As we are seeing with almost every other industry worldwide, the Commercial Real Estate (CRE) industry is being revolutionised by change, with no area immune. The global real estate market has seen a tremendous shift; the green transition, growing urban populations, as well as demographic and technological changes - all creating fresh opportunities for investors in both traditional and emerging asset classes.
Big data and data analytics have transformed real estate by enabling businesses to gain valuable insights into customer behaviour, preferences, and trends. The industry puts its best foot forward by utilizing multiple data science functions, creating valuable advantages such as risk mitigation, improvement of stakeholder engagement, accurate valuations, better market strategies, data-driven insurance and AI support in the decision-making process.
In the modern world, property valuations based on data science are changing the game. With the help of data science models, investors can make informed decisions based on high-quality data and insight. These models can combine data from hundreds, if not thousands, of sources to produce accurate valuation forecasts that can optimise investment and the development process.
Despite the excitement of new opportunities, CRE has faced some challenges in recent years that have softened demand while raising operating and financing costs. Higher interest rates, an economic slowdown, the hybrid work environment, a tight labour market and more are all contributing to the pace of change that shows no signs of easing despite economic headwinds. In the current real estate market, the challenge is more on the supply side: the market is in need of actual project availability in all sectors. Due to the complex web of legislation and tax issues in many countries, these projects often need more time to become available to the market. Yet, the demand on the investment side is still robust; the money is available, and investors are now well aware of the fact that yield expectations need to be realistic.