Shaping a New Era in Energy

In the last few years, the world has seen the energy & utilities business accelerate into a significant period of transformation as a result of the smart grid and related technologies. Today, with some early proponents leading the way, the industry is on the verge of a step-change improvement that some might even classify as a full-scale revolution. Utilities are viewed not only as being a critical link in solving the challenges we face related to climate change and the care of our planet’s energy resources, but they’re becoming enablers of growth and innovation – and even new products, services and jobs. Clearly the decisions the industry is making today around the world’s electricity networks will impact our lives for decades to come.

If the current economic environment has muted any enthusiasm for this transformation, it hasn’t been much. With the exception, perhaps, of plummeting oil prices temporarily providing some sense of calm in the sector, there are probably few people left who don’t believe the world needs to urgently address its clean, smart energy future. As of this writing, fledgling signs of an economic recovery are emerging, and along with it, increases in fossil fuel prices. As such, enthusiasm is growing over the debate about how countries will utilize billions in stimulus funding to enable the industry to achieve a new level of greatness.

There is a confluence of events helping us along this path of dramatic and beneficial change. IBM’s recent industry consumer survey (selected findings of which are featured in this publication in "Lighting the Way" by John Juliano) signals a future that is being shaped in part by a younger generation of digitally savvy people who care about – and are willing to participate in – our collective energy future. They willingly engage in more open communication with utility providers and tend to be better at understanding and controlling energy utilization.

As utilities instrument virtually all elements of the energy value chain from the power plant to the plug, they will improve service quality to these customers while reducing cost and improving reliability to a degree never before achievable. Customers engage because they see themselves as part of a larger movement to forestall the effects of climate change, or to battle price instability. This fully connected, instrumented energy ecosystem takes advantage of the data it collects, applying advanced analytics to enable real-time decisions on energy consumption. Some smart grid projects are already helping consumers save 10% of their bills, and reduce peak demand by 15%. Imagine the potential total savings when this is scaled to include companies, governments and educational institutions.

While positive new developments abound, they also are creating a highly complex environment, raising many difficult questions. For example, are families and businesses truly prepared to go on a "carbon diet" and will they stay on it? How will governments, with their increased stake in auto manufacturers, effectively and efficiently manage the transition toward PHEVs? Will industry players collaborate with one another to deal with stealth attacks on smart grids that are no longer the stuff of spy novels, but current realities we must face 24/7? How do we responsibly support the resurgence of nuclear-based power generation?

Matters of investment are also complex. Will there be sufficient public/private partnership to effectively stimulate investment in new businesses and models to profitably progress safe alternative energy forms such as solar, tidal, wind, geothermal and others? Will we have the "smarts" – and the financial commitment – to build more smarts into the reconstruction of ailing infrastructures?

Leading the Way

IBM has been a leading innovator in smart grid technology, significantly investing in energy and environmental programs designed to promote the use of intelligent energy worldwide. We created the Global Intelligent Utility Network Coalition, a strategic relationship with a small group of select utilities from around the world to shape, accelerate and share in the development of the smart grid. With the goal to lead industry organizations to smart grid transformation, we actively lead and participate in a host of global organizations including the GridWise® Alliance, Gridwise Architecture Council, EPRI’s Intelligrid program, and the World Energy Council, among others. By coming together around a shared vision of a smarter grid, we have an unprecedented opportunity to reshape the energy industry and our economic future.

The IBM experts who engage in these groups – along with the thousands of other IBMers working in the industry – have contributed significant thinking to the industry’s progress, not the least of which is the creation of the Smart Grid Maturity Model (SGMM) which has been handed over to the Carnegie Mellon Software Engineering Institute (SEI) for ongoing governance, growth and evolution of the model. Furthermore, the World Energy Council (WEC) has become a channel for the global dissemination of the model among its worldwide network of member committees.

IBM’s own Intelligent Utility Network (IUN) solution enables a utility to instrument everything from the meter in the home to miles of power lines to the network itself. In fact, the IUN looks a lot more like the Internet than a traditional grid. It can be interconnected to thousands of power sources – including climate-friendly ones – and its instrumentation generates new data for analysis, insight and intelligence that can be applied for the benefit of businesses and consumers alike.

Our deep integration skills, leading-edge technology, partner ecosystem and business and regulatory expertise have earned us roles in more than 50 smart grid projects around the globe with showcase projects in the U.S. Pacific Northwest, Texas, Denmark and Malta (See "The Smart Grid in Malta" by Carlo Drago in this publication) to name just a few. IBM also has a role in seven out of the world’s 10 largest advanced meter management projects.

The IBM Solution Architecture for Energy (SAFE), is a specialized industry framework focused on the management, maintenance, and integration of a utility’s assets and information, inclusive of generation, transmission and distribution, and customer operations. This is complemented by a world-class solution portfolio based on the most comprehensive breadth of hardware, software, consulting services, and open standards-based IT infrastructure that can be customized to meet the needs of today’s energy and utilities enterprises around the globe.

These activities are augmented by the renowned IBM Research organization that engages in both industry-specific and cross-industry research that influences our clients’ progress. This includes new computing models to handle the proliferation of end-user devices, sensor and actuators, connecting them with powerful back-end systems. How powerful? In the past year IBM’s Roadrunner supercomputer broke the "petaflop" barrier – one thousand trillion calculations per second using standard chip sets. Combined with advanced analytics and new computing models like "clouds" we’re turning mountains of data into intelligence, making systems like the smart grid more efficient, reliable and adaptive – in a word, smarter.

IBM Research also conducts First-of-a-Kind research – or FOAKs – in partnership with our clients, turning promising research into market-ready products and services. And our Industry Solution Labs around the world give IBM clients the chance to discover how leading-edge technologies and innovative solutions can be assembled and proven to help solve real business problems. For example, we’re exploring how to turn millions of future electric vehicles into a distributed storage system, and we maintain a Center of Excellence for Nuclear Power to improve design, safety analysis, operation, and nuclear modeling / simulation processes.

IBM is excited to be at the forefront of this changing industry – and our changing world. And we’re honored to be working closely with our clients and business partners in helping to evolve a smarter planet.

Turning Information Into Power

Around the world, utilities are under pressure. Citizens demand energy and water that don’t undermine environmental quality. Regulators seek action on smart grids and smart metering initiatives that add intelligence to infrastructure. Customers seek choice and convenience – but without additional costs.

Around the globe, utilities are re-examining every aspect of their business.

Oracle can help. We offer utility experts, mission-critical software applications, a rock-solid operational software suite, and world-leading middleware and technology that can help address these challenges. The result: flexible, innovative solutions that increase efficiency, improve stakeholder satisfaction, futureproof your organization – and turn information into power.

Utilities can begin with one best-of breed solution that addresses a specific pain point. Alternatively, you can implement several pre-integrated applications to ease the development and administration of cross-departmental business processes. Our complete applications and technology footprint can be standardized to focus on accountability and reduce the resources spent on vendor relations.

Oracle Is A Leader In Utilities: 20 of the Top 20 Global Utilities Get Results With Oracle

Oracle provides utilities with the world’s most complete set of software choices. We help you address emerging customer needs, speed delivery of utility-specific services, increase administrative efficiency, and turn business data into business intelligence.

Oracle Utilities offers the world’s most complete suite of end-to-end information technology solutions for the gas, water, and electric utilities that underpin communities around the world. Our revolutionary approach to providing utilities with the applications and expertise they need brings together:

  • Oracle Utilities solutions, utility-specific revenue and operations management applications:
    • Customer Care and Billing
    • Mobile Workforce Management
    • Network Management System
    • Work and Asset Management
    • Meter Data Management (Standard and Enterprise Editions)
    • Load Analysis
    • Load Profiling and Settlement
    • Portfolio Management
    • Quotation Management
    • Business Intelligence
  • Oracle’s ERP, database and infrastructure software:
    • Oracle E-Business Suite and other ERP applications
    • Times Ten for real-time data management
    • Data hubs for customer and product master data management
    • Analytics that provide insight and customer intelligence
    • ContentDB, SpatialDB and RecordsDB for content management
    • Secure Enterprise Search for enterprise-wide search needs
  • Siebel CRM for larger competitive utilities’ call centers, customer order management, specialized contacts and strategic sales:
    • Comprehensive transactional, analytical and engagement CRM capabilities
    • Tailored industry solutions
    • Role-based customer intelligence and pre-built
  • Oracle’s AutoVue Enterprise Visualization Solutions:
    • Make business and technical documents easily accessible by all enterprise users
    • Expedite document reviews with built-in digital annotations and markups
    • Boost the value of your enterprise system with integrated Enterprise Visualization
  • Oracle’s Primavera Solutions:
    • Effectively manage and control the most complex projects and project portfolio
    • Deliver projects across generation, transmission and distribution, and new clean-energy ventures
    • Optimize a diminishing but highly skilled workforce

Stand-alone, each of these products meets utilities’ unique customer and service needs. Together, they enable multi-departmental business processes. The result is an unparalleled set of technologies that address utilities’ most pressing current and emerging issues.

