A clearer understanding of the costs (and benefits) of staff hiring and turnover could affect planning and decision-making in animal advocacy organisations. Google and Google Scholar searches were conducted to identify research on these costs. One key finding was that direct hiring costs are much smaller than the less visible and measurable effects of turnover on an organisation’s productivity; once these costs are accounted for, turnover costs thousands of dollars per lost employee. Given that turnover rates may be around 20% annually in nonprofits, this can amount to substantial costs. There is also evidence from several meta-analyses that higher turnover is correlated with lower organisational performance, though the overall effects of turnover on performance may be very small.
As we’ve noted before, Animal Advocacy Careers (AAC) could focus its services on improving recruitment and retention in the animal advocacy movement and its most effective organisations. A clearer understanding of the costs (and benefits) of staff hiring and turnover could therefore help AAC to prioritise between possible actions to help the movement. For example, it could affect our understanding of how valuable it is to offer services that decrease staff turnover or hiring costs in organisations. Additionally, AAC could offer services such as headhunting for specific roles that, while potentially good for the movement overall, might actually increase turnover rates in organisations; this research could help bring clarity to the overall usefulness of offering such services.
This research may also be of interest to managers, leaders, and human resources staff in animal advocacy organisations, since it may help to inform their own planning and decision-making.
Hence, AAC undertook a brief overview of research into the costs of hiring and turnover.
Searches of Google and Google Scholar were conducted. The first 2-20 pages of results were skimmed or reviewed for each search term. There were not strict inclusion and exclusion criteria and the likely relevance of research was assessed predominantly by the phrasing of the title.
For some of the searches, we focused on existing reviews and meta-analyses rather than on identifying all relevant individual studies. For other searches, where the relevant literature seemed to be much smaller, we looked through the most relevant-seeming individual studies.
The full results are available in the results spreadsheet.
Surveys and modelling of hiring and turnover costs
One type of identified research focused on asking specific groups of organisations about various aspects of their hiring processes and organisational practices, then using a formula to model the total turnover costs.
One key finding was that direct hiring costs, such as paying for advertisements and spending staff time interviewing candidates, may account for a relatively small proportion of the total real costs. Modelling by researchers suggests that adaptation costs account for a much larger proportion of the costs — two-thirds or more of the total costs, in the identified studies that measured such costs. This includes the lower productivity of the new hire (compared to the previous occupant of the role or what they will be able to achieve once they’ve fully adapted) while they learn about their role. It can also include direct training and onboarding costs. The importance of these less obvious (and less easily measured) costs means that we probably tend to underestimate the overall costs of staff turnover.
The research often focuses on contexts that are very different to the contexts of animal advocacy nonprofits, so we shouldn’t place much weight on the specific numbers identified in the research. However, these numbers might still give a ballpark estimate of the costs; they range from thousands to hundreds of thousands of US Dollars (usually in the high thousands).
These modelling studies focus on the costs of turnover, ignoring the potential benefits. Other researchers often distinguish between “voluntary” (employee-initiated) and “involuntary” (employer-initiated) turnover; involuntary turnover could plausibly be good for the organisation by removing underperforming employees. Researchers also sometimes distinguish “dysfunctional” and “functional” turnover — the former refers to the loss of high-performing or difficult-to-replace employees and the latter refers to other forms of turnover which are less costly (or even beneficial) for the organisation.
Correlations between turnover and performance
Another body of research analyses the correlations between turnover and measures of organisational performance. These measures can include anything from employee attitudes through to the financial performance of the organisation. Measures of financial performance are the most interesting because they should account for most direct and indirect effects that, in our context, would matter for animals at the organisational level.
Park and Shaw’s (2013) meta-analysis (which included 300 separate correlations) found that turnover rates had small, negative correlations with measures of organisational performance (𝗉 = –.15). That is, organisations with higher turnover rates perform worse than those with lower turnover rates. They found that “workforce productivity” (𝗉 = -.13, 61 studies) and “financial performance” (𝗉 = -.11, 52 studies) have smaller correlations with turnover than outcomes like “customer satisfaction” and “employee work attitudes,” but both correlations were statistically significant.
They found that “involuntary turnover” (e.g. the removal of bad employees) had a statistically insignificant, very small correlation with performance; it’s unclear whether the removal of bad employees can improve an organisation’s performance in certain circumstances. This evidence may reduce some readers’ confidence that actively seeking to remove bad employees is a worthwhile endeavour. Interestingly, they found that “reduction-in-force” turnover (downsizing, where “no replacement employees are planned and the departing employees are presumed to have been at least minimally competent”) had a similar negative correlation with performance as voluntary turnover.
However, in the same year, two other meta-analyses — Heavey, Holwerda, and Hausknecht (2013) and Hancock et al. (2013) — found much smaller correlations between turnover and some measures of performance; the latter paper found a “mean corrected correlation between turnover and organizational performance” of only –.03. It looks like some studies have begun to look into the reasons for this inconsistency, e.g. Lamrani and Zavosh (2018), but it seems too early to draw strong conclusions. Another major concern is that Park and Shaw’s (2013) observed correlations might be explained by poor organisational performance increasing turnover, rather than turnover causing poor organisational performance. This seems especially plausible in the case of reduction-in-force turnover. Nevertheless, we think it is still worth devoting some resources to addressing turnover.
