Utility GIS users meet at Esri GeoConx

I spent time this week at the Esri GeoConx conference in Phoenix, Arizona. The GeoConX conference is a gathering of ~800 GIS users from gas, electric and telecom utility companies.

I always enjoy listening to GIS professionals from utility companies because they are faced with the most interesting GIS and data management problems. High on the list is data integration. Not necessarily the integration of disparate GIS datasets (although that’s an ongoing challenge), but rather GIS data integration with other systems that manage work orders, financial systems and more.

I took a lot of pictures at GeoConX and I think they tell an interesting story about the issues GIS professionals at these utility companies are facing.

Eight hundred people from 44 U.S. states, and countries as far away as New Zealand, attended GeoConX.

Esri President Jack Dangermond re-emphasized the System of Record (authoritative data source), System of Engagement (collaboration/sharing), and System of Insight (analytics) concept that he introduced at the 2015 Esri International User Conference.

He also made a comment, which he has before, that Esri spends ~27 percent of Esri’s annual revenue on research and development. That’s about $230 million per year. To put in that perspective, in 2015 Apple Computer spent 4 percent of its revenue on R&D. Renown automobile innovator Tesla spent ~18 percent of its revenue on R&D. Toyota spent 4 percent.

Granted, those companies have significantly higher annual revenues than Esri, but you have to give Esri kudos for re-investing and keeping the company ownership closely held. If Esri was a public company, or had significant external shareholders expecting typical investment ROI (Return on Investment), shareholders would want a piece of that R&D budget in their pockets.

A devil’s advocate might say that a different corporate structure might pressure Esri to be more efficient with R&D spending, but I have a lot of respect for Esri’s chosen business model, which enables it to remain ably nimble.

Location-based services are “hip.” The 18- to 29-year-old demographic leads the pack in all usage categories. Getting “kick-back” from employees who are hesitant to trust or embrace GIS technologies? Just wait a few more years as the 18-29 demographic works its way through age groups like a rat in a snake’s belly.

This slide will be interesting to those of you whom have asked where GIS lies in the adoption curve. According to Esri, GIS technology adoption has passed through the “early adopter” stage and is building momentum with the “early majority.”

The BART (Bay Area Rapid Transit) presented its implementation of enterprise GIS. I’ve heard similar stories in the past, but perhaps their most interesting data was the statement that BART has derived $3.11 in value for every $1 invested in GIS technology.

A look at Esri’s software release schedule for the next year.

Tracking and traceability was one of the hot topics, especially in the natural gas industry. While the natural gas industry is driving the technology, once it’s developed there’s no doubt the concept and technology will seep into other industries. Better systems and data = better decisions and accountability.

NYSEG/Avangrid gets my vote for “quick and dirty” mobile GIS deployment of the year. Six months, 300 iPads, develop app, train staff, deploy tablets. No enterprise-level MDM (Mobile Device Management) system. Don’t accept that iOS 10.x update prompt!

Construction as-built data should be treated as a valuable asset, not a luxury that can be cut at the end of the project. As one who has created many construction as-built maps over the years, they are preaching to the choir. An accurate construction as-built housed in an accessible database is worth its weight in gold.

This slide shows “decreased GPS performance close to buildings and under trees.” Please read my column from last month.

Last but not least…

This slide is worth a thousand words. It succinctly illustrates the problem facing nearly all enterprise GIS that are loaded with legacy data.

This particular slide describes new attributes that are being added to Esri’s pipeline data model. The driver of this action is the fact that GNSS data being collected is likely more accurate than the legacy vector data. It doesn’t matter if it’s a pipeline, a tract boundary, a valve or any other infrastructure, the age-old question is “Why doesn’t my GPS data line up with my basemap?” The answer, nine times out of 10, is because the basemap is less accurate than the GNSS data. Therein lies the rub.

When this situation occurs, there are two choices:

1. “Move” the basemap data (I’m being overly simplistic) to match the more-accurate GNSS data.
2. “Move” the more-accurate GNSS data to match the less-accurate basemap data.

Common sense tells one to move the less-accurate basemap data to match the more-accurate GNSS data. However, moving basemap data can lead to all kinds of challenges. It’s the GIS house of cards. If you start moving the cards at the bottom of the structure, the foundation becomes weak and you’ll likely need to rebuild other parts of the basemap, which can be quite an undertaking.

To that point, coordinate fields (GPSX and GPSY, and soon-to-be GPSZ) are added as attributes to store the high-accuracy coordinates of the features. Then, believe it or not, the more-accurate GNSS data is moved to match the less-accurate basemap! It seems counterintuitive, but the logic is that sometime in the future as the basemap data evolves and accuracy improves, the high-accuracy coordinate values of the features are preserved as attributes and can be “brought out of storage” and placed into service at an appropriate time in the future.

Almost every enterprise GIS faces this problem. How are you handling it?

Thanks, and see you next month.

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Photos: Eric Gakstatter