The Vision

Cross-organizational business processes and best practices are key to addressing today’s complex challenges. Oracle Utilities provides the path via which utilities may:

  • Address the "green agenda:"
    • Help reduce pollution
    • Increase efficiency
    • Complete software suite to enable the smart grid
  • Advance customer care with:
    • Real-time 360-degree views of customer information
    • Tools to help customers save time and money
    • Introduce or retire products and services quickly, in response to emerging customer needs
  • Enhance revenue and operations management:
    • Avoid revenue leakage across end-to-end transactions
    • Increase the visibility and auditability of key business processes
    • Manage assets strategically
    • Bill for services and collect revenue cost-effectively
    • Increase field crew and network efficiency
    • Track and improve performance against goals
    • Achieve competitive advantage with a leading-edge infrastructure that helps utilities respond quickly to change
  • Reduce total cost of ownership through access to a single global vendor with:
    • Proven best-in-class utility management solutions
    • Comprehensive, world-class capabilities in applications and technology infrastructure
    • A global 24/7 distribution and support network with 7,000 service personnel
    • Over 14,000 software developers
    • Over 19,000 partners

Strategic Technology For Every Utility

Only Oracle powers the information-driven enterprise by offering a complete, integrated solution for every segment of the utilities industry – from generation and transmission to distribution and retail services. And when you run Oracle applications on Oracle technology, you speed implementation, optimize performance, and maximize ROI.

When it comes to handling innovations like daily or interval meter reading, installing, maintaining, and replacing plant and linear assets, providing accurate bills and supporting your contact center and more, Oracle Utilities is the solution of choice. Utilities succeed with Oracle. Oracle helps electric, gas, water and waste management meet today’s imperatives to do the following:

  • Help customers conserve energy and reduce carbon footprints
  • Keep energy affordable
  • Strengthen and secure communities’ economic foundation

Meeting the Challenges of the Future, Today

Utilities today need a suite of software applications and technology to serve as a robust springboard from which to meet the challenges of the future.

Oracle offers that suite.

Oracle Utilities solutions enable you to meet tomorrow’s customer needs while addressing the varying concerns of financial stakeholders, employees, communities, and governments. We work with you to address emerging issues and changing business conditions. We help you to evolve to take advantage of new technology directions and to incorporate innovation into ongoing activity.

Partnering with Oracle helps you to futureproof your utility.

Surviving the Turmoil

With the new administration talking about a trillion dollars of infrastructure investment, the time for the intelligent utility of the future is now. Political pressure and climate change are going to drive massive investments in renewable and clean energy and smart grid technology. These investments will empower customers through the launch and adoption of demand response and energy efficiency programs.

Many believe that the utility industry will change more in the next five years than the previous 50. The greatest technological advancements are only valuable if they can enable desired business outcomes. In a world of rapidly changing technology it is easy to get caught up in the decisions of what to put in, how, when, and where – making it easy to forget why.

A New Era Emerges

The utility industry has, for decades, been the sleeping giant of the U.S. economy. Little has changed in service delivery and consumer options over the last 50 years. But a perfect storm of legislation, funding and technology has set in motion new initiatives that will change the way customers use and think about their utility service. The American Recovery and Reinvestment Act allocates more than $4 billion, via the Smart Grid Investment Grant Program, for development and upgrade of the electrical grid. Simultaneously, significant strides in smart metering technology make the prospect of a rewired grid more feasible.

While technological advances toward the intelligent utility are exciting, technology in and of itself is not the solution for the utility of the future. How those technologies are applied to supporting business outcomes will be key to success in a consumer-empowered environment. Those outcomes must include considerations such as increasing or sustaining customer service levels and reducing bad debt through innovative charging methods and better control of consumption patterns.

Facing New Challenges

Future smart grid considerations aside, consumer expectations are already undergoing transformation. Although some energy prices have decreased recently in light of declining natural gas prices, the long-term trend indicates rates will continue to climb. Faced with increasing energy costs and declining household incomes, customers are looking for options to reduce their utility bill. Further, utilities’ ability to meet demand during peak periods is often inadequate. According to the Galvin Electricity Initiative, “Each day, roughly 500,000 Americans spend at least two hours without electricity in their homes and businesses. Such outages cost at least $150 billion a year. The future looks even worse. Without substantial innovation and investment, rolling blackouts and soaring power bills will become a persistent fact of life [1].”

Simultaneously, environmental concerns are influencing a greater number of consumers than in the past. In April 2009, the U.S. Environmental Protection Agency (EPA) announced it had identified six greenhouse gases that may endanger public health or welfare [2]. According to the EPA, the process of generating electricity creates 41 percent of all carbon dioxide emissions in the U.S. Utilities are under pressure to offer ways to reduce the impact of fossil fuels to accommodate rapidly changing economic and social conditions.

Strategies such as rate structures that incent customers to schedule their energy-intensive activities during off-peak times would help the utility to avoid, or reduce, reliance on the facilities that produce greenhouse gases. Lowering a residential thermostat by just 2 degrees reduces reliance on less desirable sources of generation. According to McKinsey &
Company, carbon dioxide emissions can be reduced by 34 percent in the residential sector alone through enhanced energy productivity [3].

If a significant number of residential consumers could reschedule their peak usage today, it would extend the life of the current infrastructure and reduce the need to raise rates in order to fund capital investments. But at present, in most jurisdictions there is no demonstrable incentive, such as rate structures that reward off-peak usage, to motivate consumers to conserve in any meaningful way.

Aging CIS

Those utilities saddled with aging customer information systems (CIS) – and those executives who have been reluctant to adopt new technology – will be challenged to adapt to the new paradigm. Even utilities with a relatively new CIS in place may find themselves with technology not suited to today’s world. Typically, utilities have been “load serving entities” – matching supply to demand. In the new recession-prone environment, proactive utilities will need to encourage conservation to match supply. Most utilities do not have the capability to show consumers how and when they can save money by using electricity during off-peak hours.

Until utilities can address these needs, and answer customer inquiries about how to save money and energy, they will not be in a position to focus on desired business outcomes. Currently, many utilities track quantitative performance indicators, not business outcomes.

Desired Business Outcomes

Determining the tools, processes or intellectual property needed to achieve desired business outcomes can be a dilemma. Realizing targeted results may require out-of-the-box thinking. To leverage best-in-class practices, many utilities seek external expertise ranging from advisory and consulting resources to a fully outsourced solution.

When addressing the changes the future utility faces, it is easy to become focused on the what, how, when and where to deploy emerging technology rather than the most important element – why deploy at all? Figure 1 depicts Vertex’s four-level solutions approach to business outcomes as an example of keeping the focus on the “why.”

Level 1: Identify Business Challenges. What are the key issues your organization is grappling with? They may be part of the macro trends impacting the industry as a whole or they may be specific to your company. The list might include issues such as substantial bad debt, poor customer satisfaction, declining revenue and profits, high operating cost to serve, and customer acquisition and retention.

Level 2: Identify Desired Outcomes. While acting on business challenges is an integral part of the process, the desired business outcomes are the drivers that will guide you to the solution. At the same time, the solution will also determine if the desired outcomes can be achieved with in-house resources or if an experienced third party should join the team. The solution will also clarify whether you have the technology to realize the desired outcomes or if an investment will be necessary. For example, desired outcomes might include reducing bad debt by 10 percent, improving customer satisfaction from the second quartile to the first quartile, or eliminating 30 percent of the cost of the meter-to-cash process. One or more of these outcomes may require new supporting technology.

Level 3: Develop and Implement Solution. Once the specific business challenges have been fully discussed and the desired outcomes outlined, the next step requires designing the solution to enable achievement. The solution needs to be realistic, in line with your corporate culture, and deliver the right mix of technology, innovation and practicality, all with the appropriate cost-to-value ratio. Management must avoid the lure of overengineering to meet the goal, and thereby incurring more expense and complexity than needed. And the journey from perceived solution to actual solution to achieve a desired outcome might include some surprising elements.

For example, accomplishing the goal of reducing customer service costs by 30 percent might call for enhanced customer service representative (CSR) education and a reduction in the average number of calls a customer makes to the call center each year. The eventual solution may be very complex, and require touching all areas of the meter-to-cash process, along with implementing next generation technology. Or the solution may be as simple as upgrading the customer’s bill to provide more accurate and timely information. Putting more information in the customer’s hands makes billing easier to understand, resulting in fewer customer calls per year, leading to lower customer service costs. The value proposition enabling the business outcome might rely on a more robust analytics engine for analyzing and presenting data to customers. There are generally multiple paths that can bring about achieving a desired business outcome. Seeking external help on the pros and cons of the paths might be valuable to utility executives,
especially if the path involves deploying new technology.

Level 4: Measure Solution Results. Continuous process improvement must be a component of all solutions. The results must be measured and compared against the desired business outcomes. Reviewing results and lessons learned in a closed loop will empower continuous process improvement and maintain focus on the process.

Conservation and Education

While current technology may not be up to the task of helping consumers conserve and save money on energy, those restrictions will change in the very near future. Utilities need to start viewing themselves less as responders to supply and demand and more as advocates for conservation, the environment, and de-coupling of rates. Massive investments in clean and renewable energy, and smart grid technology, will empower customers to employ demand response decisions and gain energy efficiency. The real issue for the utility will not be how to implement the technology itself – wired, wireless, satellite, etc. – but how best to use the technology to achieve its desired business outcomes. Further, utilities need to be prepared for some disruption to business as usual while technology and business processes undergo a sea change.

The capability of deploying a smart grid and advanced meter management (AMM) is one of the most significant changes impacting utilities today. The outcomes are not achieved by technology alone. Those outcomes require the merging of AMM with meter-to-cash processes. The utility will realize business value only if the people and discrete processes within the customer care component of the end-toend process evolve to take advantage of new technology.

The New Reality

Most utilities already enjoy acceptable levels of customer satisfaction. As the smart grid comes on line, with its associated learning curve, myriad details and inevitable glitches, customers will depend on the utility for support and clarification. Call center volumes and average handle times will increase as the complexity of the product grows by an order of magnitude. The old standard of measuring productivity according to number of calls completed within a pre-determined number of minutes will no longer be viable. Average call length increased by a factor of four for one utility that has experimented with smart grid technology. Longer call times, however, can ultimately translate to increased customer satisfaction as consumers receive the information they need to understand the new system and how to reduce their energy bill.

