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A Practical Guide to Implementing a Talent Intelligence Platform

Most everyone in the talent acquisition space, from HR leaders to recruiters to talent acquisition professionals to staffing company executives, has noticed the world being rocked by evolving technology. We are starting to see the industry take another step forward with a new technology category: Talent Intelligence platforms.

What are Talent Intelligence platforms? Why do they matter? Do they provide real business value, or are they all hype? And how can they be successfully implemented and optimized to help organizations?

Talent Intelligence platforms do two things. First, they combine all internal and external candidate data sources to provide a holistic view of the talent available to organizations. Secondly, they make sense of the data with AI, for example recognizing that two different job titles actually represent the same type of work or that candidates with a particular combination of skills are strong matches for specific roles.

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This holistic view of data allows organizations to:

  • Match internal and external candidates against open roles
  • Dynamically understand skills and job market trends
  • Perform strategic workforce planning
  • Proactively source candidates 

In short, Talent Intelligence platforms are a foundational tool for gathering and sorting through data about jobs and people and combining data and AI to empower recruiters and organizations to make better decisions around talent. This core functionality opens up many possible use cases and represents a step up from the technologies we have been using for the past decade.

In our 3-part report, we’ll provide guidance on what Talent Intelligence platforms can do, how they work, and how to implement them successfully. We start with a look at how these tools interplay with existing talent acquisition technologies. Then, we look at the specific business drivers and use cases for a Talent Intelligence platform. We explore implementation with an eye towards different approaches and keys for success. Finally, we end with a discussion about the ROI of investments made into Talent Intelligence tools, practical advice for securing budget, followed by two case studies to show how these tools work in practice for staffing and corporate teams. 

This series will enable readers to understand what Talent Intelligence platforms are, why companies use them, and how to most efficiently leverage such tools to drive business results today.

Talent Intelligence in the Context of a TA Technology Stack

The ability of AI tools to make sense of vast amounts of online and in-house data about jobs and people is transforming talent acquisition technology. As a result, the technology ecosystem’s boundaries are shifting, making it difficult for talent acquisition professionals to stay abreast of the field. Here’s a brief orientation.

There are several broad categories of software, all of which rely on this fundamental ability of AI to understand data about jobs and people:

  • Talent Intelligence tools: These tools focus on AI-driven search capabilities, that is, finding candidates for jobs by looking at both internal and external sources of data (i.e., both candidate relationship management systems and job boards). These tools are closely related to the categories of  “social search tools” and “person-job matching tools.” HiringSolved and HiredScore have capabilities that fit in this space.
  • Labor Market Intelligence tools: These tools focus on understanding the labor market. For example, by scanning resumes of people in a given geography, these tools can give up-to-date insights on the availability of skills in that area, and hence can be useful for decisions such as where to locate a new office. Emsi, Revelio Labs, and SkyHive are vendors who, among other capabilities, provide labor market intelligence.
  • Candidate Relationship Management (CRM) tools: These tools provide a range of capabilities for tracking and managing candidates. CRMs are not new. What is new is CRMs that are leveraging AI capabilities. Vendors such as Beamery and Phenom People have capabilities in this space.
  • Internal Talent Marketplaces: Just like CRMs, Internal Talent Marketplaces are not new. What is new is the ability to understand jobs and people in terms of skill sets to uncover potential career paths, identify skills gaps, efficiently run internal “gig” workplaces, and so on. Vendors such as Gloat have capabilities in this space.

Vendors rarely fit neatly into one category and often have capabilities that cross over into other spaces. Nevertheless, this rough categorization helps provide some guideposts in understanding the space. In the context of a broader TA technology stack, Talent Intelligence platforms can be thought of as “middle-ware” that sits on top of the core applications (such as an ATS or CRM) and makes those applications more useful for end-users. A deeper discussion of how vendors differentiate and potentially integrate into existing tech is provided later in this series.

Business Drivers for a Talent Intelligence Platform


One of the most tangible benefits of Talent Intelligence platforms is the ability to find candidates who already exist in your ATS or CRM. Many firms have millions of candidate records in their hiring systems — a pre-identified talent that at some point expressed interest in working with the organization — but without a way to search, filter, and update these records in a meaningful way, their value remains locked. As a result, recruiters go straight to external sources because it’s simply faster and easier than trying to search through an ATS that was not designed for the task.

Both enterprises and staffing firms typically find that once they have a Talent Intelligence platform in place, they experience a substantial increase in the proportion of job openings filled via candidates found in their ATS or CRM database. The primary benefit of this approach is cost and time savings (why pay to re-source a candidate you already have access to?). Many firms have also found this approach helpful in merely helping find the required number of qualified candidates, as (for a variety of reasons) candidates do not seem to be as active on job boards as they once were.