The full list of references is available in the second tab of the results spreadsheet.
 For example, if one organisation was seeking a new head of operations, AAC might plausibly reach out to people in current operations roles to encourage them to apply; this might fill one (relatively difficult-to-fill) gap in the movement in one organisation but increase turnover in the other.
 The search terms used in Google Scholar were:
Turnover effects meta-analysis
Applicant numbers average.
Occasionally, research items that cited or were cited by key identified items were also reviewed. The search term used in Google was “hiring costs” OR “turnover costs”.
 The following criteria were used to decide which items to include:
Are the findings directly applicable or at least fairly comparable to the context of animal advocacy nonprofits?
Does the research item contain (or summarise) substantial empirical findings?
Is the research item unlikely to have been made predominantly redundant by subsequent research? Relevant factors affecting this criterion include the date of publication and any impressions we have of the thoroughness of the literature on the subtopic that it covers.
We did not exclude all items that failed to meet some of the inclusion criteria, if they seemed to perform especially well on others. These inclusion criteria were pre-planned.
 See footnote 5 below.
 Here are the main identified examples from academic research:
Blatter, Muehlemann, and Schenker (2012) found, in their research on Swiss companies, that average hiring costs were roughly $15,000 (10 to 17 weeks of wage payments). Of this, 29% was from “recruitment costs” (including costs for job postings, interviews, personnel costs, and external advisors) and the rest was from the “adaptation costs” (80 day average adaptation period, decline in productivity, direct training costs). The shares between these two categories of costs didn’t differ much by sector or occupation.
Muehlemann and Pfeifer (2016) found that, among German companies, recruitment costs (average just under $2,000 and 35% of the total) were lower than adaptation costs (~$3,650).
Jones’ (2008) research on the costs of turnover among registered nurses (RNs) suggests that “advertising/recruiting” ($3,378) and “hiring” ($2,679) again make up a smaller proportion of the total costs than “orientation/training” ($6,333), “newly hired RN productivity” ($7,169 for new RNs and $1,195 for experienced RNs) and “pre-turnover productivity” ($2,629).
Buchbinder et al.’s (1999) research on turnover costs for physicians again suggested that the total turnover costs ($236,383) were mostly explained by loss of productivity ($196,333, i.e. 83% of the total). This included “specific training costs of a new primary care physician, including, but not limited to, orientation costs, increased time seeing patients, and increased utilization of laboratory tests and radiologic procedures.”
Blake (2006) summarised that, “SHRM, the Society for Human Resource Management, estimated that it costs $3,500.00 to replace one $8.00 per hour employee when all costs — recruiting, interviewing, hiring, training, reduced productivity, et cetera, were considered. SHRM’s estimate was the lowest of 17 nationally respected companies who calculate this cost! Other sources provide these estimates: It costs you 30-50% of the annual salary of entry-level employees, 150% of middle level employees, and up to 400% for specialized, high level employees!”
These financial costs are converted into US Dollars using today’s exchange rates, for ease of comparability, but are not adjusted for inflation. I.e. the older the research, the more you would expect the reported numbers to be an underestimate of the costs, in today’s money. For the originally reported costs, see the results spreadsheet. Even when productivity is not accounted for, turnover costs may still be high. For example, Davidson, Timo, and Wang (2010) found just under $7,000 to replace each operational staff member in Australian hotels.
 An’s (2019) study suggests that “involuntary turnover has an inverted U-shaped relationship with organizational performance, first positive and then negative” and Rijamampianina (2015) found that “employee turnover rate significantly predicted financial and organizational performance through a cubic function.”
 Some attitudinal measures, such as employee satisfaction, might be important for animals insofar as they might affect longer-term burnout or retention of those employees within the wider animal advocacy movement; this wouldn’t be picked up in measurements of an organisation’s bottom line, but would still affect the movement’s overall chances and degree of success.
 This finding does not mean that such removals are never worthwhile, just that, when all correlations are combined, the total effects seem close to zero. It still seems plausible that, when managed well, involuntary turnover could improve organisational outcomes and that the meta-analytic results are close to zero because lots of involuntary turnover isn’t managed well (e.g. draconian or arbitrary firings of decent employees).
 Partly addressing this concern, Park and Shaw (2013) note that, “in two recent qualitative reviews, Hausknecht and Trevor (2011) and Shaw (2011) concluded that the causal relationship between total/voluntary turnover rates and organizational performance is more likely than the reverse, partly because empirical studies that have examined reverse causality empirically find much stronger results for our presumed causal sequence (e.g., Glebbeek & Bax, 2004; Ton & Huckman, 2008; Van Iddekinge et al., 2009). Supporting this, we show that lagged performance samples have a stronger negative association between turnover rates and organizational performance than do cross-sectional samples.”