But a four-fold increase in call center staff to accommodate longer calls is not economically practical. In the future, utilities will need to provide more in-depth education to CSRs so they can, in turn, educate customers. They may even need to change their hiring criteria, and seek more highly skilled call center staff who are already versed in the meter-to-cash process. For some customers, alternative sources of information such as the Internet will suffice, thus offsetting some of the strain placed on the call center.

Achieving Desired Outcomes

The following section provides examples of how the combination of advanced meter management and redefined meter-to-cash processes and tools can enable and help achieve desired business outcomes.

Accurate and Timely Data – With smart meters and the smart grid able to capture usage data in intervals as frequent as five minutes, utilities will have more current information about system activity than ever before. Developing a strategy for managing this massive database will require forethought to avoid overwhelming the back office. When fully deployed throughout a service area, customers will no longer receive estimated bills. Devices in the home will provide readouts about usage activity, and some consumer education may be needed to help households understand the presented data and how it translates to their usage patterns and billing. Demand response participation is likely to increase as consumers become more aware of the benefits of managing their energy usage patterns. The federal government’s stimulus bill funding may include allocations for retrofits for low-income homeowners. The call center can function as a resource for customers who wish to investigate this program.

Reduced Bad Debt – As noted earlier, average handle time will be a less significant metric as consumer interaction with the call center increases. The CSR will become a key element in the strategy to reduce bad debt. CSRs will be the conduit for consumer education and building rapport with the customer when resolving past-due bills. As an alternative, utilities may want to turn to Madison Avenue to help them design and roll out a customer information campaign.

Better Revenue Management – If customer education about the smart grid pays off, and consumers are using energy more judiciously, utilities will benefit. Without the pressure to make capital investments for new plants, there will be more opportunities for profit-taking and shareholder rewards. Utilities may instead be able to make profits on their energy efficiency and investments. New technologies will help utilities avoid spending the hundreds of billions of dollars that would otherwise be needed for base load. In addition, demand response participation on the part of residential consumers will better align commercial and industrial (C&I) energy pricing with residential pricing. C&I customers will see the quality and consistency of their power supply improve.

Increased Energy Efficiency – Utilities, whether municipal, public or private, will feel the social pressure to apply technologies in order to gain energy efficiency and encourage conservation. The future utility will become a leader, instead of a follower, in the campaign to improve the environment and use energy resources wisely. By using energy more strategically – that is, understanding the benefits of off-peak usage – consumers will help their utility reduce carbon emissions, which is the ultimate desired business outcome for all involved.

Increased Stakeholder Satisfaction – Stakeholders run the gamut from shareholders and public utility commissions to consumers, utility employees and executives. All of these groups will be pleased if the public uses energy more efficiently, leading to more revenue for the utility and lower costs to consumers. Showing focus on business outcomes is generally a huge plus that helps increase stakeholder satisfaction.

Lower Cost to Serve – Utilities must try to design a business model with flatter delivery costs. For example, if it costs the utility $30 to $40 per customer per year, staying within that existing range with more and longer customer calls will be a challenge. Some utilities may opt out of providing customer service with in-house staff and contract with a service provider. Recognizing that supplying and managing energy, not delivering customer care, is their core competency, a utility can often reduce the cost of customer care by partnering with an organization that is an expert in this business process. If this is the path a utility takes it is very important to find the provider that will enable the desired outcomes of your business; not all service providers are equal or focus on outcomes. We expect relationships with vendors within the industry will change, with utilities embracing more business partners than in the past.

Increased Service Levels – Public utility commissions (PUC) often review financial and service metrics when considering a rate case. Utilities may need to collaborate with PUCs to help them understand the dynamics of smart meters, along with temporary changes in customer satisfaction and service levels, when submitting innovative rate cases and programs. Once the initial disruptive period of new technology is completed, utilities will be able to increase service levels with greater responsiveness to customer needs. When the call center staff is fully educated about smart meters and demand response, they will be positioned to provide customers with more comprehensive service, thus reducing the number of incoming and outgoing calls.

Future Competition – The current and upcoming changes in the industry are so dramatic that utilities must first assess how consumers are accepting change. Reinventing the grid via the smart grid and its related products and services will create new opportunities and new business models with potential for increased revenue. The extent to which the future market is more competitive depends on the rate of acceptance by consumers and how skillfully utilities adopt new business models. It is our premise that utilities who desire the right business outcomes and focus on enabling them through process, people, and technological changes will be most able to excel in a more competitive environment.

References

  1. Galvin Electricity Initiative, sponsored by The Galvin Project, Inc., www.galvinpower.org
  2. Press Release, “EPA Finds Greenhouse Gases Pose Threat to Public Health, Welfare/Proposed Finding Comes in Response to 2007 Supreme Court Ruling,” April 17, 2009. http://yosemite.epa.gov
  3. McKinsey Global Institute, “Wasted Energy: How the US Can Reach its Energy Productivity Potential,” McKinsey
    & Company, June 2007.

Enabling Successful Business Outcomes Through Value-Based Client Relationships

Utilities are facing a host of challenges ranging from environmental concerns, aging infrastructure and systems, to Smart Grid technology and related program decisions. The future utility will be required to find effective solutions to these challenges, while continuing to meet the increasing expectations of newly empowered consumers. Cost management in addressing these challenges is important, but delivery of value is what truly balances efficiency with customer satisfaction.

Our Commitment

Vertex clients trust us to deliver on our promises and commitments, and they partner with us to generate new ideas that will secure their competitive advantage, while also delivering stakeholder benefits. Our innovative same-side-of-the-table approach allows us to transform the efficiency and effectiveness of your business operations, enabling you to lower your risk profile and enhance your reputation in the eyes of customers, investors and regulatory bodies. Working as partners, we provide unique insights that will generate actionable ideas and help you achieve new levels of operational excellence.

With a long heritage in the utility industry, Vertex possesses an in-depth knowledge and understanding of the issues and challenges facing utility businesses today. We actively develop insights and innovative ideas that allow us to work with our utility clients to transform their businesses, and we can enhance your future performance in terms of greater efficiencies, higher customer satisfaction, increased revenue and improved profitability.

Achievement of desired business outcomes is best achieved with a strategic, structured approach that leverages continuous improvement throughout. Vertex takes a four-level approach, which starts with asking the right questions. Levels 1 and 2 identify business challenges and the corresponding outcomes your utility hopes to achieve. Need to improve customer satisfaction? If so, is moving from the 2nd to 1st quartile the right target? Pinpointing the key business challenges that are limiting or impeding your success is critical. These may include a need to reduce bad debt, reduce costs, minimize billing errors, or improve CSR productivity. Whatever challenges you face, collaboration with our experts will ensure your utility is on the right track to meet or exceed your targets.

Once the challenges and outcomes have been identified and validated, Vertex partners with clients to develop effective solutions. The solutions implemented in Level 3 consist of unique value propositions that, when combined effectively, achieve the desired business outcome for the business challenge being addressed. Vertex’s proprietary “Value Creation Model” enables us to develop and implement solutions that provide measurable business results and ongoing quality assurance.

Inherent to the success of this model is the Vertex Transition Methodology, which has resulted in 200 successful transitions over a twelve-year period. Due diligence yields a clear understanding of how the business operates. Mobilizing activities lay the foundation for the transition, and a baseline for the transition plan is established. The plans developed during the planning stage are implemented, followed by a stabilization period from the business transfer to when things are fully operational.

Another key element of this model lies in Vertex’s transformation capabilities, and what we refer to as our “6D” transformation methodology. Dream, Define, Design, Develop, Deliver, Drive – our Lean Six Sigma methods guarantee successful deployment of continuous process improvement results. In addition to Lean Six Sigma, the Vertex Transformation Methodology includes change management, people and performance management, and project management.

In Level 4 of the Vertex solution approach, Vertex measures the effectiveness of a solution by determining if it achieved the desired business outcome. We utilize a Balanced Scorecard approach to ensure that the business outcome positively impacts all of the key elements of a client’s business: Customer, Employee, Operational, and Financial. As desired business outcomes evolve, Vertex will remain committed to adapting our solutions in partnership with our clients to meet these changing needs.

Transforming Your Organization

If you’re ready to transform to an outcomes- based business, Vertex has the capability to help. Our service lines include: Consulting and Transformation, IT Applications Services and Products, Debt Management, and Meter-to-Cash Outsourcing.

Our transformation approach blends innovation and business process improvement, focusing on achieving your strategic objectives via our proven expertise and insights. We bring business transformation that secures greater efficiencies, improved effectiveness and enhanced services for your organization. All the while we never forget that our employees represent your brand.

We’ll work collaboratively with you, rapidly implementing services and delivering on continuous improvement to meet your goals. We’ll build on your business needs, sharing ideas and jointly developing options for change – working together to deliver real value.

Empower Your Customers To Reduce Energy Demand

The Energy Information Administration (EIA) forecasts a continuing gap between total domestic energy production and consumption through 2030. This delta will not be closed by supply alone; customer behavior changes are needed to reduce total consumption and peak load. Electric and gas utilities face tremendous challenges meeting energy supply and demand needs and will play a pivotal role in determining practical solutions. With the right approach, utilities will deliver on the promise of energy efficiency and demand response.

