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How will you spend the day after Thanksgiving? Here’s some research that might influence your decision. In our 2015 survey of affluent Americans–a group that represents the top wealth holders in the United States–we asked how many times they participated in in-store Black Friday shopping in the past five years. Only 2% said they had participated each of the past five years, 14% said they had participated once or twice, and 3% said they had …
In the introduction to The Millionaire Next Door, a question is asked in the voice of the reader: How come I am not wealthy? The authors state: Many people ask this question of themselves all the time. Often they are hard-working, well-educated, high-income people. Why, then, are so few affluent? As I am rereading The Millionaire Next Door, as many of you are, I’m reminded of the reason the work of defining wealth in …
A recent study from Wells Fargo and Gallup found that approximately 21% of 401(k) participants take out loans or early withdrawals from these plans. Many employees are not quite familiar with the tax consequences that go along with such behaviors. The basics of good money management, while not universally taught, can be identified and learned. Financial literacy is a necessary first step in ensuring individuals make sound financial decisions. However, it is only one …
Distrust and caution are the parents of security. – Benjamin Franklin Data Points measures skepticism in relationship to one’s overall Wealth Potential™: it is positively related to net worth regardless of age, income and percentage of wealth inherited. So, those who have the greatest potential for accumulating wealth are also those who will most likely question everything with respect to how they (or you) manage and invest money. In one of our latest studies, within a sample of …
A data point is a measurement or set of measurements of a single member of a particular population. For the financial services industry, client data typically include age, income, net worth, investable assets, risk tolerance, attitudes, and perhaps big data (with or without theory). This information is traditionally used to describe wealth groups (e.g., mass affluent, ultra high net worth) and determine relevant products and services. What’s missing? The scientific measurement of relevant wealth-building behaviors and life experiences …