Location analytics is much discussed in GIS circles. We felt taking the gobbledygook out of location analytics was long overdue. Many organizations new to GIS are still grasping at the basic GIS concepts, throw the language of location analytics into the mix and you end up with ??????
What is business analytics?
Analytic systems turn an organization’s data into actionable information by discovering and illustrating patterns, trends, and relationships in business data
The typical output from current business analytic systems is in the form of statistical reports. These usually summarize data in tabular form, often including graphs and charts. Analytics are often implemented as independent business intelligence (BI) systems but can also be part of larger enterprise systems, like customer relationship (CRM), enterprise resource (ERP), and resource management systems (RMS).
But traditional business analytics systems do a poor job of answering the where question:
Where are our assets, where are our customers, where are our sales?
Where is at the heart of GIS. Visualizing data through maps, and spatial analysis.
Spatial analysis …. we are in danger of straying into gobbledegook territory. Keep reading!
The Power of GIS
Let’s start with maps. We all know maps. Amazingly useful pictures, filled with information. From a business perspective maps are more intuitive than charts and graphs. Patterns and relationships are easier to discern. Think of a satellite base map overlayed with points showing your retail outlets in a particular city, with a heat map of shopper activity. Or weather data, or demographics.
Data filled pictures (maps) are one huge advantage GIS brings. But how about digging beneath these maps. Spatial analysis provides the muscle to analyse the raw data in a GIS based on where. Complex questions can be answered using GIS. These include:
– Where are the pipelines valves located which need inspecting this month?
– Find all homes in a particular city which are located in a primary earthquake zone?
– Show me a heat map of drive time data.
– What are the primary demographics served by each of our clinics in Texas?
This is spatial analytics. Ask complex questions which relate to location (where) and have these questions answered and displayed on a map. Brilliant!
We can define location analytics as:
Mapping and spatial analysis for the world of business analytics
Business adoption of GIS – the Challenges
There is a realisation in the GIS industry of the potential use of GIS for location analytics. At the same time organizations are also realising the potential importance of maps and location analytics within their analytics mix. But there remains a disconnect. Why?
1. The challenge of GIS to BI integration.
2. GIS is confusing.
3. Current GIS solutions are often beyond the technical knowledge of business analytics users.
GIS companies have only just begun to truly find ways to integrate GIS to BI. This has been an area of focus at our company. We have started using GIS connectors to combine BI and GIS data. One successful approach has been to pull location data from platforms like SAP, store it locally on a mobile device, then combine it with ArcGIS by overlaying the data on a map, and allowing analysis and editing. This approach has some very exciting possibilities.
GIS is confusing. If you have not seen Vladimir Agafonkin talk at FOSS4G entitled ‘How Simplicity Will Save GIS’, stop reading for a moment and go watch the video!
The technology is confusing and complex. And the GIS community do a poor job of translating. I’ve sat and listened to IT folk in organizations try to converse with GIS folk. Truly two language conversations. The onus is on the GIS community to change their vernacular.
Business analytics users do not understand GIS, and the current batch of available location analytic solutions. Education is particularly important here. GIS is new to these users, they need to learn how answers to the where question provides new levels of insight. The GIS community also need provide a wider array of tools.
Common Approaches to Location Analytics Today
Let’s walk quickly through some of the location analytics tools currently available.
WebMapSolutions Business Integration Framework for ArcGIS
As part of our ongoing process to simplify the integration of ArcGIS with existing BIT systems, we have built the Business Integration Framework for ArcGIS. This framework provides a set of libraries and applications which combine data and functionality from multiple platforms providing answers to location based questions.
Business Analyst Online (BAO)
Business Analyst Online (BAO) is a market analysis tool from Esri. It provides the ability to generate maps and professional reports in minutes. Get deeper insights about businesses, people and their lifestyles for specific locations.
Esri’s geoenrichment service provides demographic and lifestyle data that describe income, consumer behavior, market potential, and more. Both WebMapSolutions business analysis app and Esri Insights provide dynamic data from the geoenrichment service
Through the ‘Maps for’ products Esri have introduced ArcGIS integration with some of the leading business analytics products, such as Cognos, MicroStrategy, SharePoint, and others.
ArcGIS is used to share, visualize, and analyze all sorts of organization data using geography as a common framework. This system can also dynamically integrate (mash up) all sorts of data, including data that has been mapped using location analytics. When integrated with the growing volume of geospatially referenced data available on the web, whole new insights begin to emerge.
Tapestry helps you understand your customers’ lifestyle choices, what they buy, and how they spend their free time. Tapestry classifies US residential neighborhoods into 67 unique segments based on demographic and socioeconomic characteristics. In the ArcGIS platform tapestry segmentation is available in four ways: web maps, reports, infographics, and data enrichment
Let’s provide a quick definition here:
Predictive analytics is the practice of extracting information from existing data sets in order to determine patterns and predict future outcomes and trends. Predictive analytics does not tell you what will happen in the future. It forecasts what might happen in the future with an acceptable level of reliability, and includes what-if scenarios and risk assessment.
Predictive analytics is an enabler of big data (a massive volume of both structured and unstructured data). Predictive analytics enable organizations to use big data (both stored and real-time) to move from a historical view to a forward-looking perspective of the customer. Predictive location analytics takes the same approach but leverages GIS.
Location analytics will see dramatic growth over the next few years. It offers some very exciting possibilities. But, plenty of work still needs to be done on the GIS side of the house, to provide integrated solutions, help educate business users and provide new, simple analytics tools.