Times are tough, but you will survive!
Doctor Gordon Giesbrecht, director of the Laboratory for Exercise and Environmental Medicine at the University of Manitoba in Winnipeg, wants to dispel the myth that hypothermia kills quickly. “If you think you have just minutes to live, you tend to panic and then you do things that are more likely to bring about a negative result.” 95 percent of those who perish in cold water aren’t actually hypothermic, he says. Their body temperatures turn out to be almost normal. Cold doesn’t kill them. It’s the terror that leads to drowning and heart attacks.
What to do? Dr. Giesbrecht recommends a straightforward 1-10-1 system: One minute to get breathing under control, 10 minutes after that for meaningful movement, and one hour after that before you lose consciousness. “Survive the first minute,” Giesbrecht says, “and you’re on your way to saving your life.” The most immediate danger comes from what’s called the “cold shock” in the first minute. This includes a gasp reflex followed by uncontrolled breathing known as hyperventilation. As one gasps for air you inhale in freezing water, making it very difficult to coordinate your swimming. Your first goal is to fight your panic and get control of your breathing. Do that within the first minute. Stay calm. Next, you’ve got ten minutes to move. Swim to safety or the safest spot you can find and crawl out of the water. After ten minutes, your muscles and nerve fibers get so cold that they don’t function anymore. If you’re running out of time and can’t climb out of the water, attempt to position your wet arms so that they will freeze on to the ice so that when you lose consciousness you won’t sink into the water. After that you’ve got about one hour before you lose consciousness.
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Below are 9 questions and answers regarding the practical application, use and understanding of the 3L Score.
1) Which of the 3L Score components is the most important to focus on?
Answer – It depends on your specific business or service. Start by looking at each 3L Score Category and number them in terms of most to least important in your decision making priorities. If you sell electronics/IT- Highest Echo Boomer %’s and Willingness to Spend scores may be your best sights. If you are investing in apartments or buying houses to rent, high Stability Strength scores are critical to find a good location. An area that could change significantly in the next few years is not a place to invest in a piece of collateral that you may own for 20-30 years.
Focus on your 2nd and 3rd highest ranking score components. This way when you evaluate multiple sites and the top scores in your 1st priority (for example, Total Population) are equal or close, you can make the best decision by comparing your 2nd and 3rd most important factors. This should be the best location for your business. Decision making made easy!
2) What is the difference between the “Daytime Employment” & “Residential Occupation Make-up components of the 3L Score?”
Answer – The “Daytime Employment” factor measures the number of workers commuting to a specific job located in your 3L Score area. The “Residential Occupation Make-up” is a measure of those actually living within your score area. They may be employed in your 3L Score area or commute to work outside your area, but all reside in your area.
3) I am deciding between two tenants who want to lease the same space from me. Can the 3L Score help me decide which applicant is less likely to default under the terms of the lease? How?
Answer – Yes. Look at the products they are selling and think of the customer profiles that are the primary buyers from each business. Given the makeup of consumers that surround your address, which has better chance of success? Look at each of the individual 3L Score components. For example, if the blue collar population is very high and the white collar make-up is very low, you would probably choose select a burger joint over a sushi restaurant as a tenant. You don’t want a tenant that goes upside down, or might struggle and default on their lease. Watch out for “pioneers” that are hoping to create a market where there isn’t one.
4) How come housing prices are not one of the components of the 3L Score?
Answer – Actually housing supply and demand, including recent number of sales, and different measures of local housing value, with particular emphasis in our algorithms on change, including price per square foot, median price, and average price are a huge component of our work. The algorithms also include mathematical functions that correlate local performance to performance within the broader marketplace outside your score area as well.
5) The whole focus of the 3L Score is local. You seem to emphasize specific local conditions over national economic indicators or the demographic/economic measurements of regional, state, or even the county I’m located in. Why?
Answer – Simply put, every business or service transaction happens at a specific address with a customer that lives or works in fairly close proximity to the location. What is the relevance to you and your business or service of the consumer make-up, spending ability, potential to change, etc. of individuals located in other parts of the United States, your own state, or too far a drive from you in your own county? Use your local 3L Score to understand the customers that surround YOU.
6) Poverty is defined as income of $25,000 or less? This does not seem like poverty to me based on the incomes of some of my customers.
Answer – Keep in mind that the income component of the 3L Score references household income. For example, 3 echo boomers making $15,000 per year and sharing an apartment have a combined household income of $45,000. One reason most housing markets won’t “recover” in the near future is that Americans have discovered that low income goes a lot further when it is “pooled,” or consolidated under one roof.
7) Why are the age cohort make-ups surrounding a business address important to understand?
Answer - Do you know your product and who buys it? To illustrate the point: If you were selecting a site for a shoe store catering to baby/toddler/preschool age children, you would probably choose (all other 3L measurements being equal), the area highest in Generation X population. Why? They have the highest percentage of children in this age range of all the age cohorts, and generally higher incomes than any echo boomers that might marry early and have babies. If your store was a toy store targeted to the same age range of children, and you had two sites to choose from where all measurements were fairly equal including the number in the Generation X age cohort, you probably would pick the site highest in Baby Boomers and the Bob Hope Generation. Grandparents are big toy buyers!
8) The “Willingness to Spend” part of my 3L Score is 48 (“economic survival is a priority”) yet my “Stability Strength Score” is 73 (“Stable”). Is this a contradiction?
Answer – No, not necessarily. It may mean, however, that you need to refocus your product mix to more “bang for the buck” value propositions.
9) How do I know the proprietary algorithms used by Catalyst Analytics produce accurate data?
Answer – Our team has invested thousands of hours and significant “blood, sweat, and tears” in the intelligent creation of tools that will assist our clients in making better decisions in less time.
Following our long and intense collaborative work to develop a specific algorithm, we test it out in the “real world” in order to evaluate the effectiveness of the algorithm. Sometimes we found that one of the key premises of the algorithm was mathematically correct, but was not accurately reflecting real world conditions. Accordingly, we adjusted the algorithm as appropriate by altering the weight given to specific variables, and added or deleted variables until the algorithm was reflective of real world conditions. It is vital to Catalyst Analytics that our customers have precise and correct data at their fingertips, and our people love this process!
The definitions of each of our algorithms is comprised of complex and specific sets of rules and functions that define a sequence of mathematical operations, which are then used by our programmers and applied to multiple fresh sources of input data for each individual 3L Score search to ensure practical measurements and predictions of socio/economic behavior in the surrounding area
For example, in our “Willingness to Spend” algorithm, four components of Inflation/Deflation are just part of what is included:
1) Demand for goods
2) Demand for money
3) Supply of goods
4) Supply of Money
Each component has a related set of developed rules (calculations) that are weighted and specifically applied to local area data input and output for households regarding each one of the above 4 components. There are further calculations that go through the processes described above in developing the algorithms applied in the 3L Score.