Make the Best Decision Possible

Building a Blueprint for Electric Utility Data - Part 1

Fri, 03 Aug 2012 10:31:00 -0600

NOTE: This is a two part series exploring the opportunities presented by data integration in utilities and why a blueprint is needed to guide the utility’s vision during implementation.

Why do utilities need data integration?
Data is a source of value. In fact, it’s the precursor of knowledge. Data must be assimilated and analyzed in relation to hypotheses to reveal the insights that, when acted upon, become knowledge-driven decisions. Unfortunately, due to a historic lack of visibility into data, utility companies tend to dismiss its true business value.

As smart meters, smart devices, and other smart technologies are deployed in electric utility companies, the massive data they invite must be treated “smartly”—as a corporate asset—rather than a data storage initiative. This requires a blueprint; in other words, a vision for the role that data can play in driving business objectives for the utility.

The need for “a single view of the truth” has been bandied around for quite a while as data has multiplied across systems and industries around the globe. But the lack of data integration deployed to deliver on this mission has shown that the value and role of data is sorely misunderstood. Before the idea of building a blueprint for utility data can become foundational to business transformation, a few questions must be answered.

What’s the point of integrating data?
Data that is used by various departments is often stored more than once in siloed systems. As soon as the source data is manipulated in relation to a department hypothesis or question, its integrity for other uses is compromised. Imagine if this manipulated data is then passed on to another department as source and applied to a new hypothesis. The information derived could be very different than had the data source been in its original form.

The point of integrating data is to relate it to other data to find irregularities and diagnose issues that jeopardize the utility’s ability to meet objectives, such as complying with regulatory mandates, improving reliability, and ensuring quality of service. Another reason is to avoid duplication that can skew results, or introduce doubt in the data’s veracity.

Let’s take, for example, a transformer that’s coming close to end of life. If the utility’s weather data isn’t integrated with load management to show that the heat wave coming tomorrow will overload its capacity, an outage could occur with restoration requiring a full equipment replacement that could take hours—or even days. With integration, analytics using the integrated data could have identified the issue and preparations made to reroute the load on the feeders, or a crew could have been dispatched to replace the transformer in advance of the event.

There are many such scenarios to illustrate the business value of integrating data. Asking the question, how do we know if billing is accurate if we cannot correlate it to energy use?, is another possibility that could keep most utilities busy for quite awhile.

What other opportunities are you seeing from data integration at your utility?

Use Smart Meter Data and Surveys to Increase Relevance for Energy Consumers

Wed, 02 May 2012 13:09:00 -0600

Utility consumers are definitely not alike; spanning the spectrum of age, orientation, needs and preferences. With utilities rolling out smart meter initiatives that support grid optimization, many consumers are still unaware of what it is, what it means, and why they should care. Recent research shows that 48% of consumers asked were unfamiliar with the term “smart meter” and 51% said they’d never heard the term “smart grid.”

Although overcoming this gap in understanding may seem daunting for utilities, the same research from the Smart Grid Consumer Collaborative found that once consumers learned more about both terms, they were supportive. This presents a valuable opportunity for utility marketers and customer service professionals to generate acceptance for smart grids by focusing communications on educating consumers about energy management, dynamic pricing, and demand response.

Creating messaging that consumers will find relevant is based on segmentation; the ability to group consumers by preferences and needs. The best way to gain an understanding of the preferences and needs of your utility’s customers is consider what you already know about them and present a short survey to uncover missing data.

Start with demographics and smart meter data. Smart meters provide foundational information that can be used to inform and direct program offerings, such as patterns of energy usage, peak usage patterns, time of use, and more. Billing and payment trends will also provide valuable insights.

Once you have those baselines, design a survey to discover your customer’s interest in the following three topics to create a segmentation strategy. The example questions beneath each topic should demonstrate how the answers can help you develop content and communications with higher relevance for specific segments.

Environment

Do you believe global warming is real?
Do you think more needs to be done to help people avoid wasting energy?
How important is it to you to protect the environment for future generations?

