The question of which is better, human or machine, has been around for a while.
Which plays chess better, the chess master or the computer? Which carries on a
better conversation, any human at all or Siri? Which drives more safely, the
human or the automated car?
In most cases, experts say, the best outcomes are achieved not by either the
human or the machine but by a combination of the two. Working together, human
and machine produce a better result than either can working alone.
Automation has already found its way into appraisal in the professional
recertification courses that appraisers take every two years. Appraisers have
their choice: the instructor-led course that meets in a hotel conference room at
a fixed time or the automated online course that the student can work through at
any hour of the day. The advantage of the instructor-led course is the opportunity
to meet with colleagues. The advantage of the automated online course is the
freedom to take on the course material at the most convenient time. The online
course won't let the student advance until the student has demonstrated mastery
of some part of the material. In terms of learning, that is probably the better
thing. The best of both worlds might be an online course that also allowed the
students to meet in a Zoom meeting to discuss their real world experiences that
relate to the cases presented in the course.
Automation has come to cars. It edges in little by little. It used to be that
driving involved shifting gears. The demand for that kind of car is gone.
Today, new cars make it difficult to so much as change lanes unless the driver
has signaled to move left or right. The car itself will apply the brakes if it
is about to crash. We are made safer, even if the car is less fun to drive.
Automation reaches medicine as well. As much as anyone, doctors take professional
pride in their skill at diagnosis and treatment. The thought that automation
might do a better job is offensive to doctors on a personal level. Yet the
Symptom Checker at medical Web sites embodies a level of knowledge of uncommon
conditions that no human could memorize. If ten patients worldwide suffer from
Santilli Syndrome, what is the chance that a general practitioner would recognize
the symptoms when the eleventh checks into the waiting room? For common ailments,
certainly the general practitioner's knowledge is adequate. For uncommon ailments,
not so much. The best outcomes in many cases are the result of the doctor working
with the online service, so that a patient's serious condition is diagnosed.
The list goes on - automated auto repair diagnostics, automated tax preparation,
automated chat bots, Siri, Alexa, and more.
The methods used by appraisers to do their work fifty years ago are almost
laughable by today's standards. Inspecting the building hasn't changed much.
But there the similarities end. In the 1970s, researching comparable sales for
a commercial property appraisal involved leafing through fifty back issues of a
real estate publication that gave a property's address, its selling price, and not
much more. Finding comparable sales involved driving around town for days to find
out whether a particular sale was of an office, an apartment, or what. Comparable
rents came from an appraiser's files or from some other appraiser, using the barter
method. Capitalization rates were gotten by algebra, not from investor surveys
or brokers' reports.
Today we access data from services that allow us to find the best comparable sales,
fully researched, in minutes, as well as comparable rents by the dozens and
capitalization rates from specific sales.
The raw material for a valuation has gone from low quality, time-consuming, and
laborious to high quality, efficient, and instantaneous.
Raw material is still only raw material. A high quality work product requires
analysis. For that, what is needed is a human/machine team.
Zaxia is a semi-automated valuation model for commercial real estate. It requires
a human user, who has the choice of letting the automated system control all the
variables involved in the calculation of property value. Zaxia will then make its
best estimate of market rent and of all the other variables - the vacancy rate,
the expenses, and the capitalization rate. It will choose the comparable sales.
But Zaxia has found that the most accurate valuations are made when the
user fine tunes the inputs, especially in the assignment of the market rent.
The user can go back and refine the inputs again and again. The result is a work
product that is part human and part machine, achieved in a far shorter time frame
than has otherwise been the case. Zaxia allows its user to "cut to the chase."
The future of valuation is all these things. It is improved research. It is a
willingness on the part of the analyst to use better methods. And it is improved
analysis not simply by a better trained human or a more refined machine but by both.
It is improved because it is the product of a better human/machine team.