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Artificial Intelligence

How is Artificial Intelligence Helping Companies Identify Talent Hotspots

The COVID-19 pandemic allowed many organizations to rethink their office location strategy and where they want to hire. Talent became a new and critical variable for office location. Location decision indeed impacts the location of the majority of your workforce.

However, the decision is typically driven by financial factors like real estate, costs, corporate taxes, or government incentives. Talent location and other considerations take a back seat.

As many enterprises are expecting to retain a hybrid workforce model permanently, location strategy will consider access to top talent and variables affecting employee experience in addition to the traditional real estate and tax considerations.

Workforce planning must bring talent into the conversation, providing granular talent intelligence that leaders can add to the equation as the organization sets its location strategy. The talent-first strategy will drive long-term business resilience and competitive advantage.

Benefits of a Talent-first Location Strategy

Workforce planning can capture these three key benefits when embedding location intelligence into talent strategy.

1. Diversity – Location decisions could hamper or boost Diversity and Inclusion goals. Talent intelligence can help workforce planning pinpoint diverse talent pools in locations not considered before. Candidates looking for enterprises with experience in diversity went up by 800% between 2017-18 and 2019-20, making a talent-first location strategy important.

2. Stability and resilience – COVID-19 was a macroeconomic and geopolitical hindrance for organizations that workforce planning leaders must mitigate. Political factors like Brexit prompted organizations with UK hub locations to consider European sites fluent in English. Organizations searching for talent at multiple locations succeeded at resiliency and stability.

3. Long-term sustenance – Effective workforce planning will help enterprises position themselves for growth. You will know whether the university ecosystem in the location can feed the talent pipeline needed to drive a long-term business strategy or meet your needs during expansion and growth.

These three factors will give your enterprise a competitive advantage.

Data and Artificial Intelligence are Informing Where to Recruit Talent

An example of data used optimally is Sydney-based Atlassian which faced a tech skills shortage. They began recruiting internationally to meet their hiring goals. The workforce planning team used data to pinpoint key European markets where talent supply exceeded demand and where the company had been successful relocation-wise in the past.

They used data to learn what those targets were looking for to optimize messaging. The team used targeted online campaigns and recruiter outreach to find the right talent, kick off the relocation conversation, and ultimately meet their hiring goals.

Enterprises can leverage location-based data and capitalize on location intelligence to ensure that the data is accurate, complete, and relevant. Companies can access and process large volumes of records faster in various formats and from different sources, for which better geocoding is essential.

Workforce planning teams use geo enrichment to append these data sources to existing corporate data. Besides, artificial intelligence (AI) can seek talent from a worldwide pool and narrow the search to a single city. AI can analyze data, report on patterns in that data, and make predictions. Then it is the task of humans to use the data to further the hiring process.

As enterprises look for talent, a distributed multi-hub strategy will become imperative to drive business growth and accelerate innovation. Trends including the adoption of communication platforms, cloud-based infrastructure enabling collaboration, and the emergence of new regulations have emphasized the effectiveness of a multi-hub strategy.

Draup’s talent intelligence platform provides workforce planning teams with data-backed insights into the global talent demand supply, cost modeling, and reskilling pathways suitable to manage talent faster.

  • Identify talent hotspots by top universities and supply sources such as top employers and talent competitors.
  • Analyze the role and location-based combinations, including the time-frame-based growth estimate of the talent pool.
  • Analyze cost based on the national median cost, including the demand of the role in the location (high cost indicates greater need).
  • Understand the skillset of the employed talent pool, educational qualifications, and certifications in a location.
  • Analyze diversity with the Diversity Analysis model to build a diverse talent pool.
  • Find talent hotspots based on the employed talent pool and the cost parameters. Compare locations and micro-target locations.