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Turnover Contagion: Diagnosing, Causes, Possible Effects

“Will the last team member to leave please turn out the lights”

New year, new job.

January is the most popular month for employees to look for new opportunities. But that doesn’t have to mean starting the year with an epidemic of departures.

People leave their jobs for all sorts of reasons.

  • Personal – for instance when a family member needs to relocate.
  • Professional – to get more pay, a promotion, or make a career change.
  • And of course,
  • Organisational – when they are no longer required or suitable for their job.

Any thriving business will want to see a healthy level of turnover in its staff. But what if your people are leaving simply because their colleagues are leaving?

We call this the Turnover Contagion Effect (TCE) and it’s something that every business should care about.

Diagnosing Turnover Contagion

You may have experienced Turnover Contagion yourself. It’s that growing sense that “everyone” in your team is job hunting, and it’s been around for as long as people have worked together.

Your colleagues may not have told you directly that they’re searching. But when there’s a sudden spate of funerals, urgent repair visits or caring for holidaying parents’ goats (all true stories) you may get a sense that something’s up.

Then there are the colleagues who are cagey about letting you see their screens. And of course the ones who quite blatantly tell the rest of the team that it’s only a matter of time before they leave.

However confident and secure you may feel in your role and the organisation, it’s only natural to begin to question your position.

Have your colleagues spotted some major flaw in the business that you’ve overlooked? Do they know something you don’t? Should you put some feelers out there, just in case?

But if you’re observing that disintegrating team from the Human Resources department, you’re probably asking rather different questions.
How did TCE start? Can you stop it spreading further? And how can you prevent it from happening in the first place?

What causes the Turnover Contagion Effect?

Turnover contagion stems from co-workers sharing how they’re feeling and how they’re valued at work. When it’s positive it contributes to more productive working environments and more engaged workers. But when workers are looking around it breeds unrest – it becomes contagious. And once TCE starts it can be hard to stop.

And it seems to be getting worse nowadays, for a variety of reasons;

  • Lower unemployment rates globally make it much easier for your employees to find a new job, and feel more confident in looking for one. There’s also some evidence that the current political climate is discouraging people from looking outside their home countries. So once an employee starts to look, they may find that they are up against far fewer competitors on the shortlist.
  • Social media, and the web in general, have made it amazingly easy to browse for new jobs, even for those who are “not really” looking. LinkedIn is the most obvious place, but there’s a wealth of job sites and careers advice sites that can stir up job dissatisfaction. Social media also spreads the contagion. It’s always been obvious when an unexpectedly large number from one team leave, but now any employee who has reasonable internal connections can spot a trend.
  • Lack of job satisfaction also contributes. Just a few little shared problems in the magic combination that includes pay satisfaction, team relationships and support, communication across, up and down the organisation, the demands of the job, and opportunities for growth and training can add to the spread of TCE.
  • Poor job embeddedness in your company makes things even worse. Studies (1) show that a highly embedded employee is less likely to leave, and very likely to motivate co-workers to stay. A well-embedded employee has many connections within the organisation and the local community, and their job fits with other aspects in their life. The stronger those links, the more committed a worker is to the organisation. Leaving their job would mean sacrificing more than salary. They also risk the loss of friendships, community links and their sense of belonging. So a company where many workers are strongly embedded is less susceptible to TCE. When workers are poorly embedded, far more are ready to leave. They’ll be updating their resumes, watching job postings, applying for new positions, and that inevitably causes an increased individual turnover.

Add these together and you may also experience a fifth factor.

  • Damaged employer reputation. As awareness of increasing staff turnover grows, your reputation as an employer may take a hit. And from there it can become a downward spiral. Your employees notice that more people are on the move. They start to think there’s something wrong with the organisation. They conclude there’s something wrong with anyone who chooses to stay, and they start their own job hunts. The internal damage spreads rapidly over social and traditional media to the local community and across your industry, making it harder to persuade new people to work with you, as well as increasing turnover. It can even start to damage the reputation of the products or services you provide.

Why does Turnover Contagion Effect matter?

When your business starts to suffer from TCE you might think there’s an upside. A long-awaited clear out of rotten wood. A way to make savings on employee costs. A chance for re-organising a dysfunctional department. And yes, all those can be somewhat true.

But whenever you lose a team member there are costs, apart from the obvious ones of losing their production and having to recruit and train a replacement. And these costs far outweigh the benefits.

  1. You lose the training you’ve invested in that person.
  2. You lose their knowledge of your business and all the relationships they’ve built up, internal and external.
  3. You may have to ask other team members to take on their workload while you recruit and then get the new hire up to full productivity – with potential detriment to their normal work.

