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As industries across the globe navigate through the changes brought about by the pandemic and technological advancement, data science is now seen as not just useful, but highly crucial in growth — whether in manpower, product or revenue.
For a considerably traditional field, the real estate industry is known to be the slowest to adapt to changes, with many industry players still prefer the tedious paperwork and personal “intuition”.
But for Huynh Ngoc Tan, a Data Director, real estate is, in fact, a big playing field for data. Coming with relevant experiences from Silicon Valley in California and about 10 years in business intelligence in financial services, Huynh learned that to obtain fast, actionable insights, a company needs to look at data.
“In real estate, there are several touch points where you can take advantage of data. From choosing the right land to building the project and even up to after selling the property — wealth management, for example — data plays an important role,” says Huynh.
Data journey
But Huynh knows that understanding and eventually applying data science and its related disciplines to any industry takes time, and may even require management change. In real estate, Huynh says, developers and agents alike need to unlock new levels of potential that can only be attained through data science.
The entire data journey is a step-by-step process — collect, measure, analyze, improve and control — that should be followed strictly to yield the best results. As Data Director of one of Vietnam’s biggest residential real estate brands, it is Huynh’s responsibility to jumpstart that journey, build a team to go through the entire process, and allow analyzed data to drive the next step’s direction.
Data in real estate
As part of any transformation project, building a solid data culture for real estate is vital to the progress, not just of the company, but its projects and the people it serves.
“There are five pillars in real estate: land or project (population density), product design (what to build on that land), project execution, sales and marketing, asset management (rental, utility). All of these can be optimized by effectively organizing and qualifying data.”
Data can be used to identify and manage risks, predict possible problems or consumer behaviors, and tailor solutions and strategy to specific problems or opportunities. This all leads to making informed property-based decisions.
And the result is worth all possible cost of data transformation, he adds.
“With data, a company can have more visibility — a common view of all aspects of the business, from top to bottom; transparency — with business happening in different levels, data ensures that there’s no more blindspot; and lastly, improved revenue — seeing the relationship between different measures and leverage enables the company to develop new revenue models.”