new video.


Christy Petrosso (Whitehead), Chief Data Scientist and Talent Economist

Christy Petrosso (Whitehead) is our Chief Data Scientist and Talent Economist, leading the strategy and design of our predictive AI algorithms and machine learning models.  Christy joined our leadership team in October 2019 with the acquisition of ENGAGE Talent. Christy holds a PhD in Economics from Clemson University and has focused her career on employment and labor economics. Her previous experiences include key data science roles with PeopleMatter (acquired by Snag A Job) and Equifax. Christy is a frequent speaker in HR Analytics and machine learning conferences. She is also an active member of the Federal Reserve Roundtable.

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