And as you lose more and more from a team you also risk the engagement and morale of all of their former colleagues. In fact, that’s the greatest risk of the Turnover Contagion Effect – that it spreads further.

As our recent White Paper says (2), “… failing to monitor and moderate turnover can result in leaver behaviour becoming a cultural mainstay of a particular role type, or an accepted norm in the business as a whole.”

Here are 11 Essential Things to Know About Employee Turnover

A Possible Cure for Turnover Contagion Effect

Like most infectious diseases, TCE is easier to prevent than it is to cure. But if you do find that you’re already suffering from TCE, there are a few dos and don’ts.

Don’t

Reduce Social Communication

It’s certainly NOT effective to apply one commentator’s suggestion of trying to “…combat the social environment that stimulates turnover”.

That social side of work may be spreading the contagion, but it’s also the foundation of the strong sense of belonging to a business and a community that encourages people to stay.

Trying to move desks further apart, ban Tweets and Facebook posts or prevent canteen gossip will cause more problems than it solves.

Do

Instead, it may be more productive to consider the root cause of the lack of organisational commitment.

You should be asking:

  • Are supervisors and managers actively supporting the teams experiencing Turnover Contagion?
  • Should you be finding ways to make your business feel a true part of your local community or your industry?
  • Are there working practices and benefits that could be flexed to make workers’ life and work more balanced?
  • Could community engagement or social responsibility programmes help?

… and Probable Prevention for Turnover Contagion Effect

But as mentioned, it’s easier to prevent than cure, so better still is to start at the beginning.

Think about who you hire and how you look after them when they start work.

Are you hiring people who align well with your company culture and values? Are you hiring people with the personality and behavioural traits that make them more likely to stay and perform in your company?

If you’re unsure, that’s where you should start. Try to find out what makes people stay with your organisation. What do your long tenure employees have in common? With your newfound knowledge of your ideal candidate, identify the applicants that fit the bill and prioritise them in your shortlist.

This may sound like a difficult task, but nowadays there are even analytics and technology solutions that can do this for you.

Once you’ve found the right people you still need to look after them and help them commit to your organisation. Introducing each new hire to your company in a motivating induction
process, where they get to know other workers, will give them a strong start.

As they become truly embedded they’re your best hope for preventing future outbreaks of Turnover Contagion.

At Sapia, we help you find your shortlist of candidates who are more likely to stay in your specific business. We combine your data with our workforce and data science to scientifically screen your applicants and predict who is more likely to succeed. And that can also include how well those candidates will fit into your team, your organisation and your community.

References

(1) Felps et al. “TURNOVER CONTAGION: HOW COWORKERS’ JOB EMBEDDEDNESS AND JOB SEARCH BEHAVIORS INFLUENCE QUITTING” © Academy of Management Journal 2009, Vol. 52, No. 3, 545–561


You can try out Sapia’s FirstInterview right now, or leave us your details to book a personalised demo


 


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Reinventing the Competency Framework: A Data-Driven Approach for the AI Era

We can’t hide from reality anymore. Talent needs are shifting overnight, and AI is redefining what it means to work. Traditional talent frameworks are no longer fit for purpose. At Sapia.ai, we believe the future of talent strategy lies in a smarter, fairer, and more adaptive way of defining what great looks like. 

Our AI hiring platform is built on the largest proprietary dataset of interview answers globally – we’re a data company at heart, and we’ve seen the power of data-driven people methodology in transforming how organisations hire and retain good talent.  

So, when it came to building a new Competency Framework that could be leveraged globally for hiring for any role at any scale, of course, we used a ground-up, data-led methodology that bridges the gap between organisational psychology and AI.

Why Rethink Competency Frameworks?

Conventional frameworks are typically crafted through expert interviews and focus groups. While valuable, they tend to be subjective, static, and too slow to keep pace with evolving job demands. As roles become more fluid and technology augments or replaces task-based skills, organisations need a new way to understand the human capabilities that genuinely matter for performance.

We wanted to identify enduring, job-agnostic competencies that reflect what drives success in a modern workplace – capabilities like adaptability, resilience, learning agility, and customer orientation.

(Why competencies and not just skills? Read why here.)

Our Approach: Where AI Meets I/O Psychology

Sapia.ai’s methodology is rooted in the science of human behaviour but powered by cutting-edge AI. We asked two core questions:

  1. Can we make competency discovery agile, scalable, and evidence-based?
  2. Can we use AI to automate the process without losing the rigour of traditional psychology?

The answer to both: yes.