Energy market projections are highly speculative as the market is characterized by high price volatility and rapid market transformation. Adding to the uncertainty is the voluntary nature of demand response and energy efficiency programs, and the critical importance of customer behavior change. Utilities are spending billions of dollars, making program penetration essential – and customer education paramount. At an end-point cost of up to $300, a five percent penetration is not the answer. Vertex can help mitigate these risks through highly effective management of customer care, CIS integration, pilot programs, and analytics. Vertex’s core “meter-to-cash” capabilities have undergone a major revolution in response to the new world of AMI, energy efficiency, and demand response. A robust set of new services will allow utilities to transform how they do business.

Smart meters put new demands on CIS platforms and traditional business processes – innovative rates, distributed generation, demand response and new customer programs all require creative change. Vertex is currently helping utilities develop and manage customer programs to fully exploit smart meter deployments and provide customer care to customers migrating to time-based rates. We deliver customer management services to drive penetration and designed to meet the unique customer care needs generated by smart meter installations, energy efficiency and demand response programs to empower customers to manage their energy use and reduce consumption, and cost-effective customer care and billing solutions to support smart meters.

Water utilities are not immune to the need for conservation. In the past 30 years, the U.S. population has grown over 50% while the total water use has tripled. On average, Americans use approximately 75 to 80 gallons of water per person per day. Vertex can help water utilities address the unique conservation challenges they face, including customer care and program support, MDMS solutions to organize data for forecasting, code enforcement, business and customer insight, and other services.

Case Study – Hydro One

Hydro One is an Ontario, Canada based utility that is one of the five largest transmission utilities in North America. As the stewards of critical provincial assets, Hydro One works with its industry partners to ensure that electricity can be delivered safely, reliably, and affordably to its customers. Vertex has been providing Meter-to-Cash outsourcing services to Hydro One since 2002.

Applying the Vertex 4-level solutions approach enabled desired business outcomes:

Level 1: Identify Business Challenges

In 2006 Hydro One approached Vertex and indicated that one of their corporate goals was to dramatically improve customer satisfaction as a result of the Hydro One customer satisfaction survey. At that point, Hydro One customer satisfaction scores on agent-handled calls had hovered in the 75-76% range for several years. Up to that time, the relationship with Vertex had focused on significant reductions to cost with no erosion to service offered to customers. Now, Hydro One was looking to Vertex to help lead the drive to improve the customer experience.

Level 2: Identify Desired Outcomes

In 2007 Vertex and Hydro One entered into collaborative discussions to evaluate and analyze the historical customer satisfaction scores, and to work jointly to develop a plan to radically modify the customer experience and improve customer satisfaction. Those discussions led down several paths, and the parties mutually agreed to target the following areas for change:

  • The Vertex/Hydro One Quality program
  • A cultural adjustment that would reflect the change in focus
  • Technology that could help support Hydro One’s goals
  • End-to-end process review

Level 3: Develop & Implement Solution

Vertex has worked closely with Hydro One to help them deliver on their goal of significant improvements to customer satisfaction. Changes were applied to process, call scripts, quality measures and performance scoring at all levels in the organization, including incentive compensation and recognition programs.

Level 4: Measure Solution Results

  • Customer satisfaction scores on agent-handled calls increased from 76% in 2006 to 86% in 2008
  • Quality monitoring program changes yielded a 10% increase in first-call resolution
  • Introduced bi-weekly Process/Quality forums
  • Monthly reviews with the client to reinforce success and progress toward targets

Modeling Distribution Demand Reduction

In the past, distribution demand reduction was a technique used only in emergency situations a few times a year – if that. It was an all-or-nothing capability that you turned on, and hoped for the best until the emergency was over. Few utilities could measure the effectiveness, let alone the potential of any solutions that were devised.

Now, demand reduction is evolving to better support the distribution network during typical peaking events, rather than just emergencies. However, in this mode, it is important not only to understand the solution’s effectiveness, but to be able to treat it like any other dispatchable load-shaping resource. Advanced modeling techniques and capabilities are allowing utilities to do just that. This paper outlines various methods and tools that allow utilities to model distribution demand reduction capabilities within set time periods, or even in near real time.

Electricity demand continues to outpace the ability to build new generation and apply the necessary infrastructure needed to meet the ever-growing, demand-side increases dictated by population growth and smart residences across the globe. In most parts of the world, electrical energy is one of the most important characteristics of a modern civilization. It helps produce our food, keeps us comfortable, and provides lighting, security, information and entertainment. In short, it is a part of almost every facet of life, and without electrical energy, the modern interconnected world as we know it would cease to exist.

Every country has one or more initiatives underway, or in planning, to deal with some aspect of generation and storage, delivery or consumption issues. Additionally, greenhouse gases (GHG) and carbon emissions need to be tightly controlled and monitored. This must be carefully balanced with expectations from financial markets that utilities deliver balanced and secure investment portfolios by demonstrating fiduciary responsibility to sustain revenue projections and measured growth.

The architects of today’s electric grid probably never envisioned the day when electric utility organizations would purposefully take measures to reduce the load on the network, deal with highly variable localized generation and reverse power flows, or anticipate a regulatory climate that impacts the decisions for these measures. They designed the electric transmission and distribution systems to be robust, flexible and resilient.

When first conceived, the electric grid was far from stable and resilient. It took growth, prudence and planning to continue the expansion of the electric distribution system. This grid was made up of a limited number of real power and reactive power devices that responded to occasional changes in power flow and demand. However, it was also designed in a world with far fewer people, with a virtually unlimited source of power, and without much concern or knowledge of the environmental effects that energy production and consumption entail.

To effectively mitigate these complex issues, a new type of electric utility business model must be considered. It must rapidly adapt to ever-changing demands in terms of generation, consumption, environmental and societal benefits. A grid made up of many intelligent and active devices that can manage consumption from both the consumer and utility side of the meter must be developed. This new business model will utilize demand management as a key element to the operation of the utility, while at the same time driving the consumer spending behavior.

To that end, a holistic model is needed that understands all aspects of the energy value chain across generation, delivery and consumption, and can optimize the solution in real time. While a unifying model may still be a number of years away, a lot can be gained today from modeling and visualizing the distribution network to gauge the effect that demand reduction can – and does – play in near real time. To that end, the following solutions are surely well considered.

Advanced Feeder Modeling

First, a utility needs to understand in more detail how its distribution network behaves. When distribution networks were conceived, they were designed primarily with sources (the head of the feeder and substation) and sinks (the consumers or load) spread out along the distribution network. Power flows were assumed to be one direction only, and the feeders were modeled for the largest peak level.

Voltage and volt-ampere reactive power (VAR) management were generally considered for loss optimization and not load reduction. There was never any thought given to limiting power to segments of the network or distributed storage or generation, all of which could dramatically affect the flow of the network, even causing reverse flows at times. Sensors to measure voltage and current were applied at the head of the feeder and at a few critical points (mostly in historical problem areas.)

Planning feeders at most utilities is an exercise performed when large changes are anticipated (i.e., a new subdivision or major customer) or on a periodic basis, usually every three to five years. Loads were traditionally well understood with predictable variability, so this type of approach worked reasonably well. The utility also was in control of all generation sources on the network (i.e., peakers), and when there was a need for demand reduction, it was controlled by the utility, usually only during critical periods.

Today’s feeders are much more complex, and are being significantly influenced by both generation and demand from entities outside the control of the utility. Even within the utility, various seemingly disparate groups will, at times, attempt to alter power flows along the network. The simple model of worst-case peaking on a feeder is not sufficient to understand the modern distribution network.

The following factors must be considered in the planning model:

  • Various demand-reduction techniques, when and where they are applied and the potential load they may affect;
  • Use of voltage reduction as a load-shedding technique, and where it will most likely yield significant results (i.e., resistive load);
  • Location, size and capacity of storage;
  • Location, size and type of renewable generation systems;
  • Use and location of plug-in electrical vehicles;
  • Standby generation that can be fed into the network;
  • Various social ecosystems and their characteristics to influence load; and
  • Location and types of sensors available.

Generally, feeders are modeled as a single unit with their power characteristic derived from the maximum peaking load and connected kilovolt-amperage (KVA) of downstream transformers. A more advanced model treats the feeder as a series of connected segments. The segment definitions can be arbitrary, but are generally chosen where the utility will want to understand and potentially control these segments differently than others. This may be influenced by voltage regulation, load curtailment, stability issues, distributed generation sources, storage, or other unique characteristics that differ from one segment to the next.

The following serves as an advanced means to model the electrical distribution feeder networks. It provides for segmentation and sensor placement in the absence of a complete network and historical usage model. The modeling combines traditional electrical engineering and power-flow modeling with tools such as CYME and non-traditional approaches using geospatial and statistical analysis.

The model builds upon information such as usage data, network diagrams, device characteristics and existing sensors. It then adds elements that could present a discrepancy with the known model such as social behavior, demand-side programs, and future grid operations based on both spatio-temporal and statistical modeling. Finally, suggestions can be made about sensors’ placement and characteristics to the network to support system monitoring once in place.

Generally, a utility would take a more simplistic view of the problem. It would start by directly applying statistical analysis and stochastic modeling across the grid to develop a generic methodology for selecting the number of sensors, and where to place them based on sensor accuracy, cost and risk-of-error introduction from basic modeling assumptions (load allocation, timing of peak demand, and other influences on error.) However, doing so would limit the utility, dealing only with the data it has in an environment that will be changing dramatically.

The recommended and preferred approach performs some analysis to determine what the potential error sources are, which source is material to the sensor question, and which could influence the system’s power flows. Next, an attempt can be made to geographically characterize where on the grid these influences are most significant. Then, a statistical approach can be applied to develop a model for setting the number, type and location of additional sensors. Lastly sensor density and placement can be addressed.

