Predictive Talent Models: What They Are And Why They’re Beneficial

What right hire looks like

Finding talent that will stay, thrive, and help an organization meet its business objectives is a key priority for people leaders. That is why it is important to recognize the best talent quickly before the competition does. However, as we all know, it is a candidate’s market. In fact, recent research shows that 33% of employees leave within their first 90 days and 46% fail within 18 months. 

The question becomes, “How can heads of talent, heads of people and CEOs better understand what the right hire looks like? And how can organizations ensure that new talent contributes in meaningful ways if they do not have complete data on their company’s values, culture, and work environment?” 

As the human capital management (HCM) space has evolved over the last decade, organizations are more heavily relying on new data analytics technologies to answer these questions. One way of doing this is using predictive talent models to analyze an organization’s highly successful employees to tease out the attributes that make them most likely to stay and perform. 

The goal of these models is to produce a holistic picture of the most successful employees that includes their strengths, competencies, working styles and workplace behaviors, as well as traditional metrics like their experience, education, and background. This picture can then be used to attract, select and retain more candidates that are likely to excel, thus informing the company’s hiring and recruiting strategy. 

However, it is worth noting that every model will be unique since every organization is different. Universal traits for highly successful employees do not often exist – it is all about the bidirectional fit between the employee and the organization. And behavioral traits are what most commonly sets highly successful employees apart from others. For example, at one organization top-performers might be more intuitive and learn new things more quickly than average. 

Working styles are also important - high performers at another organization might value working quickly over perfectionism. These models can also help to identify common weaknesses or areas for growth among successful employees. Every employee has weaknesses, but a good predictive talent model can help HR understand which weaknesses can be managed and which ones may cause problems. 

What are some other benefits of predictive analytics? First, it can help create a virtuous cycle where knowing the profile of a successful employee equips the recruiting and hiring teams to attract more successful employees and build a culture of excellence. Second, it can reduce prestige and unconscious bias to help identify desired candidates more accurately and effectively (based on competencies and skill, rather than credentials). Third, it gets talent management, business leaders and hiring managers on the same page about the types of candidates they want to attract and retain. Fourth, it helps define that elusive metric of ‘quality of hire’, which can drive stronger business performance. And finally, it speeds the hiring process and allows organizations to set up new hires for success and talent growth. 

Behavior data plays a crucial role in creating predictive talent models – a model is only as good as the data that goes into it. Because a staggering 89% of mishires are due to a soft skills mismatch, the success metrics used in a predictive talent model must include more than just technical skills. Behavioral data describes the observed actions of candidates or employees and indicates how they will perform on the job (or how they act while they are at work). This might include the following.
 

• Competencies. Can they do the job? Competencies are the skills, knowledge, and experience one needs to do the job well. This might include mastery of Python for a programmer or a CISSP cert for security. 

 

• Strengths and Gaps. These attributes together describe how someone works. Taking initiative, flexibility, creativity, and teaching others are examples of something that could be a strength or a gap. Employers need to know how they can best use a candidate’s strengths and how to manage their gaps.

 

• Cultural Alignment. How will the candidate mesh with the core values, beliefs, and practices at a company? For example, preferences for collaboration versus individuality. 

 

• Career Interest. What are the candidate’s ambitions, short and long-term goals, and motivations? For example, does the candidate want to be promoted in the next 2-3 years, or are they content with their role and more motivated by tackling new and interesting problems? Misalignment between what a candidate wants from a role and what it actually involves is a major factor in mishires. 

When building these models, it is tempting to focus on hard metrics of employee productivity, but in the long term, the behavioral aspects of candidates are a better indicator of their success. Ready to start building your model? If yes, here are some tips. 

Consider starting with a pilot program so that the team can become familiar with the process before rolling it out to other positions. It is also important to develop a method to measure competencies, strengths, and behaviors as well as background experience and education when assessing current employees. Figure out concrete ways that the knowledge gained from this analysis can be incorporated into the hiring process going forward. Finally, share the model with hiring and recruiting leads to get buy-in and then build interview scorecards to assess for the predictive attributes. 

Events of the past few years have transformed and accelerated the hiring space. Companies of all types and sizes are working to better understand and implement predictive talent models into their HR and hiring processes. The good news is there are several tools and predictive talent platforms out there that help streamline and automate that process. 

Anna Wang is Co-Founder and CTO at Searchlight. Visit Searchlight.ai Connect Anna X. Wang