A facility's location affects the trips people make to reach it and the journeys staff make to serve customers. When you're considering a new branch, clinic or service base, the question is who would get better access and how that would change the work.
The demand you plan to serve may involve repeated customer visits or requests at particular locations. People making those trips have different access needs, and the facility has its own service commitments. What counts as closer depends on the improvement you're trying to make.
| Decision objective | Demand measure | Comparison output | Outside-map check |
|---|---|---|---|
| Reach more demand | Visits, requests or units | Demand inside the same travel threshold | Capacity to serve the captured volume |
| Reduce travel burden | Trip frequency and travel measure | Weighted comparison for the same locations | Actual access and travel conditions |
| Serve distant demand | Demand beyond current reach | Outlying locations and their candidate access | Service commitments and practical trips |
Decide what closer should achieve
Choose the demand weight
Prepare a demand file with a location ID that stays the same, an address, a period and a numeric amount. Choose what one row means to match the decision. A customer-location row can include the number of visits made during the selected period. A service-demand row can include the number of requests at that location.
Keep the period consistent. Comparing one candidate against a full year of demand and another against the last quarter would mix up how a site serves demand with differences in the input. Use the same approved snapshot for every site.
If repeat activity creates most of the travel, keep that activity in the weight. A location visited weekly creates a different burden from one visited once during the period, even though both produce one pin. Don't let a simple count erase that difference.
Add a record-type field to distinguish demand, existing facilities and candidates. Give facility rows 0 in the demand-quantity column when they are included in the same file. That lets a sum represent demand without adding a facility to the workload. Keep blanks for genuinely unknown demand so you can check them.
Choose the comparison objective
Write down the service question before drawing areas. You might need to reach more demand within a fixed number of minutes, reduce repeated travel, or improve access for customers beyond the existing network. These aims can lead you to different sites.
Use your actual service rule for the threshold. If the facility is intended to provide a particular level of access, test that level consistently. A larger travel area may capture more demand, but changing only one candidate's threshold gives that candidate an unfair advantage.
For an average-travel comparison, use the same set of locations. Weight the travel measure by how often each trip is made when that suits the job. In a comparison spreadsheet, multiply each location's travel measure by the number of trips made to it. Add those products, then divide by the total number of trips. Keep a separate view of long trips because an average can hide them.
Maptive's travel areas and exports support this comparison. You still need to choose the objective and review the tradeoffs. Save that objective with the demand period before you start testing candidates.
Put feasible candidates and demand on the map
Start with sites that could become facilities. Check that each site suits the job early enough that a property in a good location doesn't take over the shortlist despite being unusable. Keep current facilities too, since they show the access customers already have.
Create New Map in Maptive, enter the map name, and select Continue. Upload the spreadsheet with its header row, then select Map Now. Open Data and Categorize Data to review the location-column matches.
Check candidate addresses against the actual site. A street address may place the marker near the building without representing the entrance people would use. Inspect access from the relevant road, especially when barriers or separate entrances could affect the journey. If you move a marker to the right place, record that change with the candidate ID.
Use the same care with high-demand locations. A point with a large share of visits or units can change the comparison a lot if it's in the wrong place. Confirm the source count and demand total before reading the pattern on the map.
For an initial weighted view, open Heat Mapping Tool, choose Represents Numerical Data, select the numeric demand column and sample, then Add Heat Map. The field must contain only numbers. Use the demand group as the sample where appropriate so facility markers don't contribute to the view.
The heat map helps you see where demand is grouped. Choose candidate sites through the actual site list and access tests rather than through the visual center of the colored area.
Compare the candidates' driving reach
A Maptive driving area assumes perfect driving conditions and doesn't account for past or current traffic. Use it to screen access, then check realistic travel conditions where the service commitment depends on congestion or a busy part of the day.
Open Map Tools and select Drive Time Polygon Tool. Enter the first candidate address, or use its marker as the origin. Set the hours and minutes for your agreed threshold, then select Add Drive Time Polygon.
Repeat for each candidate with the same time allowance. Use Edit Proximity to give each area a useful name and change its color or opacity. Include the candidate ID in the name so an exported catchment can be matched to the correct site. Keep the current-facility areas distinct from the candidates.
Click a polygon to inspect its location count and open Customize Metrics. Add the demand-quantity sum that belongs to the decision. A raw location count can include facilities and candidates if those records fall within the area. Read it as a demand count only after checking the record types included.
Compare both the amount reached and the locations behind it. Two candidates with similar totals may serve different groups. One may capture much of the same demand as an existing facility; another may reach demand that currently lies outside the network.
If you test another threshold, change it consistently for every candidate using Edit Proximity. Keep the first set of results with your decision records so reviewers can still see it. Otherwise, reviewers may compare totals made under different rules after you change the map.
Export the demand each site reaches
Use the polygon's three-dot menu and select Export Locations to get the records inside that area. Export File covers all proximities. Keep the site's ID with each output and use the location ID to join the exported records to the approved demand file.
Build a comparison sheet containing the threshold, demand period, included demand total and excluded demand for each site. Check that the export totals agree with the map's metrics. If they differ, check the selected records, enabled filters and any facility rows before drawing a conclusion.
When your rule is a distance in miles or kilometers, use Distance Radius Circles. Enter the starting address, set Proximity Within and the units, then select Add Proximity Radius. A circle answers a geometric distance question. It may contain locations whose road journey exceeds the straight-line distance to the same point.
The radius export can include driving time or driving distance as other measures. Keep those columns separate from the rule used to select the rows. Exporting driving measures for locations inside a circle doesn't turn that circle into a driving area.
Choose an output format suited to your comparison, such as XLSX, TSV or CSV. Keep the demand field and IDs needed to check the totals. If a selection returns only the closest rows, it cannot support a claim about every demand location without checking the rest.
Check the comparison's weak points
Separate overlap and uncovered demand
Don't add candidate catchment totals to estimate network reach. A demand location can appear in several catchments, and summing their totals would count its demand several times. Compare each candidate first.
For combined driving-area reach, join the exports for those areas by demand-location ID and keep each location once in the combined set. Compare that set with the full demand file to find the locations outside it. Keep their quantities in the uncovered-demand total, using the same snapshot as the included demand.
With circles, the multiple-circle export offers an option that returns each row only for its closest circle when areas overlap. That assigns rows in a specific way. Check whether nearest-circle assignment suits your operation before using it to propose how to assign customers.
The radius export's outside-results option can identify records excluded by the circles. Use driving-area exports for a road-time coverage question. Keep the method with the result so a reviewer knows what being outside means.
Check capacity and practical access
Review the building's capacity against the demand it would need to handle. Look at operating hours, staffing, usable space and other limits that affect the facility. A high captured-demand total can create a capacity problem even when the site offers better access.
Check lease terms, permitted use, physical access and local restrictions before making the site decision. Inspect known journeys and the most demanding trips. For a facility people travel to, consider whether the actual entrance and hours fit those trips. For a service base, review the trips staff would make from it.
Add checks you haven't resolved to the comparison sheet with an owner and a due date. Keep mapped reach, observed travel and property evidence in separate fields. That makes it possible to reject a candidate you can't use without hiding the access benefit it offered, and to identify what still needs checking before the remaining site can be approved.