Feeder Modeling Technique

Feeder conditioning is important to minimize the losses, especially when the utility wants to moderate voltage levels as a load modification method. Without proper feeder conditioning and sufficient sensors to monitor the network, the utility is at risk of either violating regulatory voltage levels, or potentially limiting its ability to reduce the optimal load amount from the system during voltage reduction operations.

Traditionally, feeder modeling is a planning activity that is done at periodic (for example, yearly) intervals or during an expected change in usage. Tools such as CYME – CYMDIST provide feeder analysis using:

  • Balanced and unbalanced voltage drop analysis (radial, looped or meshed);
  • Optimal capacitor placement and sizing to minimize losses and/or improve voltage profile;
  • Load balancing to minimize losses;
  • Load allocation/estimation using customer consumption data (kWh), distribution transformer size (connected kVA), real consumption (kVA or kW) or the REA method. The algorithm treats multiple metering units as fixed demands; and large metered customers as fixed load;
  • Flexible load models for uniformly distributed loads and spot loads featuring independent load mix for each section of circuit;
  • Load growth studies for multiple years; and
  • Distributed generation.

However, in many cases, much of the information required to run an accurate model is not available. This is either because the data does not exist, the feeder usage paradigm may be changing, the sampling period does not represent a true usage of the network, the network usage may undergo significant changes, or other non-electrical characteristics.

This represents a bit of a chicken-or-egg problem. A utility needs to condition its feeders to change the operational paradigm, but it also needs operational information to make decisions on where and how to change the network. The solution is a combination of using existing known usage and network data, and combining it with other forms of modeling and approximation to build the best future network model possible.

Therefore, this exercise refines traditional modeling with three additional techniques: geospatial analysis; statistical modeling; and sensor selection and placement for accuracy.

If a distribution management system (DMS) will be deployed, or is being considered, its modeling capability may be used as an additional basis and refinement employing simulated and derived data from the above techniques. Lastly, if high accuracy is required and time allows, a limited number of feeder segments can be deployed and monitored to validate the various modeling theories prior to full deployment.

The overall goals for using this type of technique are:

  • Limit customer over or under voltage;
  • Maximize returned megawatts in the system in load reduction modes;
  • Optimize the effectiveness of the DMS and its models;
  • Minimize cost of additional sensors to only areas that will return the most value;
  • Develop automated operational scenarios, test and validation prior to system-wide implementation; and
  • Provide a foundation for additional network automation capabilities.

The first step starts by setting up a short period of time to thoroughly vet possible influences on the number, spacing and value offered by additional sensors on the distribution grid. This involves understanding and obtaining information that will most influence the model, and therefore, the use of sensors. Information could include historical load data, distribution network characteristics, transformer name plate loading, customer survey data, weather data and other related information.

The second step is the application of geospatial analysis to identify areas of the grid most likely to have influences driving a need for additional sensors. It is important to recognize that within this step is a need to correlate those influential geospatial parameters with load profiles of various residential and commercial customer types. This step represents an improvement over simply applying the same statistical analysis generically over the entirety of the grid, allowing for two or more “grades” of feeder segment characteristics for which different sensor standards would be developed.

The third step is the statistical analysis and stochastic modeling to develop recommended standards and methodology for determining sensor placement based on the characteristic segments developed from the geospatial assessment. Items set aside as not material for sensor placement serve as a necessary input to the coming “predictive model” exercise.

Lastly, a traditional electrical and accuracy- based analysis is used to model the exact number and placement of additional sensors to support the derived models and planned usage of the system for all scenarios depicted in the model – not just summertime peaking.

Conclusion

The modern distribution network built for the smart grid will need to undergo significantly more detailed planning and modeling than a traditional network. No one tool is suited to the task, and it will take multiple disciplines and techniques to derive the most benefit from the modeling exercise. However, if a utility embraces the techniques described within this paper, it will not only have a better understanding of how its networks perform in various smart grid scenarios, but it will be better positioned to fully optimize its networks for load and loss optimization.

Smart Meters on a Roll in Canada

Electricity supply challenges in Ontario, Canada, have led the provincial government there to take aggressive action on both the supply and demand sides to meet customer electricity needs. Between now and 2025, it’s estimated that Ontario must build an almost entirely new electricity system – including replacing approximately 80 percent of current generating facilities (as they’re retired over time) and expanding the system to meet future growth. However, just as building new supply is vital, so too is conservation. That’s why Ontario’s provincial government is introducing new tools like smart meters to encourage electricity consumers to think more about how and when they use electricity. By implementing a smart metering infrastructure by 2010, the province hopes to provide a foundation for achieving a more than five percent reduction in provincial demand through load shifting, energy savings and price awareness.

Hydro One owns and operates one of the 10 largest transmission and distribution systems in North America, serving a geographic area of about 640,000 square kilometers. As the leading electricity transmitter and distributor in Ontario, the company supports the province’s goal of creating a conservation culture in Ontario and having a smart meter in every Ontario home and small business. The company’s allocation of the province’s target was 240,000 smart meters by 2007 and the full 1.3 million by 2010.

The task for Hydro One and other local distribution companies (LDCs) in the province is to meet the government time line while at the same time building an enabling solution that provides the most upside for operations, demand management and customer satisfaction. Working with the industry regulator and the LDCs, phased goals were established and allocated among the major utilities in the province.

ADVANCED METERING INFRASTRUCTURE AND SOLUTION ARCHITECTURE

Advanced metering infrastructure (AMI) is the term used to describe all of the hardware, software and connectivity required for a fully functioning smart metering system. To view AMI as just a technology to remotely read meters and bill customers, however, would be to miss the full potential of smart metering.

The core of the solution resides with the requirement for a ubiquitous communications network and an integration approach that provides for the exploitation of data from many types of devices (automated meter reading, load control, in-home displays, distribution monitoring and control and so on) by making it available to numerous enterprise applications (for example, customer information, outage management, asset management, geographic information and work execution systems).

To meet this requirement, the Hydro One team architected an end-to-end solution that rigorously sought open standards and the use of IP at all communications levels to ensure that the network and integration would be available to and compatible with numerous applications.

Hydro One’s AMI solution is based on standards (ANSI and IEEE) and open protocols (Zigbee and IP) to ensure maximum flexibility into the future as the technology and underlying applications such as in-home energy conservation devices (two-way real-time monitors, pool pump timers and so on) and various utility applications evolve.

Smart Meters

The “smarts” in any smart meter can be housed in virtually any meter platform. Meter reads are communicated at a frequency of 2.4 GHz by a radio housed under the meter’s glass. In essence, the hourly meter reads are transmitted by hopping from one meter to the next, forming a self-organizing network that culminates at the advanced meter regional collector (AMRC). This type of local area network, or LAN, is known as a mesh network and is known for its self-healing characteristics: if communication between meters is interrupted for any reason, communication paths between meters are automatically rerouted to the regional collector to ensure that data is delivered reliably and on time. The installed smart meters also have a “super capacitor,” enabling the meter to send a last communication to the utility when there has been a power outage.

Repeaters

Repeaters provide a wireless range extender for the meters and are used in less densely populated areas in the province to allow data to be transmitted from one meter to the next. Typically, repeaters are needed if the hop between meters is greater than 1 to 2 kilometers (depending on a number of factors, including terrain and ground cover).

Advanced Metering Regional Collectors

Typically installed on poles at preselected locations within a local area network, advanced metering regional collectors (AMRCs) gather the meter readings in a defined area. Most importantly, the AMRCs provide access to the wide area network (WAN), where data is sent wirelessly back to Hydro One. The AMI solution is designed to accommodate either wireless cellular or broadband WAN to backhaul hourly meter reads to the advanced metering control computer.

Advanced Metering Control Computer

The advanced metering control computer (AMCC) is used to retrieve and temporarily store meter reads from the regional collectors before they’re transmitted to the meter data management repository (discussed below). The information stored in the AMCC is available to log maintenance and data transmission faults, and to issue reports on the overall health of the AMI system.

Meter Data Management Repository

MDM/R is the acronym for the province-wide meter data management repository. The MDM/R provides a common infrastructure for receiving meter reads from all LDCs in Ontario, processing the reads to produce billing quality consumption data, and storing and managing the data. The Ontario government has entered into an agreement with the Independent Electricity System Operator to coordinate and manage implementation activities associated with the MDM/R.

Billing

Time-of-use “bucketed” data is sent from the MDM/R to Hydro One for any exception handling that may be required and for customer billing. Hydro One prepares the bill and sends it to the customer for payment.

Web Presentment of Customer Usage Data

Customer electricity usage data will be available to customers by 9 a.m. the day after they use it via a secure website. This data will be clearly marked as preliminary data until the customer has been billed.

GOALS, OBJECTIVES AND KEY ACCOMPLISHMENTS

To successfully deploy the smart metering solution described above, the Hydro One team set out to accomplish the following goals and objectives (which are enshrined in project governance plans and daily project activities):

  • Balance investment with the regulatory process to ensure that smart meter investments don’t get ahead of changes in regulatory requirements.
  • Design, test, prototype and pilot prior to buying or building – a rule that applies to all aspects of the smart meter solution architecture, from the meters and communication network to the back-office systems.
  • Delay building solution components until line-of-business requirements are locked down. Solution components that are unlikely to change will be built before other components to minimize the risk of rework.
  • Test smart meter deployment business processes, technology and customer experience throughout the process.
  • Ensure positive customer experience and value, including providing customers with information and tools to leverage smart meters in an appropriate time frame.
  • Use commercial, off-the-shelf (COTS) products where possible (as opposed to custom solutions).
  • Include estimation of total cost of ownership (one-time and ongoing costs) in architectural decision making.
  • Enable commencement of time-of-use (TOU) billing in 2009.

