The best employee retention strategy is the one that will most significantly reduce the volume of regrettable turnover – i.e. stop people who you want to stay from leaving. There isn’t a one-size-fits-all retention strategy, but there are ways to identify what the best strategy is for your organization and some key things to get right to reduce the likelihood of regrettable turnover. You have to apply these strategies to retain your best employees who are leaving.
The Best Employee Retention Strategy
The best employee retention strategy has four steps:
- Find out the types of people who intend to leave, and why
- Choose one or two areas to improve on and take action
- Measure your improvement
- Repeat
Employee retention under the Microscope
Working for an employee feedback company and being a psychology and data geek has some fairly obvious temptations – for one, there’s a pile of anonymised, valuable data at my fingertips that can help answer all kinds of questions.
The Culture Amp platform allows companies to collect data from onboarding, engagement, effectiveness, exit and many other surveys throughout the employee lifecycle, which means we can link this data to gather deep insights on a range of company issues. By linking employee engagement survey data with exit data, we’re able to help predict the types of people who are the most likely to exit your organization next and why.
Geeking out on Employee Retention Data
Surprisingly, not everyone spends their spare time exploring employee data correlation, but if you’re curious, here’s a quick tour. If not, skip over this bit and go down to, ‘Top 10 reasons people leave.’
I’m a survivor
When we look at engagement data correlated with exit data, we talk about favourable, neutral and unfavourable survival rates. It all sounds a little extreme, but obviously, we’re just talking about survival of employment, rather than survival of the person. They’re probably quite healthy and happy, albeit perhaps working somewhere else (maybe with a competitor?).
- A favourable survival rate tells us the percentage of employees who rated a question favourably (agree or strongly agree) who stayed with the organization
- A neutral survival rate tells us the percentage of employees who rated a question neutrally (they didn’t agree or disagree) who stayed with the organization
- An unfavourable survival rate tells us the percentage of employees who rated a question unfavourably (disagree or strongly disagree) who stayed with the organization
By comparing the favourable, neutral and unfavourable survival rates, we can understand how much impact the issue explored by the question has on retention – this is reflected in the retention driver score for each question.
Survival curves
Another way to look at drivers of retention is to graph survival curves. This tracks the impact of drivers over time. As you can see in this graph for the question: I believe there are good career opportunities for me at [Company], 72% of people who had unfavourable responses to the question stayed, whilst 84% who had neutral responses stayed. It’s considered a moderate driver because people need to see it as unfavourable for it to have a significant impact on their decision to leave. As you can see, the gap between the neutral and favourable responses is small (I’d consider it statistically insignificant).
Taking a look at the question: I am proud to work at [Company], we can see that it’s a strong driver of retention. The neutral and unfavourable lines track together, and there’s a significant gap between them and the favourable response line. If people are proud of their organization, they’re far more likely to stay than if they aren’t proud or are impartial.
Often, survival curves can also help us disprove popular ideas about why people leave organizations. For the question: I believe my benefits package is equal to or better than what is offered by similar employers, you can see that the favourable, unfavourable and neutral lines track together. This aspect of employment is having very little impact on retention.
Top 10 reasons people leave
Let’s take a look at the top ten reasons people leave as identified by linking data from engagement and exit surveys. This data comes from the survey results of employees at New Tech organizations. See below for the top 10 drivers of retention and their driver retention scores.
- [Company] motivates me to go beyond what I would in a similar role elsewhere (24%)
- I am proud to work for [Company] (20%)
- I am happy with my current role relative to what was described to me (20%)
- I believe there are good career opportunities for me at [Company] (17%)
- I know how my work contributes to the goals of [Company] (17%)
- I would recommend [Company] as a great place to work (16%)
- I rarely think about looking for a job at another company (16%)
- I have confidence in the leaders at [Company] (12%)
- We have enough autonomy to perform our jobs effectively (12%)
- [Company] is in a position to succeed over the next three years (11%)
If you had the same top ten drivers for your company – which would you choose to focus on, and what would you do?
Some drivers, like the first around motivation, the sixth around recommending the company as a great place to work, and the seventh around looking for another job will be improved by working on the other aspects in the list, and improving employee engagement overall.
If you have a low score for number three, regarding how a role compares with what was described, you may want to check your job ads for hyperbole. There’s no point promising the world to a great candidate if you can’t deliver – they’ll just leave. It’s worthwhile checking in with new starters after onboarding to see how the reality of the job compares with their expectations.
Number 4, relating to career opportunities is a common driver of retention – together with other aspects of learning and development. Depending on the size of your business you may want to consider formal career development paths. Even initiatives as simple as ensuring all roles are advertised, and proactively communicated internally as well as externally can make a difference.
Communication is a common theme in most engagement and retention results. People want to know the company’s goals, how they’re tracking against them, and how their job is contributing. This is reflected in 6 and 10. Having confidence in the leaders (8) can also be improved by sharing how decisions are made and being open about progress.
Autonomy (9) is highly valued by many employees and as we can see, drives retention. People’s expectations of how they’re managed are evolving and we must bring our managers with us by providing up-to-date training. It’s been a long time since Douglas McGregor presented his Theory X and Theory Y thinking – essentially suggesting that so long as people are able, they will do the right thing. This shift from managers micromanaging to enabling continues to roll out.
Demographics
Retention data also allows us to investigate trends along demographic lines – and as with much demographic data – the results for this dataset were troubling.
Gender
One worrying finding, that matches the findings of other researchers, was that women were 69% more likely to leave a tech company than men. The post-survey exit rate was 8.3% for women vs 4.9% for men (N.B. This is not an annual rate which would probably be higher).
Amongst people who left their company, women who left were significantly less likely to feel there was open two-way communication than men who left. Women were also far less likely to feel that work was divided fairly in their team or area of the company.
These findings correspond well with previous analyses we have conducted using our New Tech benchmark data. However, being able to predict the most common reasons women are likely to leave, allows companies that see lower scores on these issues in their surveys to potentially take targeted action and help prevent some women from leaving.
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Age and tenure
The most common groups of people who left tech companies were those who have been with the company between two to four years and aged between 25 and 34 years.
People who are leaving are 29% more likely to be 25-34 years old.
Leaving is:
33% more likely if they’ve been with you for 6-12 months
31% more likely if they’ve been with you for 1-2 years
45% more likely if they’ve been with you for 2-4 years
Who’s doing a great job?
One organization I worked with to help improve employee retention is Box. We used Culture Amp employee engagement survey data collected from Box employees and compared responses between employees who stayed and employees who voluntarily left over the 18 months following the survey. The analysis was conducted by Culture Amp using de-identified aggregate data to ensure employee confidentiality was maintained.
Among our Employee Engagement Index questions, we found the best predictor was whether people could still see themselves at the company in two years – no huge surprise. Boxers who stayed were 28% more likely to say they could still see themselves at Box in two years.
This finding supports the ongoing use of direct retention-type questions in any employee engagement index. Interestingly, when we compared the two groups’ responses to whether they would recommend Box as a great place to work there was only a 12% higher result for those who stayed. While positive to see this narrow gap, the result suggests that using this Net Promoter type question alone may not be optimal if you want to predict retention.
Box’s top drivers of retention were:
- People cooperate to get the job done
- Feel like part of a team
- Believe there are good career opportunities for them at Box.
As you can see – there are a couple of new ones unique to Box that don’t show up in the aggregate all-New Tech data – this is the strength of doing your research, acting, and measuring improvement.
