The claim of an average 4 hours extra unpaid work per week is not clearly explained. Is it an arithmetic mean calculation, originating by adding up all the answers given and dividing by the 1,663 participants in the survey? That seems odd presuming there wasn’t an option to record a minus figure for skiving off early.
The implication that the report tries to generate is that most people are working a considerable amount of time without being paid – actually calculated at £1.5bn unpaid labour per week (based on the average national salary of £23,450 – itself a pretty useless average mean).
Why not present a median average – identifying the mid-point showing that half the population work more than this and half clock in fewer overtime hours? Or state the mode average which would indicate the figure that is most commonly worked in overtime.
Better still – I’d like to know how many people arrive at work and leave at their scheduled hours within this survey. We are told that 71% of respondents “regularly work through lunch breaks” – but what does that mean? Regularly is a subjective measure – and how do we know they don’t go home early instead?
Okay, so the truth is this survey is nothing more than the usual type of “PR survey” – more about generating some coverage than revealing anything that is statistically robust.
This is underlined by the further “analysis” into cities that are above average on their average overtime. But how many people actually participated in these cities – compared to the population of those cities.
There is a very tenuous link to the company behind the survey promoting its “easy online takeaway ordering” and claiming it had spotted a trend for takeaway orders from offices and other places of work at lunchtime and post-5pm. The statistical nature of this “trend” is not clarified, but of course, the marketing inspired research proved it.
I recently assessed a student dissertation for the CIPR Diploma which claimed that numeracy was not rated highly as a required skill by PR practitioners. Leaving aside the statistical validity of that “fact”, the misuse of maths in surveys within the PR world does nothing to demonstrate any real grasp of statistics.
This is important when real understanding of figures is required to justify a place among senior management by PR practitioners and also when they are involved in explaining complex financial data or other statistical information.
Another critical area comes in budgeting and I’m often surprised by how few practitioners seem to have any experience of putting together financial calculations for campaigns.
We often read criticisms about the standard of English in press releases and other communications, so perhaps it is not surprising that practitioners’ arithmetical abilities don’t add up either.