January's record-breaking cold front, also named the polar vortex, was an extreme weather pattern that affected nearly 80 percent of North America. Based on statistics gathered from more than 4000 energy measurement points at over 250 sites across North America, energy management provider Panoramic Power was able to compile data revealing that off-hour energy consumption, incorrect temperature settings and inefficient equipment contributed to significant financial losses during the extreme cold snap.

The company reports that the storm resulted in unusually high levels of energy consumption and device failures at multi-site retail chains and large square footage commercial buildings where Panoramic Power energy sensors are installed. One common theme from this data is how a lack of proper energy planning contributed to financial loss and a disruption of business.

Some of the data findings include:

  • 10 percent of retail stores had non-functional heaters or boilers
  • There was a 30 percent increase in off-hour energy consumption
  • The largest impact was specifically in places such as Texas that do not normally use heating equipment with over 400% increase in overall energy consumption
  • Efficiency of heating equipment dropped by 30% during the peaks of the storm resulting in 30% excessive energy consumption during operating hours

"The "polar vortex" weather system that blasted North America with extreme cold resulted in financial loss for many businesses that did not have strategic energy management technology in place," said Yaniv Vardi, CEO at Panoramic Power. "This is a wakeup call for enterprises to place a higher priority on their proactive energy management technology strategy. Best-in-class companies can prevent financial losses due to inefficient energy consumption and poor facility maintenance data."

As weather patterns continue to disrupt businesses and their infrastructure, companies can implement technology that provides visibility into energy consumption at the system level. Data and analytics reveal usage patterns and trends, and identify maintenance issues before failures occur. This can result in operational processes that leverage intelligent data to optimize energy use and reduce consumption across a retail chain's portfolio.