Predicting retention: How companies can avoid costly employee turnover
In many organizations, the actual costs of turnover are overlooked in recruitment strategies. While enormous resources are invested in job profiles, hiring funnels, and assessment processes, one crucial question remains unanswered: Will the person hired today still be with the company in 18 months?
Current data shows an average misplacement rate of 14%, and as high as 30% in junior programs. With 50 hires per year, this already results in losses well into the six-figure range. Much of this cost could be avoided if recruiting took into account not only the probability of success, but also the probability of termination.
The true cost of employee turnover
The well-known cost factors, such as recruiting expenses, onboarding, and training, are only the tip of the iceberg. In fact, depending on the role, hiring the wrong person can cost between €45,000 and €100,000, and in the case of executives, up to €300,000. The direct costs of searching for and training new employees alone add up to as much as €60,000.
Added to this are hidden costs such as:
- Loss of productivity,
- demotivated teams,
- loss of expertise, and
- damage to reputation.
Companies have it in their own hands to avoid these. This is because employees often resign not because of the job itself, but because of a mismatch between expectations and reality – patterns that would have been visible during the recruitment process.
The unsurprising exit
Current data shows that early turnover is rarely a coincidence. 14% of employees leave because the tasks do not meet their expectations, and 17% leave due to a cultural mismatch. The SHRM Global Culture Report confirms that 64% of employees who perceive their corporate culture negatively actively look for another job.
The common denominator: a mismatch between expectations, culture, and personality. These risks are predictable, however, not through intuition, but through data-based personality analysis.
Recognizing invisible red flags
Truly costly mistakes are rarely caused by obvious warning signs, but rather by personality patterns that remain invisible during interviews. AI-based methods based on the Big Five and the Entrepreneurial Capital developed by Zortify make these risks measurable.
Among other things, the Big Five show:
- how stable someone remains under pressure (emotional stability and frustration tolerance),
- whether the need for autonomy and organizational structure are compatible, and
- how well people cope with change, ambiguity, and high complexity.
Entrepreneurial Capital adds to this analysis with future-critical skills like resilience, self-efficacy, agility, and solution orientation – the very factors that determine long-term performance and retention.
In combination, the Big Five and Entrepreneurial Capital reveal the invisible red flags that trigger early attrition: personality and context mismatches, fragile stress profiles, and unrealistic expectations. AI provides a solid basis for decision-making where gut feeling fails.
Predicting retention with AI
Modern NLP-based methods analyze how people think, prioritize, and deal with uncertainty. This results in a reliable prediction for long-term retention.
Companies that use such data can reduce their misplacement rate by 30%. Often, avoiding a single misplacement pays for the entire technology investment.
Typical green flags in applicants include:
- A realistic self-assessment,
- Value congruence,
- A conscious decision to take on the specific role, and
- The ability to communicate needs and boundaries.
At the same time, companies benefit from presenting everyday work life in a blunt manner. The best talents prefer realistic descriptions. Surprises on the first day, by contrast, undermine trust and drive turnover.
The business case: Data-driven decisions save a lot of money
For a company with 50 hires, the picture is as follows:
- Mismatch rate without data-driven methods: 14%, corresponding to 7 mismatches
- Costs: 7 × 45,000 = 315,000 €
- With personality analysis: Mismatch rate 10%, corresponding to 5 mismatches
- Costs: 5 × 45,000 = 225,000 €
- Savings: 90,000 € per year with a technology investment of around 35,000 €
- ROI: 2.6x, payback in less than 5 months
In addition to the financial effects, companies benefit from more stable teams, greater knowledge retention, better performance, and employer branding that signals long-term loyalty.
What companies can do straight away
- Short term: Analyze past cases of employee turnover: What signs were already visible during the recruitment process?
- Medium term: Track retention by hiring channel and personality profile, measure cultural fit and personalize onboarding based on individual profiles.
- Strategically: Early implementation of legally compliant, transparent AI systems to minimize bias and hiring risks, especially in light of the EU AI Act.
Using AI to tackle talent shortages
The most costly mistakes in recruiting are not the candidates who drop out of the process, but those who are hired and resign a few months later. Bad hires are not an isolated HR issue, but a strategic business risk in the six-figure range.
Personality-based assessments have thus become a business-critical tool. Organizations that can predict turnover make better decisions – and win in a market where talent is the scarcest resource.
Prof. Dr. Florian Feltes
Prof. Dr. Florian Feltes is co-founder and co-CEO of zortify and a forerunner in AI-supported HR innovation. Together with his team, he develops intelligent personality diagnostics and helps companies identify the perfect candidates—without expensive assessments and without bias. His vision: a world in which every company can effortlessly form high-performance teams and create work environments that allow human potential to flourish.
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