I remain surprised as I monitor happenings in the global geospatial industry that we have not progressed as far as we should have in our thinking in a number of key areas. This is especially the case in the application of geospatial data to inform decision-making in the holistic planning of government services and retail networks. What has happened to "location, location, location" as the alma mater of the geospatial industry? Where are the great academics of yesteryear that developed and drove these principles?
As a practitioner, I have applied the science of using accessibility modelling to look at optimizing government services and retail networks. This has lead to the publishing of the Guidelines for improving geographic access to government service points that has guided potential users in some of the key principles that need to be considered when looking at optimizing the network of public services in a country. Some important principles is the use of a Greenfield approach that looks at what is the optimum number of service points and where ideally they should be located. This approach does not consider what is presently in existence.
In the real world, there is existing infrastructure that has cost millions to develop that must be taken into consideration in optimizing the provision of services. Some of the existing services will have not been optimally located from the start and ideally should not form part of a future solution. In the positioning of service points one should also look at prime sites - sites where facilities should ideally be located (eg near a cluster of government services). In the private sector the location of competitors is also critically important. The consideration of these factors necessitates the use of what I term a Brownfields approach.
In combination, these two approaches enable one to verify an important decision and that is - whether the government services or retail network should be expanded, reduced or relocated? To be able to get to this point, one has to have integrated critical geospatial datasets into the accessibility models. This includes demand (ie target population) and supply side (ie location of existing outlets & competitors). One needs to look at these two pivotal aspects of the well known economic principle to try and understand the the environment within which this is happening. In the concept of the Diamond of Spatial Network Analysis this a key aspect.
In the global community people glibly talk about "access". What is access? It is the connecting of supply and demand or origins and destinations through some form of transport network taking into consideration particular modes of transport. This could be scholars walking to school, people using buses or trains to get to work or private vehicles to reach banks. It requires a transport network that links origins to destinations and considers the mode of transport and the average distance or time a customer should ideally travel to reach a destination.I am quite sure that the future will see the use of drones as a key transport method of getting goods to customers (not ignoring the IoT that has already impacted and traditional methods of accessing services).
The question is often asked - how is the travel distance or time determined? One way is to conduct social surveys and to collect the information from beneficiaries or consumers. A more accurate way is to collect data on customers using a particular facility over a period of years from service providers, geolocating their residential or business address and then defining their primary and/or secondary trade areas. The average distance or travel time can then be calculated from the trade areas. Very importantly, the travel elasticity can also be calculated and used in gravitational flow models.
Demand, supply and access are foundational aspects of the Diamond of Spatial Network Analysis. However, the target population for your service point or retail outlet might be people earning a certain income and for that facility to be financially viable, you need a certain capacity within a particular distance or travel time. By not taking into consideration consumer purchasing behaviour you might be allocating facilities to areas that are not going to use it or you might be missing out on areas that may be a very lucrative markets. Therefore, knowing how many people are using your services or products is invaluable in targeting your market more effectively.
Consumer purchasing behaviour can be obtained from nationally representative household surveys, such as the TGI Consumer survey conducted in many countries across the world. This information then needs to be integrated into a geospatial environment so that secondary datasets can be combined with the survey data to model and map it using small area estimation techniques. Across the world countries are implementing these types of surveys that can be used to provide critical data on consumer data for use in Spatial Network Analysis.
In the global community, saturation in the retail sector of developed economies is becoming a real concern. In developing economies locating service points in their optimum locations right from the start could dramatically improve service delivery. To enable countries to achieve the Sustainable Development Goals (SDG) requires a holistic approach to the provision of services. The Diamond of Spatial Network Analysis is a key concept that will enable this to be achieved.