Closing the Loop Between Performance Management and Talent Acquisition

February 28, 2023

min read


Kerry Wang

Many HR and People leaders dream of a closed-loop system linking performance management to talent acquisition. It’s been called the holy grail for a competitive people strategy, and there’s many reasons for that. Information from the recruiting process is valuable for managing, retaining and promoting candidates who go on to be hired. And information on how those candidates ultimately perform in the organization helps talent acquisition teams improve their efficiency and accuracy at bringing in more high performers who continue to raise the talent bar.

Hiring Great People Requires Great Data

Hiring high-performing employees is always the goal. But the current economic outlook in the US that demands greater organizational performance has made hiring quality a top priority. A potential economic downturn, reduced headcount at companies in many verticals, slower growth and a new focus on profitability in the startup world means that organizations need every employee to be a top performer. Lower headcount goals make each incremental hire so much more critical, and companies are willing to take extra time and effort to find the best person. 

This push for performance extends to current employees as well; with increasing business pressure and more people available in the talent market, many organizations are more willing to manage out low-performers in the hopes of hiring someone better. For this strategy to work, they need to trust their hiring process can identify and bring in high performers. This requires knowing what greatness looks like and applying that knowledge to job setup, assessment scorecards, and the ultimate hiring decision.

Without data, organizations rely on instincts and anecdotes about what qualities make an employee excel at their company. Basic hiring techniques aren’t much better; Google’s research found most unstructured interviews have zero relationship with future performance. Bias creeps in, mistakes are made, and the company suffers. 

What the Closed Loop Could Mean for You

A data-driven method to identify greatness allows talent acquisition teams to get much more predictive at making better hires. When top-performing employees deliver up to 400% more productivity than average ones, cracking the code on predictive hiring directly can have huge benefits to business outcomes

Moving up a level, better hiring also gets rid of many “people problems” and frees up company leadership to work on other things to push the business forward. It eliminates costs associated with attrition and poor performance, such as backfilling roles, extra training, and burning out managers and colleagues. It also helps HR and TA to be recognized for the work they’re doing. Better hiring also improves the employee experience — having good colleagues improves people’s day-to-day work life considerably which leads to higher productivity, more innovation, and better customer service. On the other side, a single bad hire can drag down an entire team and make everyone else unhappy, less productive, and more likely to quit (read more about the costs of attrition here). This is especially important at the manager level, because leaders can have such a dramatic positive or negative effect on the rest of the team.  

The Status Quo

Some organizations, mostly enterprises with large People Analytics teams, have built some version of a closed-loop performance management and talent acquisition system in-house. Some have worked…and some have not.

The most famous example is Google, whose People Analytics team has been able to identify the right number of interviews and competency assessments that have the highest probability of bringing in the right people (Spoiler alert: GPA and school had no correlation with future performance). Sunrun was able to find performance indicators when hiring for a couple roles, but it took a team of analysts a whole year of work.

On the other hand, Twitter did a similar analysis and found that their interviews were not predictive of future employee success. The main challenge with building your own closed-loop system is the accuracy and completeness of people data available in siloed HR systems. Other issues with manual analysis include the risk of bias when humans interpret the data and how quickly the work goes out of date as the company grows and changes. 

For large organizations to build a continuous learning loop well, and for small and mid-sized organizations to do it at all, they need technology that can collect and analyze recruiting data and performance data efficiently and effectively. Even more powerful is the ability to surface valid predictions and recommendations that can drive better talent selection, retention, and performance. Searchlight with Lattice creates that connection. 

The Searchlight-Lattice Partnership

The Searchlight-Lattice partnership runs on autopilot with little to no manual work. Data can be automatically shared via software integrations, or pulled in via CSV files in about ten minutes. The results update automatically to drive value for both talent acquisition and performance management teams. 

Searchlight improves hiring efficiency and quality by identifying what characteristics make someone great at a specific organization (they call these “talent models” and since every organization is unique, every talent model is unique as well) and applying that data to job setup and candidate selection. Searchlight’s AI collects available data in the ATS and HRIS, and adds its own assessment on candidate power skills, culture alignment, work motivations and hiring outcomes either pre-hire and/or within the 6-month new hire window. Searchlight’s research found that its talent acquisition products can triple the predictiveness of selecting a high performer, and its Talent Models can be shared with performance management systems to onboard and manage employees more successfully. The predictiveness of Talent Models increases over time as the system collects and learns from every new hire and performance review. This is where Lattice’s data plays a critical role.

Digital mortgage lending platform Snapdocs uses both Searchlight and Lattice as part of its HR tech stack. Using Searchlight to apply Lattice performance data into the hiring process helped them to improve quality of hire, increase employee lifetime balue by 1.5-4X, decrease time to productivity for new employees by 25%, gather and analyze talent data 80% faster, surface the qualities that predict successful employees, and drive executive alignment at Snapdocs. You can read more about their story here.  

Together, Searchlight and Lattice provide visibility into the full employee experience process - Searchlight covers the initial hiring process until six months on the job, and Lattice’s performance management covers from the six-month mark to their last day. 

The closed-loop holy grail is no longer out of reach for most organizations. Reach out today to learn how Searchlight and Lattice can help you get there. 

Kerry Wang

Co-Founder & CEO

Kerry, our CEO and co-founder, merges Org Psychology and Computer Science expertise. Passionate about people, psychology, and tech, she enjoys weekend reading and reality TV.

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