Revenue and Cost Management
Electric Customer Revenue and Cost Management (RCM)
Applies a Strategy Pioneered in the Airline Industry to Reduce Costs and
Increase Revenue in Both Regulated and Competitive Electricity
Markets
Jackson Associates provides regulated electric utilities and competitive
ESPs with RCM capabilities in a three phase process
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An optional initial client RCM assessment provides a comprehensive, confidential
evaluation and assessment of current potential for RCM cost savings and revenue
enhancement
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Individual RCM projects focus on priority items which can be implemented
immediately to reduce costs and increase revenues
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A comprehensive RCM system, composed of integrated project components, provides
optimized pricing strategies, supply options, demand response programs, energy
service,load management, and other strategies
Also See
MAISY On-Site Revenue and Cost Management Workshop
What is Revenue Management (RM) ?
Revenue or Yield Management (RM) came of age in the airline industry in the
early 1980's. RM is now recognized as a critical element in cost-minimizing
and revenue maximizing strategies pursued in airline, hotel, car rental and
many other industries. Applications in these industries have provided revenue
increases of from 3% to 8% with profit increases ranging from 50% to 100%.
RM is a well-recognized empirical business strategy that optimizes product
pricing, offerings, supply development, distribution and other business functions
to maximize revenue. RM is accomplished with empirical customer information
and micromodels of customer behavior.
The most familiar example of RM is airline ticket pricing, where the demand
for air travel in different market segments at different times has been been
statistically estimated and applied to the inventory of airline seats to
determine prices that maximize total airline ticket revenues. As time to
departure draws nearer, the price of a ticket increases providing increased
revenue for the airline and greater travel options for airline passengers.
While this example may seem, at first, to suggest an airline process quite
different from one that can be applied in the electric industry, peak demand
pricing, time of use rates and demand response programs actually provide
a comparable mechanism for providing time-varying price signals with the
approach of daily or seasonal peak demand periods.
Current RM Applications in the Energy Industry
Current applications of RM analysis are limited to commodity-related products
and services; e,g., development of natural gas contracts and prices traded
across a given system of gas pipelines. While these analyses reflect important
RM applications, they represent a small fraction of the gains that can be
made by extending the RM model to optimize cost and revenue of individual
electric and natural gas customers in both regulated and competitive markets.
Electric Customer Revenue and Cost Management (RCM): Extending the RM Model
Energy suppliers, whether utilities in regulated markets or ESP's in competitive
markets, differ from their counterparts in most other industries in that
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suppliers can buy back a portion of the energy that would be supplied to
individual customers at a price that benefits both the provider and the customer
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the cost of serving individual customers differs substantially depending
on the customer's hourly load characteristics and
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individual customer's cost of service can be significantly altered by the
energy supplier with a variety of options
Electricity Providers (EP) combine a complicated mix of generating, transmission
and distribution equipment, and in some cases wholesale power purchases,
to meet the power needs of customers in each hour of the day and throughout
the year. Generating resources can vary from low-operating cost, high-capital
cost baseload units to high-operating cost, low-capital cost peaking units
while wholesale market contracts can range from spot purchases which reflect
current market prices to fixed long term contracts. EPs combine these supply
resources in the most economical way on an hour-by-hour basis to minimize
the cost of providing electricity service. The cost of meeting the power
needs of each individual customer is determined by the mix of resources
associated with that customer's power demand in each hour of the year and
that customer's geographic location in the power grid. The cost of generating
power in the most expensive hours of the year can easily be five times the
cost of generating power in the least expensive hours while transmission
and distribution (T&D) constraints can substantially increase cost of
service in specific geographic areas.
For both regulated and competitive EP's, the cost of providing service to
any two customers with identical annual electricity use can vary by as much
as 50 percent because of different hourly patterns of use. Unlike airlines,
EP's can undertake well-defined activities to modify the cost of serving
an individual customer by altering that customer's hourly electricity use
patterns and by reducing the cost of delivering service to that customer's
geographic location.
Discrepancies between individual customer cost of service and traditional
pricing provide a huge profit potential for innovative pricing strategies.
Revenue management provides a quantitative strategy for optimizing electric
rates for individual customers and customer segments. The most profitable
quintile of electric customers typically provide returns of 30 percent of
commodity revenue while the least profitable quintile account for losses
of the same magnitude. Electricity providers without empirically-based pricing
strategies will find their customer base, revenues and profits shrinking
as their most profitable customers are enticed away with more competitive
price offers and their existing customers reflect an increasing portion of
unprofitable customers.
