The world is full of an unprecedented amount of data, with 2.5 quintillion bytes added daily to the internet, according to IBM.
The vast volume of information has led to the term ‘big data’, which, despite becoming a buzzword, still holds importance in the sense that businesses can unlock key insights by analyzing large amounts of data. And the opportunities to extract value from big data appear poised to grow even more.
By 2020, there will be twice as much high-value data worth analyzing, predicts IDC.
One area worth analyzing already is energy usage and cost. Too many businesses overlook energy as a fixed cost or an afterthought, not realizing that they can easily reduce their monthly bill and improve their sustainability by using simple data analysis.
With Energy Analytics Software (EAS), companies can tap into the world of big data to reduce their energy costs. Rather than guessing what’s behind their energy bills, EAS allows them to look at historical and real-time energy usage and see how their business processes and systems factor into their energy costs.
For example, a company may not realize that they’re being hit with high demand charges, which is dictated by a business’s peak energy usage in a 15-30-minute interval over the course of a month. In fact, 50% of most organizations’ energy expenses are based on these periods.
So if a company happens to use most of their energy between 1:00-1:30 p.m., for instance, they may end up paying significantly more than if their energy usage was more evenly dispersed throughout the day. And that’s where analytics can come into play, by helping companies identify and visualize peak usage periods so that they can shift their processes to ultimately reduce their bills.
Analytics can also curb future charges, such as by mitigating the effects of capacity tags, which are rate identifiers based on how much strain a company puts on their regional power grid during the peak period of utilization across the grid. Companies want to limit their energy consumption during the measurement periods used to determine capacity tags, because in as little as an hour, companies could have their capacity rate set for all of the following year. By analyzing past and present data, EAS helps companies identify when capacity tag measurement periods are likely to come, so they can strategically reduce their usage.
Aside from cutting costs, analyzing energy data also allows companies to more easily reach sustainability goals, whether it’s for regulatory or corporate responsibility reasons.
For example, energy analytics allow companies to benchmark their energy usage against like buildings and their own historical usage. If companies just glance at their energy bills, they won’t know how they’re measuring up to their goals. Moreover, EAS allows companies to make sense of specific data points such as greenhouse gas emissions and compare that similar facilities.
This ability to take big data and make sense of it in areas such as energy helps companies improve their bottom lines and stay on top of their goals. Overall, nearly two-thirds of senior decision makers “see big data as a key enabler of their organization’s effectiveness/competitiveness,” according to Capgemini.
And as the quantity of data continues to grow, it’s more important than ever to be able to sift through information to find quality data that helps your business thrive.
Request a complimentary energy efficiency assessment to find out how Artis Energy’s RTIS® energy analytics platform can provide you with the visibility and insight to transform energy from a fixed cost into a distinct competitive advantage.