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Traditional searches of job boards have been based on titles or keywords. For example, a recruiter might look for “accounting manager” or “SuccessFactors” or “electrical engineer.”  These searches can miss candidates who do not have the right keyword in their resume, and they can also turn up bad matches where the keywords exist, but the individual is nonetheless a poor match for the job or has “gamified” their resume.

AI-driven intelligent search can outperform keyword search because the AI has a broader “understanding” of the job and skills requirements. For example, it may recognize that someone is a good candidate because they have skills adjacent to what is asked for, even if they haven’t listed the particular skills asked for in the search, or if their current job title doesn’t match what was queried. Intelligent search is less likely to be fooled by an inaccurate job title. By assessing the skills found in the resume, it can match candidates to job openings even if the title is misleading. 

AI-driven intelligent search has other tricks up its sleeve. A recruiter can feed it a job description and say, “Find me candidates who fit a job like this.”  AI can even say, “You liked these candidates in your first pass of the data; here are some more who look very similar.”

This intelligence is possible because the AI has been trained on millions of job descriptions and potentially billions of data points. The advantage of the Talent Intelligence tool is that it works at scale, simplifies and streamlines the recruiter’s workload, enabling recruiters to spend less time on busy work and more time assessing and engaging a curated shortlist of qualified candidates. 

The net result is more effective searches. It is comparable to the effectiveness of a search engine like Google or Bing today versus more static “web portals” from years past. Google can be almost eerily accurate in finding the web page you need based on your search terms because it’s not just matching keywords; it’s applying AI to determine what will most likely meet your needs.


Satisfaction with legacy Applicant Tracking and Candidate Relationship Management Systems is typically low, and tools such as CRMs (which require substantial investment) are sometimes woefully underleveraged. Many firms would like to switch vendors to take advantage of the latest capabilities in the market yet are unable to for various reasons (e.g., contractual, cost-related, organizational-related). A study by showed that 32% of users reported their ATS didn’t have the features they need, while TTL’s survey research showed that ATS and CRMs were the most commonly reported TA tech systems to be considered “underwhelming” by TA leaders. In such a scenario, a Talent Intelligence platform can be a tool to supercharge such legacy hiring systems, enabling recruiters and HR leaders to tap into the latest capabilities in matching, sourcing, and AI-based predictions without requiring a massive systems overhaul or vendor swap.

What makes this approach possible now?

Talent Intelligence platforms have arisen, rather suddenly, for two reasons. First is simply that the technology and data sources to make them practical now exist. In particular, the ability of AI to “read” natural language and find patterns in data is now well-established; while still a technical marvel, it’s become an everyday technology.

Secondly, the difficulty of finding talent is greater than ever. One of the main reasons for this is the imbalance between supply and demand for specific skill sets. The overall unemployment rate is not particularly meaningful in talent acquisition these days. Some skills are readily available in the market. For other skills, organizations are engaged in a full-on war for talent. 

The convergence of possibility and need has made Talent Intelligence platforms a hot topic.


Implementing a Talent Intelligence tool that will work with your existing technology stack is simpler than implementing a tool like an ATS or CRM. Nonetheless, it does need to be rolled out thoughtfully. Below we provide an overview of implementing a Talent Intelligence tool.


Vendors have essentially taken two approaches to product development. One group of companies essentially offers a recruiting platform of some kind (typically a CRM, sometimes with Talent Management modules and internal career pathing) with AI-based functionality powering the system. The advantage of such a solution is the system is ostensibly intertwined with a unified data structure. The disadvantage is that it typically requires a “rip and replace” of existing technology and thus also typically requires a more significant investment and commitment to pursue. 

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The second approach is to power existing hiring systems with Talent Intelligence. In this scenario, the platform essentially acts as a middleware that ingests data from existing hiring solutions and enhances them via AI. The advantage of this approach is that firms can more quickly deploy the solution and typically do so at less cost. Further, since core systems are not being disrupted, there generally is less business and process disruption. 


Before one even begins implementation, one needs to get buy-in from key stakeholders. For staffing firms, where the ROI of a Talent Intelligence platform is direct and readily measurable, engagement will typically include the executive leadership team, the CIO or CTO, as well as recruiting and sourcing teams. 

However, in any large enterprise, there are likely to be many stakeholders in any technology project. In the case of talent intelligence, stakeholders will likely include the CIO or CTO, leaders within HR responsible for HR technology, the talent acquisition team, and legal. As with any project, there may be a battle in the background to find the budget even when ROI is not disputed. 

