Introduction

• The pandemic has changed the way people work, although the potential arrival of large scale vaccination means a return to the office (of some form) is on the horizon
• Virtually all companies had to adapt very rapidly in spring 2020, and despite some teething problems, most are now coping well with remote work
• There is a wide range of views on the efficacy of working from home (WFH), and it is fair to say that some groups have enjoyed it more than others
• A number of surveys have been carried out to ascertain willingness to return to the office in the mid-term, although none have specifically (to our knowledge) focused on the actuarial market; this is the gap we are trying to address
• We will not be providing an opinion on the efficacy of WFH; rather we have tried to report (as neutrally as possible) what our survey respondents have expressed on aggregate
• This survey should NOT be seen as a way to press a “pro-WFH” or “anti-WFH” agenda, nor should it be seen as an attempt to reinforce or present certain stereotypes (related to gender, parenthood etc). Where differences exist, we have tried to put forward an explanation where possible.

Executive Summary

• We surveyed over 565 catastrophe modelling and exposure management professionals (for simplicity we will use the term CatEx) in the first 3 weeks of Jan 2021, with 80 responses
• Our aim was to understand their work from home (WFH) preferences when an eventual return to the office happens; the survey questions can be found here
• Women intend, on average, to work from home (WFH) more than half a day extra compared to men (average female WFH intentions of 3.1 days/week vs average male intentions of 2.5 days/week WFH)
• Very few women intend to return to the office full time, or even 4 days a week (equivalent to 0-1 WFH); in fact the vast majority would want 2 days in the office or less (ie 3 or more days/week WFH)
• Respondents of all ages showed significant appetite to WFH for large parts of the week, but there don’t appear to be very large differences across different ages (ie younger respondents are just as likely to ask for WFH as older ones)
• Average Employer satisfaction scores were slightly higher for women (8.0) vs men (7.4)
• We only surveyed CatEx professionals, and so the findings should not extrapolated to other job families. That being said, we have recently carried out the exact same survey with over 1100 UK-based general insurance qualified actuaries and the findings were very similar (female WFH of 2.5 days/week, male WFH of 3.1 days a week, with similar demographics in terms of age spread)

High level statistics

Please note the following:

• “Mean” refers to the mean (average) number of desired days WFH
• “StDev” refers to the standard deviation of desired days WFH
• “Avg” is shorthand for average (ie mean)
• “Carers” is another way of saying the respondent has dependents; ie, of all our male respondents, 53% had caring responsibilities; of all our female respondents, 50% had caring responsibilities
• “Avg Emp Score” is the average score given to the “How likely are you to recommend working for your current employer”; it is on a range of 1-10, and akin to a “Net Promoter Score”, where those scoring 9 or 10 are considered “Promoters”
• We asked respondents for their gender, and offered 4 options: Man/Woman/Prefer not to say/Non-binary. No one selected “Non-binary” or “Prefer not to say”

Results by gender and age

In the chart, please note that men are coloured orange and women light blue. The larger the bubble size, the higher number of respondents of that particular age with that specific WFH preference.

Age could influence WFH preferences but there does not appear to be a strong relationship between these two variables within our responses. Preferences at both extremes are worth noting though:

• Relatively few people expressed an “extreme” choice (ie 0 or 5 days WFH)
• Only one respondent actually wanted 0 days WFH (ie 5 days in the office)
• Younger women (30 or under) seemed to prefer 2 or 3 days WFH
• Younger men (30 or under) seem to have a spread of preferences
• Men between 30 and 40 seemed to prefer 3 days WFH, but 2 days was very strong as well
• We did not have many female responses in the 30-40 range, an important demographic, which is limiting for our analysis

Results by gender and dependents

One of our questions asked respondents if they had dependents or caring responsibilities. We can make the following observations:

• There wasn’t a single male respondent that wanted 0 days WFH (ie 5 days in the office)
• Men without dependants seem to overwhelmingly prefer 3 days WFH; among men with dependents, both 2 and 3 days WFH seemed about even and comprised most of the responses for that segment
• In the women without dependents segment, the highest nummber of responses was received for 2 days/week; among women with dependents, most respondents went for either 2 or 3 days/week
• Taking all men into account, 3 days WFH seems to be most prevalent; for all women, it was a close run contest between 2 and 3 days WFH, with 2 days being marginally more popular overall

Employer satisfaction score

Our survey asked how likely respondents were to recommend working for their employer, on a scale of 1-10. Responses can be thought of as an employer “Net Promoter Score”:

• respondents scoring 0-6 can be thought of as “Detractors”; they are likely to complain about their employer
• respondents scoring 7-8 can be thought of as “Passives”;
• respondents scoring 9-10 can be thought of as “Promoters”; they are likely to promote working for their employer

Whilst there isn’t a clear relationship, nonetheless, we observe that very few detractors want 0 or 1 days WFH; in other words, very few detractors want to spend extensive time at home. This is not the case with passives or promoters, who show a good spread of willingness to work in the office full time (ie 0 days WFH) all the way through to the other end of the spectrum (5 days WFH, ie a full time home worker). Also observe how few people want 0 or 5 days WFH.

