As more and more utilities turn to Collecting & GIS solutions, these products continue to evolve from primary data collection to advanced analysis tools used for operations and planning.

The objective is to lower costs and improve customer service. Still, a lot goes into every application to develop a trustable data model that utilities can use effectively.  

So, let's look at the steps for what's involved. The success of any Collection/GIS model is based on three factors, so we'll walk through those and provide information and analysis along the way.  

Accurate Depicting the Locations  

Start with an accurate depiction of all physical infrastructure assets that make up the network, including the cables, lines, and structures. This depiction can be used with a base map and foreign assets data-i.e., from other utility systems, to provide the foundation for automated map making.  

The data model can be used for  many elementary asset management functions when attribute information is added. These data support the basic spatial and attribute query operations that are familiar to GIS users.  

But this is just the beginning. All collected data can also be the foundation for other management functions like customer service, executive information systems, operations and engineering.  

Modelling the System Operation  

The second key factor in this kind of modelling is providing a utility map that accurately represents the actual utility asset's network.  

The accuracy of this model is determined to a significant degree by the accuracy of the topology. Attributes may be stored in a way that defines whether a given  

line is unobstructed or not. When this combination happens, sophisticated applications become possible, especially in subsurface engineering analysis that involves extensive geology analysis.  

Spatial Representation  

The third key factor in this kind of modelling is integrating an accurate spatial representation into the other utility databases, creating a unique digital workflow.  

These may include finance, accounting or work management systems. A broad array of aspatial data is necessary to enable those integrated functions that makeup both the traditional and unconventional automated mapping/GIS data and information, including geo-demographics, billing and customer files (e.g. satisfaction surveys).  

The heart of any Collecting/GIS application is the spatial model of both the assets and the land base features. The attributes of both of these entities are usually stored in an RDBMS (Relational Database Management System), which is referenced in documentation and descriptions of an automated system that performs analysis, creates maps, measures productivity, and shares data throughout the whole enterprise and beyond.