How to Build Talent Personas that Improve Hiring Efficiency

Posted on July 13, 2022

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Hiring EfficiencyQuality of Hire

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Many of the forward-thinking Talent and People leaders I talk to get really excited about the idea of building Talent Personas. These use real-world data from an organization to build a profile of the employees that tend to excel there (this is also called an “ideal candidate profile” ). These profiles are invaluable to recruiters and HR business partners in several ways. First, they ensure everyone involved in the hiring process is aligned on the type of candidate they are looking for. Second, they help recruiters work more quickly and improve overall hiring efficiency. Finally, they help recruiters identify candidates more likely to excel at their organization (especially ones from nontraditional backgrounds), which can improve Quality of Hire, offer acceptance rates, retention, and manager satisfaction with the new hires.   

But building accurate, useful talent personas is a challenge. Gathering the right data, avoiding bias, building the profile into the hiring process, and keeping it up to date are all tricky tasks. Here’s a step-by-step process for building personas that are actionable and useful for recruiters.  

1. Analyze company culture and identify top performers

In this context, “culture” doesn’t just mean values – it also includes processes and how the organization or team in question manage and organize their work. For example, a highly innovative culture will value innovation, but might also give employees more time to work on side projects and give individual engineers or managers more decision-making power. 

There are many different qualitative and quantitative ways to measure company culture (including Searchlight) and companies can typically identify top performers based on performance reviews. This lays the groundwork for additional analysis. Some organizations with forward-thinking People Analytics and HR teams may already be doing this, but analyses from before the Covid-19 pandemic are likely no longer accurate because of how dramatically work patterns have changed at most organizations. Recently, our customer Talkdesk shared how they had to update their Employer Value Proposition and Personas post-pandemic, and Searchlight helped them do it in a scientific and data-driven way.

2. Model high performers

Next, gather data on high performer’s behavioral traits. Behavioral traits include competencies, strengths and gaps, cultural alignment with the organization, and career interests. This should include soft/power skills and their approach to work (collaborative versus results-driven, more comfortable with process versus uncertainty, etc.) as well as more traditional metrics like education, work histories and technical skills. The goal here is to identify what sets high performers apart from other employees at your organization. 

3. Build Talent Personas

Build a profile of the ideal candidate for your organization or team based on all this data. Part of this process should be testing for adverse impact or bias. Searchlight regularly tests our platform for bias to make sure candidates of different genders or ethnicities are not being unfairly favored or discriminated against.  

Be sure to go over the new talent brand personas with all members of the hiring team, company leadership, and other important stakeholders to gather feedback and get the hiring team on the same page. 

4. Adjust hiring process as needed

Rewrite job descriptions, interview questions, and make other changes to the hiring process to make sure it’s attracting and evaluating candidates based on the new personas. For example, if you find your ideal candidate profile includes a high value for Innovative cultures, make sure to emphasize that in your recruitment marketing content and job descriptions.

5. Use post-hire data to evaluate Talent Personas

Talent personas should be evaluated over time. Some ways to do this are measuring Quality of Hire to see if new hires are going on to excel, or gathering feedback from new hires at regular intervals to see if their experience matches the personas. For example, if this process identified that a particular team has a highly collaborative culture, but several new hires who joined that team reported that it’s not very collaborative, that part of the personas might need to be revisited. 

6. Keep personas up to date as the company grows

Talent personas at startups and companies in hypergrowth mode can lag behind the current size and needs of the company because building talent personas takes time. Imagine a 100-person organization that’s growing quickly; the Talent Personas they built at 100 people will be outdated by the time they grow to 300 people because the organization will have different needs. If they don’t update those personas, they’ll no longer be making the best hires for their current needs. This is why bringing post-hire data back into the process of building the talent personas is so important. 

All in all, building talent personas is tremendously helpful for recruiters, but it requires relatively mature People Analytics capabilities with sophisticated analysis of organizational culture and high performers. It’s not a one-and-done scenario – making useful talent personas requires ongoing work to update them as the company changes and grows. 

But the payoff is significant. One Searchlight customer said that the hires they made after implementing a predictive talent model were the strongest their team had made in the two years at the company, and other customers have reduced time-to-fill by 40% and increased retention by 25%. Improved hiring efficiency leads to better Quality of Hire, higher offer acceptance rates, and improved manager satisfaction with the new employee. Especially in light of a changing hiring environment, I’d strongly urge forward-thinking companies to consider Talent Personas as a way to ensure they’re hiring the best possible candidates for their organization.   

Kerry Wang

Co-Founder & CEO Kerry is the co-founder and CEO of Searchlight. After studying both Org Psychology and Computer Science at Stanford, she loves nerding out on all things people, psychology, and tech. On the weekend, you’ll find her reading a book or watching reality TV.

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