As the world gets used to a new work-from-home based life, companies have begun to re-evaluate their real estate profiles. But in truth, digital transformations like the internet, mobile phones, and automation were irrevocably changing and disrupting the reality of the real estate market before COVID-19 shut down much of the world’s office space. In the face of this new reality, companies may have no choice but to drastically alter the way in which they consider and evaluate their real estate profile. Ongoing disruptions have no clear timeline for normalcy, only increasing the need for answers in a time of such uncertainty. While many companies evaluate their real estate decisions with fairly mature business processes, only a select few fully utilize the currently available technologies and novel datasets to provide tailored, actionable insights in a muddled industry space.
What is Spatial Analytics?
From geospatial analysis, to GIS, to location analytics – there are a lot of terms for what is referred to here as spatial analytics. All of these terminologies boil down to the same extension of a simple question – where? Where do I want my next site to be? Where are my competitors located? Where do my customers actually live? This addition of ‘where’ helps give a spatial context to our data and analyses in a way that differs from most data science efforts. The inclusion of that physical context is not only the defining characteristic of spatial analytics, but also its main benefit. It is often easier for our minds to use the context of location to better understand valuable insights. That ease of understanding and innate context allows spatial insights to be particularly valuable and more easily actionable. In the larger context of real estate, we are able to apply the full range of spatial tools to determine ideal future locations be it in the context of expansion, consolidation, or merger & acquisition activity.
Real Estate Analytics Provides Cross-Industry Insights
By adding the spatial component of modern technology, spatial analytics bridges the gap from discovery to actionable insight. Companies and stakeholders often have access to robust internal data sets, such as event-driven utilization, that are not being leveraged to their fullest extent within their business practices. In the analytics space at large, there also exist additional technologies and datasets – GPS routing data, mobile phone data, high resolution demographics – that expand the insights and level of detail analyses can provide. Routing datasets that calculate across differing times of day can minimize commuter impact in new real estate development. Mobile phone data and granular demographic data can provide a highly accurate view of customer segmentation, retail footprint, and cross-shopping competitors to better inform siting decisions in a retail context. GPS data of maintenance staff or shipping can provide a highly accurate view of warehouse utilization or manufacturing throughput to inform consolidation decisions. This data exists and these analyses are possible. Your organization need only position itself with the necessary expertise to fully capture the value these powerful solutions can provide.
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