We began with a rich dataset of over 37,000 job descriptions across industries and role types. Using large language models (LLMs) and advanced NLP techniques, we extracted over 200,000 behavioural descriptors. These were distilled down through a four-step process:

  1. Behavioural Descriptor Extraction
  2. Clustering and Labeling
  3. Cluster Analysis by I/O Psychologists
  4. Thematic Categorisation and Definition of Competencies

This resulted in a refined list of 25 human-centric competencies, each with clear behavioural indicators and practical relevance across a wide range of roles.

Built to Scale. Built to Adapt.

Our framework is intelligent, but importantly, it’s adaptive. Organisations can apply this methodology to their own job descriptions to discover custom competencies. This bottom-up, role-data-led approach ensures alignment to real work, not just theoretical models.

And because the framework integrates directly with our AI-powered hiring tools, you get a connected system that brings your talent strategy to life. 

Our framework comes to life in the following tools: 

  • Job Analyser – Starting with a job description, it creates a unique competency profile for each role to build tailored structured interviews in seconds.
  • Structured Chat-based Interviews that assess candidates’ responses according to the competency profile for consistent candidate assessment.
  • Talent Insights Reports from every interview with deep reasoning and explainability for fair and objective hiring decisions.
  • Phai Career Coach for internal mobility and employee growth that considers their competency strengths and career aspirations.

The Future of Talent Acquisition & Development is Competency-First

Skills alone cannot predict success. Competencies do. As AI continues transforming how we work, Sapia.ai’s Competency Framework offers a scalable, scientific, and fair foundation for hiring and developing the talent of tomorrow.

Want to see how it works? Download the full framework.


 

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It’s Time to Stop Hiring for Skills, and Start Hiring for Competencies

If you’re a CHRO or Head of Recruitment at an enterprise today, chances are you’ve been inundated with messages about the importance of “skills-based hiring.” LinkedIn’s recent Work Change Report (2025) is full of compelling data: a 140% increase in the rate at which professionals are adding new skills to their profiles since 2022, and a projection that by 2030, 70% of the skills used in most jobs today will have changed.

This is essential reading. But there’s a missed opportunity: the singular focus on “skills” fails to acknowledge the real metric that talent leaders need to be using to future-proof their workforce — competencies.

Skills vs Competencies: The Crucial Distinction

  • Skills are task-specific capabilities. Think Python programming, Excel, or even negotiation.

  • Soft skills refer to interpersonal or behavioural qualities like adaptability, communication, and resilience.

But skills on their own — even soft ones — are generic, disjointed, and often disconnected from real-world performance. In contrast:

  • Competencies are clusters of skills, knowledge, behaviours and abilities that are observable, measurable, and context-specific.

Put simply, competencies answer the all-important question: Can this person apply the right skills, in the right way, at the right time, to deliver results in our environment?

Why Competencies Matter More Than Ever

The Work Change Report outlines a future where job titles are fluid, roles evolve quickly, and AI is a constant disruptor. This creates three massive challenges for hiring at scale:

  1. Roles are changing faster than static skill frameworks can keep up

  2. Job candidates may have non-linear, cross-functional backgrounds

  3. The shelf-life of technical skills is shrinking rapidly

Skills alone don’t tell us whether someone can succeed in a role that will look different 12 months from now. But competencies can. Because they measure not just what a person knows, but how they apply it.

Adaptive Talent: The New Competitive Advantage

The LinkedIn report highlights a critical insight: organisations now prioritise agility in entry-level hiring. And there’s a good reason for that. With professionals expected to hold twice as many jobs over their careers compared to 15 years ago, adaptability is not just a nice-to-have. It’s core to success.

But you can’t measure agility with a keyword on a CV. You measure it by looking at competencies like:

  • Learning agility

  • Change resilience

  • Cross-functional collaboration

  • Problem-solving in ambiguous contexts

When you shift the focus away from skills to behavioural competencies that can be defined, observed, and assessed in structured ways, you open yourself up to a much more dynamic and more useful way of managing talent.

Building a Competency-Based Talent Framework

To hire effectively at scale, particularly in a technology-driven world of work, talent leaders must shift their lens:

  1. Define Role-Specific Competencies: Move beyond job descriptions based on qualifications or vague skill sets. Break roles down into measurable competencies that reflect current and emerging performance expectations. This step is crucial for organisations to be able to accurately assess role-fit in the next stages. Sapia.ai does this automatically, taking job descriptions and building role-specific competency models in seconds.

  2. Assess Competencies Fairly and Objectively: Use structured behavioural interviews, ideally at scale. These provide a much more accurate picture of a candidate’s readiness than self-reported skills or credentials. Sapia.ai’s AI powered interviews enable competency assessment, at scale.

