[Research] Brokerage Performance 2008/2009 – Speculative Analysis

The annual Brokerage Performance Report put together by REALTrends is one of the most useful and important studies for the real estate brokerage industry.  Unfortunately, the last report was released in 2007, and nothing has been released since then.

The trouble with the 2007 Report, as valuable as it is, is that it uses 2006 data from respondents who submit the information voluntarily.  And housing market started to decline sharply really starting in 2007, and 2008 may have been the annus horribilis of the real estate industry.  It may be that the respondents of the REALTrends study simply didn’t want to tell anyone how horrible a year 2007, and then 2008 was even worse.

Either way, lacking 2007 and 2008 performance data means that it is nearly impossible to guess what constitutes “average” performance.  And lacking information means decisionmaking is at best made in a vaccuum with no baseline, and at worst is haphazard.

I’ve always been keenly interested in tracking as much performance data as possible.  And I’m into speculating on stuff I can’t measure.  So I figured I’ll take a foolish crack at some numbers.

The Data and the Assumptions

I began with the 2007 Brokerage Performance Report from REALTrends, and took the section referring to the “Average Company Profile” (p. 13 of the report).

I then took the National Association of REALTORS Existing Home Sales dataset (available here) for 2006-2008 and looked at the year over year decline in transactions and in average sale price.

What the NAR data shows is that from 2006 to 2007, transactions declined by 12.75% while prices declined by 1.31%; from 2007 to 2008, transactions fell by 13.08% while prices fell precipitously by 9.54%.

The difficulty in the analysis arose primarily from the fact that REALTrends doesn’t make its formulas or logic public (nor should anyone expect them to do so, since that is their intellectual property).  I couldn’t figure out how to calculate for important numbers like “Company Dollar %” and trending is nearly impossible given only 3 years of data that actally shows an increase from 2004 to 2005 then a decrease in 2006.  I assume the trendline is downwards from 2006 – 2008, but have no idea how much.  In turn, that meant that the key number, “Average Profit” (expressed as a percentage of GCI) is impossible to compute.

So… I constructed my own assumptions-filled table with the following key assumptions:

  1. Sale Price = Sales Price from NAR data
  2. Commission Rate = 2.5% per side
  3. Company Dollar % = Hold constant from 2006 to 2008 at 27.8%.  I really couldn’t see a way to justifiably assume that brokerages would have paid out more money to agents to hold onto them in a severe downmarket.  On the other hand, I couldn’t say that they didn’t.  So the safe assumption seemed to be to hold it constant.
  4. Expenses = Hold constant from 2006 at $1,761.  Lacking any data, I could see an argument that companies would have reduced expenses sharply; on the other hand, I could also see the argument that companies would have spent more in 2007/2008 to try and offset falling sales.  I computed the Expenses for 2006 based on REALTrends data of 4.3% profit (expressed as % of GCI).

The resulting table is here:

Sale Price$300,000
Sell-Side Commission$9,000
Broker Split20%$1,800Agent Split80%$7,200
Advertising Cost$0$0
% of Buyer Leads25%
Expected Value$2,813
Expected Profit$4,613

[Note that the REALTrends “Avg. extrapolated co. $ / unit” number does not match the Avg. company dollar per unit from my calculations. I consider the REALTrends numbers to be more accurate, as those are based on actually reported numbers by respondents, but no explanation is provided.  I must assume that the variance arises from different Commission % from the actual survey data, or different calculations/data on units.]

What immediately jumps out is that without really taking the 12% and 13% decline in transactions into account, the profit numbers look grim indeed for the fictional “Average Company”.  2006 wasn’t exactly a healthy number, but according to those calculations, 2008 was less than a third of 2006.

The Performance Table, 2007 and 2008

With those assumptions made clear, here’s what I’ve come up with:

The numbers are grim, to say the least. Because I think the assumptions are, on the whole, likely to be too positive, rather than too negative.  Perhaps company dollar stayed even with 2006 numbers, but it seems more likely to me that top producers in a down-market demanded and got concessions.

In any case, 4.3% profit (on GCI) of 2006 wasn’t healthy to begin with.  The 1.48% profit of 2008 is devastating — especially if we think of that as the average.  So assuming that to be true, it means that half of the real estate companies made less than a penny-and-a-half on every dollar of revenues in 2008.

