Sales Ratio Studies: Make sure your GIS is doing the heavy lifting

By Billy Burle, VP Sales and Marketing

It’s been said that “if a picture is worth a thousand words, a map is worth a thousand pictures”.  I couldn’t agree more.  The power of maps and GIS is the ability to quickly visualize information to give you a greater sense of understanding and clarity about all of the data you have at your fingertips.

I could write for days regarding all of the examples related to the power of spatial visualization (that’s a fun phrase to say, isn’t it).  However, because I like you, I’m going to spare you all of my spatial ramblings and focus on just one example – sales ratio studies.

The role of a local government assessor is to ensure fair and equitable taxation for the property owners in their jurisdiction.  Essentially, like properties in the same geographic location should have similar appraised values.  Visit www.IAAO.org for a plethora of resources relating to fair and equitable taxation.

Now, let’s look at sales ratios within a specific neighborhood.  The example below shows the calculated appraisal statistics for the selected parcels. They are also sorted into various ranges and color coded as such.

Outliers shaded blue
Outliers shaded blue

Immediately I can see I have a potential problem.  In fact, I bet if I asked my 9 year old daughter which two properties do you think are causing my problem, she would get it without giving it any thought.  If I pop over to the list view and sort by sales ratios, I’ll see my two problems rise to the top.  Obviously, I can see there’s a huge the difference between appraised value and sales price resulting in my high sales ratios.  In this case chances are the improvement or house has not been picked up yet.

List view sorted by sales ratio
List view sorted by sales ratio

So while I want to flag these two and send them back through a workflow so that the appropriate data is updated, I still need to finish looking at the rest of the neighborhood.  Therefore, I filter these out and once again view the map to see that everything looks much better.  I have better stats and a more even distribution of sales ratios.

Sales ratios after filtering
Sales ratios after filtering

Voila! The reason this is so efficient is that with the help of the map I didn’t have to spend my time reviewing all of the good data, rather I spent my time reviewing the bad data.  The map did the heavy lifting of filtering between the two.

An even simpler example of GIS quickly filtering the bad from the good is seen below.  Here graduating circles are dropped on the map representing an attribute such as appraised value.  Within less time than it takes to click on a parcel, I can see which parcels need to be reviewed.  Or most likely in your case, you can quickly confirm uniformity in with your appraisals.

Graduated circles providing a quick comparative analysis
Graduated circles providing a quick comparative analysis

These examples were created using DREAMaps Online.  If you would like to see more contact sales@sds-inc.com or register for one of our upcoming webinars found here -> https://smartdatastrategies.wordpress.com/dreamaps-online-webinars/

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s