Key project accomplishments to date have included:

  • Building an in-situ lab using WiMax and meters in rural areas to test and confirm open protocols, wireless broadband interoperability, and meter performance;
  • Conducting a community rollout of about 15,000 meters to develop and successfully test and optimize meter change automation tools and customer communication processes;
  • Mass deploying of just over a quarter of a million meters across the province;
  • Designing and beginning to build the communication network to support the collection of hourly reads from approximately 1.3 million customers.

METER AND NETWORK DEPLOYMENT

Meter installation teams surpassed a notable milestone of 250,000 installed smart meters as of December 2007. Network deployment began in 2007 with a planned ramp-up in 2008 of installing more than 2,000 AMRCs province-wide.

Meeting these targets has required well-coordinated activities across the project team while working in parallel with external entities such as MeasurementCanada and others to ensure compliance with regulatory requirements.

Throughout meter and network deployment activities, Hydro One has adhered closely to three primary guiding principles, namely:

Safety. The following initiatives were factored into the project to help maintain a safe environment for all employees and business partners:

  • Internal training was integrated into the project from the inception, establishing a thorough yet common-sense compliant safety attitude throughout the team.
  • No employee is permitted to work on the project without a full safety refresher.
  • Safety represented a key element of incentive compensation for management and executive personnel.

Customer service. Given the opportunity to visit literally every customer, the success of this project is being judged daily by the manner in which the project team interacts with customers.

  • Every customer is provided with an information package within 15 to 30 days of the meter change.
  • Billing windows are scrupulously avoided through automation tools and integration to CIS in order to eliminate any disruption to the size, look and feel of the customer bill.
  • All customers receive a personal knock at the door before meter change.
  • All life-safety customers are changed by appointment or have positive contact made prior to meter change if they cannot be reached for an appointment

Productivity. Despite Hydro One’s rural footprint – which includes some areas so remote they must be accessed by all-terrain vehicle, boat or snowmobile – the installation teams maintain an average of 39.6 meters per installer-day with a peak of 97 per installer-day. They have achieved this through automation and a phased ramp-up of installers, including training and joint fieldwork with Hydro One’s partners.

IN-HOME CONSERVATION AND DEMAND MANAGEMENT

Testing will soon be underway using third-party devices for residential demand response programs that operate on the mesh network, including two-way realtime monitors, automated thermostats and load control devices. Optimally for customers, meters will serve as the key head-end device, connectable to numerous other devices within the home as illustrated in Figure 2.

While much of this technology is still in its infancy, North America-wide AMI deployments will rapidly accelerate resulting in greatly enhanced customer service opportunities going forward.

LEVERAGING THE SMART NETWORK TO INCREASE UTILITY EFFICIENCY

Hydro One is also looking ahead to applications that will leverage the smart metering communication network to increase the efficiency of its operations. As illustrated in Figure 3, these applications include distribution station monitoring, enhancements to outage management, safety monitoring, mobile work dispatch and work accomplishment, and asset security. All of the above applications have been tested in a proof-of-concept environment, and individual projects are planned to proceed on a business case basis.

Microsoft Helps Utilities Use IT to Create Winning Relationships

The utilities industry worldwide is experiencing growing energy demand in a world with shifting fuel availability, increasing costs, a shrinking workforce and mounting global environmental pressures. Rate case filings and government regulations, especially those regarding environmental health and safety, require utilities to streamline reporting and operate safely enterprise-wide. At the same time, increasing competition and costs drive the need for service reliability and better customer service. Each issue causes utilities to depend more and more on information technology (IT).

The Microsoft Utility team works with industry partners to create and deploy industry-specific solutions that help utilities transform challenges into opportunities and empower utilities workers to thrive in today’s market-driven environment. Solutions are based on the world’s most cost-effective, functionally rich, and secure IT platform. The Microsoft platform is interoperable with a wide variety of systems and proven to improve people’s abilities to access information and work with others across boundaries. Together, they help utilities optimize operations in each line of business.

Customer care. Whether a utility needs to modernize a call center, add customer self-service or respond to new business requirements such as green power, Microsoft and its partners provide solutions for turning the customer experience into a powerful competitive advantage with increased cost efficiencies, enhanced customer service and improved financial performance.

Transmission and distribution. Growing energy demand makes it critical to effectively address safe, reliable and efficient power delivery worldwide. To help utilities meet these needs, Microsoft and its partners offer EMS, DMS and SCADA systems; mobile workforce management solutions; project intelligence; geographic information systems; smart metering/grid; and work/asset/document management tools that streamline business processes and offer connectivity across the enterprise and beyond.

Generation. Microsoft and its partners provide utilities with a view across and into their generation operations that enables them to make better decisions to improve cycle times, output and overall effectiveness while reducing the carbon footprint. With advanced software solutions from Microsoft and its partners, utilities can monitor equipment to catch early failure warnings, measure fleets’ economic performance and reduce operational and environment risk.

Energy trading and risk management. Market conditions require utilities to optimize energy supply performance. Microsoft and its partners’ enterprise risk management and trading solutions help utilities feed the relentless energy demands in a resource-constrained world.

Regulatory compliance. Microsoft and its partners offer solutions to address the compliance requirements of the European Union; Federal Energy Regulatory Commission; North American Reliability Council; Sarbanes-Oxley Act of 2000; Environmental, Health and Safety; and other regional jurisdiction regulations and rate case issues. With solutions from Microsoft partners, utilities have a proactive approach to compliance, the most effective way to manage operational risk across the enterprise.

Enterprise. To optimize their businesses, utility executives need real-time visibility across the enterprise. Microsoft and its partners provide integrated e-business solutions that help utilities optimize their interactions with customers, vendors and partners. These enterprise applications address business intelligence and reporting, customer relationship management, collaborative workspaces, human resources and financial management.

Real-Time Automation Solutions for Operation of Energy Assets and Markets

Areva T&D offers solutions to bring electricity from the source to end-users, building high- and medium-voltage substations and develops technologies to manage power grids and energy markets worldwide. It is a full-fl edged solution provider, offering safe, reliable, efficient power distribution down to the lowest level end-user consumption. Its software applications cover all the strategic operational business processes of an energy utility, including optimization of transmission and distribution grid operation; management of wholesale and retail market operations; and energy transaction solutions involving strategic business processes from energy trading, energy scheduling and dispatch management to demand-side management and settlements.

As long as advanced monitoring and control infrastructures have been used for grid management, Areva T&D has been at the forefront of innovation. Its strategy has always been to supply the most accurate real-time vision of the network infrastructure. This has led to several major breakthroughs, including Areva’s latest e-terraVision™ product.

The e-terraVision technology provides control rooms with higher level decision support capabilities through visualization tools, “smart applications” and simulation – thus improving situation awareness. This operator-friendly system enables power dispatchers to fully visualize their networks with the right level of situation awareness and proactively operate the grid by taking the necessary real-time corrective actions.

Expertise acquired in the high-voltage network enables Areva to supply distribution monitoring and control applications as well, and these have greatly influenced its distribution management strategy. As a result of early successes, the company developed an adapted eterra product offer for distribution customers.

Areva T&D continues to integrate unique new concepts to meet market trends and innovation. For example, Areva T&D SmartGrid solutions are designed to supply the following benefits.

  1. Alignment with deregulation trends in the consumer electricity market, including:
    • Making the process of changing energy supplier easier;
    • Providing better service quality for energy usage, including accurate and appropriate billing of actual consumed energy;
    • For specific countries where nontechnical losses are significant, allowing accurate audits to be conducted; and
    • Allowing for differentiated energy offerings with greater pricing flexibility and integration of renewable energy offers.
  2. Support for further structural benefits discussed and validated as part of international working groups on SmartGrid initiatives:
    • Better selectivity of the IEDs in medium- and low-voltage leads to reduce the number of customers affected by outages, thus improving service quality and reducing maintenance costs.
    • Careful monitoring of low-voltage grids, including consumption by phase and distribution cell – which is especially relevant in terms of renewable energy generation.
    • Online asset monitoring, which enables predictive maintenance, thus increasing assets’ life span.
    • Dynamic security management of primary and secondary networks. Introducing renewable energy sources into the distribution network poses a challenge. Combined infrastructures for monitoring systems for distribution and metering will be needed in the near future.

All these challenges have driven the definition and development of Areva SmartGrid solutions. The company’s enhanced supervision and control center products, including smart metering, supply all the advantages of automation technologies to distribution networks.

Leveraging the Data Deluge: Integrated Intelligent Utility Network

If you define a machine as a series of interconnected parts serving a unified purpose, the electric power grid is arguably the world’s largest machine. The next-generation version of the electric power grid – called the intelligent utility network (IUN), the smart grid or the intelligent grid, depending on your nationality or information source – provides utilities with enhanced transparency into grid operations.

Considering the geographic and logical scale of the electric grid from any one utility’s point of view, a tremendous amount of data will be generated by the additional “sensing” of the workings of the grid provided by the IUN. This output is often described as a “data flood,” and the implication that businesses could drown in it is apropos. For that reason, utility business managers and engineers need analytical tools to keep their heads above water and obtain insight from all this data. Paraphrasing the psychologist Abraham Maslow, the “hierarchy of needs” for applying analytics to make sense of this data flood could be represented as follows (Figure 1).

