Today, in our globalised and digitised world, information is generated and flows at unprecedented levels. Consider the numbers: within the next hour alone, we will generate 8.5 billion emails, 34,200 new websites and 144 million Google searches.
Ninety per cent of all the data that exists today was created only in the last two years, which gives you a sense of the enormity of the task in making sense of the data. The term ‘big data’ refers to large collections of voluminous, complex data that defies traditional attempts to process or manage it.
For facilities-management companies like Spotless, the capture and storage of big data is nothing new. The game-changer has been the introduction of the Internet of Things (IoT), which enables devices – not only tablets, smart phones and computers, but every kind of physical piece of hardware – to be connected through network activity.
“Basically, any device can be individually connected to the internet and used to collect and exchange information about anything from the physical environment – temperature, lighting, air quality, humidity – to inventory and asset performance,” says Derek Del Nevo, Spotless Business Insights & Data Analytics manager.
But as explained by Derek, simply having big data is not the panacea – it’s knowing how to look within the data for nuggets of insights that provide real value to businesses and customers.
“Many businesses are actively utilising IoT sensors on assets to capture more information regarding performance and behaviour of equipment,” he says. “However, the data on its own doesn’t provide much value or differ greatly from traditional Building Management Systems (BMS) data. Only when the data is overlayed with algorithms that highlight trends and give you insights, does the real value start to emerge.”
For Spotless, this means identifying smarter ways to manage a building more efficiently, sustainably and resourcefully. Spotless is currently running a data-exploration experiment in one of its hospital contracts, using BMS data, as well as IoT sensing data, energy data and external sources such as the weather. The insights afforded by the experiment revealed untapped trends, correlations and causes of malfunction, thereby allowing the team to focus on a predictive maintenance regime that optimises the operating parameters to enhance energy use and reduce the risk of equipment failure. The results could afford building owners major cost savings and improvements in efficiencies, while offering customers a more sustainable, consistent and reliable environment.
“Predictive maintenance means that we are using historic and real-time data to run our operations; we can leverage data – literally as it’s being created – to make the best evidence-based decisions possible, get maximum use out of our assets and optimise maintenance schedules and strategies,” says Derek.
“Ultimately, facilities-management organisations that don’t actively invest in data insight are unlikely to lead the businesses of tomorrow.”