Geospatial data brings context to everything

Geospatial data brings context to everything

Geospatial data may sound a little abstract, but it is (quite literally) everywhere. Whether you’re following your maps app to a new place or tracking a parcel, this data helps us to see not just the location of something but its status, travel and any related events – often in real-time.  

We may rely on this kind of data in our everyday, but it is often misunderstood and underutilised in business. To start, we can define geospatial data as information with three main elements. The first is an object, event or phenomena, the second is a location and the third is temporal information i.e. a time.  

For businesses, this can provide invaluable insight into their weak areas, shedding light on problems in surprising ways. Alternatively, it can be used in a pretty map for self-congratulatory presentations. I’m going to show you how to avoid the latter. 

Misconceptions

The benefits of seeing data mapped out geographically may seem apparent, but many people don’t realise the full potential of this. The common perception of geospatial data is that it is simply a pretty feature, something to roll out for presentations or curiosity’s sake. But the temporal aspect is easily overlooked when the data is presented as a static map. 

Changes over time in the data can show how different regions compare with each other or how they can affect each other. Further, geospatial data is increasingly used for forecasting. Anomalies can be used to predict incoming events or changes to the environment that could affect your enterprise, and trends in your data can back this up. 

Examples of this value can be found in almost any industry. It can be used to better project risk and determine appropriate premiums for different geographic areas in insurance, or for lenders to assess credit risk scores for agricultural lending. It can even be used to help electricity providers get ahead of potential faults and failures in the grid. 

Since Covid-19, mapping has become widespread with population data, video, social media, maps and weather being utilised to show live data. It is through geospatial analysis that we are now able to see complex relationships between data in an easily understandable, visual way. 

At least, that’s the goal of geospatial analytics. 

Unfortunately, data can be misrepresented or poorly shown in visualisations that makes it confusing for the user, defeating the entire point of geospatial data.  

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Avoid poor visualisation to succeed 

As previously mentioned, it’s not just about gathering geospatial data and analysing it. Visualisation is key to getting the most from your data and maps should be as clear as possible. Colour theory plays an important part in making spatial analysis and data visualisations digestible. 

Users of the maps should fully understand what to look for in changing colours, locations and other features within visualisations, so that decision-makers can act on observations more effectively.  

Reaping the benefits of geospatial data in business 

Businesses can get significant value from geospatial data through anticipating and preparing for possibilities arising from changing spatial conditions or location-based events. For example, a UK-based company might monitor regional performance by splitting maps into their own defined areas and comparing performance. This makes it possible to make better decisions by figuring out which regional areas need additional support. 

Here is an example of how geospatial data analytics can work in practice for a national retailer: 

  • Spotting trends to make improvements at a specific site store, for example, how frequently a shop is cleaned which could be affecting retail sales. 
  • Acting on the trends by enlisting extra resources or further training for staff. 
  • Anomaly detection for deliveries that appear to have been successfully delivered but were not. 
  • Investigation into the reasons why deliveries were made incorrectly by tracking the journeys of couriers. This could lead to better decision making around poor performance or training requirements. 
  • In retail, geospatial data enables businesses to understand the relationship between stores, products and preferences across metrics that can impact sales performance and overall performance.  

Geospatial analytics have the potential to bring indispensable context to everything. By revealing patterns, effective visualisations from geospatial data can give businesses valuable and novel insights into their business that will empower them to make real improvements to their operations and better serve their customers. 

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