Getting it right: 99.9% pure OMS data
OMS Basics
An outage management system allows utilities to better support the detection and restoration
of service interruptions. Mature products and custom solutions support the following
functionality
-
Graphical display of trouble calls, outages and crews
- Rapid Prediction of Outages from trouble calls
- Creation of Outages from SCADA information
- Separate call-taking application or interface to billing system
- Reporting & archiving capabilities
- Efficient user interface
OMS operations are characterized by long periods of light activity, punctuated by storms.
During storms, any deficiencies with the software or the underlying data are magnified,
potentially rendering the system useless.
For a typical utility, the most expensive part of an OMS is the data. However, because the
database is often in place before an OMS is deployed, this cost can be hidden. Much of the
cost of deploying an OMS can be attributed to making the GIS data model support OMS,
finding and fixing inconsistencies in the GIS data, reconciling customer information between
GIS and the billing system, and bringing all the data up to an acceptable standard.
An OMS depends heavily on the data completeness and quality. The OMS is typically very
good at revealing problems with the underlying GIS data, but not so good at fixing them.
The OMS may be especially sensitive to certain kinds of errors, especially errors that result
from uncommon combinations of processes.
Separate dataset
GIS in utilities grew out of facilities management and automated mapping. The data and
modeling requirements of these systems differ from the requirements of OMS. Therefore, all
OMS systems rely on a separate database for their operation. OMS databases are highly
optimized to support prediction and switching operations, at the expense of maintainability.
One of the requirements utilities face in deploying these systems is to build a bridge between
their operational data, and the OMS data structure. This bridge is used often.
Even utilities in stable areas face changing facilities and customer locations. Utilities in
growth areas (e.g. Phoenix, Arizona) add thousands of new customers each month. The
highly-tuned OMS data structure must be refreshed regularly from the underlying facility
data. Some vendors offer an incremental update tool for accomplishing this, while others
require that the OMS data be rebuilt for any change in the facility data.
High Volume
In early 1998 the Northeast U.S. experienced a massive ice storm. Tens of thousands of
customers lost power, some for more than two weeks. During this event, call centers were at
their maximum throughput for days, taking thousands of calls per hour. And utilities that had
contracted with outside call centers were flooded with data from those services. The modern
call center has given customers the expectation that they can report information and get
feedback. This customer expectation translates into a high volume of data throughput for the
OMS. When done right, the OMS can keep up with call center and Interactive Voice
Response (IVR) system volumes, providing the operational crews with synthesized
information on the state of the network.
Mission Critical
In the days of smaller utilities and lower customer expectations, operational personnel did not
consider OMS to be important. Now, with a fire hose of data pointed at them from offshore
call centers and IVRs, and performance-based rates on the horizon, OMS has become
mission critical.