Electric providers have as much potential pricing flexibility with
respect to pricing power as peak hours and peak seasons approach as airlines
have in pricing tickets as the time of departure approaches. Furthermore,
electric providers can also exert more control over the cost of serving
individual customers yielding greater potential for increasing revenue and
reducing cost at the same time (this ability to influence customer cost of
service provides an electric market extension titled Revenue and Cost
Management).
RCM is a process which optimizes electric utility and energy service provider
product pricing, offerings, supply development, distribution and other business
functions to maximize profits. At an operational level, the RCM process
determines electric rate structures, demand response programs, distributed
generation investments, wholesale purchases and sales and all other important
activities which determine electric revenue and costs. While many of these
activities are already part of utility and ESP management processes, they
are typically undertaken in isolation,often as part of a qualitative process,
thereby missing the substantial benefits that arise from a simultaneous
consideration of interactions and the insight that a computerized optimization
process provides.
Since electricity suppliers can impact both revenue and the cost of serving
individual customers, the potential benefits of a combined Revenue and Cost
Management Strategy (RCM) are substantially greater than what can be achieved
under the revenue-only strategy pursued in other industries.
In regulated utilities, where pricing flexibility is limited, immediate
RCM benefits derive primarily from activities that improve individual customer
costs and from demand response and other incentive programs. The lack of
pricing flexibility is offset, however, by the knowledge that any investment
made in the customer can be recouped without worrying about the customer
switching to another supplier. Over time rate structure, supply strategy,
energy service measures and initiatives in many other areas benefit the regulated
utility and its customers.
Competitive electricity providers have greater pricing flexibility
but less incentive to make investments in customer energy use characteristics
because of potential supplier switching. Immediate results are provided for
competitive ESPs through a combination of pricing strategies, demand response
programs and customer cost reduction options. Beyond these immediate results,
competitive electricity providers also benefit from rate structure, supply
strategy, energy service measures and a variety of other initiatives.
Individual Electric Customer RCM Requirements
Electric customer RCM requires that individual customers (i.e., a statistically
representative sample of customers or the entire population) serve as the
basic unit of analysis. More aggregate customer representations such as
traditional segment-based analysis are inappropriate for electric customer
RCM processes because electric market applications take advantage of differences
in characteristics and behavior of customers within traditional customer
or market segments.
Thus, individual customer 8,760 hourly loads must be used to calculate cost
of service, and to evaluate demand response, load management, distributed
generation and other cost and revenue relationships. MAISY statistical and
engineering analysis software expands billing file data to 8,760 hourly loads
with end-use load detail to support these evaluations.
Why Does an RCM Process Make so Much Difference in Costs and Revenues?
RCM changes electric provider economics drastically because it:
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Changes cost of service, revenue and profitability focus from customer classes
(residential, commercial, industrial) to individual customers providing insights
and options not previously available
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Quantifies demand and supply relationships so that the most beneficial pricing
strategies, demand response incentives, distributed generation and other
program parameters can be determined accurately for individual market segments
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Integrates diverse options such as strategic pricing, demand response, load
management, and distributed generation in a simultaneous analysis process
so that interactions are taken into account automatically
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Identifies specific actions which electric providers can undertake to reduce
costs and increase revenue
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Permits immediate responses to changes in market conditions.
RCM in the electric industry represents the same kind of transformation
that it did in the airline industry: moving from a qualitative attempt to
minimize cost and maximize revenue to a scientific, quantitative process
that extracts hidden cost savings and revenue enhancements. In the
airline industry, airlines like American and Delta who actively embraced
revenue management profited while airlines like Pan Am and Peoples Express,
who were slow to adopt this management strategy, went out of business. Current
evidence on transitions underway in electric markets suggest similar fates
for electricity providers based on their efficacy in adopting RCM.
How can JA RCM Projects Provide Immediate Cost Savings and Revenue Enhancing
Benefits ?
Jackson Associates RCM projects provide immediate client benefits because
they move cost of service and revenue evaluations from an aggregate
customer-class focus to individual customers, identifying cost-saving and
revenue-enhancing opportunities that are hidden at the class level. For example,
one of the first steps in any RCM application is to determine individual
customer cost of service, to compare that cost to revenue provided by the
customer and to identify specific options for reducing customer cost and/or
enhancing revenue. This process applies Jackson Associates proprietary load
profiling/cost-of-service software which extends each customer's billing
file data to 8760 hourly loads with end-use detail and computes a detailed
analysis of the customer's cost of service.
