Matt Woolford - Data Standardization and Assessment Practices in Michigan

The assessment profession stands at a crossroads. As Matt Woolford, Equalization Director in Allegan County, Michigan, sees it, we're entering an era where our traditional methods must evolve to meet rising expectations for transparency, accuracy, and equity. The key to navigating this transition? It all comes back to data.

The Zillification Challenge

"The zillification of the industry is upon us," Woolford observes, referencing how companies like Zillow have fundamentally changed public expectations around property valuation. These platforms consume our public data, run it through AI algorithms, and produce instant valuations that property owners increasingly view as authoritative.

This presents both a challenge and an opportunity. The challenge is obvious, when a homeowner compares their Zestimate to their assessed value, discrepancies raise questions about our credibility. The opportunity lies in recognizing that better source data improves not just our own assessments, but every system that relies on our records.

Building the Foundation

Woolford's work on Michigan's CAMA data standards reflects a fundamental truth: you can't build accurate valuations on inconsistent data. "Whether you're in Allegan County or Kent County or Wayne County... we need similar configurations on those key variables," he explains. This isn't just about technical consistency, it's about creating a shared language for assessment across jurisdictions.

The state's adoption of formal data standards, developed jointly by the Michigan Assessors Association and Michigan Equalization Directors, represents real progress. But as Woolford notes, "There's still a lot of work to be done in terms of best practices." Standards are just the beginning; implementation and continuous improvement are where the real work happens.

The Cost Approach Reality Check

Michigan's reliance on the cost approach, supported by state-contracted Marshall & Swift manuals, illustrates another data challenge. Woolford identifies the critical components: accurate data collection, appropriate land values, skilled analysis, and reliable cost models. Miss any one of these, and your valuations suffer.

The state's guideline to physically review at least 20% of properties annually acknowledges this reality. Many counties supplement field reviews with oblique aerial photography, but Woolford emphasizes that "data collection and having accurate data is one of the big challenges" facing assessors, particularly given budget constraints.

Land valuation presents its own complications. In rural areas like Allegan County, limited vacant land sales force assessors to rely on abstraction methods and time adjustments. As Woolford notes, you either "expand your area of analysis or you can go back further in time", both requiring sophisticated analytical skills.

The Equity Imperative

While Michigan's five-year audit cycle currently treats statistical measures like coefficients of dispersion as "informational items," Woolford sees the writing on the wall. "The importance of these equity measures is going to become more important," he predicts.

The targets are clear: residential CODs under 5 are ideal, 5-10 acceptable, and anything approaching 15 raises serious concerns. But achieving these metrics requires what Woolford calls "unicorns", professionals with combined GIS, spatial analysis, and statistical skills who can "slice and dice" data to identify and correct biases.

Preparing for Tomorrow

Woolford's advice to newcomers reflects his data-centric philosophy: "Understand that data is the foundation of what we do." But he goes further, urging the next generation to develop geospatial and analytical skills that will be essential as "algorithms bring challenges to bear" on traditional assessment methods.

This isn't about replacing human judgment with machines. It's about ensuring that when property owners compare our assessments to algorithm-generated values, our work stands up to scrutiny because it's built on authoritative data and sound methodology.

Key Takeaways

Data standardization isn't optional anymore. As AI-driven valuation models proliferate, inconsistent or poor-quality data undermines not just individual assessments but the entire profession's credibility.

Statistical equity measures will shift from "nice to have" to mandatory. Start building those analytical capabilities now, before state requirements catch up with public expectations.

The "zillification" of assessment is here to stay. Rather than viewing it as competition, see it as pressure to improve our data quality and analytical methods. The better our source data, the better every system that uses it performs.

Investment in skills matters as much as technology. Those "unicorn" professionals who combine traditional assessment knowledge with modern analytical skills will define the profession's future.

The assessment profession has always been about fairness and accuracy. What's changing is how we achieve those goals. As Woolford reminds us, "This is not your father's Oldsmobile." The sooner we embrace that reality and build the data foundations to support it, the stronger our profession becomes.