Blog Zero Or Who is George Dell and Why Should You Care?

I’m an appraiser, just like you.

I dedicate this blog to asking big questions, inviting opinions, exploring new ways of doing things. I’m daring you and me to step out of our collective comfort zones and think in new ways about our profession. I’m hoping that the dialog that we develop will lead to positive changes. Questions from a number of peers motivated this effort.

These questions include:
• Why do we use valuation solutions developed in 1932 to solve 2016 valuation problems?
• What are the 2016 solutions to our 2016 valuation problems?
• Is our valuation process really scientific?
• Why do we follow a defined “valuation process,” instead of the scientific method?
• Have our appraisal institutions failed us?
• And finally – Is the appraisal profession dying?

To begin, my background and education informs a different viewpoint about the valuation profession. My BA was in accounting. I witnessed the resistance of that profession to technology change – the spreadsheet — and the eventual embracing of its power. My academic love was (and remains) economics. Specifically, econometrics as a blend of economic theory, mathematics and “statistics.” I always saw appraisal as a subset of econometrics, where the subject matter (appraisal theory) is the econometric theory of assets.

Econometrics seemed simpler.

Econometrics equals measurement of economic things – like real estate and other assets. My econometric education focused the tools to measure those economic things. It made sense, even as some of the statistics did not. Anyway, I learned a lot about statistical software packages (instead of spreadsheets). Today the most popular data analysis package is ‘R’ and its environment ‘RStudio.’

Early on, I was impressed at how practical these tools were and how well the practice of appraisal did its job. Even then, though, it bothered me that most of the software, including spreadsheets, assumed I had to take a random sample. I knew appraisers did no such thing. We did something different. We collected muddy data, compared numbers and a few ratios – to show the client a thinking process to arrive at the estimate of value. When I began my career these methods and tools seemed to work well. Pick the comps, make adjustments, Go. However, that world was about to change.

Lurking in a corner, on the floor of my trainer’s office, was something called a computer. He said it might be wonderful, but he did not know how put it together or use it. We had just started typing our form reports, and to him that was a big enough change. But that thing in the corner bothered me. I knew it was quicker, and very obedient, so long as you could put it together and tell it exactly what to do. But learning the computer also involved learning scary programming stuff.

To overcome this fear, I went back to school, three different ones. Math brush up, multivariate calculus, theoretical econometrics at UCSD, applied econometrics and statistics at SDSU, and computer science at NU. Mostly graduate-level courses. 16 years of two classes per semester. Every statistics and econometrics graduate class taught at two San Diego universities. And a certificate program in GIS/GIA (Geographic Information Analysis) at UCR extension. I was torn between getting a PhD (yes I admit I wanted it for its prestige) versus the crazy desire to see the next class in a related field, and see how it may apply to appraisal. My instructors included two Nobel Prize winners (in time-series analysis), and an instructor from Moscow, teaching insurance (risk) in the mathematics department at SDSU. (He described how difficult it was to teach the profit motive in the Soviet Union). And I took classes in computer programming. At the time, I did not know that I was striving to be a data scientist. The field had not yet been invented.

I did know that I wanted things to be simple and useful.

I wanted things to make sense, instead of . . . well not making sense. Unfortunately, my life at three universities created dissonance as I tried to reconcile my appraisal education with my econometric education. When I began my career, traditional appraisal techniques worked well. But things had already started to change and those traditional tools couldn’t keep pace and lacked the analytical muscle of the statistical tools I was learning. I became active in the Appraisal Institute. I naively thought I could bring my new-found truths of statistics, graphs and computer power to the profession. But, there was resistance. Yet, this resistance could not stop the economic principle of change. These changes magnified the differences between traditional tools and statistics. Today, we do see descriptive statistics and graphs in our curricula. This makes me happy. But . . .

Also mudding the waters were colleagues who advocated statistical practices that had become outdated by advanced methods, big data and newly developed software solutions. In other words, some of our leaders failed to keep abreast of state of the art academic practices. But who could blame them? It’s hard to replace accepted thinking every few years.

This blog, website, classes, and soon to be published forum are dedicated to exploring, to asking questions, to helping appraisers live the truth. To provide valuers simple, useful tools which make sense. To truly serve the public good. To reduce, or even prevent the next swing of economic insanity. To bring some excitement, satisfaction, and joy to the individual appraiser.

We can make personal sense. We can feel better about what we do. And we can see ourselves in a positive light of service. It is possible.

That is our dedication.