16:20 | 17:00
Keywords defining the session:
Takeaway points of the session:
- Location Intelligence is a new kind of “intelligence” under development that is going to become an essential asset to companies as Business Intelligence, Artificial Intelligence and Data Analytics became in the past.
- Product features, design and UX on one side and technologies on the other that make Location Intelligence possible are still in development, with complex and interesting challenges to be overcome in the close future.
The origin of Business Intelligence can be traced well into the past, but it was in the 90s when it started being widely used by companies as an umbrella term to describe “concepts and methods to improve business decision making by using fact-based support systems”. This provided companies with invaluable information about anything impacting the business (market, competitors, its own consumers, …) they could take into account when making decisions that drove the strategy of the company. Having an upper hand over competitors or improving actual pain points from consumers are two simple examples of how companies would benefit from using BI.
The 21st century brought bigger and more complex systems that generated more and richer data, and more sophisticated processes had to be developed in order to analyse and gain insights from it. This includes the development of advanced Data Analytics and Big Data, that allowed to process huge volumes of data, detecting patterns and extracting specific insights, and different types of Artificial Intelligence (like Machine Learning, Deep Learning or Computer Vision) that allowed automation of algorithms to provide an output based on millions of past cases to support human understanding and decision making.
With the help of these technologies BI reached a whole new level, evolving into three essential areas: descriptive analytics (old school BI – summarize a situation based on data and break it down into something that a human can interpret), predictive analytics (anticipate a future scenario so the company can prepare for it) and prescriptive analytics (advice on what to do to reach a desired scenario).
More recently, we have seen the development of a new type of data that can change important parts of how BI is conceived and used: location data. There are a number of factors (extended adoption of e-commerce, internet of things, opening public systems to citizens, smart cities, massive use of map-based smartphone apps including transportation, food delivery, social networks, etc.) that widespread the usage and generation of data that is geolocated, that is, it’s linked to a pair of coordinates that put the data in the context of a position in a map.
All this data is very fragmented and comes from very different sources, some public from different institutions and some private from companies in different industries. But, if properly cleaned and combined they can provide a powerful snapshot of different key aspects that directly impact any kind of business, both online and offline. This includes data relevant to brick-and-mortar stores like traffic in a street or peak hours in a store, but also distribution of clients that are affiliated to the brand (for marketing purposes), distribution of e-commerce clients (to improve logistics), impact of city planning (for smart cities), etc.
It’s now clear that the companies that more quickly adapt to get the most out of Location Intelligence (including channeling their data towards a LI system and combining it with external data to get the full picture) will be the ones building better products and gaining efficiency in their operations, hence building successful businesses.
In this talk we will present the evolution of Location Intelligence, and how existing BI and AI, combined with GIS systems, are driving the next wave of intelligence that is going to be a game changer for how companies strategy is planned and decided across all industries. We will also showcase the complexities it currently presents, both regarding building products that allow companies to interact with LI (product features, design, UX, …) and also the technologies that power LI (location data, GIS, databases,… ).