The relationship between money and happiness
The recent news of the tragic suicides of two high profile individuals, Kate Spade and Anthony Bourdain, is a timely reminder that money can’t buy happiness.
It’s also a gentle reminder of the private battles people fight, and the importance of practising the philosophy of R U OK?Day throughout your life, in the form of regular check ins with friends and family.
The relationship between money and happiness is a complex one. Just this month, Boston Private published a study, conducted by CoreData, of US High Net Worth individuals which uncovered the wealth priorities, feelings and goals of America’s rich.
The research, carried out between February and March 2018 via an online survey, canvassed the views of 300 Americans with between $1 million and $20 million of net investable assets (excluding their primary residence).
Interestingly, the study found people predominantly pursue wealth to achieve emotional rather than material goals.
Nearly two thirds of those surveyed equated wealth with peace of mind, while more than half cited happiness. The younger generation of Millennials, as well as business owners, were more inclined to see wealth as a gateway to happiness.
However, the study also revealed the emotional cost or wealth burden that wealthy individuals carry. While this burden can take many forms, the study cites the tendency of some people to feel guilt or regret due to time spent away from family, or anxieties related to the weight of expectation in providing for others, and making a positive contribution to society.
There are two sides to every coin, and while money certainly provides a level of financial security, it often comes with a great sense of responsibility. And as we’ve seen too often, wealth is not an antidote to depression or the sense of despair individuals feel when they commit suicide.
If you’re interested to read more of the research findings, you can download Boston Private's The Why of Wealth study here.
Correlation and causation
This concept of wealth and happiness got me thinking about a common mistake people make when interpreting trends in a data set between correlation and causation. Two things are said to be correlated when they demonstrate a relationship – or connection.
If two factors are positively correlated, it means that they both increase and decrease together, and if they are negatively correlated, one increases when the other decreases.
What’s important to understand though, is that just because two things are connected, does not mean that one is directly causing the other to change.
There might well be a correlation between wealth and happiness - but being rich doesn't in itself cause you to be happy. And being happy certainly doesn't cause you to be rich (although that would be nice).
For more on correlation and causation, see this article from The Conversation.
What's driving your customer satisfaction?
We are working on a project for a client right now with the objective of helping them better understand how to improve the customer experience.
One of the biggest challenges businesses face when undergoing CX transformation, is knowing which levers to pull to get the best outcome – both in terms of bang for your buck, and overall customer satisfaction.
In these types of projects, a common research technique called multiple regression can be instrumental in helping you decide on which factors to focus your attention.
In simple terms, multiple regression assesses the relationship between a dependent variable – such as overall satisfaction – and two or more independent (exploratory) variables – such as communications, fees and charges, or customer service.
The strength of the model can be assessed by examining the coefficient of determination (R2), which lies between 0 and 1. The closer to 1, the stronger the model; what R2 is telling you in essence, is what proportion of the variation in overall satisfaction is predicted by the independent variables in your model.
By asking your customers to rate their satisfaction with a range of underlying attributes, and comparing this against their overall satisfaction with your business, you can identify the derived importance of each underlying attribute to customer satisfaction.
In undergoing this exercise, you can identify which aspects are the ‘tickets to play’ (ie. high stated importance but low derived importance) and which are the ‘primary areas’ to focus on (ie. high stated importance and high derived importance).
You can also make an assessment of how your organisation is travelling in these key areas, via Quadrant Analysis, which allows you to map satisfaction against importance to determine your key competitive advantages (ie. high importance and high performance) as well as your key weaknesses (ie. high importance and low performance).
While we may never truly understand the relationship between wealth and happiness, there is a lot that statistical research techniques can tell us about your customer, and what ultimately makes them happy.
Kristen is a highly motivated and passionate researcher with eight years' experience in the market research industry. As Director of CoreData Western Australia, she is based in our Perth office and responsible for business development, client relationship management and project management across a diverse client base.
Kristen has a deep understanding of the financial services industry, strong client engagement skills and is a regular media commentator. Her Perth client base spans aged care, banks, super funds, not-for-profits and utilities.
Before relocating to Perth to establish the WA business, Kristen was Head of Financial Services in CoreData’s Sydney office. Prior to joining CoreData in 2009, she was a financial journalist for seven years.
Kristen is a graduate of the Australian Institute of Company Directors, has a Master of Business Administration (Exec) from the Australian Graduate School of Management, a Bachelor of Arts, Journalism (with Distinction) from Curtin University of Technology and is a fully accredited member of the Australian Market and Social Research Society of Australia.