  • Insight represents decisions made based on analytics calculated using new sensor data integrated with existing sensor or quasi-static data.
  • Knowledge means understanding what the data means in the context of other information.
  • Information means understanding precisely what the data measures.
  • Data represents the essential reading of a parameter – often a physical parameter.

In order to reap the benefits of accessing the higher levels of this hierarchy, utilities must apply the correct analytics to the relevant data. One essential element is integrating the new IUN data with other data over the various time dimensions. Indeed, it is analytics that allow utilities to truly benefit from the enhanced capabilities of the IUN compared to the traditional electric power grid. Analytics can be comprised solely of calculations (such as measuring reactive power), or they can be rule-based (such as rating a transform as “stressed” if it has a more than 120 percent nameplate rating over a two-hour period).

The data to be analyzed comes from multiple sources. Utilities have for years had supervisory control and data acquisition (SCADA) systems in place that employ technologies to transmit voltage, current, watts, volt ampere reactives (VARs) and phase angle via leased telephone lines at 9,600 baud, using the distributed network protocol (DNP3). Utilities still need to integrate this basic information from these systems.

In addition, modern electrical power equipment often comes with embedded microprocessors capable of generating useful non-operational information. This can include switch closing time, transformer oil chemistry and arc durations. These pieces of equipment – generically called intelligent electrical devices (IEDs) – often have local high-speed sequences of event recorders that can be programmed to deliver even more data for a report for post-event analysis.

An increasing number of utilities are beginning to see the business cases for implementing an advanced metering infrastructure (AMI). A large-scale deployment of such meters would also function as a fine-grained edge sensor system for the distribution network, providing not only consumption but voltage, power quality and load phase angle information. In addition, an AMI can be a strategic platform for initiating a program of demand-response load control. Indeed, some innovative utilities are considering two-way AMI meters to include a wireless connection such as Zigbee to the consumer’s home automation network (HAN), providing even finer detail to load usage and potential controllability.

Companies must find ways to analyze all this data, both from explicit sources such as IEDs and implicit sources such as AMI or geographical information systems (GIS). A crucial aspect of IUN analysis is the ability to integrate conventional database data with time-synchronized data, since an isolated analytic may be less useful than no analytic data at all.

CATEGORIES AND RELATIONSHIPS

There are many different categories of analytics that address the specific needs of the electric power utility in dealing with the data deluge presented by the IUN. Some depend on the state regulatory environment, which not only imposes operational constraints on utilities but also determines the scope and effect of what analytics information exchange is required. For example, a generation-to-distribution utility – what some fossil plant owners call “fire to wire” – may have system-wide analytics that link in load dispatch to generation economics, transmission line realities and distribution customer load profiles. Other utilities operate power lines only, and may not have their own generation capabilities or interact with consumers at all. Utilities like these may choose to focus initially on distribution analytics such as outage predication and fault location.

Even the term analytics can have different meanings for different people. To the power system engineer it involves phase angles, voltage support from capacitor banks and equations that take the form “a + j*b.” To the line-of-business manager, integrated analytics may include customer revenue assurance, lifetime stress analysis of expensive transformers and dashboard analytics driving business process models. Customer service executives could use analytics to derive emergency load control measures based on a definition of fairness that could become quite complex. But perhaps the best general definition of analytics comes from the Six Sigma process mantra of “define, measure, analyze, improve, control.” In the computer-driven IUN, this would involve:

  • Define. This involves sensor selection and location.
  • Measure. SCADA systems enable this process.
  • Analyze. This can be achieved using IUN Analytics.
  • Improve. This involves grid performance optimization, as well as business process enhancements.
  • Control. This is achieved by sending commands back to grid devices via SCADA, and by business process monitoring.

The term optimization can also be interpreted in several ways. Utilities can attempt to optimize key performance indicators (KPIs) such as the system average interruption duration index (SAIDI, which is somewhat consumer-oriented) on grid efficiency in terms of megawatts lost to component heating, business processes (such as minimizing outage time to repair) or meeting energy demand with minimum incremental fuel cost.

Although optimization issues often cross departmental boundaries, utilities may make compromises for the sake of achieving an overall strategic goal that can seem elusive or even run counter to individual financial incentives. An important part of higher-level optimization – in a business sense rather than a mathematical one – is the need for a utility to document its enterprise functions using true business process modeling tools. These are essential to finding better application integration strategies. That way, the business can monitor the advisories from analytics in the tool itself, and more easily identify business process changes suggested by patterns of online analytics.

Another aspect of IUN analytics involves – using a favorite television news phrase – “connecting the dots.” This means ensuring that a utility actually realizes the impact of a series of events on an end state, even though the individual events may appear unrelated.

For example, take complex event processing (CEP). A “simple” event might involve a credit card company’s software verifying that your credit card balance is under the limit before sending an authorization to the merchant. A “complex” event would take place if a transaction request for a given credit card account was made at a store in Boston, and another request an hour later in Chicago. After taking in account certain realities of time and distance, the software would take an action other than approval – such as instructing the merchant to verify the cardholder’s identity.

Back in the utilities world, consideration of weather forecasts in demand-response action planning, or distribution circuit redundancy in the face of certain existing faults, can be handled by such software. The key in developing these analytics is not so much about establishing valid mathematical relationships as it is about giving a businessperson the capability to create and define rules. These rules must be formulated within an integrated set of systems that support cross-functional information. Ultimately, it is the businessperson who relates the analytics back to business processes.

AVAILABLE TOOLS

Time can be a critical variable in successfully using analytics. In some cases, utilities require analytics to be responsive to the electric power grid’s need to input, calculate and output in an actionable time frame.

Utilities often have analytics built into functions in their distribution management or energy management systems, as well as individual analytic applications, both commercial and home-grown. And some utilities are still making certain decisions by importing data into a spreadsheet and using a self-developed algorithm. No matter what the source, the architecture of the analytics system should provide a non-real-time “bus,” often a service-oriented architecture (SOA) or Web services interface, but also a more time-dependent data bus that supports common industry tools used for desktop analytics within the power industry.

It’s important that everyone in the utility has internally published standards for interconnecting their analytics to the buses, so all authorized stakeholders can access it. Utilities should also set enterprise policy for special connectors, manual entry and duplication of data, otherwise known as SOA governance.

The easier it is for utilities to use the IUN data, the less likely it is that their engineering, operations and maintenance staffs will be overwhelmed by the task of actually acquiring the data. Although the term “plug and play” has taken on certain negative connotations – largely due to the fact that few plug-and-play devices actually do that – the principle of easily adding a tool is still both valid and valuable. New instances of IUN can even include Web 2.0 characteristics for the purpose of mash-ups – easily configurable software modules that link, without pain, via Web services.

THE GOAL OF IMPLEMENTING ANALYTICS

Utilities benefit from applying analytics by making the best use of integrated utility enterprise information and data models, and unlocking employee ideas or hypotheses about ways to improve operations. Often, analytics are also useful in helping employees identify suspicious relationships between data. The widely lamented “aging workforce” issue typically involves the loss of senior staff who can visualize relationships that aren’t formally captured, and who were able to make connections that others didn’t see. Higher-level analytics can partly offset the impact of the aging workforce brain drain.

Another type of analytics is commonly called “business intelligence.” But although a number of best-selling general-purpose BI tools are commercially available, utilities need to ensure that the tools have access to the correct, unique, authoritative data. Upon first installing BI software, there’s sometimes a tendency among new users to quickly assemble a highly visual dashboard – without regard to the integrity of the data they’re importing into the tool.

Utilities should also create enterprise data models and data dictionaries to ensure the accuracy of the information being disseminated throughout the organization. After all, utilities frequently use analytics to create reports that summarize data at a high level. Yet some fault detection schemes – such as identifying problems in buried cables – may need original, detailed source data. For that reason utilities must have an enterprise data governance scheme in place.

In newer systems, data dictionaries and models can be provided by a Web service. But even if the dictionary consists of an intermediate lookup table in a relational database, the principles still hold: Every process and calculated variable must have a non-ambiguous name, a cross-reference to other major systems (such as a distribution management system [DMS] or geographic information system [GIS]), a pointer to the data source and the name of the person who owns the data. It is critical for utilities to assign responsibility for data accuracy, validation, source and caveats at the beginning of the analytics engineering process. Finding data faults after they contribute to less-than-correct results from the analytics is of little use. Utilities may find data scrubbing and cross-validation tools from the IT industry to be useful where massive amounts of data are involved.

Utilities have traditionally used simulation primarily as a planning tool. However, with the continued application of Moore’s law, the ability to feed a power system simulation with real-time data and solve a state estimation in real time can result in an affordable crystal ball for predicting problems, finding anomalies or performing emergency problem solving.

THE IMPORTANCE OF STANDARDS

The emergence of industry-wide standards is making analytics easier to deploy across utility companies. Standards also help ease the path to integration. After all, most electrons look the same around the world, and the standards arising from the efforts of Kirchoff, Tesla and Maxwell have been broadly adopted globally. (Contrary views from the quantum mechanics community will not be discussed here!) Indeed, having a documented, self-describing data model is important for any utility hoping to make enterprise-wide use of data for analytics; using an industry-standard data model makes the analytics more easily shareable. In an age of greater grid interconnection, more mergers and acquisitions, and staff shortages, utilities’ ability to reuse and share analytics and create tools on top of standards-based data models has become increasingly important.

Standards are also important when interfacing to existing utility systems. Although the IUN may be new, data on existing grid apparatus and layout may be decades old. By combining the newly added grid observations with the existing static system information to form a complete integration scenario, utilities can leverage analytics much more effectively.

