As we’ve been hearing for some time now, all utilities that utilize ESRI technology for their GIS will at some point, sooner or later, need to migrate to the new Utility Network (UN). As time marches on, later is starting to become sooner for more and more utilities across the country. I was surprised recently when I learned that one long-time customer of ours, who I have always considered to be “middle of the road” when it comes to the timing of new technology adoption, is moving forward with a migration to the utility network and will have an active project going by mid Q2 of this year. For them, they felt like they could no longer wait on some of the benefits inherent with UN. Understanding their current situation, I completely agree with their decision.
As a part of their overall migration project, there is a GIS data cleanup component. This will be true for almost all, if not all utilities as they migrate to the new high-fidelity environment. As the environment, its associated capabilities and the related applications all become more sophisticated, the accuracy and integrity of the data must be better to support the increased functionality. Here is a partial list of some of the data issues we’ve been seeing that are causing errors when migrating to utility network:
- Stacked features (overlapping line features or stacked point features)
- Invalid geometry (features with null geometry or linear features that “back up” on themselves)
- Missing features (e.g. primary line connected directly to secondary line with no transformer)
- Incorrect connections (e.g. meters connected to primary lines, transmission main connected directly to distribution main, 3 phase devices connected to1 phase lines, mixed voltage connectivity)
- Incorrect device placement (e.g. streetlight placed where logically a transformer should exist)
The following types of errors have a less significant impact on the migration process itself, but still affect overall quality and completeness of the network:
- Disconnected geometric network features
- Geometric network banks missing units (e.g. a 3-phase transformer bank having only two units)
- Invalid or missing attribute values that are critical for mapping and further network behavior (e.g. missing pressure, missing pipe size, incorrect phasing, no overhead/underground designation, incorrect open/closed status)
- Incorrectly connected lines that cause network loops
- Indeterminate flow direction in the geometric network, prohibiting establishment of proper terminals of directional UN features
So, does your data have these types of anomalies? Very likely, almost certainly, it does. Without a continuous, focused program to check for and remediate these kinds of things, your GIS editors, as good as they are, will occasionally introduce errors like these. Over time, they accumulate. So, if the move to UN requires that at least some of the errors in your GIS data be corrected, what should you do about it? I think at a high level, you have two options:
- When the time comes for your organization to make the move to UN, include data cleanup as part of the overall effort, or
- Start on a cleanup program now, ahead of your migration to UN.
For most organizations, I think option 2 is the right choice. The move to UN will be a substantial project which will require a lot of planning and a well-crafted roadmap for success. There will also be a significant amount of organizational change management required as a part of this project, considering the number of people in your company who touch the GIS. If you can do a good portion of the data cleanup work ahead of the actual migration, you remove this component from the requirements, thus simplifying the project to a certain extent. This is true whether the cleanup work is done with internal staff or with the involvement of outside consulting resources. Given the potential complexity of your migration to UN, anything you can do to remove requirements must be considered a plus.
The second major reason to consider initiating your GIS data cleanup efforts now, rather than later during the migration effort, is the benefits that will accrue to your organization from enhanced data. Increased data integrity means more reliable results from external applications which depend on GIS data and more reliable information for field personal when they’re on the scene.
If you decide to embark on a data cleanup project ahead of your migration to UN, I have one more suggestion for you. I believe that quality is contagious, so spread the word about your quality improvement efforts. Let as many folks in the organization as possible know what you’re undertaking. I believe this is particularly applicable to your organization’s field staff. They see your facilities first hand, so they know if their representation in the GIS is correct or not. Get them involved in providing quality feedback and keep them informed of your progress and you’ll have the foundation for long-term win-win relationships. For more thoughts on this, please see a previous blog at:
If you have questions or would like more information on how to get going on a data cleanup effort, please get in touch, we’d love to talk. Thanks for reading!