At DNV, our mission is to safeguard life, property, and the environment. We do this throughout a variety of industries, and as the head of the electric grid ecosystem and product center at DNV, my focus is on helping optimize risk assessment, remediation, and overall reliability of critical assets at our electric utility customers. In order to do this, my team uses data to identify problem areas and potential issues for our customers (ideally before they happen).

Like many organizations, our utility company clients are sitting on copious amounts of data from a variety of sources, including mobile applications and streaming data captured by grid-edge technologies. However, without an advanced analytics solution that could surface relevant trends and information, this data was an underutilized asset.

That led us to build Cascade Insight, an enterprise solution that infuses data and insights into a comprehensive platform that utility companies use to optimize their operations, reduce risk, and improve the reliability of their electrical equipment. This process necessitated us getting a handle on the data we were already collecting, making sense of the constant stream of new information our clients were pulling in, and presenting it all in an easy-to-understand interface. 

Unique challenges and opportunities in the utilities industry

As opposed to typical for-profit enterprises, utility companies were created to serve the public good. One of their main focus areas is driving operational efficiencies to maintain affordable rates and deliver better service for customers.

Utilities employ skilled professionals as knowledge workers, but creating a simple, visual way to analyze their data is a hard skillset to find in abundance. DNV’s effort to create an analytics consortium was driven by the opportunity to bring knowledge workers from different utilities together to collaborate on challenges with their peers. Much in the same way that researchers are able to collaborate on projects across time and space, we wanted a consortium of utility providers to be able to pool efforts on major problems affecting the industry beyond their individual companies.

Capturing and transforming data to transform the utilities industry

The key to making this collaboration possible would be having an analytic application that could pull in data from across a number of sources. Each utility company generates a tremendous amount of data from a variety of touch points, making the first challenge one of volume and ingestion: The destination system has to be able to handle data from disparate sources and in a range of formats, especially from mobile and field sensors/equipment. Transforming this data into something usable becomes more complicated when you realize that utilities often have different data naming conventions in addition to capturing different pieces of data.

This presented the first challenge for our product team in building Cascade Insight: What is the data that is most important to capture? Being IT professionals and software vendors, my team initially focused a lot on the technology. However, defining the data requirements was important for understanding what data you need to measure to provide analytical insights. And my team at DNV struggled with that in spite of having all this data and domain knowledge. Fortunately, the team at Sisense was able to come out and help us with this process.

The Data Journey: From Raw Data to Insights

The right data, the right platform, the right partner

The experts at Sisense live and breathe data analytics — and the Sisense platform is designed from the ground up to connect with disparate datasets and infuse insight from those sources anywhere users need them. Working with the Sisense team, we were able to nail down the data requirements that were needed to create the high-level insights, such as the overall health of a transformer, that would improve the lives of our utility company end users. Armed with this understanding, we were able to use Sisense to develop the Cascade Insight platform in just six months, a rapid timeline for building an enterprise product from scratch!

As a seasoned IT professional, I knew that our platform had to consume clean data if it was going to deliver accurate insights. The old adage “garbage in, garbage out” rings very true when it comes to data analysis, and we had to do a number of things to verify that the data entering the Cascade Insight platform was clean. It started with implementing data validation rules, including basics like only accepting numbers for numerical inputs, etc. Data quality starts when you first capture information; keeping bad data from getting in your calculations in the first place is key. 

We also had to ensure that the information captured across our utilities was consistent. For example, when considering data captured on/by a transformer, a couple of the obvious data points are make and model. However, a utility may have another 40-plus items about that transformer that it’s capturing data on that may either be documented with a different naming convention or not even captured by other utilities. So, when building out Cascade Insight, we chose 16 key dashboards that our clients would benefit from and ensured that the data captured from each of the clients was clean and consistent and could be ingested into our analytics application.

Driving immediate impact with analytics

Cascade Insight had an immediate positive impact for our utility company clients. Professionals are now able to quickly identify equipment and processes that are at risk or are performing suboptimally, drilling down to specific components on a map that are having problems. From there, they can proactively provide maintenance to those components and help keep the lights on for millions of customers. But this is just the starting point for Cascade Insight.

By creating this consortium of utility providers that collaborates across utilities, we hope that this will encourage ongoing communication among the utilities. By collaborating on best practices, and as new challenges are discovered, this coalition can begin defining future dashboards and coming up with standards for the associated data that must be gathered to drive meaningful insights for them and users like them. This collaborative work style, uniting a number of utilities, is a practice that can be replicated across other industries, in particular health care. Bringing together really talented professionals and providing them data in an accessible application instead of jumbled numbers in a spreadsheet helps drive positive, high-value results.

Whatever your industry and your company, you’ve got some data you can use to drive revenue. The key is to understand that data, learn to capture and prepare it properly, then present it to your users in a way that is meaningful to them. The right BI platform can go a long way toward making that process possible, and the right partner (like Sisense) can give you the support and expertise you need to make your dream a reality. To hear more about DNV’s analytics journey, check out our conversation here! 

Ron Howard is head of electric grid ecosystem & product center for DNV. He has over 35 years of experience in the utilities industry with a focus on IT and software products. Having worked for both software vendors and utilities, he has devised and delivered many successful software products and has spoken at numerous industry events and conferences.

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