| Defining Demand |
| Written by Jonathan Smoke | |
| 12.14.2007 | |
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Discuss this article on the forums. (0 posts) On Wednesday I highlighted a recent academic paper on estimating the demand for new homes over the longer term. In the paper, the methods used to estimate demand at a national level are well described as are the data sets behind them. Would it strike you as odd that most market researchers don’t follow the same type of method of estimating demand for a specific residential development? Well, they don’t. What may have been done initially as the only practical way of measuring feasibility has turned into a paved cowpath touted by many as the only way to measure demand. But before you decide to build a superhighway down that same path, let me tell you about a better way that does live up to the principles espoused in the Harvard paper. The tried but not true way that many define demand for housing is based on what I like to call demonstrated demand. Demonstrated demand is quite simply historical home closing data. Don’t get me wrong, demonstrated demand is very important in market research. We’d be lost without it, and I’ve spent more than a year trying to assemble the best data on home closings to help my own analysis and enable other market researchers. You can use such historical data to build statistical models to project likely absorption paces by price point. And since such a model is built from real closing information, the projections are realistic about what volumes should transact at a certain price in a specific project or submarket area.  But inherently this data has one major flaw that makes its representation as demand less than ideal. Actual home closings used as demonstrated demand are a factor of both demand and supply. So they are not a complete representation of demand because they are biased by what was available for purchase in that market.Simple case in point: Is there demand for new homes under $50,000 in your local market? Well demonstrated demand would say no, because in most places no new homes have been sold in that price point. Yet we all know that if there were a way to deliver new homes at that price point there would be a lot of demand. That’s a simplistic case, but researchers are often guilty of making developers and builders blind to real opportunities in front of them by perpetuating that demand is simply measuring what has sold. So what happens? The same type of product continues to be delivered and only minor innovations slightly above and slightly below what has historically been in the market typically take place. Sometimes new ideas are attempted only with a lot of guts and risk or lucky guesses from anecdotal insights or experience copied from elsewhere. So while the status quo is perpetuated, what happens? Entire gaps in the product space exist and buyers either go to other submarkets, settle for something not quite what they wanted, or decide not to buy. Any of those results are not optimal for the developer and builder because those results equate to lost sales, less than satisfied customers, lost revenue or margin potential, or all of the above. The right way to measure demand is to do it independent of housing. This requires analyzing household growth and consumer segmentation. Armed with such analysis you can estimate real demand—i.e., estimate the number of new households in a particular area that will need new housing. By understanding their demographic and lifestyle traits, you can deduce the type and price of housing they will want. You can then do powerful things with this demand understanding. You can look at a market and identify where demonstrated demand doesn’t quite align with estimated demand. You can match up estimated demand with some estimate of supply or inventory to see where competition is most fierce or where there is no competition. Finally you can credibly defend the source of demand that enable those absorption estimates. Next week I will show you a real example of comparing demonstrated demand to estimated demand. Hopefully I will convert a few to the notion that understanding demand is more than measuring last year’s supply. 
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