The counter is that this is too grim a picture, because companies started cutting costs in 2006 — closing offices, laying off FTE staff, etc.  So while company dollar was down, expenses were dramatically slashed to provide a higher profit margin.  Without actual data, we’ll never know which is the true picture.

Furthermore, as is evident from above, it’s difficult/impossible to project what the decline in transaction units did to brokerage performance because there are no figures provided for average # of transactions by a brokerage company.  What we have, instead, is average per agent productivity.

If these projections/extrapolations are correct, then the average per agent productivity is down nearly 25% from 8.8 to 6.7.  For a company with 500 agents, that means 1,000 fewer transactions in 2008 as compared to 2006 just from the impact of decline in transactions. Coupled to the decline in company dollar attributable to decline in home prices, and this picture emerges:

Top 20 Markets Housing Affordability

RankCityPrice To Income RatioPrice To Rent Ratio City CentrePrice To Rent Ratio Outside Of City CentreMortgage As A Percentage Of Income
1Vancouver, Canada16.0228.7426.88105.93
2New York, NY, United States12.3419.0316.9088.57
3San Francisco, CA, United States12.3016.0314.7288.87
4Toronto, Canada10.6621.9121.2570.22
5Boston, MA, United States10.3318.6311.7475.06
6Honolulu, HI, United States8.9918.4915.8264.92
7Oakland, CA, United States8.5213.8911.0660.79
8Los Angeles, CA, United States8.4216.0912.8461.15
9Mississauga, Canada7.7817.1118.4450.71
10Fremont, CA, United States7.3315.1914.1950.81
11Victoria, Canada6.5417.3014.4442.96
12Montreal, Canada6.4421.4219.5942.56
13Irvine, CA, United States5.8113.5712.3941.71
14Miami, FL, United States5.7611.557.4142.64
15Jersey City, NJ, United States5.5913.237.8639.95
16Washington, DC, United States5.4412.958.0938.37
17San Diego, CA, United States5.2213.1711.0038.02
18Kelowna, Canada5.2013.4512.8234.60
19Portland, OR, United States5.0612.1411.2537.06
20Ottawa, Canada 5.0219.4014.1632.82

The result is a 15% decline in 2007, and a 20.5% decline in 2008.  Companies are hemorrhaging money.

Only Data Can Satisfy

As interesting as this exercise has been, it ultimately poves dissatisfying.  Because it is unreasonable to think that companies did not adjust their expenses with the times.  Of course they did.  But how much?  To what degree?  And what were they able to cut?

It seems reasonable to speculate that companies have cut office space (saving on rental expense), cut staff, and other overhead.  It may be that companies have cut agents, which would impact the total transactions number.  Or it may be that many agents (and companies) have learned new skills like selling REO properties, or working more with investors.

All of these things have costs associated with them, and without the data, it’s just speculation.

I hope that REALTrends and its survey participants will return to putting the information out to the public so that practitioners can make rational decisions about what they ought to be doing.  Because in cases like this, only real data from real companies can actually satisfy the craving.


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Rob Hahn

Managing Partner of 7DS Associates, and the grand poobah of this here blog. Once called "a revolutionary in a really nice suit", people often wonder what I do for a living because I have the temerity to not talk about my clients and my work for clients. Suffice to say that I do strategy work for some of the largest organizations and companies in real estate, as well as some of the smallest startups and agent teams, but usually only on projects that interest me with big implications for reforming this wonderful, crazy, lovable yet frustrating real estate industry of ours.

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2 thoughts on “[Research] Brokerage Performance 2008/2009 – Speculative Analysis”

  1. Most businesses are slow to make change and adapt to market changes.

    One has to be nearly ruthless in adapting quickly.

    Also many Brokerages pile on the overhead too fast when times are good and find it difficult to shed overhead when times get tough.

    As landlords and property managers, Real Estate Agencies know it is tough to cancel Leases.

    The lesson is expand and add to overhead carefully and slowly and react and adjust quickly when things slow down.

  2. Most businesses are slow to make change and adapt to market changes.

    One has to be nearly ruthless in adapting quickly.

    Also many Brokerages pile on the overhead too fast when times are good and find it difficult to shed overhead when times get tough.

    As landlords and property managers, Real Estate Agencies know it is tough to cancel Leases.

    The lesson is expand and add to overhead carefully and slowly and react and adjust quickly when things slow down.

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