Leveraging capital projects for GIS success

Leveraging capital projects for GIS success

Rick Frymyer
Orlando Utilities Commission
6003 Pershing Avenue
Orlando, FL 32822

Abstract
This paper will look at how the Orlando Utilities Commission was able to use current work activities and capital projects to leverage the development of their GIS. The cost to develop an enterprise-wide GIS can easily exceed the budget of an organization. But by designing projects to include the collection of information that will be used in the GIS, implementation costs and time can be greatly reduced. Specific examples will street light inventories and joint use surveys.

Defining specific goals and objectives well in advance of implementing new GIS technology or expanding your existing GIS technologies greatly improves the chance of success. The earlier you begin to understand what you want the future GIS to accomplish, the better you are positioned to identify opportunities to leverage against future GIS conversion/data migration efforts and costs.

I am suggesting that opportunities are found when integrating GIS technology concepts into engineering design, outage management and work management processes as well as capital projects not related to GIS implementation, prior to ever starting your GIS implementation project.

More often than not, the cost to implement GIS ends up far greater than the anticipated budget you initially suggested to senior management for their “move forward cautiously” nod and “come back later with more info” directive. This is a normal occurrence as we try hard to avoid early “sticker shock”. And, in most cases, it isn’t until you are well into the planning phase that you finally realize what your GIS scope encompasses and the true costs associated to achieve it.

One should consider how technology can interface with your current business processes and how daily work activities and projects can be used to leverage the development of the GIS. By designing work processes and projects to include the collection and maintenance of information/data that will be used in the future GIS, implementation costs and time can be greatly reduced.

Orlando Utilities Commission (OUC) has made good use of this approach. Knowing the ultimate goal was to develop an enterprise-wide GIS, OUC used two capital projects to begin developing important, fundamental components of the GIS.

One of the initial goals of the GIS implementation was to combine information from multiple drawing sets into the GIS database and eliminate the maintenance of redundant data. OUC maintains seven different sets of AutoCAD drawings representing the OUC electric distribution system. The drawing sets included over 4,400 maps and detail drawings.

Based on a 1997 GIS implementation planning study, OUC knew that one of the data conversion needs was to collect more accurate facility locations and information about the facilities. The cost for converting the data was included in the GIS implementation plan. At the time, the cost exceeded the amount OUC was able to budget. Subsequently, the project was postponed.

However, over the last three years, OUC has used two capital projects to develop components of the GIS database. OUC’s outage management system implementation and field data collection project was used to build essential database components for the implementation of GIS. The approaches taken significantly reduced the cost for data migration. The projects were designed to meet the future GIS database model requirements.

The first project was the implementation of an Outage Management System. To support the OMS a complete recompilation of the feeder/circuit maps to include full connectivity of all devices and conductors. This also produced a set of circuit drawings that met the topological requirements of the GIS. The second project which I will describe more fully was a full electric structure field inventory.

The field data collection project was driven by the need for a current and accurate street light and joint use inventory. This task could only be accomplished by field inventorying each pole. We also added to the project scope, the collection of all pad mounted transformers and switchgear.

To improve tracking and maintenance of the facilities an asset number (unique number) was attached to each structure. Because there was a need to improve the positional accuracy of facility structures and validate information about the system, the project was expanded to include the collection of GPS data and device information in addition to foreign attachments and street lights. The cost to collect the additional information was minimal. The majority of the cost for the field inventory was the time spent getting to each structure.

To assure the project outcome would be compliant with the GIS, a default electric database model was used to define the field data dictionary. The goal was to limit the amount of translation work necessary during the data conversion phase of a future GIS implementation.

A Microsoft Access database was developed containing tables and attributes replicating the electric database model. The database included only features that were to be collected as part of the field data collection project. This effort facilitated the migration of the collected into OUC’s electric GIS database with minimal translation work.

Another major benefit is the reduction of work necessary to adjust the electric facilities to the more accurate landbase being provided by the Property Appraiser. The collection of an accurate geographic location eliminated the need for the conversion technicians to move each structure, conductor and device to a more accurate location. Instead, a program was developed to link the device and the structure and snap the conductor and devices to the new accurate location.

This was accomplished by assigning the structure asset number to the devices on that structure in the digital source drawings (this was a normal map maintenance activity). The task then was to confirm the snapping programs solution and make any corrections because of errors in the original data. The time savings from this automated process directly translated into lower conversion costs.

Not only was the cost for data conversion moved from the GIS implementation budget but the outcome of the field data collection project also produced increased revenue. The additional revenue further reduced the cost of the GIS implementation.

In closing, OUC gained several advantages toward their eventual GIS implementation by performing the field data collection project and the OMS implementation prior to, and as independent capital projects not associated with the implementation of GIS.

For one, conversion data quality was improved greatly. Secondly, time to convert data was reduced by 50%. And thirdly, overall data conversion costs for the GIS implementation were reduced by 50%.