When I first advised people on the application of GIS and location data analytics the world was still a fairly business-centric place. OK- we all used mobiles but mostly to talk.

Today, we transact on mobiles as never before. If we order a product we need it delivered where we are going to be and that is rarely the office, home or another fixed location.

Visualising location data is not enough today.

Standalone GIS systems are limited as much as standalone analytics. Everything our customers, our suppliers, our staff and our stakeholders do has a spatial element. Not static, but moving. Anyone following @MrScottEddy on Twitter will know this!

Any enterprise seeking to gain competitive advantage must be able to extract the value of location data across all areas of the fingerprint they leave on the world. And to do that they must be able to analyse how this spatial data interlinks with all the other data held within and without the organisation.

  • Structured
  • Semi-structured
  • Unstructured
  • Batch & real-time

That is how a number of innovative location intelligence vendors help join location data with all these disparate data sources. Witb the help of self-service discovery in a secure platform, APIs, and data stores they open up the ability to find new correlations and predict future outcomes better.

See how:-

  1. Multinational BBVA analyses the territorial dynamics of credit card transactions to predict, plan and make decisions. 
  2. Disaster response teams analyse before & after scenes at earthquake sites to deliver help more effectively
  3. To mitigate climate change by predicting outcomes of planned growth and activity

This can, and should be, embedded in the operational and enterprise applications of each organisation. In this way, personas across the whole organisation, from the frontline to headquarters, can apply skill, knowledge and observation to turn insights into optimal outcomes