It is also worth noting that no detractors wanted to 5 days a week WFH - perhaps they’re not keen on their employer but still want to come in every now and again (unhappy but not unhappy enough to avoid the office altogether).

The p-value for the difference in mean employer satisfaction rating between men and women is 0.0943311 and in other words is not statistically significant (ie there’s a 15% chance it could have occurred simply by chance).

Results by prior experience of WFH

We asked all respondents to also note how much time they had spent WFH pre-pandemic. Responses were captured as free text and then manually coded, using mid-way points where a range was given (eg if someone said “1-2 days a week”, we would code it manually as 1.5).

On the chart we have plotted the 45 degree line; the line represents responses where the desired WFH going forward is the same as pre-covid. Points “above the line” should be interpreted as “respondents who want to spend LESS time WFH compared to previously” (ie more time in the office). Points “below the line” should be interpreted as “respondents who want to spend MORE time WFH comapred to previously” (ie less time in the office).

It is striking that with the exception of a few responses that were “on the line” (ie wanting as much WFH as previously), virtually everyone else wanted more WFH compared to what they had previously done.

Concluding comments

I was very pleased with the overall response to my WFH intentions survey, and intend to run it again (perhaps with slightly different questions) when the pandemic allows a gradual return to the office.

One conclusion is that women and men have quite similar expectations on how many days they would like to spend in the office. I would note that unlike our survey for actuaries (where the findings were statistically significant at virtually every level), the findings here are NOT statistically significant (likely due to the smaller sample size; the actuarial survey had 174 responses, this one only 80). There are a number of non-parametric tests that can be used and for example the p value for the unpaired two-sample Wilcoxon test for the difference in mean WFH between men and women is 0.2872181. In other words, there is a 29% chance that the difference in mean WFH between men and women could have occurred by chance alone. Whether this is important to you is another matter. As a comparative, the same p-value for the actuarial WFH survey was zero to 4 decimal places.

There also doesn’t appear to be a strong relationship between employer satisfaction scores and WFH preferences. More satisfied employees might be willing to spend more time in the office, however, the opposite argument could also be made - employees could be happy BECAUSE they’re not spending much time in the office. We also have to remember that everyone is WFH right now, and employee satisfaction scores could well change if/when a wholesale return to the office happens. Indeed, satisfaction scores could feasibly go up OR down; some might be feeling more satisfied because they’re back in the office, and others may feel more miserable at the thought of having to do a commute again.

One aspect that we did not survey was seniority in role - it could be the case perhaps that more senior personnel would express a stronger preference for less WFH (ie more time in the office), although we simply don’t know. We acknowledge total WFH is likely to create problems in certain aspects of team work and collaboration - “white-boarding ideas” is very difficult via Zoom. Perhaps the future will see something akin to “compressed days” - some time in the office, most of it spent in meetings/collaboration/training/mentoring, with “individual work” done from home.

Thank you again, and as always, I welcome all comments and feedback.

#

About me

I have spent the last 17 years recruiting for senior actuarial, catastrophe modelling and analytical positions in the UK, and abroad (principally the Americas and Bermuda). My client base ranges from consumer insurance, commercial lines and Lloyds of London to more unusual operations involved in insurance linked securities, private equity and broking. I also research and write virtually all of our research reports, including compensation surveys.

Prior to joining Hanover Search in 2010, I spent 6 years working as lead consultant for the insurance and financial services division of Hays, a global FTSE-250 listed recruitment group.

Prior to university I spent 2 years working in sales for Churchill Insurance, one of the legacy companies of Direct Line Group.

I have a degree in Economics and Mathematics from York University and have completed a number of development courses, including a Strategy and Finance module with INSEAD and a psychometrics certificate with Cambridge University. In the summer of 2020 I completed two R-based courses with Essex University’s Summer School in Quantitative Social Science.

I have 2 young children under 5 so I don’t really have any spare time, but when I get a moment, I usually spend it reading.

Get in touch

Other than my research work (eg salary surveys), I am an active member of Hanover’s search and selection team. My recruiting philosophy can be summarised very simply as:

• Contrary to what most recruitment firms claim, the world does not revolve around “superstars”; a hard working, knowledgeable, experienced actuary who gets on with people is the kind of employee any company would be happy to have

• I look to provide enormous amounts of information to candidates for the searches that I run, and I’ve lost count of the number of times people have said “This is the best information pack I’ve ever seen”. I’ve also never had a candidate complain that I sent them too much information.

I am always happy to: discuss the results and methodology of this survey, help your organisation with recruiting at the £100k+ base salary level or provide informal benchmarking advice on salaries. For all queries, please email me: michael.stefan@hanoversearch.com

Other reports

Since early 2018, I have authored a number of reports/briefs and a selection is listed below. My older reports will always be available to download directly from the cloud (right click, save as, no registration needed). A few are listed below.

-Demographic Analysis of Actuarial Teams in the London Market

-Demographic Analysis of Cat Modelling Teams in the London Market

-2019 Market Developments for Actuarial, Catastrophe and Data Science

-AI & ML Expertise in the major insurance Companies

Since early 2020, I have transitioned into hosting my salary surveys online. You can find my 2020 Cat Modelling and Exposure Management Salary Survey here. The 2021 version will be published this summer.