About 6 years ago, our small team created BuiltSpace, and set out to solve the GHG/energy problem in large numbers of buildings. We knew that buildings produce about 49 percent of the greenhouse gas, and consume about 50 percent of the energy globally. We determined that energy is about 20 percent of building operating costs, and there was growing consensus that building GHG emissions are potentially catastrophic to our global climate.
GHG emissions from buildings is a global problem, involving millions of buildings. Can we leverage our collective intelligence to solve this problem?
Our initial approach was to build a database of thousands of buildings, and collect and analyze energy data about these buildings. We found many buildings that wasted energy, but without better knowledge of these buildings we couldn’t begin to improve them.
We discovered that we need to know much more; the energy consuming equipment in each building, how the buildings are designed to operate, how they are operated and used, and how they are maintained. This knowledge about individual buildings simply hasn’t been easily available across large numbers of buildings. We needed to change that.
If you don’t know buildings, you can’t fix them. That’s true when applied to greenhouse gas emissions and energy efficiency, but also everyday building operations…the other 80 percent of operational costs. Globally, facilities services, the provision of labour to manage, operate and maintain buildings, is a $1.12 Trillion annual cost to building operators and tenants. What if, by having better information at hand, you could actually manage facilities service costs, and knock 20-30 percent off of your overall operating costs, while now having the knowledge to actually address GHG and energy efficiency?
Current facilities service processes prevent the adequate capture of this building knowledge. So we found that we needed to change these processes, creating asset-centric service processes, used by occupants, service providers, and facilities operators, to capture and access building knowledge contained in our building knowledge-base.
Today, we have created individual building knowledge-bases for over 14,000 buildings with automated service processes capturing building knowledge from service vendors, tenants and facilities operators. Now we need to leverage intelligence, from people or machines, to analyze this knowledge, and apply it to solving operational and energy efficiency problems. We are now working with cognitive technologies to leverage this knowledge-base of buildings, to make and future buildings more sustainable.
Our approach is scalable, and process-oriented, meaning we can apply processes, not hardware, to improve any, and every, building. We can do this, together.