Utilities have invested billions of dollars over the last five years in technologies designed to operate the electric grid more efficiently, reliably, safely, and cost-effectively. As deployment of smart grid infrastructure reaches an inflection point, utility executives are faced with the difficult task of determining how to best make use of the data generated by intelligent devices to drive business benefits. In many cases, utility analytics have been the key to unlocking this hidden value, there are examples of utilities recovering half the costs of their smart grid programs by detecting and preventing energy theft. Other companies are reporting improvements in service reliability of over 35 percent, enabled in part by the deployment of sophisticated analytical capabilities.
With more than 60 utility smart grid analytics use cases in existence, choosing a starting point for implementing an analytics program that optimizes value across the enterprise can be a daunting task, and there have been many lessons learned from early adopters. Some early adopters have undertaken ambitious initiatives focused on implementing big data applications without a well-defined data analytics road map, resulting in a significantly delayed return on investment. Conversely, other more conservative utilities have been more surgical, deploying one-off applications, which ultimately leave money on the table.
Therefore, creating a business case for analytics requires a methodology that transcends the technological and operational considerations of the utility, as well as one which can be easily articulated to key decision makers.
How do you do it?
The first step in determining the best way to utilize recently deployed infrastructure is by conducting an assessment of the use-case capabilities (people, process, technology) that have already been deployed. During this phase, it is also important to gain an understanding of the high-priority use cases, as well as those that, which may not be relevant given the operating characteristics of the utility. This initial survey should also be used to identify the functional domains (e.g., grid analytics, customer analytics) upon which to focus future workshops, strategy sessions and data requests. A market scan of peer utilities, similar markets and relevant vendors should be conducted as well.
Note: Use cases focused on energy efficiency and conservation are typically unattractive in states without revenue decoupling.
Prioritization must take into consideration the overall value (return on investment), ease of implementation and the speed at which benefits accrue.
By mapping value vs. implementation effort, one can rapidly understand the quick wins, long-term investments and unattractive initiatives that should be deferred indefinitely. Additionally, many use cases have inherent affinity (such as reliability and asset management) and tend to be enabled by the same key process redesigns, organizational changes, applications and data sources.
Therefore, use cases should be assessed and prioritized holistically, taking into account any affinity and codependent value drivers. It is also critical that the analytics road map be periodically refreshed as applications are enabled, new investments are made or new use cases emerge.
Note: Creating a reporting dashboard can be a quick win resulting in a one-time or short-term benefit that requires minimal implementation effort. Equally, leveraging sensor data for use cases such as distribution automation and fault location isolation and service restoration (FLISR) to enable predictive control can be a more complex, long-term undertaking but ultimately yields greater, continuous benefits.
Understanding the value and ease of implementation as relative rankings can be helpful for targeting key business cases to investigate further. However, a more thorough business process based cost-benefit analysis is typically required. The cost-benefit analysis and business case should explore all benefits including traditional bottom line benefits, as well as those that may accrue to customers and more intangible benefits, such as improved regulatory relations.
Note: While some benefits can be easily quantified and/or monetized (such as avoided costs due to labor efficiencies) other benefits may not be, but are nevertheless important in today's customer-centric regulatory environment (e.g., customer satisfaction scores).
The final step in any analytics program is measuring and validating the benefits outlined in the initial business case. Apart from evaluating progress for internal budgeting purposes, transparency into benefits realization has become a common requirement of regulators, particularly around use cases that have tangible customer impacts such as reliability and resiliency measures. The key to realizing true benefits is putting in place effective structures and processes for governance, identifying and verifying benefits owners, as well as clearly articulating any methodologies used in the calculation of the benefits.
Note: Much like the analytics road map, benefits realization is a dynamic process and must be updated as organizational and technology changes occur.
The benefits of utility analytics are no longer theoretical; there are now a growing number of real examples of what utility companies have achieved. Half of the recovery costs of BC Hydro's smart meter program will be found in detecting and preventing energy theft. PPL Electric has reported a 38 percent improvement in service reliability enabled in part by the deployment of sophisticated analytical capabilities. Oklahoma Gas & Electric, in a bid to substantially shed load by 2020, is using customer analytics to gain visibility on individual customers' responses to price signals. This is enabling them to identify the best customers to target with specific marketing campaigns.
In each of these cases, clear strategic goals or business problems have been addressed by using a combination of analytical solutions. Utilities have made significant investments in intelligent infrastructure; as the first wave of smart grid deployments nears completion, it has become clear that analytics is the key to unlocking additional value for utilities, shareholders and customers. With the right framework and road map in place, utility analytics offers the ability to turn the smart grid from theory into practice, seizing the opportunity to improve service, reduce costs and increase reliability.
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