Big Data & Analytics

Imagine knowing your customers well enough that you could develop products and services that fit their specific needs, encouraging innovation, and delivering what customers want. Feedback from customers tells us we need to do a better job communicating with them, both in the content we send and the channels through which we send it.

As we learn more about our customers, we can better understand their needs and preferences and target communications accordingly, resulting in more effective customer service, increased customer empowerment and improved customer satisfaction. That is the power of big data and analytics – the new frontier in understanding and improving the customer experience. In 2016, AEP will build an internal team to enhance our knowledge and experience with big data and analytics.

Data-gathering Infrastructure

Today, AEP’s smart grid technology is at the forefront of providing us with robust and frequent information, using smart meters, communications networks and data management systems. Smart grid technologies empower customers to use energy more efficiently and manage costs. The data collected also helps AEP to customize programs and services for customers. Smart meters were initially used to automate meter reading, improve bill accuracy and to manage physical assets, people and outages.

Today, we are learning how additional analytics, based on this data, can help us predict equipment failure so we can proactively take action to prevent an outage from occurring. For example, we are using an analytic that can identify when specific distribution transformers are on the brink of failure, allowing us to fix or replace them before an outage occurs.

Other analyses help us identify meter configuration errors, potential meter failures and meter connection issues based upon the internal temperature of the meter. They also help us to identify and prevent energy theft – a public safety concern and a threat to our revenues. And, we are exploring how analytics can help us improve our interactions with customers, such as improving the accuracy of the outage information we give customers if the lights go out.

Big Data Olympics

To improve our interactions with customers and their experience with us, we need to better understand their preferences and expectations. In 2015, our customer service organization launched an initiative to build a comprehensive, 360-degree view of our customers. Using a broad set of information about our customers from many sources, we looked at an array of things including usage and payment history, website visits, mobile alert history, call center activity, program participation information, outage data and demographic information. We tested several hypotheses to improve our understanding of customers, including proactive communications, improved call center services and performance, and broader adoption of existing payment, savings and energy management programs. We called this project the Big Data Olympics.

In 2015, our customer service organization launched an initiative called Big Data Olympics where we used a broad set of information about our customers, such as: usage and payment history, website visits, mobile alert history, call center activity, program participation information and outage data - to help us better understand their preferences and expectations.

The results were eye-opening and led to further discussions and exploration of additional analytics to help drive improved customer web experiences and better target marketing and advertising campaigns. In addition, our call center managers found the data helpful to address the needs of repeat callers. The analysis found the majority of repeat calls were coming from one customer segment; additional analysis will help us develop solutions that will reduce the number of repeat callers.

Having a more comprehensive view of our customers will allow our companies to design better products, services and outreach programs. And, it will help us have more meaningful conversations with customers about how we balance our capital investments to meet the objectives of the communities we serve.

The Big Data Olympics also included a case study to develop a work force optimization model to help us improve our ability to forecast future workloads and optimally assign the work to employee and contract crews, balancing cost and work efficiency with customer needs. We used historical data to generate a forecast and optimization software to determine the best way to do certain jobs, based on the type of work, cost profile and geography.

We learned there are potential opportunities that not only achieve significant cost savings but allow us to dedicate more resources to priorities that directly impact customers’ experience. We believe this will increase customer satisfaction in the long run, as well as increase employee engagement and satisfaction.

As we increasingly begin to use data to better understand, communicate with and serve our customers, it is important to recognize that data privacy remains a critical priority for AEP and our industry. We continuously work to protect the confidentiality of customer information and to prevent unauthorized use. Because of the substantial investment in cyber-related defenses by AEP to defend its critical systems, we believe AEP customers should be confident in the security of data and information.


Applying big data concepts and analytics to better manage our business and serve our customers requires a major shift in how we think and a technical skill set that we need to develop. We need to better understand how to deliver greater value to our customers.

Through the use of analytics, our 2016 goals are to:

  • Determine how to better serve and market to our customers
  • Sustain continuous improvements to ensure we have the resources we need
  • Improve reliability and reduce risk for customers and AEP
  • Expand Big Data Olympics to other business units
  • Begin to build a data and analytics foundation for AEP as we transition to the next-generation energy company

As we build in-house knowledge of data analytics, we know it will take at least two to three years to achieve the skill level and experience we need. We have established an enterprise analytics services team and a customer and grid analytics team, pairing the knowledge and expertise of our Information Technology team with that of our Customer & Distribution Services group. As we develop our own internal talent and infrastructure, we will work with partners, including IBM and others, to fill in the gaps until we get there.

This is an emerging field that creates new job opportunities for the future. The biggest challenge we face is a shortage of talent with the right technical and analytical skills needed for this type of work. According to the McKinsey Global Institute, the “demand for deep analytical talent in the United States could be 50 percent to 60 percent greater than its supply by 2018.” We need a plan to attract the best talent because we will be competing with high-tech companies, such as Google and Apple.

Learn more about workforce planning