Educational

Do you know what a smart-grid does?
Would you participate in a time-of-use (ToU) program?
Do you know how smart meters can be used to impact the environment?

Economic

Do you take measures to save money on your electric bill?
Do you know that energy management can save you money?
Is your electric bill pushing your budget comfort zone?

By scoring the answers, you will be able to create a segmentation program with three tracks of messaging that address the consumer’s highest interest area. It is evident from the variance in the topics of the environment, education and economic concerns, the same messaging will not appeal to all of your customers.

When you review your smart meter data in correlation to the survey answers, you should be able to discover patterns that will provide insight to the combination of messaging and program offers that will have the highest impact on customer response.

For example, if you see a pattern of lower energy use, on-time payments and an affirmative answer to environmental questions, those consumers may be more receptive to information and programs designed around conservation, sustainability, and “green” messaging.

Focusing communications on a consumer value proposition applied to consumer segmentation raises a consumer’s willingness to respond which provides utilities with the opportunity to influence change and the adoption of your smart meter and smart grid programs. Relevance, driven by segmentation is a key strategy utilities can use to encourage behavioral change and energy savings.

Bryan Truex, Sr. Director, Utility Analytics

PS - Please remember to follow me - @BryanTruex - on Twitter!

Developing the Smart Grid Consumer Value Proposition

Wed, 28 Mar 2012 12:12:00 -0600

Consumers are most interested in self-focused benefits when considering how they engage with services and selecting which products they purchase. This focus does not change when the service is electricity. As customer service and marketing professionals for utility companies work to create engagement and modify consumption behaviors, they must apply their primary messaging to a value proposition that resonates with consumers.

What Electricity Consumers Care About

A number of themes were revealed by the Smart Grid Customer Collaborative (SGCC) during their Excellence in Consumer Engagement Study that analyzed 150 customer-facing U.S. Smart Grid programs. Four takeaways can be applied to create more consumer programs for smart meter deployments:

Set and deliver on short-term expectations.
The true benefits from a Smart Grid can be years away. Keep messages focused on setting expectations that can be delivered on within a few months—a year at most—to create a record of follow-through that builds trust and credibility for your utility. Messaging that keeps consumers informed of events that impact them personally, such as smart meter installation, privacy, and billing concerns are examples to consider.
Provide information about primary concerns.
The SGCC study found that every smart meter deployment that was analyzed had received complaints. Change is difficult and misinformation is rampant when something that consumers just expect to be there takes on a different form—such as electricity. From concerns regarding health, privacy, and pricing to security and even meter-reader job loss, it’s important to ensure that consumers are informed about all facets of change introduced by smart meters. By helping them to establish a comfort level that allows them to ignore speculations put forth by naysayers, a smooth transition becomes possible.
Make the impact personal.
Saving money has a direct impact on the consumer’s lifestyle where environmental benefits are more aspirational. It is much more difficult to visualize the benefits of carbon reduction in comparison to what an additional twenty dollars can buy each month, for example.
Minimize the effort to take action.
Consumers’ lives are busy. Electricity usage is not high on the priority list of things they need to do something about. The simplicity of the programs you design coupled with a high perception of personal impact will be instrumental in driving higher participation and enrollment. But the true tipping point will be based upon the urgency and purpose that your messages manage to convey. As in all industries, the motivation promoted by a call to action must spur consumer response.

It is important to note that messaging and education is not just for consumers, but also must be provided to internal employees. Consistency is critical across each experience the consumer has, including the call center, marketing messages, the meter installer, and even a conversation between an employee and a father during the 7^th-inning stretch at his son’s little league game.

As the research indicates, the smart meter consumer value proposition is based on recognition of personal impact, establishing an informed comfort level about what the change means for them, and seeing that the utility is meeting the expectations they set.

Moving into the future with smart meter data, customer service and marketing programs will be able to refine the consumer value proposition with segmentation and more personalized insights that can produce even higher participation in new programs that are more effective at changing electricity consumption behaviors.

