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Why A New Approach to Geospatial Data Is Needed Post-Pandemic

Also referred to as “spatial data”, geospatial data is the term used to describe any type of data with a geographic component. From mapping and navigation to fast food delivery, the development of geographic information science has benefitted a diverse range of organisations around the world and geospatial data is fast becoming one of the most valuable types of data in today’s competitive business landscape. 

 

As well as being used to help businesses compete in their respective marketplaces, real-time, location-based technology played a central role in supporting the global response to the COVID-19 pandemic. According to Greg Scott, Inter-regional Advisor, UN-GGIM at United Nations, “while in the past some countries may have seen the limited value in the role of geospatial data in decision-making, the dynamic nature of the pandemic and urgency required in response has crystallised its importance.” 

 

Having been recognised as efficient, accurate and cost-effective, new use cases for geospatial technology have continued to pop up across all industries since the early days of the pandemic. And organisations are changing their approach to geospatial data in order to unlock its value. 

 

How Geospatial Analytics Is Helping to Drive Business Decisions in A Post-Pandemic World 

 

While accelerating our move to “virtual”, the pandemic also emphasised the importance of our physical place in the world and therefore the increasing value of location intelligence. When viewed through geographic information system (GIS) technology, geospatial data acts as a powerful decision-making tool that enables businesses to extract location-based insights from environmental, demographic, and topographic analysis. 

 

Geospatial analytics involves collecting, combining, and visualising various types of geospatial data: GPS, location sensors, social media, mobile devices, satellite imagery etc. Here are some examples of business practices that are now leveraging geospatial data analysis methods: 

 

  • Visit attribution – combining property and mobility data to determine numbers of shop visitors 
  • Investment research – analysing consumer behaviour and movement patterns to drive investment decisions 
  • Competitive intelligence – evaluating the impact of competitors and other points of interest based on their locations 
  • Risk assessment – estimating how vulnerable a business is to an accident based on the size, shape, location, purpose, and occupancy of its building 
  • Consumer insights – observing consumer patterns in order to strategically plan business locations and inventories 

 

Better, faster decisions come from knitting together location data with the universe of proprietary and public sources that track millions of phenomena and entities” and this emerging field of business intelligence is likely to become a defining business capability as we move forward in a post-pandemic world. 

 

Let’s Talk Geospatial Analytics 

Putting geospatial data to work for your business can often be easier said than done. For expert advice regarding geospatial data integration and analytics, get in touch with the experts at Slingshot Simulations today.  

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