When deploying an IUN, there can be a tendency to use just the newer, sensor-derived data to make decisions, because one knows where it is and how to access it. But using standardized data models makes incorporating existing data less of an issue. There is nothing wrong with creating new data models for older data.

CONCLUSION

To understand the importance of analytics in relation to the IUN, imagine an ice-cream model (pick your favorite flavor). At the lowest level we have data: the ice cream is 30 degrees. At the next level we have information: you know that it is 30 degrees on the surface of the ice cream, and that it will start melting at 32 degrees. At the next level we have knowledge: you’re measuring the temperature of the middle scoop of a three-scoop cone, and therefore when it melts, the entire structure will collapse. At the insight level we bring in other knowledge – such as that the ambient air temperature is 80 degrees, and that the surface temperature of the ice cream has been rising 0.5 degrees per minute since you purchased it. Then the gastronomic analytics activate and take preemptive action, causing you to eat the whole cone in one bite, because the temporary frozen-teeth phenomenon is less of a business risk than having the scoops melt and fault to ground.

Developing a Customer Value Transformation Road Map

Historically, utility customers have had limited interactions with their electric or gas utilities, except to start or stop service, report outages, and pay bills or resolve billing questions. This situation is changing as the result of factors that include rising energy prices, increasing concerns about the environment and trends toward more customer interaction and control among other service providers – such as cell phone companies. Over the next five to 10 years, we expect utility customers to continue seeking improvements in three key areas:

  • Increased communication with their utility company, through a greater variety of media;
  • Improved understanding of and control over their own energy use; and
  • More accurate and timely information on outage events and service restoration.

Moreover, as the generations that have grown up with cell phones, the Internet, MP3 players and other digital devices move into adulthood, they will expect utilities to keep pace with their own technological sophistication. These new customers will assume that they can customize the nature of their communications with both friends and businesses. Utilities that can provide these capabilities will unlock new sources of revenue and be better able to retain customers when faced with competition.

The intelligent utility network (IUN) will be a key enabler of these new customer capabilities and services. But not all customers will want all of the new capabilities, so utilities need to understand and carefully analyze the value of each among various customer segments. This will require utilities to prepare sound business cases and prioritize their plans for meeting future customer needs.

One of the first initiatives that utilities launching an IUN program should undertake is the development of a “customer value transformation road map.” The road map approach allows utilities to establish the types of capabilities and services that customers will want, to identify and define the gaps in current processes and systems that must be overcome to meet these needs, and to develop plans to close those gaps.

TRANSFORMATION ROAD MAP DEVELOPMENT APPROACH

Our approach for developing the customer value transformation road map includes four tasks, as depicted in Figure 1.

Task 1: Customer Requirements

The primary challenge facing utilities in defining customer requirements is the need to anticipate their desires and preferences at least five to 10 years into the future. Developing this predictive vision can be difficult for managers because they’re often “locked into” their current views of customers, and their expectations are based largely on historical experience. To overcome this, utilities can learn from other industries that are already traveling this path.

The telecommunications providers, as one example, have made substantial progress in meeting evolving customer needs over the last decade. While more changes lie ahead for telecommunications, the industry has significantly enhanced the customer experience, created differentiated capabilities for various customer segments and succeeded in developing many of these capabilities into profit-generating services. This progress can serve as both an inspiration and a guide as utilities start down a similar path.

The first step in defining future customer requirements is to segment the customer base into the various customer groups that are likely to have different needs. Although these segments will likely vary for each utility, we believe that the following seven major customer segments serve as a useful starting point for this work:

  • Residential – tech savvy. These are customers who want many different electronic communication pathways but don’t necessarily want to develop a detailed understanding of the trends and patterns in their energy usage.
  • Residential – low tech. These customers prefer traditional, less high tech ways of communicating, but may want to perform analysis of their usage.
  • Residential – low income. These are customers who want to understand what’s driving their energy expenditures and how to reduce their bills; many of these customers are also tech savvy.
  • Special needs. These customers, often elderly, may live on fixed incomes and are accustomed to careful planning, and want no surprises in their interactions with providers of utility services. They frequently need help from others to manage their daily activities.
  • Small business. These commercial customers are typically very cost-conscious and highly adaptable and seek creative but relatively simple solutions to their energy management challenges.
  • Large commercial. These are customers who are cost-conscious and capable of investing substantial time and money in order to analyze and reduce their energy use in sophisticated ways.
  • Industrial. These very large customers are sophisticated, cost-conscious and increasingly focused on environmental issues.

The next step in defining future customer requirements is to understand the points in the utility value chain at which customers will interact with their utility. Based on recent trends for both utilities and other industries, the following “touch point” areas are a good starting point:

  • Reliability and restoration;
  • Billing;
  • Customer service;
  • Energy information and control; and
  • Environment.

Not all of these requirements will be important to all customer segments. It is essential to establish the most important requirements for each segment and each touch point. Figure 2 provides one example of a preliminary assessment of the relative importance of selected customer requirements for the reliability and restoration category, across the seven specified customer segments. Each customer need is assigned a high (H), medium (M) or low (L) rank.

Once this preliminary assessment is completed, utilities should consider conducting several workshops with participants from various functional departments. The goal of these workshops is to obtain feedback, to evaluate even more thoroughly the importance of each potential requirement and to begin to secure internal acceptance of the customer requirements that are determined to be worth pursuing. Departments that should participate in such workshops include those focused on regulatory requirements, billing, corporate communications, demand-side management, customer operations, complaint resolution and outage management.

One way of making the workshop process more “real” and therefore more effective is to develop customer use scenarios that incorporate each potential requirement. For example, the following billing scenarios could be used to illustrate potential customer requirements and to facilitate more effective evaluation of what will be needed for billing:

  • Billing Scenario 1. I want my gas and electric bills to be unified so that I don’t have to spend extra time making multiple payments. Also, I want the choice of paying my bill electronically, by mail or in person, based on what’s convenient for me, not what’s convenient for my utility.
  • Billing Scenario 2. My parents, who are now retired, receive fixed pension checks, and I want their utility to set up a payment plan for them that results in equal payments over the year, rather than high payments in the summer and low payments in the winter. My parents also want the ability to see a summarized version of their bill in large print, so that they can easily read and understand their energy use and costs.
  • Billing Scenario 3. My kids are on their computer nearly all of the time, and the remainder of the time they seem to be playing their video games. Also, they rarely turn off lights, and all of these things are increasing my energy bills. I want my utility to help me set up a balance limit so that if our energy usage reaches a set level, I’m automatically notified and I have the option of taking some corrective actions. I also expect my meter readings to be accurate rather than simply rough estimates, because I want to understand exactly how much energy I am consuming and what it’s costing me.

In addition to assessing the value of each requirement to customers, it is also important to rank these requirements based on other factors, such as their impacts on the utility. Financial costs and benefits, for example, clearly need to be estimated and considered when evaluating a requirement, regardless of how important the requirement will be to customers. To draw all of these assessments together, it is useful to assign weights to each assessment area – for example, a weight of 35 percent for customer importance, 30 percent for utility costs/benefits and 35 percent for the value that regulators will perceive. Once an appropriate weighting scheme is applied, the utility can rank the requirements and develop a list of those with the highest priority.

Task 2: Gaps

To assess gaps in current capabilities that could prevent a utility from meeting important and valuable customer requirements, the utility should next identify the business processes, organizations and technologies that will “deliver” those requirements. This requires a careful analysis of current and planned process, organizational and technology capabilities, which can be challenging because other initiatives will be affecting these areas even as customer requirements evolve. Moreover, many utilities do not have accurate, detailed documentation of current processes and systems. Therefore, a series of workshops and interviews with functional and technology leaders and staff is necessary. The results of these workshops should be supplemented by analysis of planned systems and process transformations, in order to assess current gaps and to determine whether those gaps will be closed – based on plans that are already in place. If such gaps remain, new projects and capital investments may be required to close
them and to meet expected customer requirements.

During the gap assessment process, it’s critical that the customer value team work closely with other IUN teams to ensure that the customer value gap analysis is coordinated with the broader gap analysis for the IUN program. Important areas to coordinate include automated meter information, demand-side management, outage management and asset management.

Task 3: Business Case Support

While conducting the first two tasks, the assessment team should be able to develop a deep understanding of the costs required to meet the important customer requirements as well as the financial benefits. Because it’s typical to develop consolidated business cases for the IUN, the customer value team should work with the overall IUN business case team to support business case development by bringing this information into the process.

Task 4: Transformation Road Map

This final task builds on an understanding of both the customer requirements and the gaps in current operations to create the customer value transformation road map. The initiatives in the road map will typically be defined across the following primary areas:

  • Process;
  • Technology;
  • Performance metrics;
  • Organization and training; and
  • Project management.

For each of these areas, the road map will establish the timing and sequence of initiatives to close the gaps, based on:

  • The utility’s strategic priorities and capacity for change;
  • Linkages to the utility’s overall IUN transformation plans; and
  • Technology dependencies and links to other work areas.
  • Figure 3 provides a summary of the initiatives from a typical customer value transformation road map. The detail behind this summary provides a path to transforming the customer-related operations to meet expected customer requirements over the next five to 10 years.

    CONCLUSION

    Our “customer value transformation road map” approach provides utilities with a structured process for identifying, assessing and prioritizing future customer requirements. Utilities that are successful in developing such a road map will be better prepared to build customer needs into their overall IUN transformation plans. These companies will in turn increase the likelihood that their IUN transformation will improve customer satisfaction, reduce customer care costs and lead to new sources of revenue.