Building a business case around smart grid data.
Ron Clanton is a partner and the smart grid national sector leader for KPMG in the United States. He can be reached at email@example.com. This article represents the author’s views, and not necessarily those of KPMG.
Much has been said about the smart grid’s potential for transforming the utility business. But while the industry has focused on technology, process and organization, another factor—data—likely will prove to be a key transformational driver. Benefits for utilities and their customers depend on how effectively companies make use of a torrent of new and powerful data.
Smart grid represents the largest and most pervasive transformation that utilities will likely undertake, as it’s a transformation in infrastructure, business, and technology on an unprecedented scale. Smart grid also provides substantial amounts of new data, and utilities must decide how to best use that data for business value.
Like most large-scale transformation initiatives, smart grid projects traditionally focus on technology, process, and organization. However, a fourth element—data—has the potential to be a key transformational driver in helping utilities leverage new opportunities from smart grid investments.
Smart Grid Transformation
The smart grid transformation is a unique challenge, as it isn’t limited to a specific technology, functional area, or even organizational group. Its impact is broad and affects business operations, resources, infrastructure, systems, and data. In short, smart grid has the potential to transform a utility’s entire business.
The electric distribution system will be transformed by a multitude of new devices and technologies such as smart meters, grid monitoring sensors, data collection nodes, and voltage regulation devices. These devices will communicate and operate over new communication networks and feed new business applications (i.e., meter data management systems). Success in this transformation will depend on interoperability and the ease and effectiveness with which devices and systems share data and interface with each other.
From an operational perspective, smart grid will change the business of distributing electricity, as processes should be reengineered or adapted to take advantage of new capabilities. The nature of the utility-customer relationship will also change. What was once an interaction limited simply to monthly billing will expand to allow for increased levels of information exchange and greater customer involvement in decisions about electricity consumption.
Smart grid also highlights the nascent role of information management. New meters, sensors, and grid devices will provide volumes of data that previously haven’t been available. Newly available data on interval demand, interval consumption, meter condition, and grid status can be a source of potential business value if it’s properly developed, managed, and leveraged.
This transformation also comes with new resource needs and skill requirements, as new technologies and operations require knowledgeable people to manage them. Additionally, the way utilities measure performance and operational effectiveness should adapt to account for new ways of doing business.
The convergence of these forces presents significant opportunities for utilities to improve existing processes and develop new capabilities, such as:
• Increased operational efficiency: Reduced operating cost, increased automation, and streamlined processes can be achieved in the areas of meter asset management, the meter-to-cash process, field service management, and preventive maintenance.
• Expanded relationships with customers: Interval consumption data instead of only a once-monthly read, smart meters, time-of-use pricing, and direct load control devices enable customers to make more informed decisions regarding their electricity usage and become more proactive.
• Advanced power management capabilities: New grid management infrastructure and applications will enable greater distribution automation, self-healing capabilities, and more efficient power generation and dispatch, leading to reduced outages, improved restoration times, and lower generating costs.
Given this pervasive transformation, how should utilities approach a smart grid program in order to maximize the benefits to the business? The traditional approach to large transformation projects typically focuses on technology, process, and organization as the framework that governs how projects are justified, managed, and measured. Indeed, these elements are vital for smart grid. The technology component focuses on developing a robust architecture that integrates disparate operational systems and business applications. Interoperability is a key factor in this component. The process component focuses on redesigning business practices to exploit new functional capabilities, and utilities can use smart grid as a means to make processes and customer interactions more efficient and cost-effective. The organization component can provide opportunities to rationalize resource needs, develop and acquire needed skills, and rearrange organizational structures.
While these factors are critical, developing the full value of smart grid requires a broader approach that recognizes the role and importance of data as a transformation driver and a significant source of business value and benefit. A unique aspect of smart grid is that infrastructure, such as new meters and grid sensor devices, provides an abundance of potentially useful information. The challenge for utilities is how to identify and use that information. Developing the opportunities presented by this data can provide new value as well as enable a multiplier effect by leveraging existing investments for additional value.
