By Bill Meehan, ESRI
When I ran an electric utility operations division, one of my favorite employees was a guy named Stanley. Stanley started as a line worker. He climbed poles, became a foreman and then a supervisor. Finally, Stanley managed all the crews in the region. I remember how Stanley worked.
In the northeastern U.S., the hot, humid summer months particularly present a storms threat. You never know how severe the thunderstorms will be or where they will strike. Because this part of the country is heavily treed and most distribution lines are overhead, one violent storm could damage the electrical system significantly and result in many outages.
As crews rolled back into the service center after a day of work, Stanley had to decide whether to keep workers on overtime in case trouble hit or to send them home and hope nothing bad would happen.
Stanley had a routine. He checked the latest weather forecast to see where a storm would likely hit. He also knew which areas of the system were more vulnerable than others. He listened as crew chiefs told him where poles were leaning and wires were frayed. He knew where they hadn’t trimmed trees in a while and where the fussy customers lived. Stanley then stood outside and smelled the air. After his routine, which took a few minutes, he would walk back into his office, call the union steward and tell him how many crews to keep on overtime.
If Stanley kept too many crews and nothing happened, he would have wasted overtime money and would be shorthanded in the morning. If he kept too few workers or none and something bad happened, he would have had to scramble to get people back to work, which was difficult and sometimes dangerous. During all the years I knew Stanley, he rarely made the wrong decision.
Then Stanley retired.
Thousands of workers like Stanley will leave the industry during the next several years. The average age of U.S. utility workers is nearly 50, and more than 148,000 utility employees fall in the 55- to 64-year-old range, with another 26,000 employees older than 65, according to the U.S. Bureau of Labor Statistics. A recent study published by the National Rural Electric Cooperative Association (NRECA) showed that 61 percent of line superintendents are 50 or older.
Imagine all the wisdom and analytic power that will be missing when these workers retire. People like Stanley know where infrastructure problems exist. They know where the utility has not trimmed trees. They know the location of old and frayed wires that are waiting to fall down. They remember where storms generally hit and the problems storms cause.
Many utilities are missing an ability to capture as much of that wisdom as possible before the Stanleys of the industry retire. We need a way to share what retiring workers know and how they know it.
The Need to Capture Information
The common denominator of that knowledge is location. Utilities have been capturing facts in a geographic information system (GIS) for years. GIS can capture observations and predictive information, collect data from all kinds of sources and help utility staff make better risk predictions the way Stanley did. GIS can create geoprocessing models that document the data sources, run analysis and produce results in the form of a map.
Storm Planning Results
The key is to have these models validated and supplemented by experienced workers before they leave so utilities can build a knowledge infrastructure.
I discussed this recently in a blog and received valuable feedback from others in the utility industry.
Victoria Morrow, GIS manager for Broward County government in Florida, said knowledge retention is important for all aspects of government.
“How do we capture the years and years of experience in emergency operations, traffic management, 911, elections, etc., before these experienced workers retire?” Morrow said. “As GIS manager of a large metropolitan county, this issue is seen across almost all departments. It is even more pronounced in those agencies that have only just begun to embrace GIS technology.”
The concern is shared by any department that collects and stores data. This institutional data is a must in almost every industry. We acknowledge a need for it, but what can organizations do to get the data that is stored in the heads of seasoned workers?
Collecting Subject Matter from SMEs
Concerns accompany the idea of moving information from the mind of a subject matter expert (SME) to a tangible, accessible database. How do we best approach the task? What questions do we need answered? How do we compile and use this information once we have it?
Ron Brush, president of New Century Software, said gathering SMEs in a room has been a successful approach.
“We have a meeting facilitator, a GIS analyst and a system map on a big screen,” Brush said. “We ask the SMEs to tell us about different parts of the system they know best. The analyst creates new features and feature classes–usually polygons–and captures the knowledge about that part of the system.”
SMEs can impart information related to known problem areas, installation methods and materials used, landowner information and more. The SMEs’ names, dates and other metadata are attached. This information then can be vetted with other SMEs and organized later into a more usable format.
“The spatial SME approach will be important for gas distribution operators as they move forward with their DIMP planning and implementation,” Brush said. “While this approach may not replace Stanley’s ability to predict the weather, it can help retain valuable knowledge about utility assets that might otherwise be lost. Plus, I think it’s a compliment to the SMEs to acknowledge their experience and value to the organization.”
In the absence of SMEs, some industries are relying on historical incident data to fill the gaps in knowledge, said http://www.spatial-edge.com“>Sentil Prakash Chinnachamy, GIS project coordinator of business development for Spatial Edge.
“Institutional knowledge management is similar to metadata management–a challenging work flow in several federal, private agencies, usually blamed as a time- and resource-consuming process,” Chinnachamy said. “Combining old-school methods with the latest technologies could help. Imparting institutional knowledge collection in the data collection work flow is a way to go.”
For companies that have not started the data collection, it is better late than never, Chinnachamy said.
Add it to the To-Do List
The concept could be worthwhile to pursue, said GIS technician DeAnna Hohnhorst at Georgia Power.
“As a GIS technician with skills in building geodatabases, spatial analysis and modeling, I would be pleased to add this type of endeavor to my project list,” Hohnhorst said.
Transmission Risk Results
Gathering experts in a room and drawing concerns on a map for entry into a GIS has significant value. By applying spatial analytics, we can combine SME data with authoritative data. This analysis connects the dots between what people know and what operations or historical data is stored in the system. Also, the visual presentation in a GIS-based model builder environment gives experienced workers the ability to investigate variables in something crucial such as a risk assessment. Stanley might look at the model and say, for example, “You forgot to include soil types in the assessment; trees fall over easier in sandy soil than in clay.”
Stanley was doing spatial analysis in his head. He was taking data from sources, merging that data with his own and co-workers’ experiences, and predicting where problems most likely were to occur. He mitigated or at least prepared for the problems. When a storm hit and outages occurred, Stanley never was surprised; he had a restoration plan in his head ready to go.
The common denominator of Stanley’s thinking was geographic location. Stanley connected the dots related to geography. The intersection of the many problems together created for him the areas of highest risk and vulnerability. If the storm hit there, he would be ready.
Most utilities have collected an enormous amount of data that can be used for spatial analysis within a GIS. Traditionally GIS has been used for making clearer maps of the electric system, but it now serves as a framework and foundation for the knowledge infrastructure.
For utilities, this knowledge infrastructure is as much an asset as the actual pipes, wires and hardware of the electric or gas system. The more knowledge a utility has about its assets, employee experiences, customer behavior and the world around them, the better management decisions will be.
Bill Meehan joined Esri in 2002 and is director of worldwide utility solutions. He has an extensive background in utility operations management including information technology and GIS integration.
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