Optimizing Union Election Locations

We were contacted by Food Workers Union whose members *(numbering in the thousands) covered multiple states and hundreds of locations. The Union wanted to optimize poling locations for their upcoming elections. They wanted targeted locations within a certain distance and drive time of each store. The Union also wanted to keep crowds to a minimum so an upper limit of members per poling location was added.

With this information, we analyzed the location patterns of the data and provided a draft of preferred sites. We provided information in both map and excel form so the union could see the results and make revisions. With the preferred revisions from the union, we re-analyzed the preferred locations and finalized the process.

The end product was a large format PDF map of all locations and an excel list of selected locations. The map included all locations with the selected sites highlighted. Distance rings and drive time areas around each of the selected sites. Along with a resulting Trade Area used to calculate the max members per location.

Using this geographic analysis of Union locations and the associated membership numbers we successfully streamlined the poling location selection process. Optimizing the entire process for all involved.

We can perform this geographic analysis (or additional queries) for your Union or local membership as well. Let us know how we can help.

Demographics tend to be a pretty boring thing. Yet they are very important to just about every aspect of business. Typically people are used to seeing demographics in some article or research stat piece. Or in more detail in a dedicated report that is a standard but boring 1-3-5 Mile radius ring study. For a review on past examples of how a radius search works start here.

We are going to elevate our demographics game to another area that isn’t talked about much.

What can you get out of Demographics?

Take your existing data (lets say a trade area or service area) and populate that boundary with all kinds of specific demographic information that pertains to your goal.

This isn’t the laundry list of potential values like Population, Households and Income. We can custom tailor the variables that you need and calculate new ones based on that info. Then package all the targeted variables up into a webmap that you can reference and work with. Keeping the data useful and relevant for ongoing projects.

We find this new way to visualize targeted demographic information about your location very useful when combining that data with other inputs. It then becomes a baseline of research data for your team.

We hope this short glimpse into a new way of displaying demographic information sparks some key uses in your organization. If so we would love to put something together for you.

Trade Area Basics

We had a client project that fit this sample set perfectly. We started from a location list of over 300 stores with the associated number of employees included in the data. Goals were create 10 equal trade areas (and the associated center location for each) based on a set distance & drive time. They also had to include roughly the same number of employees per trade area. Second goal was to show the 10 densest locations based on the number of employees per location.

After running the distance rings, then the drive times like shown in the previous Trade Area Basics articles, we added the extra dimension of number of employees. Finishing with the appropriate trade areas based on location and final numbers.

Second goal was approached a bit differently. Starting with a smaller distance of 5 miles we performed geographic searches trying to find the 10 locations that had the most employees without duplication.

Overall here is what we ended up with.

Great project to show off how to use Trade Areas in a practical way. Answering real world questions with the use of GIS.

Contact us for you next Trade Area map project.

The Trade Area

We take the best of all variables and draw what the typical pattern would be for someone to get to your site. Most importantly including number of other locations someone could go to. Radius and Drive Times do not account for this.

In this example we have added three other locations and their respective trade areas then added the trade area for the new location.

The areas we are showing here are derived from a combination of radius, drive time and physical and mental boundaries along with store locations. Remember no matter what area you come up with there will always be outside factors that will influence your potential trade area.

Much different than either of the previous examples. While all examples have their uses we find trade areas to be the most useful. Of our three examples which do you prefer?

Let’s wrap everything up for you with a real world example.

The Drive Time

Basically this is done by accessing road type and an associated speed for each road segment. The software estimates out the area one could travel at assumed posted speeds. Also the model typically does not include for any time stopped at a stop sign or signalized intersection. Better said, just straight driving time no stopping.

This can also be adjusted for time of day. By default it does not account for any traffic. You can add your selected time of day and directionality to the search to get a rush hour value as well if needed.

While this does a better job showing a trade area that is more probable based on physical boundaries, it missed mental boundaries. Is someone really going to travel 10 min by freeway to get here? Well that depends on what the draw is. That’s where the final leg of our trade area journey comes in.

We will look at the final approach in part 3 of our series, the trade area.

Have Questions? Contact Us.

The Radius

While this is useful in a simple yet standard setup, it could miss very important items like physical and mental boundaries. Kind of like this sample.

While we are showing a 3 Mile radius, we are ignoring in this example that the area show only has population in half of the area due to the mountains on the east. More commonly known as a 180 Degree trade area.  It’s also ignoring mental barriers like people on the other side of I-215 and their unwillingness to travel further south away from their typical traffic pattern.

For better or worse this is typically the starting point for all trade area analysis. We use this approach all the time to illustrate simple distances between targets. We also use it in to build the basics of a trade area you will learn about in Part 3

Overall it’s a good starting point for simple comparisons but it’s lacking. We will look at Part 2 in this example set next, the Drive Time approach.

Have Questions? Like to know more? Contact Us.