Data as a transformational driver and a source of business value refers to the following three areas:
• New functional capabilities: The ability to perform new functions as well as perform existing functions better. Time-of-use pricing and direct load control, for instance, are new capabilities that meter data supports.
• Decision support: The wealth of new data supports enhanced decision-making and planning capabilities. For example, the myriad data elements on condition and operating status that new smart meters provide (i.e., tamper alert, low battery warning) can lead to improved preventative maintenance planning and improved meter purchasing strategies.
• Increased automation: Many utilities are upgrading distribution grids by installing numerous new and modern grid control and monitoring devices. These devices can provide an order of magnitude increase in available data on grid operations over what is currently available. Utilities can use this data, via their distribution management and outage management systems, to automate processes that could lead to reduced outage times, improved restoration, and streamlined field service operations.
These areas highlight how closely data is intertwined with the other components of the smart grid transformation. Data shouldn’t be examined in isolation. It should be examined on equal footing with technology, process, and organization.
Smart grid architecture can create a paradigm shift in the role of data and can bring new and additional data in several ways. Smart grid greatly increases data sources and collection points and brings enormous increases in data volume. Data flows will also change, as data communications that were typically unidirectional and periodic will evolve to become bidirectional and nearly real time.
As a result of these changes, many distribution management operations can be automated and streamlined. Opportunities exist to improve field service operations, asset management, new service marketing, grid reliability, outage management, and rate design. Data can be elevated from merely a process input to a source of new capabilities.
Value from Data
In a typical business transformation, data requirements are identified as part of a process design or systems implementation. By supplementing this with a more deliberate approach that involves identifying the available data up front, utilities can use that data to drive opportunities rather than limiting the implementation to only what a process or system needs. While data is closely intertwined with technology and process, it doesn’t provide value automatically. The potential benefits of data must be deliberately identified and developed. A simple three-step process can help utilities use data to drive value in a smart grid transformation (see Figure 3).
In the first step, “identifying available data,” the process focuses on assessing current systems; understanding data capabilities; and identifying new data that’s available but either isn’t being captured or is captured but not used. For instance, smart meters typically are capable of recording dozens of data elements regarding condition status, event monitoring, and usage, but most utilities capture and use only a fraction of those data elements in order to feed legacy processes. A transformational approach won’t look at data through the filter of existing business operations and systems, but instead will assess the entire set of available data and look for new possibilities.
The second step, “assessing potential value,” includes comparing potential data against planned usage, and searching for additional opportunities outside the planned solution set and current requirements. Looking beyond legacy processes for ways to develop new capabilities and optimize existing capabilities will help the company to define the value proposition for transformation and begin building a business case that aligns with strategic objectives.
In the final step, “developing the transformation,” the utility will map the identified opportunities to its enterprise model; identify relevant stakeholders, and what the new data elements will mean to them; and design transformational objectives. This includes defining new processes or changes to existing processes that use the data; identifying requirements for systems and integration; and estimating the effect on performance. A detailed business case and cost-benefit model will define the quantitative and qualitative benefits. And an implementation road map will demonstrate how the data-driven transformation will occur—and just as importantly, how it will integrate into the overall smart grid program.
Figure 3 illustrates how this approach can be applied in the areas of meter asset management and distribution management, and some possible outcomes in each step.
This three-step process is designed to be simple, as its effectiveness ultimately relies on how well it integrates into the broader smart grid program, while causing minimal disruption.
A Broader Approach
Managing a transformation the size, breadth, and complexity of smart grid will be a significant challenge to utilities. Maximizing the value of this transformation, however, demands a new, broader approach to identifying and cultivating potential opportunities. The data-driven smart grid approach looks at data proactively rather than letting data needs be driven solely by process and system requirements. This approach complements—but doesn’t replace— traditional approaches to large-scale business transformations, and demonstrates the value in placing data on equal footing with technology, process, and organization.
Leveraging data as a source of value is the key to establishing and realizing a strong smart grid business case.