By Suited

Using data with purpose, for profit

For Firms
For Firms

Using data with purpose, for profit

By Suited

Financial services firms are slowly coming around to the idea of using data in everyday decision making. Firms that demonstrate a holistic adoption to AI are reaping the highest returns on their investments in this technology, and we believe this stands true when applied to recruiting and the work of HR professionals. 

When it comes to Human Resources, 77% of organizations rated HR analytics as important, but only 32% of them felt ready or somewhat ready to handle them. Many HR professionals are unaware of how to use the data they are presented with, and understandably end up relying on old, less data-driven habits across a variety of recruiter oriented tasks such as resume screening. 

So, should HR professionals try to learn to speak data backwards and forwards? No, probably not. Using data should lessen the burden on your team, and using data for data-sake will only create fatigue and frustration at new processes which can hinder its adoption by employees. Data analysis, including machine learning, must have purpose; it must easily accomplish something otherwise difficult. It must, and can, elevate the performance of the work at hand. 

Here are some ways we recommend using data with increased intention and effectiveness in your recruiting processes:


Use data to free up recruiter time 

One of the main value propositions of any good sourcing and assessing platform is to free up the time of recruiters. But to really achieve this, recruiters have to have trust that the data they’re interpreting is accurate. 

Trust is difficult with AI for two main reasons. First, the mathematics behind AI models are complicated by design so that they can search for non-linear patterns in multidimensional space. This means that it can look for high performance patterns across multiple personality traits. But, this also means that sometimes AI provides unexpected predictions. It’s hard to trust predictions that run counter to how you expect certain people to perform at your firm.

In Suited’s case, we instantly surface the highest potential candidates to the top of your digital resume stack. The predictive validity of the candidates we recommend is anywhere from ten to twenty times more predictive than what a recruiter would be able to do by reviewing a candidate’s resume. This is because the model is trained for specific firms and is entirely data-driven — it does not have any predisposed expectations that can lead to bias. 

Sifting through and analyzing resumes is an incredibly laborious and easy to automate task. If a recruiter knows that the firm only has 15 openings, you can set a limit on how many candidates you have to reach out to in order to ensure all of those openings are filled. If you know that your firm has a 45% acceptance rate of job offers, you can set your resume limit to 35. Instead of sifting through potentially hundreds of resumes manually, you can trust that your data is strong, use the data to order the candidates based on likely matches and dedicate those unwasted hours to more strategic matters. 


Use data to understand your current employees better

Most sourcing and assessing technology provides you with previously undiscovered or unquantified information about your current employees. Suited, for example, requires at least 100 employees at your firm to take an assessment that provides us with the information needed to create a custom algorithm for your firm. While this assessment’s main purpose is to help you recruit the right talent, it can also serve another purpose. 

What can that data tell you about what’s happening at your company? Do you see gaps in certain competencies that, if hired for, could help your firm be more well-rounded? Discuss these gaps with your leaders and determine if having a more well-rounded group would help you achieve a competitive advantage.

Through this data, you can also get insight on what drives success at your firm. One way to leverage this is to provide customized coaching to those under-performing employees who lack certain, crucial traits. For example, if your company’s top performers all score highly on the trait of “Openness,” you can provide feedback or training on how to approach problems with a sense of broad-mindedness. This might be especially helpful at retaining a diverse workforce.

You can also use this data to showcase this data to candidates. Maybe the data tells you that your firm values individuals who display a particular trait, such as “Altruism.” Use this (maybe) unexpected insight to your advantage to point out what makes your firm unique during an interview. 


Use the data to bring in people with new ideas and perspectives 

Using the power of AI, recruiters can easily and effectively consider more people from more places with diverse backgrounds. To really accomplish this, you must be willing to accept that a candidate who attended an Ivy League school may not necessarily possess the traits or experiences that would be most beneficial to your firm.

For example, perhaps a trait such as “Attention to Detail” is highly predictive for success. A first-generation college student who attended a public in-state school on scholarship has needed a keen sense of attention to detail in order to navigate through the college/scholarship application process with no experienced help from a family member. At a firm that has no precedent of hiring students from in-state schools, and without the data to tell you that this particular trait is useful to have in a hire, you may have overlooked someone who would match with your high performers and who could bring a new and welcomed perspective to your workplace.  


Use data to stay on track with diversity goals 

A reason why many firms fall short on their diversity goals is that hiring managers and recruiters rely on their gut instincts. To create a truly fair system for all candidates and an efficient and reliable process for companies, we can no longer solely rely upon our intuition — we need evidence. Using company specific data and AI that tests for adverse impact has been shown to effectively overcome unconscious bias that has been found to be persistent in traditional resume screening.

Additionally, expanding upon your traditional talent pool can help expand your firms’ reach to diverse groups of individuals. By relying on your same old sourcing mechanisms, you cut your firm off from the possibility of reaching candidates who may not have heard of you before but would be a huge value-add to your business. 

Ultimately, data can help your firm truly optimize your investment in people, so long as it’s trusted, understood, and used to execute specific action plans. With the proper tools and attitude, your HR team can lead by example, and become the culture change agents your entire firm needs when it comes to technological transformations and their return on investment.