What Benefits does RCM Provide Regulated Utilities ?
A regulated utility RCM process optimizes, subject to regulatory constraints,
individual customer revenue and cost of service with utility-initiated actions
in each the following areas:
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Demand response initiatives
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Load management
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Energy services
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Metering
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Rates
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Economic development
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Capacity expansion
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Central plants
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Distributed generation
Applying RCM techniques within regulated utilities provides a variety of
benefits to the utility (and, ,therefore, to its customers). Among these
benefits are:
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Reduced costs and increased revenues which translate into lower customer
rates
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Greater customer rate equity
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More efficient and reliable electric supply systems
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Better positioning for potential future deregulation
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Reduced weather and wholesale price risks
The value of an RCM system is a function of how close the current system
is to its "optimized solution." The question then is, how much can an
existing utility accomplish with actions in the above areas to reduce
costs and increase revenues?
Analysis of utility rates in Texas indicates that the top 20 percent of customers
within a rate class provide profits (beyond the ordinary rate of return)
on the order of 30 percent of commodity sales revenues while the bottom 20
percent result in losses of about the same magnitude. These estimates are
consistent with recent reports by NewPower CEO, Eugene Lockhart of profit
margins of 15 percent or better from the "small business" customers that
they target. In addition, the broad declining-block rate structures used
in most utilities also distorts the relationship between the price customers
pay for electricity and the cost of providing that service.
These situations contribute to system inefficiency by encouraging overconsumption
of electricity by some customers and in some time periods where the price
paid by the customer is less than the cost that the utility incurs in delivering
the services. Appropriate RCM measures targeted at these "unprofitable"
periods will always reduce costs, increase utility net revenue (total revenue
minus total cost of service) and improve system efficiency. That is, reducing
"overconsumed" electricity use with RCM will always reduce cost of service
more than it will reduce revenue. Furthermore, additional revenue will be
generated if this "saved" electricity can be profitably sold on the wholesale
market.
Optimization of demand response and other incentive programs provides regulated
utilities with an option for increasing revenues by paying only the smallest
incentive to acquire customer demand response. For instance when a utility
or electric provider develops demand response program incentives consistent
with generation costs, there is likely to be, for instance, only a single
air conditioner cycling program which pays the customer, say, $14/ton/year
to install radio controls on commercial chillers.
However, offering a single demand incentive to all customers is the antithesis
of an optimized demand response program. Economic principles show that the
same level of demand savings can be achieved at less expense if different
prices are offered to different customer segments or if a bidding program
is used to elicit demand response commitments. That is, the quantitative
characterization of demand response programs required by RCM always provides
greater demand savings for less cost.
How About Energy Service Providers (ESP's) in Competitive Markets ?
ESP's have greater flexibility in revising prices because they do not have
to meet regulatory revenue/cost of service requirements; however, that advantage
is tempered by the ability of individual customers to switch suppliers. RCM
applications in competitive markets include representations reflecting customer
switching behavior.
Interestingly, customer switching behavior provides even greater profit potential
for energy suppliers in competitive markets because customers with negative
profits do not have to be served while competitor's customers with positive
profits can, with successful strategies, be identified and captured.
Additionally, the same RCM activities described above for regulated utilities
can be applied to improve the profitability of serving individual customers.
What Makes Jackson Associates Energy Customer Revenue and Cost Management
Applications Unique?
The following Energy Customer Revenue and Cost Management Systems components
are uniquely available in Jackson Associates RCM applications:
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Statistical and engineering software to expand billing file data to 8760
hourly loads with end-use load detail
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MAISY Utility Customer Databases for any area in the US or Canada
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Individual customer cost of service data determined with a proprietary process
which utilizes utility, ESP or market cost information
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Individual customer profitability characterizations
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Statistical models to quantify demand response and other incentive relationships
required in revenue-enhancing analysis
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Technology data describing energy service measures, DG technologies and other
physical systems
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Behavioral relationships reflecting customer responses to RCM activities
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A microsimulation modeling process required to integrate the above factors.
