Discovery Phase

Discovery and Data Collection Phase of the Appraisal Cycle

After the inquiry/protest season concludes, the appraisal process transitions to the data collection and analysis phase. During this time, appraisers may be seen throughout the county in neighborhoods and commercial areas as they are measuring new residential or commercial construction, reviewing and updating characteristics of existing construction and/or land parcels, and reviewing, updating, or adding inventory of present or new businesses. Yearly updated aerial imagery, digital field devices for data collection, and GIS analysis tools are utilized to assist in staff efficiency and ensure proper valuations and equitable results during the assigned/limited time for this phase. This process requires collection and analysis of three types of data: General data which affect values on national, state/regional, or neighborhood levels. Specific data about the site and improvements of a property. Comparative data which regards recent sales, cost, and income information for similar properties.

General Data may include:

• Trends in business cycles, the economy, financing options, population, price levels, building costs, purchasing power, and tax rates.
• Physical factors affecting value, the most important of these is location, others are size, topography, appearance, lot size/shape, street pattern, soil and subsoil conditions, drainage, hazards, climate, utilities, nuisances, conformity of improvements, and proximity to supporting facilities.
• Economic factors such as population levels, balance of land use, vacant land, new construction, price and rent levels, vacancy rates, lender attitudes, utility costs, insurance rates, wage levels, and transportation systems.
• Governmental factors such as municipal services, planning and zoning, building codes, development regulations, taxes, special assessments, and services.
• Social factors such as population density, crime rate, income levels, labor supply and skill levels, and cultural activities available.

Specific Data may include:

• Ownership data, including owner’s identity, type of ownership (warranty deed, titling information, etc.), easements or encroachments, zoning regulations, assessed value and taxes, and deed restrictions and covenants.
• Site information, including a description of the land (size, shape, topography, and location) and public improvements (paving, walks, curbs, sewers, utilities), corner influence, building orientation, accessibility of the site, and any advertising value offered by the site are also considered. Data collected for an industrial or commercial property may be very different from that needed to appraise a single-family residence.
• Improvement information such as the size, quality and condition of all buildings and physical improvements, along with an analysis of their layout, style, and design. A clear statement about the current use of the property should also be included. If multiple uses exist, they should be noted and documented as carefully as possible.

Comparative Data may include:

• Cost data, which may be obtained through developers and general contractors, or the use of Marshall & Swift (a private firm that studies and develops costs for markets across the country). The cost data may also be used as historical cost for individual properties and as a basis for developing up-to-date factor tables to make historical costs current.
• Sales data, which is collected and basic adjustments are developed, such as time and location, as well as adjustments for different property characteristics. As a result, benchmark properties for comparison purposes are established.
• Income data may be gathered from income and expense statements. The development of economic rents, vacancy and collection loss allowances, discounts, effective tax and recapture rates.

The General, Specific, and Comparative data described is needed for development of an accurate property tax appraisal. Computer usage has increased availability of historical and statistical data related to appraisals. Statistical analysis of large amounts of data using techniques like regression analysis permit the development of valuation factors which can substitute for some of the data described above.