  3. Build Pathways for Development and Internal Mobility: A competency framework makes it easier to identify transferable strengths, development gaps, and future-fit potential. It gives employees clarity on how to grow within the business. Using an AI-powered coach can help ensure that talent is being continuously developed against the organisation’s competency framework.

The Future of Work Requires Depth, Not Just Breadth

LinkedIn’s data shows that people are learning more skills more quickly than ever. But the real question for talent leaders like you is: Are those skills being applied in ways that drive value? Are we hiring for task proficiency or performance?

The truth is that the organisations that will thrive in an AI-driven, skills-fluid economy aren’t the ones chasing the next hot skill. They’re the ones designing systems to identify, develop and scale competence.

Keen to Shift to Competencies, but Lacking a Framework? 

Sapia.ai has developed a comprehensive Competency Framework using a data-driven approach. Download the full paper here.


 

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The AGC Debate: Are AI-Written Interview Answers a Red Flag or Smart Strategy?

Every day, we read stories of increased fake or AI-assisted applications. Tools like LazyApply are just one of many flooding the market, driving up applicant volumes to never-before-seen levels. 

As an overwhelmed hiring function, how do you find the needle in the haystack without using an army of recruiters to filter through the maze?

At Sapia.ai, we help global enterprises do just that. Many of the world’s most trusted brands, such as Qantas Group, have relied on our hiring platform as a co-pilot for better hiring since 2020. 

Our Chat Interview has given millions of candidates a voice they wouldn’t have had – enabling them to share in their own words why they’re the best fit for the role. To find the people who belong with their brands, our customers must trust that their candidates represent themselves. Thus, they want to trust that our AI is analysing real human answers—not answers from a machine.  

The Rise of GPT 

When ChatGPT went viral in November 2022, we immediately adopted a defensive strategy. We had long been flagging plagiarised candidate responses, but then, we needed to act fast to flag responses using artificially generated content (‘AGC’). 

Many companies were in the same position, but Sapia.ai was the only company with a large proprietary data set of interview answers that pre-dated GPT and similar tools: 2.5 billion words written by real humans. 

That data enabled us to build a world-first:- an LLM-based AGC detector for text-based interviews, recently upgraded to v2.0 with 99% accuracy and a false positive rate of 1%. An NLP classification model built on Sapia.ai proprietary data that operates across all Sapia.ai chat interviews.

Full Transparency with Candidates

Because we value candidate trust as much as customer trust, we wanted to be transparent with candidates about our ability to detect artificially generated content (AGC). As an LLM, we could identify AGC in real time and warn candidates that we had detected it. 

This has had a powerful impact on candidate behaviour. Since our AGC detector went live, we have seen that the real-time flagging acts as a real-time disincentive to use tools like ChatGPT to generate interview responses. 

The detector generates a warning if 3 or more answers are flagged as having artificially generated content. The Sapia.ai Chat Interview uses 5 open-ended interview questions for volume hiring roles, such as retail, contact centre, and customer service, and 6 questions for professional roles, such as engineers, data scientists, graduates, etc.

Let’s Take a Closer Look at the Data… 

We see that using our AGC detector LLM to communicate live with candidates in the interview flow when artificial content has been detected has a positive effect on deterring candidates from using AI tools to generate their answers. 

The rate of AGC use declines from 1 question flagged to 5 questions – raising the flag on one question is generally enough to deter candidates from trying again. 

The graph below shows the number of candidates, from a total of almost 2.7m, that used artificially generated content in their answers.  

Differences in AGC Usage Rate by Groups 

We see no meaningful differences in candidate behaviour based on the job they are applying for or based on geography.

However, we have found differences by gender and ethnicity – for example, men use artificially generated content more than women. The graph below shows the overall completion ratios by gender – for all interviews on the left and for interviews where the number of questions with AGC detected is 5 or more on the right. 

Perception of Artificially Generated Content by Hirers. 

We’re curious to understand how hirers perceive the use of these tools to assist candidates in a written interview. The creation of the detector was based on the majority of Sapia.ai customers wanting transparency & explainability around the use of these tools by candidates, often because they want to ensure that candidates are using their own words to complete their interviews and they want to avoid wasting time progressing candidates who are not as capable as their chat interview suggests.  

However, some of our customers feel that it’s a positive reflection of the candidate, showing that they are using the tools available to them to put their best foot forward. 

It’s a mix of perspectives. 

Our detector labels it as the use of artificially generated content. It’s up to our customers how they use that information in their decision-making processes. 

This concept of having a human in the loop is one of the key dimensions of ethical AI, and we ensure that it is used in every AI-related hiring product we build. 

Interested in the science behind it all? Download our published research on developing the AGC detector 👇

Research Paper Download: AI Generated Content in Online Text-based Structured Interviews

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