Yeah, It’s Got a HEMI: High-end Results from a Low-cost Geospatial Package

By Charlie Marlin, Graphic Technologies Inc

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Readers of a certain age will remember when Chrysler introduced the HEMI engine. By making the cylinder head hemispherical rather than flat, Chrysler got more power from a given engine displacement. Valves were mounted in line rather than side by side, which allowed for larger valves, which meant more fuel and air to the cylinder; the placement of the sparkplug at the top of the hemisphere enabled a more complete combustion; and the hemisphere also dissipated less heat so that peak pressure could be maintained at a higher level.

The proof is in the pudding: In 1964, cars with HEMI engines took first, second and third place at the Daytona 500.

Today, Chrysler uses the term to associate today’s HEMI engines with the breakthroughs of the past. So the point of saying “Yeah, it’s got a HEMI” is to proclaim innovation and power.

Disruptive Technology

According to Wikipedia:

“The term “˜disruptive technology’ was coined by Clayton M. Christensen and described in his 1997 book The Innovator’s Dilemma. In his sequel, The Innovator’s Solution, Christensen replaced the term with the term “˜disruptive innovation’ because he recognized that few technologies are intrinsically disruptive or sustaining in character. It is strategy that creates the disruptive impact.”

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The example of disruptive technology I like best is the LCD wristwatch. When first mass produced, it was no competition for the Swiss watchmakers. When someone showed it to them, they viewed it with skepticism, asking “But where is the movement?” A decade later, the Swiss watch industry was in shambles. Now it survives only at the very high end, and it has given up distinguishing itself from LCD watches by telling better time. The analog watch has become an ornament, not a tool.

The general phenomenon (see Figure) is that the new or disruptive technology often does not perform as well as the dominant technology. As it improves, it slowly eats away at the dominant technology’s market share. Eventually, the disruptive technology replaces the dominant one, or relegates it to a niche role. Think of digital photography as another example. The first digital cameras were expensive and had low resolution. Today, film is not dead, but it has been replaced to a large extent.

My claim is that we are on the verge of another disruptive combination of technologies that will change how utility companies use geospatial information technology.

The dominant technology is the full-function fat-client GIS editing seat. It has added more functionality than the normal user can learn and adopt. You see this when vendors describe capabilities that are really cool, but you realize only a small number of power users would ever learn to use them effectively.

The disruptive technology does not yet have a name, but it can be seen in products that have been called “viewers.” These “viewers” are rapidly making a name for themselves as their capabilities grow and functionality increases.

Stages of Viewers

Viewers began their life in the GIS world by providing an approximate or similar representation of the data seen on a full GIS edit seat. This progressed to providing equivalent representations. As an example of a disruptive technology improving to the point where it surpasses the dominant technology in certain ways, today’s viewers have the ability to provide the user with multiple views that may or may not be the same as seen on the full edit seat. Today’s viewers can even provide specialty views that are not provided by the full edit seat and can include data that is not in the GIS.

Stage 1: View. At its least, a viewer provides a graphical display of geospatially related objects. A viewer at the next sub-stage will show geospatial data as a seamless map so the user does not have to call up particular facets by name or number. More functional still is an intelligent map. The user can query objects for attribute information (not seen in the graphics, but available in a database), such as the diameter of a main or the manufacturer of a transformer.

Stage 2: Redline. At its least, redlining means non-destructive markup-like a crayon on an overlay. More functional markup consists of basic drawing tools: line, circle, polygon, text, etc. Another improvement is the ability to place symbols, and an especially helpful variant is to place the same symbols used by the GIS.

Further up the scale comes more sophisticated drawing that includes “drafting” or “CAD” capability like dimensioning, snapping to vertices and precision placement. Extending still further is the ability to set hyperlinks. These may link to URLs, to photographs, to scanned drawings, etc. At this point, the “viewer” is effectively growing its own data.

Setting or recording tabular data as part of redlining represents yet another extension of redline functionality: “Intelligent Redlines.”

Have we gone beyond what most would consider a simple “viewer” yet?

Stage 3: Information Sharing. This stage can be seen as a subset of the redline stage, but it changes focus from what the user records to what the user does with it. Information sharing started by printing a view and sending the paper. Then it took a digital step by sending screenshots instead of paper.

Now, viewers can be used to send markups to the home office, engineering center or other field personnel. There are several natural applications here. A field worker may find that a facility exists in fact but not on the map. He draws it, assigns attribution, and sends the results back to the mapping editors to incorporate into the GIS. In another example, the supervisor who approves field inspections has the option of sending a case that requires immediate attention directly to the engineering service center for repair, rather than sending it to the inspection database as usual and waiting for the information to eventually filter out to the service center.

More sophisticated viewers can also push redlines to the GIS. This sub-stage can take several forms. The user may send merely a picture of the markup to GIS editors. Or, he may send tabular-only changes to a supervisor who records approval and posts directly to the GIS. Or, the markups may be incorporated in the GIS as an alternative or a separate redline layer. Or, the markups may be sufficiently robust that they can be incorporated into the GIS as properly sequenced transactions.

Is “viewing” the right word for these activities?

Stage 4: Analysis. Analysis, like information sharing, has a different focus from basic viewing. Instead of just looking, the user analyzes the data to see what it means.

Suppose a user wants to know what features are located within a certain distance of a facility. The “viewer” can produce a buffer zone around the facility in question and graphically show the user what features are within the specified distance. One step further would be to provide a count of each type of facility within the buffer zone.

