How to Know If It Is Time to Leave Your Job

Abstract

This article is about how to know if it is time to leave your job, and how far research on why people quit can help. Three pieces of research bear on it. A meta-analysis of the antecedents of voluntary turnover (Rubenstein and colleagues, 2018) found that thoughts of leaving and job search were among the strongest predictors of leaving, and that many relationships depend on context. A study of job embeddedness (Mitchell and colleagues, 2001) found that links, fit and sacrifice predicted staying beyond satisfaction and commitment. A conceptual paper (Lee and Mitchell, 1994) models leaving as four distinct decision paths. All three describe who leaves and how, not whether leaving is right for you. None studied finance staff. The three steps at the end are practical readings, not tested methods. This article is not career, financial, legal or medical advice.

The Sunday evening feeling

It is Sunday evening and the dread has started again, earlier than last week. A recruiter's message has sat in your inbox since Thursday.

You have been telling yourself that you will decide after the year-end. But you keep asking the same thing in the shower and on the train: is it time to leave your job, or is this just a bad season?

Time to leave your job: what is the evidence?

The research cited here cannot tell you whether to go. It describes who tends to leave, what keeps people in place and how leaving unfolds. That is useful for thinking about your own decision, but it is not a verdict on it. The studies used large samples, two employee samples and a theoretical model, and none was limited to finance. The next three sections cover what each one found. None of them tested the three steps at the end.

What a meta-analysis of voluntary turnover found

Rubenstein, Eberly, Lee and Mitchell (2018) combined research on the antecedents of voluntary turnover in three steps. They ran a meta-analysis, tested moderators, and discussed where the field should go. The abstract says the results show newer predictors and updated effect sizes for traditional ones, and that many relationships are context-dependent.

The authors' accepted manuscript reports 316 articles, 57 predictors and about 1,800 effect sizes. Among the strongest links with leaving were thoughts of withdrawing from the job (rho = .56) and job search (rho = .40). Job satisfaction (rho = -.28) and organisational commitment (rho = -.29) were weaker. Sex, education and ethnicity were close to zero. This is summarised from the published abstract and the accepted manuscript.

Read your own Sunday evenings through this. Thinking about leaving is among the strongest signs that people leave, which is close to restating the question. This is an inference. It predicts who leaves on average, and it does not show whether leaving was right for them.

What a study of job embeddedness found

Mitchell, Holtom, Lee, Sablynski and Erez (2001) introduced job embeddedness, which has three parts. These are links to other people, teams and groups, fit with the job, organisation and community, and the sacrifices a person would make by leaving. They developed the measure with two samples.

Job embeddedness predicted both intent to leave and voluntary turnover. It explained significant additional variance beyond job satisfaction, organisational commitment, job alternatives and job search. The abstract does not give the sample sizes or the results in numbers. This is summarised from the published abstract.

Read what holds you in place through this. People stay because of links, fit and what they would give up, and not only because they are satisfied. This is an inference. The study explains staying and leaving, and it does not say whether staying is good for the person.

What a model of how people leave proposed

Lee and Mitchell (1994) proposed the unfolding model of voluntary turnover. It uses ideas from decision making, statistics and social psychology. It models the turnover process as four distinct decision paths, each with its own focus, psychological processes and external events.

The authors suggest five specific contributions of the model and make recommendations for testing it and for future research. This is a theoretical paper, so the abstract reports no data. This is summarised from the published abstract.

Read the recruiter's message through this. People may leave by different routes, and an outside event can start one of them. This is an inference. The abstract does not describe the four paths in detail, and a model is a way of thinking about the question, not a test of it.

Time to leave your job: three steps

None of these is a tested method, and none was studied in finance teams. They combine what the research points to with ordinary practice. Where a step goes beyond the research, it says so.

1. Separate this job from this period. A hard season is not the same as a wrong job. List what will change in the next three months, and what will not. This is a judgement, and no study cited here tested this step. For instance: "The close ends in two weeks, the new system goes live in January, and my manager's style will not change."

2. Name the one thing that would change your answer, and ask for it with a date. Make the request first, so that the decision rests on what you learned. This is a judgement, and no study cited here tested this step. For instance: "If I could hand over the Friday reporting, I would stay. I will raise it by 20 November and decide by 15 December."

3. Write down what you would leave behind and what you would move toward. The embeddedness study counts links, fit and sacrifice, so include them. Compare the two lists and look at whether you are moving toward something or only away from something. This is a judgement, and no study cited here tested this step. For instance: "Behind: my team and the flexible hours. Toward: a bigger scope and a manager I respect."

If exhaustion is part of the picture, Burnout in Finance: Why High Performers Hit the Wall goes into that. For the question of whether rest is enough, there is Does a Holiday Cure Burnout? Why the Relief Fades So Fast. When you have not said what you think, see Why You Stay Silent When You Disagree With Your Boss. If the hours are the reason, Long Working Hours: What Research Links to 55+ Hours a Week looks at that. And Coaching or Therapy? How to Choose When Work Wears You Down is about what kind of support to look for.

Questions People Ask

Does wanting to leave mean I should leave?

Not by itself. In the meta-analysis, thoughts of leaving were among the strongest signs that people leave, but that describes who leaves and not who should. Whether to go is a judgement that only you can make.

Should I leave before I have another job?

The studies cited here did not test that. It is a financial and personal decision. Check your contract, your notice terms and your savings, and take advice if you need it. This article is not financial or legal advice.

How long should I wait before I decide?

The studies cited here did not test waiting periods. Setting a date for the decision is a judgement. It can keep the question from drifting, and the date can be moved if you learn something new.

Can coaching help me decide?

Coaching is educational support for work patterns. It can help you sort what belongs to the job from what belongs to the period, and think through your options. It is not treatment, and it will not make the decision for you. No study cited here tested coaching.

When it is more than a hard decision

A hard decision is one thing. It is more when you feel numb, persistently low or anxious, when you cannot sleep, when work feels hopeless, or when you notice physical symptoms. In those cases talk to your doctor, your occupational health service or a qualified mental health professional before you decide. If you ever think about harming yourself, contact emergency services or a crisis line in your country at once. This article is not career, financial, legal or medical advice. Coaching is educational support for work patterns. It is not treatment and not a substitute for it.

Sources

• Rubenstein, A. L., Eberly, M. B., Lee, T. W., & Mitchell, T. R. (2018). Surveying the forest: A meta-analysis, moderator investigation, and future-oriented discussion of the antecedents of voluntary employee turnover. Personnel Psychology, 71(1), 23–65. DOI: 10.1111/peps.12226 (Summarised from the published abstract and the authors' accepted manuscript.)

• Mitchell, T. R., Holtom, B. C., Lee, T. W., Sablynski, C. J., & Erez, M. (2001). Why people stay: Using job embeddedness to predict voluntary turnover. Academy of Management Journal, 44(6), 1102–1121. DOI: 10.5465/3069391 (Summarised from the published abstract.)

• Lee, T. W., & Mitchell, T. R. (1994). An alternative approach: The unfolding model of voluntary employee turnover. Academy of Management Review, 19(1), 51–89. DOI: 10.5465/AMR.1994.9410122008 (Summarised from the published abstract.)