Dealing with Big Data in the Community Management Sector
“Data-rich but insight-poor" is an accusation frequently levelled at today's CAFM users and organisations, as highlighted in a recent article I read in UK’s IWFM Facilitate magazine, which focuses on harvesting data in commercial buildings.
The article addresses a very relevant question regarding data which is, “What is the value of this information if it isn't being analysed and used for a purpose?” The fact is everyone is buying technology and collecting data, but few are interpreting and reacting to it, or even know what they want to do with it.
Whilst the same issues are faced within commercial buildings in the Middle East, it got me pondering about the collection of big data in the context of the residential communities served by FM service providers across the GCC.
Whilst there may be a resistance to some of this new technology in the commercial sector, due to the fact that FM service providers are often asked to fund the costs within already small margins, we have noticed that there is definitely an appetite in the residential sector from individual tenants and landlords who occupy their own properties.
Common areas of residential towers and apartment buildings can certainly benefit from sensors and big-data analytics in the same way a commercial office building can, but individual dwellings can also take advantage of data insights. Sensors installed in homes and around them are able to gather various bits of data like atmospheric pressure, temperature,
the number of visitors/occupants (Internet of Things), and insights based on AI can be applied to benefit the individual building and its efficiency.
I have also noticed many tenants and property owners within the community I live in, asking for recommendations about which model of smart thermostat to buy on social media groups. These thermostats, such as the Google Nest which has been around since 2011 and is now 3rd generation and uses AI behind the scenes to work out when you need air conditioning and include things like motion sensors to detect room occupancy. Other smart home options commonly discussed are from ‘Honeywell Home’ and ‘ecobee’ who ask users to opt into their “donate your data” initiative whereby they ask for consent to share anonymised real-life data from your ‘ecobee’ smart thermostat which can help leading energy scientists design more efficient and sustainable homes and communities.
Such data insights from hundreds of thousands of homes help scientists better understand how our energy usage changes over time. Sharing to advance sustainable futures is certainly a hot topic particularly with the record high temperature being witnessed in Europe this summer.
Whilst the use of this new technology is on the rise within the residential sector, we need to consider whether the cost of installing such thermostats outweigh the benefits for a tenant unless they go the expense of installing and removing the units as and when they move? The question is how we can we encourage landlords to invest in such technology to drive sustainable living in our communities?
One of the biggest challenges we also have to consider, if we are able to gain actionable insights about the efficiency and the life-cycle of assets in the residential sector, is the differing levels of maintenance undertaken in each property, as well as the variety of set points used by residents. With many buildings and properties being rented, and the landlords often being unwilling to commit to any maintenance spend, and no central CAFM or record of maintenance activities, are data insights even available?
As my colleague Paul Bullard aptly said, “Getting data is key but it requires an overarching caveat. Don't just do something for technology's sake. For example, don't buy your entire workforce a Fitbit if there is no value in the data that you're recording from them. People collect too much data, and that data is often not valuable; you simply end up wading through tranches of information that are of no benefit to anyone."
On a more positive note, a great example of big-data collection and insights is DEWA’s “My Sustainable Living Programme” which provides landlords and tenants information about their water and electricity consumption, comparing efficient similar homes to your own consumption. A valuable element of this initiative is the automated alerts that DEWA generates from AMI (Advanced Metering Infrastructure). This is something I have personally benefitted from when we received an alert of “high water usage” (by email and SMS) as our water consumption had increased at home by some 50% over 48 hours. The alert allowed us to trace the issue, of which we were not previously aware, and have it addressed immediately saving both water and money.
I’m sure these alerts have benefitted many other within the community, and I believe more initiatives like this are definitely the future.
(The blog is written by Adrian Jarvis, Director of FSI Middle East)