Leadership and Selection Assessments provide significant value to an organization. Those who invest in a data-driven approach experience increased retention, improved quality of hires, successful onboarding, and cost savings by selecting a ‘best-fit’ candidate.

What Do We Mean by ‘Assessment’?

Ascend Talent Strategies (ATS) leverages a data-driven, multi-method approach to assessing talent, whether the focus is on finding the ‘best-fit’ candidate, supporting a promotion, or further developing an employee’s skill set. Assessments integrate several sources of data that include a candidate’s personality traits, motivational drivers and drainers, critical thinking and problem-solving capacity, and behavioral tendencies. The art and science of assessment assist Human Resource and Talent Acquisition leaders to bolster their decision-making by providing relevant and objective information about a candidate’s strengths and developmental needs, as well as their fit for the company culture and team dynamics.

Assessments add an extra layer of discernment to the hiring process that promotes a more holistic, or complete, view of each candidate. They enable Human Resource leaders to integrate several pieces of information that can be used to support traditional hiring practices in an efficient manner.. The use of a multi-trait, multi-method approach to talent assessment is key to driving the best hiring decisions.

Comparison to Traditional Hiring Practices

Traditional hiring practices tend to rely on subjective criteria, such as resumes, initial impressions, and personal judgment. While this information can be helpful in assessing fit within an organization, team, or role, it also invites the integration of unconscious bias and stereotypes in the process. The impact of a ‘bad-hire’ based on subjective impressions and biases can influence many areas of a business, both in the short-term and long-term.

In comparison, the integration of data-driven, objective criteria in the form of selection and leadership assessments provides a more objective and efficient hiring process that ultimately decreases the risk of an organization making a ‘bad hire’. Utilizing a holistic approach to talent selection allows for a more detailed and comprehensive, not to mention reliable and valid, (as well as legally defensible) illustration of a candidate’s traits within the workplace.

Organizational Benefits of Using a Data-Driven Approach

Now that we’ve defined ‘Assessment’, let’s look at 5 organizational benefits of investing in a data-driven approach.

1) Increased Retention

In addition to personal reasons for leaving a role, changes in employment rates are also influenced by macro events (e.g., COVID-19, Brexit, financial crisis of 2008). Historically, these changes have had a large impact on organizational retention rates. Over the past several years, many industries have experienced significant turnover and have been searching for innovative ways to address this concern. The good news is that injecting data-driven approaches into talent strategy influences the length of time a candidate is likely to stay with a company. By placing the right people in the right positions, employees tend to be more engaged and are less likely to leave their role.

2) Employment Brand

Incorporating data-driven assessments can also positively impact an organization’s employment brand. While people may think that candidates could be “turned off” by the request for additional time and effort needed for the assessment, our experience suggests otherwise. We often hear that candidates feel comforted by the fact that the organization is willing to invest in our process because it shows they are working to ensure the best decision is being made regarding fit with the role and organizational culture. Moreover, candidates are typically eager to receive feedback on their assessment and view the process as an investment in their development.

3) Improved Quality of Hire

The inclusion of data in the recruitment and hiring process significantly increases the chance of making a ‘good-hire’ and helps to decrease the impact of the bias that can occur. It helps to differentiate candidates by offering additional data points that assess personality, work style, motivation, and cognitive, or problem-solving capabilities. In addition to these data points, the understanding of the company culture and vision informs the Assessment process to create customizable solutions for integrating an employee into the company or new role.

4) Successful Onboarding

Once an employee begins a new role, Human Resource teams need to plan, track, and benchmark the effectiveness of their onboarding activities. By leveraging a data-driven strategy, these teams can better understand the strengths and developmental needs of their employee and customize the onboarding experience to increase their chances of success in the role. We, at ATS, believe in partnering with our clients to help them focus on the needs of their employees and to define onboarding criteria that set their candidates up for success. 

5) Cost Savings: Selecting the ‘Best-Fit’ Candidate

According to the U.S. Department of Labor, the average cost of a ‘bad-hire’ is at least 30% of an individual’s first year expected earnings. Breaking that down, an employee hired at $50,000 will cost the company around $16,000 should they not stay or be successful in the role. The use of data in the hiring process promotes a more complete view of each candidate and allows human resource leaders to integrate several pieces of information that can be used to support traditional hiring practices. We have found that companies experience cost savings due to improved efficiency in hiring, increased employee engagement, and the focus on candidate fitness for a particular role.

A company’s investment in data-driven talent decisions is an investment in its future. The impact of utilizing comprehensive data about a candidate provides several benefits, as outlined above. In fact, the costs, financial or otherwise, associated with a ‘bad-hire’ are likely to be detrimental to an organization, which begs the question of whether we can afford not to incorporate data into our hiring decisions.