No doubt, statistics and data can play a huge role in what investments are likely to succeed and which ones have a higher chance of tanking. Both of these, statistics and data, can give a very good picture as to the potential future of an investment or an investment’s potential. However, I oftentimes hear people justifying a particular investment based solely off some quoted pile of statistics or computerized data.
Now, not to pull my super-nerd card and confess that I was a math geek and took AP Statistics in high school, but I’ve never forgotten that class and I catch myself remembering things I learned in it on a fairly regular basis throughout life. Granted, most of the time it’s to explain to my mother that her justifying some random fact is based on completely skewed information (she’s not always the best at seeing different sides to things), but what I learned also comes in handy in my real estate investing world as I scrounge through various investment opportunities.
In thinking of what I know about statistics and data and looking at my own experience with them, I think it’s worth throwing out some considerations for you to ponder once you start getting into them yourself.
6 Essential Considerations When Looking at Real Estate Statistics & Data
Consider the source.
I shouldn’t have to remind you of this one — I’m sure you know to be careful of the source of anything, but it’s one of those things that can be surprisingly easy to forget to consider. Where are the statistics and data coming from that you are looking at? They may be from an individual, but more often, you are probably looking at some company-published data sheet online somewhere.
It’s very easy for people to come up with statistics that support their viewpoints, so be cautious of the validity of what someone is showing you based simply off their standpoints. Or maybe it’s not that their information is biased to their viewpoint, but maybe the person just legitimately has no idea what they are talking about, and therefore the information they give you is as off-base as their education levels (not literally education levels but rather how much they know about the subject they are talking about).
So definitely consider reputation and accuracy of a company and their information before making too many decisions based on what information you are looking at. For instance, I find Yelp reviews to be extremely accurate. However, sometimes if a company is ranked a little lower than desired but I think they seem OK, I will look at the reviews from the people who rate the company with less stars and see what they actually wrote. Very quickly, I often will ignore a review if the person wrote few details or seemed like they were whining or have some other indication of not being representative of the truth. On the other hand, if someone rates a company poorly and goes into objective detail about their reasoning for that rating, I’m much more inclined to trust it. Yelp is obviously a completely different animal than real estate statistics, but it’s a good example of the legitimacy of a source of information (the author of the Yelp rating and written review in this case). Some principles apply in considering any source.
Beware of skewed data.
This one definitely got drilled into me in AP Statistics. One of my favorite examples of skewed data is in the statistic of car accidents within a certain radius of one’s house. At the time, the statistic was something like “95% of car accidents happen within 25 miles of one’s home.” What people took out of this statistic was that they needed to be more careful closer to home because they were more likely to have an accident!
OK, no, that is skewed data. The reality for this data was that very few of those people polled ever drove further than 25 miles away from their home. So of course most of the accidents would happen within that radius — few people were ever outside of that radius! See what I mean? I have a few other favorite examples, but I’ll leave it at that one, as I think you get my point. There is often another side to the statistic that isn’t presented or considered, or there is a strong reason why the statistic would show the outcome it showed. Always consider those things!
Question how numbers were calculated.
What variables are being used to generate the statistics and data that you are looking at? This falls very closely in with considering the source of data (who is presenting it) and potential skews in the data. My favorite example of this in real estate investing is when someone presents you with the “ROI” (return on investment) of an investment. Do you know how many different versions of ROI there are being presented out there?
The minute someone tries to convince you of the ROI of anything, your first question would be asking what exactly is being included and considered in their calculation of ROI. For example, if the presented ROI of a rental property includes some years-long speculation on appreciation, I automatically start questioning the calculation. I never present an ROI of a rental property that includes appreciation. I don’t know that appreciation is actually going to happen, so I could be totally lying to you if I start making up those numbers. But you’d be surprised how many people do.
Or another one is the cap rate or cash-on-cash calculations. Make sure you know that the presenter knows what the actual equation for these numbers is. Where those oftentimes go wrong is that someone doesn’t include all of the expenses of a property when determining the net. More often than I care to admit, I see someone advertise a 20% cap rate for a property. My alerts immediately go off, and I ask them to tell me how exactly they got that number because a 20% cap rate is freakishly unrealistic. Maybe not in all cases, but it’s worthy of investigating the red flag. Whatever you do, always have someone break down to you exactly how they got to the number they are presenting.
Question the relevance.
This one is huge for real estate investing and one I see more than a lot. The one I see most often is a published table of the top however many cities in the United States for some variable like cash flow or appreciation or growth or stability. I remember one table that was presented in a forum that was the top some number of cities for appreciation across the United States. What the numbers in the table reflected, though, were in relation to rental properties. There is a method of investing in rental properties solely for appreciation, yes, but more rental property owners are concerned with cash flow. This table was trying to convince rental property investors which cities to buy in based on appreciation.
Well, it is quite common knowledge that the highest appreciation cities don’t cash flow at all (LA, San Fran, New York, etc.)! There are other cities that go through shorter big waves of appreciation where you can get cash flow in for some amount of time, but those cities would need to be clarified in a table like this that is showing data for rental property owners. I think it was 16 or so cities listed in this table, and of these, only one of them that I remember being on there would have even given way to a smidge of monthly cash flow.
So if you are looking at data supporting what cities are appreciating the most, make sure you are only investing for appreciation. Don’t look at a table of only appreciation data if you are considering cash-flowing rental properties. For those, work backwards. Find information on the cities with the best cash flow, then rule out any undesirable cities (declining, scary, whatever) in this list, see what’s left, and then look at the appreciation potential of each. I’m telling you, I’m not sure I’ve ever seen a single table of U.S. cities that someone has posted in a forum post be anything I would actually look at when determining where I want to buy. They are missing a ton of information, and they are rarely relevant to what I need.
Know the difference between primary and supportive data.
Now, where those tables could be used, and should be considered, is as supportive material. If you find an investment opportunity and you’ve done quite a bit of analysis and all is looking good, using those kinds of tables or other data sources can be great for confirming what you have already found or questioning it. I would never use those tables as the primary reason I buy a property, but I may use them as supportive evidence as to why I should or shouldn’t buy the property. See the difference? Here’s another example of primary versus supportive data. In terms of market analysis, it is absolutely critical for me to know that a market I’m investing in is a growing market and not a declining one. Population data, jobs data, and industry data are all information I consider to be primary data. I will absolutely decide whether or not I want to pursue an investment opportunity in a particular market based on what these numbers tell me. I will rule out an investment opportunity that is in a market that shows a decline. Supportive data, on the other hand, would be something like projections for appreciation or a ranking in relation to some variable (like in the tables I mentioned) or just more specific variables — like whether a state is landlord or tenant friendly, for example.