Utilities are using data analytics to improve their service, gain a better understanding of the customer, and improve operational efficiencies.
Analytics strategy creates a holistic picture
By aligning business intelligence with an analytics strategy, a more holistic picture of the business is created. While strategies differ from utility to utility, the concept remains the same: improve business processes through the use of data.
Before establishing a strategy, internal teams need to decide what data they need and how that data will be used to serve the end goal. Without a strategy in place, the data is useless.
Utilities are able to choose from a wide variety of data analytics tools to determine how best to use its new data. By using it in a predictive fashion, utilities will have the knowledge to enhance operations and customer experiences. Utilities can apply statistics on top of data in order to improve forecasting. This can be used to apply predictive analysis which will help the utility improve its planning processes. “What if” questions are very helpful when it comes to planning for extreme weather conditions.
Trend analysis and asset management
Detailed data analysis can also provide the structure for looking at trends, as well as at asset management based upon the history of the asset. More broadly, it can become a key strategic differentiator for the utility with the ability to apply quantifiable metrics (supplied by better data analysis) to a business case.
Energy efficiency and demand response programs also stand to benefit from a more detailed analysis of new data. Detailed energy consumption data can be used by the utility to segment and target customers, and provide them with valuable consumption feedback. This is the basis of true energy efficiency, on a granular, customer-by-customer level. Utilities can even give their customers more consumption data in order to make them more aware of new technologies and the importance of energy efficiency. They can assess their own consumption patterns in order to reduce their utility bills. Good data, in a timely fashion, will give both customers and operations the ability to make good decisions that will improve overall long-term energy efficiency, service levels, demand response, sustainability and energy reliability.
In this way, the value of data will be maximized.
Predicting asset health
The main objective of predictive analysis is to avoid potential catastrophic asset failures. Real-time data availability provides the potential for learning more about the asset, the ability to provide more timely identification of potential asset issues, and greater maintenance cost savings.
Of course, all of this requires taking the new real-time data available, deciding which data is most valuable for the task at hand, and then "layering" or "factoring" that data for further analysis. In effect, utilities need to decide what data is critical towards establishing the most effective final solution.
The idea here is to extend the useful life of an asset and make greater utilization of transmission and distribution substation transformers. Appropriate technology should be adopted to measure the performance and condition of equipment to make better maintenance decisions.
Streaming data is assessed in real-time for any irregularities and data irregularities will trigger appropriate alerts which are transmitted immediately to the relevant decision-makers. This immediate response can help avoid further damage to equipment and safety of utility workers is also improved.
Managing manpower requirements effectively
With real-time data and analytics, the utility is able to quickly locate and resolve problems. They can better-plan their asset maintenance and operate assets closer to their operating limit. They will also have the ability to determine the optimum time to replace an ageing asset.
This translates into cost savings and enhanced workforce efficiencies across the board.
The technology changes are significant and impact all departments within the utility. Daily operations are becoming more complex by the day as a result. In response to these changes, utilities will need to integrate vertically and create new organizational structures to best address the changes. It is also essential that utilities supply their workforce with the relevant new skill sets required to support the new operations and technology.
Real-time and future predictions
In order to make accurate decisions about the utility’s assets and operations, information from all departments must be assessed. The intricate interconnections must be fused to create a more holistic viewpoint.
So much more insight can be obtained from the amalgamation of data from different silos.
New connections of previously unconnected data can be made, and utilities will eventually be able to understand its system as a whole... rather than a sum of its parts.
It's also about asking new questions and the ability to use all the new data to establish a new strategy. This is going to open the door for increased innovativeness when it comes to how data is mined.
Data analytics is certainly going to play a powerful role in how utilities move their businesses forward in the future.