3 Reasons Why Utility Companies Need a Business Intelligence Strategy
“Developing a clear picture of forecasted demand provides management with a guide on capital spending and any needed infrastructure repairs or investments”
One technology tool that enables utility or energy companies to achieve multiple interconnected goals is cloud-based business intelligence solutions. Cloud BI platforms can help utilities on several fronts including operations, boosting customer satisfaction metrics, and enabling management to make smart predictions that lead to better business decisions.
Some of the core benefits of choosing a cloud-bi solution vs. on premise solution include:
- Easier integration with other services (consider Microsoft Power BI and Office 365)
- Seamless updates and maintenance that doesn’t interrupt business flow.
- Lower expenses due to not requiring hardware and having low implementation costs.
- The ability to bring in and leverage the power of social network data.
Along with these benefits, cloud BI solutions can help utility companies with the following:
1. Streamlining Operations
Armed with BI data, utilities can accurately predict energy and utility demand by looking at past metrics and then building projections. They can also look at data that shows demand compared to distribution, allowing them to spot
bottlenecks or technical issues that are preventing the smooth flow of services such as water or electricity.
Demand forecasting is complex because it requires integrating multiple data sources. Utility providers need to consider their area’s population changes and economic growth data as well as very detailed weather information. An advanced cloud BI tool such as Microsoft’s Power BI can help utility companies to easily tweak the variables in their demand forecasting models. Developing a clear picture of forecasted demand provides management with a guide on capital spending and any needed infrastructure repairs or investments.
Utilities are also adopting a business intelligence strategy to help them spot market trends, find the best commodity trading partners, and guide them on how to allocate energy trading actions.
2. Improving Customer Satisfaction
During Hurricane Sandy, PSE&G, a New Jersey utility created a task force of workers to read and respond to customer Tweets. When service was restored, the company had a more than three-fold increase in Twitter followers and they were able to provide fast and efficient updates to their customer base. Where does cloud BI for utilities come into play? They can incorporate data from social networks to identify trends and to gain an understanding of just how many people are using social to communicate.
Utilities are a low margin industry, so they need to balance their requirement to decrease operating costs while also ensuring higher customer satisfaction. BI provides insights into customer service, for example contact center wait times and other call center metrics can be reviewed carefully. The ability of BI to correlate different data sources can help link issues such as high wait times with another operational problem or a certain time of the day/week. Review of BI data and implementation of the resulting insights means a streamlining of the call center, with faster response times, and higher satisfaction scores.
3. Smarter Decisions through Smarter Data
With cloud BI, management can not only see if demand is rising or falling, but can gain an understanding of why it is occurring, giving them much needed context. Context is the core benefit of a business intelligence strategy, as it is able to take data from multiple sources and allow the user to develop correlations that were previously hidden.
These correlations or insights are what allow management to make smarter and faster decisions, whether it’s reacting to spikes in demand before they happen, or sending out messaging within minutes of an outage. Cloud based BI also can bring in data from sources such as social. Tweets about the utility provider directly or related keywords or hashtags can be collected and analyzed in real time. Management can then make decisions as necessary in response to the trends, for example to slow down a rash of complaints.