Customer hourly load data are drawn from the widely-used MAISY Utility Customer
Databases and/or from MAISY load development software which imputes hourly
load data from billing information and limited customer information. Technology
information is based on extensive analysis of energy service measures and
load management programs. Jackson Associates has been modeling and estimating
energy customer behavioral relationships and customer-detailed cost of service
data for utilities and energy service providers for twenty years. Finally,
the energy customer microsimulation process applied in the full MAISY RCM
system was developed by Jackson Associates in the mid-1980's and has been
applied in more than two dozen of applications since that time.
Jackson Associates Revenue and Cost Management Experience
Jackson Associates (JA) has experience in providing each of the components
which comprise the system as well as experience in comprehensive computer-based
energy systems analysis. A brief summary of JA experience in these areas
is provided below.
Industry Experience is important. JA has worked with utilities across
the US and Canada for over twenty years providing energy and demand forecasting,
DSM, integrated resource planning, competitive market analysis, utility customer
database, DG analysis, profitability modeling, market strategy and other
support services for electric and gas utilities.
Detailed Customer Databases provide the platform for all RCM analysis.
Energy-related customer characteristics including end use energy and hourly
loads are included along with available customer characteristics that help
determine customer responses to RCM measures. RCM databases are composed
of either a statistically representative sample of residential, commercial
and industrial customers or a full census of client customers.
MAISY Utility Customer Databases can be utilized
to supplement information available for client customers. MAISY hourly load
profiling software is applied to existing customer billing data to provide
a comprehensive database of 8760 hourly load profiles for all customers in
the system providing end use detail.
Demand Response and Other Customer Incentives. Jackson Associates
has experience modeling and forecasting customer response to nearly every
utility industry incentives used today.
ESM and Load Management Impact Analysis and Modeling are important
components in the RCM system, reflecting the results of conservation, new
technology applications and load management actions on individual customers
including both customer participation and energy and hourly load impacts.
JA has extensive experience representing virtually every demand side management
(DSM) and load management initiative or program instituted by utilities and
customers over the last fifteen years. Clients for whom we have conducted
this analysis include Arkansas Power and Light, Austin Electric Utility,
Central Hudson Gas and Electric, Entergy Corp, Consolidated Edison Company,
Entergy, Inc., Gulf States Utilities, Louisiana Power and Light, Mississippi
Power and Light, New Orleans Public Service, Niagara Mohawk Power Corporation,
New York Power Authority, New York State Electric and Gas, Orange and Rockland
Utilities, Rochester Gas and Electric and Washington Water Power.
Customer-Detailed Cost of Service is required to evaluate the cost
of serving individual customers. JA has developed a proprietary process to
develop cost of service for individual customers; this cost of service process
is compatible with traditional utility cost of service analysis. JA has developed
customer cost of service for six individual utility service areas since 1999.
Customer Rate Information and Revenue Analysis is applied to each
individual customer in the RCM customer database providing immediate, accurate
information on changes in rate structures. This process is applied in all
MAISY Utility Customer Databases.
Customer Energy Use, Fuel and Technology Choice Modeling is applied
to each individual customer in the RCM database in a microsimulation modeling
process to determine the impacts of individual RCM activities on customer
energy and technology choices. Both short-run changes in equipment operation
and long-run changes in equipment efficiency, fuel choice and technology
choice are included in this modeling process. JA has twenty years experience
in conducting this kind of modeling application in the JA proprietary CEDMS
and REDMS commercial and residential end use forecasting models, which have
been used by more than two dozen utilities and state energy agencies to forecast
energy use, evaluate DSM programs, forecast new technology penetrations and
conduct Integrated Resource Planning.
Economic Development Analysis is required to determine the energy-related
impacts of economic development programs. MAISY RCM systems apply the forecasting
techniques developed in CEDMS and REDMS to determine the energy use and hourly
load impacts of differential growth in service area market segments.
MAISY End Use Forecasting Models forms the basis
for DG analysis and evaluations conducted in MAISY RCM systems. Applicability
of a variety of DG technologies are evaluated for each individual customer
in the RCM customer database for each year in the analysis.
Computer-Based Energy Systems Analysis. JA proprietary CEDMS and
REDMS end use forecasting models, first introduced in 1982, combine technology,
behavioral, statistical and policy representations and analysis to forecast
energy use, customer populations, technology choices, utility and government
program impacts and to identify and evaluate optimal utility program impacts.
The individual customer-detailed microsimulation based simulation and
optimization process applied in these models in over two dozen applications
is the same process applied in the MAISY RCM systems.
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