Two Opposing Views on Smart Meter Data Analytics

Tue, 06 Mar 2012 17:10:00 -0600

Quite a dichotomy has emerged in the utilities industry over when to develop meter data analytics. As I spoke recently with attendees of the Utilities Analytics Institute’s 2012 Summit, two opposing views emerged.

On one hand, some utility companies have been extremely focused on their AMI and smart meter rollouts – some as a result of their ARRA funding and related deadlines – and haven’t focused on what to do with the data the smart meters generate. Utilities in this camp have been storing the data, but only using it to bill their customers.

The data has not been leveraged for any other purpose and the cost of simply storing it to satisfy regulatory requirements is raising some eyebrows. This has people considering whether there are business benefits in analyzing the data. Summit attendees in this camp seem to have come seeking ideas for how to get business value from their stored data.

In the second group are utility companies that are beginning their smart meter rollouts and, as part of their implementation, are seeking answers to their questions of how best to leverage the smart meter data. Most that I spoke to in this camp came to the Summit with ideas in mind and were seeking to have them validated.

The business case for storing this data has driven them to find business benefits from analyzing the data to offset the cost of simply storing it to keep regulators happy. Hence they are exploring how to create meter data analytics that focus on improving customer management, asset management and overall business performance.

Regardless of which camp they find themselves in, the good news is that they both recognize that there are benefits in developing meter data analytics. And the Summit speakers provided ideas for meter data analytics that fall, roughly, into three categories:

Customer analytics – these analytics leverage smart meter data so that customer behavior can be analyzed. For the first time in the history of the industry, distributors can literally create actual load curves for every customer. These load curves can be used to segment customers based on their usage patterns and enable the utility to offer attractive price plans to customers while lowering their peak usage. A win-win for both the consumer and the utility!
Asset analytics – this group of analytics takes the smart meter data and combines it with the distributor’s energy delivery model. Doing this can enable a visualization of how loads are affecting distribution assets over time, allowing utilities to modify how and when they perform preventative maintenance to assets. Where assets are consistently operated near capacity, maintenance can be applied more often thereby reducing unplanned outages. Where assets are consistently under-utilized, maintenance can be delayed and some costs avoided entirely.
Financial analytics – these analytics seek to protect the revenues of the utility. Smart meter data can be used to systematically detect where non-technical losses (i.e. theft) are likely occurring and enable utilities to take more immediate remedial action. Also, the meter data can be used to improve tracking of the end-to-end meter to cash process, ensuring that the utility is billing every meter every month (or whatever period they choose to bill customers).

While a few utilities are focused on one of these areas, many utilities are building business cases that exploit analytics across each of these categories. However, in either case, Summit attendees agreed that a single, centralized “one version of the truth” was the best approach to managing the data that powers all of the analytics.

So while there is dichotomy about when to focus on meter data analytics, there is much more agreement that business value exists in the smart meter information and, through continual analysis, utility companies can enjoy tremendous amounts of business value across their enterprise, driven by their data.

Smart Grids: The Challenges of Complexity and Data Volume

Wed, 29 Feb 2012 15:34:00 -0600

Essentially, the term “smart grid” refers to the digitizing of the electricity delivery system through the installation of devices that enable two-way communication and control. This improvement to a utility’s infrastructure is primarily focused on getting more data and being able to take more intelligent action. This data will become the most important asset that the utility will be able to use in the future to understand how their operations are working in real time and how the utility can better—and more efficiently—serve its customers.

There are two challenges that utilities must answer with the evolution of the smart grid—complexity and data volume.

Traditionally, utilities sent out operational meter readers once per month to gather data on energy use. The utility then had a monthly data point to work from to determine energy consumption patterns.

With smart meters, data is collected remotely – for example, every 15 minutes. This amplifies the data volume from one data point per meter per month to 96 data points per day. But, it also means that forecasting models can use granular, detailed data rather than aggregate data to better predict and anticipate energy use.

The complexity comes in when utilities begin to consider the use cases for all of that data volume. The types of data analytics that can be developed from a “load once, use many times” multiply beyond what’s been possible in the past.

