From the moment we roll out of bed we are surrounded by data and the actions taken because of it. There is the weekly forecast humming on the television, constructed from hundreds of weather station data points. As we scroll through a news feed on our phones as the coffee brews, dozens of ads are served to exactly our eyeballs, the ad’s content based on a complex web of data points ranging from browsing history to physical location. By the time we walk out the door, dozens of actions have been taken based on data collected for and from ourselves, and it all defines what we do and how well we do it.
The same is true within the utilities industry, where increasingly thorough field data collection is spurring innovation, preventing accidents, and boosting efficiency. Data collection has long been a staple of the industry, though, and data collection alone does not lead to action and change.
Montana-Dakota Utilities (MDU), an energy company providing natural gas and electric service to the United States’ Northern Great Plains region, implements a software solution called Pipeline Inspection Manager (PIM). PIM is used to track, schedule, execute, and archive field data inspections for a variety of assets, including, but not limited to, those monitored under regulatory compliance guidelines. MDU also uses the data to increase the safety and efficiency of their operations. Nicole Garrett, Quality Assurance and SMS Manager at MDU, says field data shapes the actions of the company at every level, from developing performance metrics to analyzing the risks and causes for accidents or outages.
“Field data can help us select initial KPIs when unexpected patterns or discrepancies are found”, says Garrett.
One such example was found in the MDU emergency response time data. Data revealed differences of as many as 100 minutes between emergency response times to incidents, a variation that MDU sought to fix. Emergency response times became a KPI for the team, driving them to find and remedy the root causes for the delays.
Along with reacting faster to incidences, field data has also enabled the MDU team to preemptively reduce or avoid incidents by identifying systemic trends in the data. Revealed patterns can only be acted upon if they are discovered, after all. The data, once viewed through the clarifying lens of a sensibly chosen KPI, is suddenly placed into context.
Across MDU, the use of field data has jumpstarted cross functional collaboration between teams who would normally work siloed. Teams are now able to see a larger perspective of the company’s risks and, together, find and rank the importance of those risks.
MDU’s field data is used heavily to predict and avoid incidents and to increase safety for employees and the public, but that formula won’t be the same for every company, says Garrett. “It’s not a one-size-fitsall model – Every company is different, and every company’s metrics are going to be different”
As data collection becomes more common and sophisticated, it is clearly not enough to blindly collect information without subsequent action. The benefits of implementing strategies centered around data, as seen in the safety improvements made by Montana-Dakota Utilities, are too great to ignore.