Skip to content

Leveraging Talent intelligence in AI-Era Recruitment

Featured Image

Some background

In the 30+ years I’ve operated on all sides of HR and HCM Technology, I experienced countless iterations of every single HR process or capability area as they were supposedly evolving to the newest view of best practice.

Typically, these HR process optimizations, evolutions, or transformations emanated from two types of circumstances.

1️⃣ One type of scenario involved major HCM technology innovation, often not readily foreseen.

2️⃣ The other related to a change in how the process was conceptualized or thought about in order to garner more compelling business benefits if not sustained competitive advantage.

The latter type of significant progress in an HR process or HCM activity area, along with the various ways HCM Technology enables the corresponding new vision or strategy, often leads to a proliferation of new use cases for innovative technology.

Examples might include

The discipline of Compensation Management evolving into the more holistic Total Rewards Management model, or Vendor Management (around procuring contingent labor) evolving into the discipline of Extended Workforce Management (which includes many more strategic aspects), or Workforce Planning evolving into Strategic Workforce Planning which is much more inter-connected across business functions and stakeholders and continuous in nature.

With that as a backdrop, let’s recognize that the Recruiting or Talent Acquisition domain has witnessed a steady stream of more sophisticated and effective practices replacing former iterations, in other words, the evolution of this domain has occurred as well.

Results such as the ability to attract and retain top, best-fit talent while also managing costs out of the process are now much more attainable, of course with the help of better technology and user experiences.

That said, more impactful strategies and approaches in this arena, as with all the other HR process areas, are usually a direct consequence of having and applying more HCM-related data insights in the flow of work.

What is talent intelligence (TI)?

Talent intelligence

Talent intelligence refers to the efforts of an organization to collect, analyze, and leverage as a true asset all useful and reliable internal and external workforce, industry, and labor market data.

External ‘TI’ data is often largely about the company’s competition and surrounding industry dynamics and data points. Internal information in the scope of a talent intelligence initiative almost always includes current and future labor and skill needs and corresponding gaps.

Moreover, talent intelligence efforts are usually more successful if external data or industry benchmarks are used within comparisons against an organization’s trends and results.

Compensation practices or the pricing of jobs and job families is considered foundational benchmark data, but other common data comparisons and trendlines in the TI realm include various staffing ratios, cuts of demographic data, KPI’s like revenue per employee, engagement, retention, and turnover rates and trendlines, relating the same to customer satisfaction levels, internal mobility and promotion rates, sources of new hires, candidate flow activity, trends around workforce size, HR department staffing in relation to workforce size (e.g., 1 HR staff per 100 employees is an oft-cited stat), time to productivity, etc.

In short, the primary goal of talent intelligence is to help companies make the most data-informed and timely workforce-related decisions. Regarding how talent intelligence differs from people analytics or ‘PA’, the latter takes a broader look at data focusing on the entire employee lifecycle – including on boarding, off-boarding and even alumni hiring.

‘PA’ encompasses the broader set of data that might relate to performance, engagement, productivity, or attrition. Examining this type of PA data, companies can make decisions regarding talent management, workforce planning, organizational design, and operational improvements among many other important HR / HCM endeavors.

➡️ As workforce, labor market and HCM-related data insights (aka talent intelligence) get increasingly diverse, far-reaching and inter-connected, more opportunities will no doubt arise for businesses investing in both TI and PA.

Of course, recruitment in the AI 🤖 era also involves elevating the level of personalization in crafting the most effective employer value proposition, the ability to infer the presence of skills even if not explicitly highlighted or culture fit based on past job successes and employer reputations, improving employer brand attractiveness by following the prescriptive guidance of what approaches and strategies have worked to-date, and the degree of candidate fit being assessed across more dimensions than ever.

Also, with respect to the sourcing and use of gig workers, contingents and contractors, today’s corresponding set of processes clearly extends further in scope than just procurement, deployment and cost management elements.

⚠️ Other critical activities relative to these non-employees include optimizing their scheduling, onboarding, evaluation and as-needed coaching while still ensuring compliance with all relevant IRS worker classification and management rules.

Finally, it should be noted that whether an organization uses gig workers, contractors, contingents or regular employees, all these workforce segments can help, or hurt, the reputation of a business.

The intersection of TI and TA (Talent Acquisition)

As talent intelligence involves strategic analyses and actionable insights on the broader talent landscape inside and outside the organization, it usually incorporates external talent pool analyses within all skill supply/demand analyses.

Within the TA realm, TI can inform such critical elements as:

  • Candidate sourcing
  • DEIB trends and potential issues
  • Other HR compliance aspects
  • Candidate retention and compensation strategies
  • Minimizing candidate abandonment and offer rejection rates
  • Readiness to enter new lines of business or new geo markets
  • Predictive modeling to forecast future talent needs – especially when changing business plans and priorities triggers a change in the skills needed

Key technology implications

HR Technology

There’s no question that interoperability sits at the heart of digital transformation and TA is no exception. This is because interoperability is all about facilitating the integration of various, often disparate systems and technologies for fluid communication and data sharing.

Naturally, this pertains to the various data insights across the talent intelligence spectrum, as the typical organization is using and working with data from at least 6-8 HR / HCM technology platforms to service both the operational and strategic HCM needs of the HR department, line managers, employees, corporate leadership, government agencies and external partners.

It was formerly, commonly understood that enterprise systems – HCM or non-HCM related that needed to be linked – should communicate data in a shared structural format. This used to be referred to as semantic interoperability, which was often the goal, but now it extends to ensuring that exchanged information has the same meaning for the receiving system as it does for the sending system.

This requires the use of metadata and controlled vocabularies or ontologies so that the data is not just structurally correct but also contextually meaningful!

Parting comment

Talent intelligence encompasses whatever reliable data, from whatever sources, and whether emanating from within or outside the organization, that can inform critical decisions about the workforce and optimize the outcomes of all related HR processes and HCM activities.

HR analytics in the 80’s and 90’s was extremely insular in scope. The 2000’s ushered in people analytics which supported the needs of all relevant stakeholders not just the HR department.

Now talent intelligence, and with the help of AI and technology innovation, organizations have a far better if not superior opportunity to derive competitive advantage from what is truly their #1 asset: Their workforce.

Steve Goldberg
Steve Goldberg
‪HR Process & Tech Leader | HCM Analyst/Advisor

Steve Goldberg's 30+ year career on all sides of HR process & technology includes HR exec roles on 3 continents, serving as HCM product strategy leader and spokesperson at PeopleSoft, and co-founding boutique Recruiting Tech and Change Management firms. Steve’s uniquely diverse perspectives have been leveraged by both HCM solution vendors and corporate HR teams, and in practice leader roles at Bersin and Ventana Research. He holds an MBA in HR, is widely published and is a feature speaker around the globe. He’s been recognized as a Top 100 HRTech Influencer. Steve is also a close advisor to Azilen Technologies, this post’s sponsor.

Related Insights