Examples include:

Customer Analysis.
With much more data coming from meters at more granular intervals, utilities have the opportunity for better revenue protection. By looking deeper into smart meter data, it’s possible to determine where supply is being lost, identify theft situations and also understand customers better. The ability to analyze consumption behavior matched against payment behavior, for example, can help utilities create better payment programs to reduce bad debt.
Asset Management.
Analysis can also be done on capital intensive equipment, such as transformers, to monitor use and potential maintenance issues to avoid an outage. With foresight, new equipment can be ordered in advance of the problem and replaced before an outage occurs. Having a contextual basis for asset decision making also helps operators understand how assets are functioning and whether required maintenance should occur sooner for heavily loaded assets versus extending time between maintenance for under-utilized assets and optimizing operating expense.
Distribution Management.
With data that provides insights to population trends, an overlay can be done with consumption patterns to better determine how much to invest in distribution for a certain community or geography. Once again, these types of insights can allow utilities to find alternative plans for building out into new sub-divisions or business parks.

To learn more, listen to this podcast with Jill Feblowitz, Practice Director, Business Technology at IDC Energy Insights, and me as we discuss smart grid technologies and how utilities can use data to improve operations and customer service.

Analytics Make Smart Grids Smarter

Wed, 29 Feb 2012 11:44:00 -0600

The advent of smart grid and smart meter technology is changing the utility industry’s business model. As a result, utility companies face new requirements to provide advanced analytical and decision-making capabilities. The need to integrate data from many systems such as the Meter Data Management System, the Customer Information System (CIS), the Outage Management System and others, increases the value of the grid while supporting data delivery to a wider range of applications and data consumers. Utility companies will need to provide this information for many business needs such as the corporate portal, outage management, dynamic pricing, and meter-to-cash analysis.

Utility companies need to develop the infrastructure to support the requirements demanded by growing data volumes, new business users, and new data subject areas. There is also an ‘active’ aspect to the requirements as the infrastructure must support the ability to quickly move data into the analytical environment to perform operational analytics and drive real-time decision making based on detailed granular data throughout the utility.

Drivers of an active Smart Grid analytics platform

Like the telecommunications, retail, and airline industries, the utilities industry has the ability to drive business processes based on detailed customer behavior. These drivers include being able to:

Determine the true effectiveness of energy efficiency programs through the analysis of AMI data and provide more accurate credits.
Identify financial issues in the meter-to-cash process, such as incorrect re-bill processing or improper reading adjustments.
More accurately identify transformer issues and load increases based on individual customer usage patterns, rather than simply on peak day estimates.
Improve customer communications and program enrollment by targeting customers across multiple dynamic segments, rather than a fixed set of predetermined segments.
Use Geospatial capabilities to visualize customer usage and event trends.

Many other examples of using detailed meter data exist. The critical aspect is providing the utility company with the ability to support these many applications of the data without creating an unmanageable clutter of data repositories.

A second set of drivers focuses on architectural necessities to support the many data consumers who need access to the valuable information.

Four necessary drivers must be considered:

Provide the performance and scalability to support:
- Large data volumes of interval and event data from smart sensors and smart meters.
- An increasing number of users accessing the data in different ways, such as very tactical Web services and deep historic trend analysis running at the same time.
- Reduced data latency from the time events have occurred to the time decisions are driven by the data.
Manage costs by simplifying the development and administration of the integration of differing data sources into a common platform, while maintaining data granularity and consistency.
Ensure data security through the proper control and auditing of data across the environment to support the different user requirements, from the external customer to the financial analyst.
Ensure data accuracy through the use of standardized and agreed upon business rules applied to the data.

By taking a holistic approach to data integration, an active Smart Grid analytics platform becomes highly effective when used throughout the utility to improve performance, efficiency and customer service. Making the best decisions possible is dependent upon gaining the richest insights from all available data in as close to real-time as possible.

Learn more by downloading the white paper, How Teradata Makes the Smart Grid Smarter, by one of Teradata's experts, Casey Higgins, Teradata Principle Solution Architect.