Spatially Enabled Solutions: A Modern Approach to an Old Problem
Although seemingly very different questions, they relate to the same fundamental issue of
optimizing cost and service level trade-offs. Neglecting to effectively answer these questions can
result in inefficiencies that needlessly waste resources and undermine the full potential benefits
of related improvement initiatives.
This paper looks at the need, and a modern approach, for reconfiguring service delivery
networks. It examines how SDNs evolved and could have subsequently become outdated. We
will outline the data, geospatial technology, computational tools, and process developments that
have enabled us to address challenges related to updating SDN configurations. We will also
present the concept, step-by-step process, and application of geospatial modeling techniques for redesigning and optimizing SDNs. The focus of this paper is on field-asset (wires and pipes)
service provision. It is therefore primarily directed at leaders of utility distribution companies,
and more specifically those—internally or externally—who provide construction, operation,
maintenance, and restoration services to related field assets and customers. While this paper
highlights issues and developments primarily in the electric and gas utility industries, the stories
are similar, and the concepts are applicable to phone, cable, and other field-asset service
businesses in general.
An old problem
As the electric and gas utility industries in the United States took shape early in the 20th century,
technological advancements and economies of scale significantly decreased costs as production
and demand increased. This continued after World War II as electric usage was doubling every
nine to 10 years from 1946 to the early 1970s. Residential electric rates (current dollars) dropped
from $1.56 per kWh in 1907 to 19 cents in 1947 and to 9 cents by 1967.* Advances in
metallurgy, welding techniques, and pipe rolling overcame the barriers of transporting gas from
the wellhead to the customer resulting in the construction of thousands of miles of natural gas
pipeline. Natural gas consumption grew from 1.6 MMcf in 1931 to 4.2 MMcf in 1947 and 17.4
MMcf in 1967.** Productivity improvements during this period were focused almost entirely on
technological advances in the supply and transmission of electricity and natural gas.
(Hirsh 2001), (Tussing
and Tippee 1995)
During this time, utilities scrambled to build and expand distribution systems to connect more
and more customers and drive early economies of scale in supply. For the first half of the 20th
century gas and electric service was, for the most part, localized and concentrated in population
centers. Following World War II, traditional population centers were growing and spreading
outward to the suburbs as cheaper automobiles provided access to lower-cost housing options.***
Construction, operations, maintenance, and restoration organizations expanded their service
delivery networks to keep pace with growth. Developments of SDNs were initially driven more
by necessity and compliance than by coordinated planning. Even well-planned SDNs became
outdated and inefficient as traffic patterns and geographic concentrations of utility fieldwork
changed over time.
In the 1970s, technological progress in supply and transmission failed to mitigate rising fuel,
financing, and construction costs causing electricity and natural gas prices to more than double
during that period. Customers quickly became disenchanted with the utility system and were
demanding better prices and more reliable service.(Hirsh 2001) Congress got involved and passed a
series of legislation over the next 20 years to encourage more efficient energy pricing,
conservation, and competition in the supply and generation sectors. Distribution inefficiencies
that were once overshadowed by productivity and cost improvements in generation and supply
were now coming under increased scrutiny as officials gained comfort with more progressive
forms of regulation.
Faced with the reality or prospect of rate caps, reductions, or performance-based rates,
distribution companies have embarked on numerous initiatives aimed at improving their business
performance. Updating the SDN configuration to effectively address current and future work
demands has long been a challenge that previously was difficult, if not impossible, to effectively
approach. Determining the right number, size, location, staffing, and territory assignment is little
more than guesswork without accurate data, computational tools, and an objective process of
analysis. Redesign errors or inaction can have costly and lasting consequences. Too many
service centers or inappropriate staffing levels cause unnecessary facility and labor costs. Too
few service centers or inefficient territory assignments increase windshield time and travel costs,
and decrease responsiveness and field-force efficiency. Until recently, these types of problems
were approached—if at all—by intuition and “chart, compass, and ruler” techniques. (Ballou)
Enabling Developments
Several key advancements related to computational tools, processes of analysis, and input data
have made it possible to address SDN design challenges quickly and accurately. The
development of high-level programming languages and powerful mainframe computers in the
1960s and 1970s made possible the broader application of quantitative techniques developed in
the 1940s from military and operations research. Industry application of these quantitative
techniques—such as linear programming, heuristics, and simulation—for solving resource
allocation, distribution, and transportation planning gained value as a decision-making aid.(Shycon
and Maffei 1960) Since then, the rapid growth in desktop computing power and the introduction of
improved algorithms is allowing organizations to model and solve very large supply-chain
problems in a matter of minutes instead of days or weeks.(Bendiner 1998) While most of the early
developments focused on optimizing the physical distribution of tangible goods or products,
these developments were directly applicable to the delivery or provision of services.
Information technology improvements and integration within utility operations and customer
care have generated a wealth of geo-based customer, service center, field-asset, and workdemand
data. Geospatial technology advancements in the early 1980s combined the computer
display of geographic features, such as points, lines, and polygons, with database management
tools for assigning attributes to these features. Likewise, a “location” attribute could be added to
traditionally tabular data—such as service centers, customers, and field-assets—and layered with
shapes such as roads and assigned territories. The integration of geospatial technology with
supply- and service-chain optimization tools created a powerful application for visualizing and
solving SDN problems.
