Geospatial site selection: from a business question to a shortlist

“Where should we open next?” sounds like a single question. In practice, it combines several decisions: which customers to serve, how far they will travel, what the site must accommodate and which uncertainties the business can accept.

LGM connects spatial data and computation to help turn that question into an investigation. The useful result is not simply a pin on a map. It is a shortlist of places, the evidence behind each candidate and a clear account of what still needs checking.

Define the site before searching the city

A neighborhood market with 10–20 stalls needs a different analysis from a regional shopping center. A sports facility, office hub or school introduces another set of requirements.

Begin with a brief that specifies the territory, intended users, approximate footprint, access requirements and expected output. Separate requirements that cannot be negotiated from preferences that can be traded off.

For example, a market study might require pedestrian access and space for deliveries. Proximity to public transport could improve a candidate’s ranking. Confirmed permission for commercial use would need authoritative local evidence, not an inference from a map label.

Build the comparison from complementary layers

Four groups of evidence provide a useful starting point:

• Demand: population distribution, relevant demographic indicators and nearby activity generators.
• Access: streets, crossings, public transport and barriers that shape practical journeys.
• Existing supply: comparable businesses or facilities and the areas they already serve.
• Constraints: parcel information, land use, physical conditions and documented restrictions where available.

No single layer answers the whole question. A dense neighborhood may already have adequate provision. An apparently empty area may reflect incomplete business records rather than unmet demand.

LGM’s raster and vector services support working with these different representations together. Local collections can add details that global data does not contain.

Keep exclusions separate from preferences

A common analytical mistake is to combine every indicator into one score too early. A high demand score should not compensate for a site that fails a mandatory requirement.

First identify exclusions supported by the available evidence. Then compare the remaining candidates using explicit preferences. If access is weighted more heavily than surrounding population, say so. Compare alternative weightings to reveal whether the shortlist is stable or depends on a narrow assumption.

The goal is an explainable decision process, not a precise-looking number without a defensible meaning.

Move from priority zones to candidate sites

Citywide screening and site-level selection should be separate stages. The first identifies promising neighborhoods or corridors. The second investigates smaller areas using more detailed evidence.

The Tbilisi research illustrates this progression from broad territorial questions toward specific priorities. A high-priority zone is an invitation to investigate, not confirmation that any particular parcel is available or suitable.

At the smaller scale, useful follow-up checks include ownership, current occupation, pedestrian conditions, servicing and local approval requirements. These may require customer data, professional review or a visit.

Deliver a shortlist that supports the next decision

A useful deliverable includes candidate geometry, supporting indicators, source dates, missing evidence and the reasons a candidate was included. It should also explain what new information could change the recommendation.

That structure lets a business team discuss trade-offs while a GIS professional continues the spatial analysis. It also makes the next investigation more focused: resolve the uncertainty that matters most, rather than collect every available dataset.

To begin, open LGM GIS with one territory, one proposed service and a question you can evaluate against real-world evidence.