Change. It’s clear that appraisal, as a vocation, has changed.  Many appraisers are considering new careers.  Others are preparing to meet new demands.  Yet others are doing . . . nothing.

Which mind are you?

Escape.  Retool.  Or be in denial.

I have taught with Valuemetrics.info for over 17 years now.  And was on the Appraisal Institute’s first development team for the Statistics, Finance, and Modeling course.

For me, we are now in the second real property “crisis”  since that ‘reform.’  And the fourth slowdown/crisis in my career.

How do you respond?

Escape:  The people who move away from appraisal generally have some other skills or experience in another field, or related field.  Most continue doing appraisal while seeking other work.

Learn:  Some people see and act on change.  The driver of valuation change is technology:  it comprises big data, the science of analysis, and computation software which obsoletes 1930s appraisal “process.” We have two paths of learning:  1) That imposed narrowly from others (like the GSEs), doing things for what they expect; or, 2) Imposed broadly by self, for personal dignity, competence, money and fun.

Do nothing:  1) Roll the dice, and hope things get better; and, 2) “Let’s not think about this.”

In the past, for many, method three — “wait, do nothing” worked just fine.  This time is different.  I see four reasons:

1. The GSEs (FannieMae and Freddie Mac) are dominated by quant thinking – “Just get me the data, and we can auto-algorithm calculate the rest of the way. The “modernizing” to hybrid, value-acceptance, and automated methods are proof of this thinking.
2. Technology advantages can be Luddite-resisted for a while – but eventually users and clients and even regulators see the typing on the screen. Eventually old horses get replaced by smelly gas cars.  Forms get replaced with data-stream delivery to customized dashboards.
3. New needs present themselves. User benefits do not become ‘needs’ until someone realizes they are possible!  Risk/reliability scored appraisals become possible.  Collateral lenders and portfolio managers soon see reliability scoring and forecast values as a need.  Investor users want the ability to integrate current reliability with forecast economics.  Equity enforcers (judiciary, assessment, and social justice) see the way to show fairness and quantify any bias.
4. Professional requirements will change. This can be the form of new licensing and education regulation, or reform in existing professional organizations.  It can also mean the rise of new organizations (such as the CAA) which specifically build on today’s data-analytic human-interface tools.  The CAA (Community of Asset Analysts) is dedicated to better serve clients, regulators, and the public good.

Artificial intelligence and data science require human expertise to provide reliable unbiased reproducible results.  Education and practice in data science (including AI) is best and fast learned by those with field-related knowledge as a base for connecting theory to tools to practice.

For appraisers, the practice is market and method.  The learning requires interactive use of visualization, simple descriptive statistics, graphs, and an attitude of curiosity.  Appraisal can be fun again!

For those seeking new careers, modern use of AI, data science, and brain/machine interface is best learned with a subject-matter expertise sidecar, not from pure theory and “computer coding.”

For those who wish to do nothing, it’s easy.  Do nothing.