IBM Helps Make Buildings More Efficient, Thanks to Data
Maintaining buildings and other assets can eat up a large chunk of an organization’s operating budget. But by properly instrumenting a building and paying close attention to the data it generates, organizations can those costs, and get better at predicting potential failures too.
At first glance, buildings and data don’t seem to have much in common. Buildings are tangible assets, built on concrete foundations, designed to shelter people and things from the weather in the real world. Data, on the other hand, is an intangible asset, often stored in “the cloud,” that has little value in and of itself.
But the adept facilities manager ignores data at his own peril. According to this IBM white paper, data generated in “smart buildings” and other smart assets has the capacity to save large sums of money for the owners of said smart buildings and assets.
How much money? In the white paper, IBM reports its Real Estate and Site Operations team realized a 15 percent savings in energy costs by applying 50 analytical rules to some of its buildings. The rules governed how facilities managers responded to data gathered by pieces of equipment — think heating and air conditioning (HVAC) equiment — combined with data on energy use and climate data.
What’s more, IBM was able to slash the amount of time required to complete work orders by 50 percent. That level of improvement is enough to pique the attention of any facilities manager.
IBM also cites how data helped a major metropolitan water and sewer authority improve its operations. According to IBM, the organization uses advanced spatial analytics to help predict potential issues with its pipelines based on location, time, weather, and other factors. IBM doesn’t say exactly how much the organization saved. Suffice it to say, its operating costs have come down, along with the average amount of time required to fix problems.
Small organizations don’t have much to gain by instrumenting their small facilities with data collection capabilities. But neither do they have to be facilities. There is a lot of potential to harness operational data from big equipment, like freighters and oil tankers.
One of IBM’s Japanese customers uses data analytic technology to combine many critical functions into one common cloud-based infrastructure. IBM says the sensors capture “the operating conditions of critical equipment, such as vibrations from ship engines, and communicate this data in real time to the company’s global technology solution for failure analysis and predictive maintenance.”
Other companies use IBM data analytics technology to boost revenue. IBM cites one customer — a North Sea oil drilling company — that combines weather alerts, satellite imagery, and sonar data to provide precise tracking of ice flows, which can interrupt drilling operations.