Leaders in large enterprises interested in taking advantage of a talent intelligence platform need to do the upfront work of engaging stakeholders to have the support they need to proceed with the implementation. In particular, HR leaders should build a business case that (a) addresses and articulates actual business needs and whose success and progress can be measured, and (b) meets the needs of company stakeholders in the process. A business case can be enhanced (and implementation improved) by creating process documents in advance that show how specific workflows will change pre-and post-implementation. 


An organization implementing a Talent Intelligence platform will start by cataloging their data sources and what data fields they need to capture. Data is the “food” for any good AI-based system. A first step in successfully implementing a Talent Intelligence platform is to calibrate data across systems and hiring functions. There will likely be relevant data in:

 Internal HR systems  

  • Applicant tracking and candidate relations management systems which contain information on people who applied for jobs
  • The HRIS that contains information on current and past employees
  • Other specialized HR systems which may contain information about skills, qualifications, etc. that may not be in the HRIS

External data sources

  • Job boards and resume warehouses such as Indeed, Monster, CareerBuilder
  • Social media sites such as LinkedIn or Facebook

Once data sources are determined and scoped, it becomes the job of data integration specialists from the Talent Intelligence platform vendor to build the links to pull this data together to become usable. Most modern systems have reasonably good APIs that allow access to data to enable this kind of data integration.


After determining what sources of data you would like to use, it’s important to take the time to consider the quality of the data.  A data assessment audit is a straightforward but essential step in implementation. Here’s why:

In theory, when a candidate applies for a job, the recruiter follows the standard processes. The resume ends up in the Applicant Tracking System (ATS) or Candidate Relationship Management system (CRM). If this happens, the organization just needs to “plugin” the talent intelligence tool and extract the data.

In reality, recruiters often fail to follow the standard processes, or there are multiple groups/stakeholders that follow their own bespoke process. When you look into the ATS or CRM, many candidates do not have an attached resume, for example. The resume exists someplace else, perhaps in a folder on the recruiter’s hard drive.

Because of this discrepancy between how things should work and how they do work, an important step in implementing a Talent Intelligence tool is to audit the status right at the start. This isn’t hard to do. You can go into your ATS or CRM and look at a random sample of candidates to see what percentage of resumes are missing. After that, it’s a matter of tracking down where they are. Typically, recruiters will know where those files are. It’s just a matter of going through the process with each recruiter until you find all the different places where data is stored. If you find there are still holes in your data where resumes are missing, you can assign an intern to reach out to candidates to send in recent resumes so they can be added to the system.

Once you have found the data, it can be imported into the ATS or CRM and made available to the tool. Companies should use the exercise as an opportunity to standardize best practices across the firm, particularly when it comes to data capture.


In some ways, the technical implementation is more straightforward than the next steps of the process: training and user adoption. Training is not the issue per se as Talent Intelligence tools are easy to use. The bigger challenge is getting recruiters to use an unfamiliar tool. Recruiters may well decide “it won’t work” even before they have seen the tool.

The best approach to this phase of implementation is traditional change management practice. First, involve recruiters early on so they can give input into what the tool should do. Communicate often and listen. Be sure you keep in mind the recruiter’s perspective; you need to be able to answer their question, “What’s in it for me?” 

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Second, leaders should do all that is possible to establish process documents and provide relevant training to make the transition as easy and seamless as possible. Even a Talent Intelligence platform implemented as an enhancement to the existing technology stack will come with some change in the process. If these new processes are not documented and disseminated to recruiters and sourcers, they will likely fall back on what is “familiar,” and the tool may create new confusion. 

User adoption is one of the key pieces to a successful implementation. When evaluating vendors, you should ask for adoption rates post-implementation at specific periods (e.g., 1 month, 3 months, 6 months post-implementation) and understand how each vendor will support the organization in rolling the tool out and training users. 

These change management practices are well-known but too often overlooked in a rush to get a new technology online.


Talent intelligence tools can be implemented in a matter of months. They layer in a new search capability onto your existing systems rather than requiring you to tear out the old system and replace them. They typically “breathe new life” into an existing legacy ATS or CRM by providing the search capability that makes the systems more useful for recruiters.

From a purely technical point of view, one could get a system up and running within 30 days. However, the challenge, especially in large enterprises, is that there are many internal hoops the HR technology team has to jump through before a project can be approved, and bespoke organizational requirements and integrations can sometimes add additional time. 

The takeaway for HR leaders interested in implementing talent intelligence is to devote as much time to getting internal stakeholders aligned as to working with the vendor to get the new technology installed.

In the next of our 3-part series, we’ll dive into methods you can use to measure the ROI of Talent Intelligence software, and ways to secure a budget for investment. To stay updated on the latest trends and information regarding TA software, be sure to join our membership portal.


The post A Practical Guide to Implementing a Talent Intelligence Platform appeared first on Talent Tech Labs.

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