Here is an article by one of our experts, Pete Thirlby who specialises in technology within the Real Estate sector. He covers the massive changes in Real Estate tech, from mainframes to Big Data, AI, Internet of Things, Data Analytics as a Service and Business Intelligence.
“Back in the 1980’s I was co-founder of a software company, which specialised in creating systems for the (then) new generation of PC’s. Myself and my colleagues had learned our programming skills whilst studying for PhDs using massive mainframe computer systems with clunky user interfaces and torturously slow software development cycles. We seized upon the new generation of “Micro Computers” that had emerged in the 1980s and new software tools that let us develop systems far quicker.
We started to develop software for the commercial real estate market, creating a system that allowed agents to match client requirements against a database of available property. We created a centralised service to compile the database of property and distributed it by electronic bulletin board. Fairly rapidly, we had all of the major agents using our system with over 100 clients.
This was before the internet. In short, we had used technology to disrupt an industry, revolutionised the distribution of information, automated manual processes and consolidated effort. I guess these days we would have beards and drink flat whites in some trendy loft studio near Old Street.
30 years ago PropTech was confined to the primal needs of the commercial real estate world, namely managing the process of finding tenants or a suitable property, managing the process of rent and services charge, and valuing the property. And that was about it.
These processes remain core to the PropTech offerings that are currently on the market and over the years they have been augmented by new technologies, but we have not necessarily seen disruptive change. The advent of the Internet in the 90s bought about huge changes in the way that property could be marketed, but, did this really shake the residential and commercial agency markets? New technological developments are bringing new products to the market but will we see further ‘disruption’?
Let’s examine the potential for change.
Virtual and augmented reality
This technology certainly has the potential to enhance and quicken the design process, allowing the client to get closer to what their space will could look and feel like. Certainly, this technology will impact the way that architects and designers work with their clients, reducing the cycle time from concept to finished product.
However, in reality, is this tech making an existing process more efficient rather that creating a new model?
Internet of Things (IoT)
IoT has the potential to enhance the way that we monitor and control space. It’s noticeable that some BMS vendors are now rebranding as IoT vendors. Closer control and monitoring will enable more cost efficient and environmentally sustainable use of our workspaces. As suggested this technology is already disrupting the BMS market, causing established vendors to shift their stance as new players start to infiltrate their market with new platforms that allow monitoring and control of workspace use, CO2 levels, basic energy use and focussing on a ‘Wellbeing’ agenda.
IoT has the potential to also produce lots of Big Data, but what does that mean?
The potential for Big Data within real estate is enormous. At a micro scale, looking at data from IoT sensors and BMS and meter data and also on a macro scale, analysing value trends etc.
But, as Dan Areley of Duke University said:
Big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it…
There is the potential for Big Data to extract nuance and understanding from complex systems. In real estate terms, to be able to identify how factors such as weather, occupancy and footfall can impact on cost and environmental impact.
The issue with Big Data is that by its very nature, it is big. So big that conventional Business Intelligence tools cannot really cope with the sheer volumes that are in play and the complexity of the relationships between the data. The potential for disruption through enhanced insight is always possible but, with current tech, unlikely.
But there is hope, in the form of AI/Machine Learning, how would this look for the Real Estate industry?
Artificial Intelligence (AI)/Machine Learning
AI/Machine Learning is the new kid on the analytics block and is the key to unlocking the value of the Big Data that could disrupt many aspects of the real estate world, such as valuations, sustainability, planning and market analysis.
The driver behind AI/Machine Learning is Data Science, a whole different approach to analytics. It is not so much about the evolution of Business Intelligence (BI), but more of a completely new approach, a new species.
BI is about KPIs, charts and answering questions that we knew – in very crude terms – sorting, grouping, charting and comparing data that exists in regular structures. Data Science offers the opportunity for discovering new questions to be answered and takes the approach of statistically analysing the data, so that the relationships between the different data types can be articulated as a model. As that model becomes refined and perfected that gives us the intriguing possibility of prediction.
DAaaS – Data Analytics As A Service
Data Science isn’t new, it has been around for around 30 years and arguably, has been driven forward more recently by faster processing, high capacity storage. This is now manifesting itself as DAaaS – Data Analytics as a Service. Cloud providers such as Amazon Web Services and Microsoft Azure are offering storage, data handling and modelling tools to provide the possibility of creating predictive analysis opportunities based on our own data. However, these tools require new skills in our teams, Data Scientists to create the models that we need.
So don’t be surprised to see service providers and end users on the real estate market recruiting and training Data Scientists, which will lead to the creation of value from Big Data. This value, in terms of strategic and operations advice will in turn reveal The Big Answers and also The Big Questions.”