A gas engineer might want to know where all the sections of cast iron main are located. Or an electrical engineer may want to track down all the transformers from a particular manufacturer. These questions can be answered by a thematic query, which finds the features of interest and highlights them. Next, the software can provide a report of the features of interest so the user can paste them into Excel or another software package.

This sort of analysis relieves human beings of tedious processes and lets them use human talents more fully, sort of like a truck takes on the work of hauling heavy weights long distances and lets the driver decide where it needs to go. The thematic query gives the utility engineer a great tool for analyzing what sorts of facilities are in the service territory and where they are located. Then he can relate the pattern to causes and effects so he can respond and plan effectively.

Stage 5: Applications. So far we have mainly surveyed functionality that exists within viewer products. In this fifth stage, applications written in Visual Basic, Java or .NET further extend the capability of viewers. These applications can be separated into three groups of increasing sophistication: basic, complex and heavyweight.

Basic Viewer Applications

A few examples of basic viewer applications have been discussed already: data collection, inventory, inspection and data validation. All these have some common elements. In each example, field personnel gather information as part of a business process. Each example eliminates paper from the process, which reduces errors and re-processing costs. This combination generally provides sufficient economic justification for such applications.

There is an additional benefit that is not usually taken into account. It is real but difficult to quantify: These basic applications build human capital. For many people who use them, it will be their first experience with computers at work. These basic applications will build their confidence and lead them to use computers for more complex tasks that bring the utility greater and greater rewards.

Complex Applications

Each of the following applications has saved significant money or made money for utility companies, either by improving the economics of decisions, allowing crews to work more efficiently, or allowing a consumer to buy when he is ready.

Load computation. This is an application for the field or the office. Suppose you want to add electric service to a new house in an established subdivision. If you could simply add the service from an existing transformer, you would save money over adding a new transformer. To decide, you need information about the transformer, its historic load, some engineering standards for loading, and the expected load for the new house. Some of this information may not reside in the GIS, but it can be added to the data seen by the viewer and linked to appropriate facilities. Using this data, the application computes the expected load and lets the user make the most economic choice within engineering constraints: simply add the service, upgrade the transformer, or install a new pole with a new transformer.

Network trace. In a simple form, a network trace answers the question “What is the next control device upstream toward the breaker?”

Valve isolation. This application uses a network trace to answer a more complicated set of questions. “If I need to shut down a section of a main, what valves do I need to close? Where are they? What are their numbers? And which customers will be affected?” The valve isolation application can be used both for planned shutdowns and for emergencies.

Loop makeup. In the communications space, the basic trace can be extended to do loop makeup, which can be used for DSL Qualification. This application shows how a utility used “viewing” software to grow revenue. Suppose a consumer calls the phone company and asks whether he can get DSL service at his home. If the phone service representative can respond during this first call, the consumer is much more likely to sign up for the service than if the rep says something like, “Let me find out, and I’ll call back within 48 hours.”

Vegetation management. In one form, this application uses a network trace to build “scout” maps for a circuit. The scout drives the circuit, touching the screen as he finds encroachment and assigning a priority. A GPS unit records the location and places a symbol that is color-coded to show the priority. The scout can cover multiple circuits in the time it would take a bucket truck to cruise one circuit. After the scout has covered several circuits, a supervisor uses his collected data to prioritize the tree-trimming operation through third-party contractors.

Outage analysis. Although there are outage systems that cost millions of dollars and do a lot of work, some utilities would like a simpler and less costly solution. Using a network trace and some business/engineering logic, one simpler solution accepts trouble calls and infers the most probable point of failure on a circuit. It also allows the user to hypothetically change the status of switches and determine the amount of system load that would be shed by that change. In only a few minutes (either in the office or in the field), he can recommend a repair plan that would cause the least disruption of service.

Scenario planning is a broad category that means finding the answers to “what if?” questions. One example comes from the previous description of outage analysis. But there are many other possibilities, once the data is in place and a “viewer” enables an engineer to ask questions and solve problems.

Heavyweight Applications

Heavyweight viewer applications share a higher level of complexity and integration.

Field design and estimating. The user sketches work in the field, estimates the cost using compatible units, and then sends the design back to the GIS. This application builds upon the redlining stage and information sharing stage, but adds integration with compatible units from a work management system as well as the cost estimation.

Engineering analysis interface. Traditionally, preparing a model of the distribution network for engineering analysis required hours, even weeks, of an engineer’s time. It was a slow, tedious process. An engineering analysis interface allows the engineer to prepare the model in minutes. This sort of speed and ease has a multiplier effect on the analysis software’s value: The engineer uses it more often, does more iterations, tries more scenarios, and makes a better network.

What’s in a Name?

We’ve come quite a distance, from a fairly weak motor to an engine that breaks barriers. We started with a viewer that displayed graphic data without attributes, and now we have design tools and engineering analysis interfaces.

My claim seems to be true, at least in part. Software that has traditionally been called a “viewer” is used today for tasks that were previously limited to full GIS edit seats. To what extent this “viewer” software will displace full edit seats is an open question. I think there will always be a strong place for the full edit seats. But as the number of people who can effectively use geospatial technology continues to expand, I believe the number of “viewer” seats will grow faster than the full edit ones.

I will end with a question. What should we call a “viewer” that has so much more capability than viewing?

With proper acknowledgement to Chrysler, maybe we should just call it a “HEMI.” ❮❮

Charlie Marlin has more than 20 years experience making graphics technology work for companies across the globe. As a consultant with Graphic Technologies Inc. (GTI) he helps clients grow the value of their geospatial data by sharing it with field and office users throughout the enterprise.

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