We received a great deal of feedback and questions about our blog around the fusion of BI and GIS and how they complement each other. Even the terminology is blending where the term Location Intelligence (LI) and Location Analytics (LA) is bantered about more and more. So I wanted to add some clarity around the fusion of BI and GIS by providing additional examples and also help paint a picture of how you could extend your analysis capabilities.
First let us look at the potential around both visualization and insight these two applications produce. The often-oversimplified initial thought is “ok, so these are dots on a map…so what?” What is missed is the understanding of spatial relationships – and that’s where it gets interesting. When BI and GIS combine, you can easily answer questions like:
- How many customers are in a 5-minute drive time?
- What facilities/employees/customers are in this storm path?
- What is the cannibalization rate of opening a new branch/ATM/store within a certain distance?
- What kind of reach or impact of my marketing campaign am I seeing?
- How does location correlate to a medical procedure or condition?
These applications, with all the new data from smart phones and other mobile devices, are just scratching the surface of future capabilities. For demonstration purposes, I am going to detail a couple of fictional scenarios to show how the GIS and BI fusion would typically work in the real world.
Using the fusion of BI and GIS in logistics operations
Pam has a motto to always have a plan and be prepared – and she lives by her motto at work as well. As Vice President of Operational Risk for a large logistic company, her job is to identify risks and assess exposures with impact to Operations, facilities, technology and deliveries. She used to have an operational dashboard that displayed servers, call centers and her network of trucks and planes. The typical BI dashboard allowed her to see gages and dials with certain KPIs (Key Performance Indicators). While in a lot of ways this has worked for her, she’s finding it more useful having the same metics in a map-centric format. Her new GIS enhanced dashboard allows her to overlay a future storm’s path and have a three-day warning that enables her to move key assets, reroute shipments and shift call center operations. Her facilities are also mapped and she can zoom in and monitor deliveries and fleet metrics while drilling into the level of detail she’s interested in right from the map.
The benefit to Pam is that she has the tools needed to make sure everyone is prepared and can respond quickly and effeciently to things and events that could impact deliveries, all while saving the company millions over time.
BI and GIS in fraud management
As of today BI and GIS are being used to visualize and predict crime patterns so law enforcement can better understand where to position their personnel. BI can display historic crime statistics, show trends, and GIS can target the hot spots. When you combine all of these things together, you have the information needed to help prevent crime, especially credit card fraud.
Matthew works for a credit card company as a Director of Fraud Management. He has a theory that when you shop or dine out with your credit card, it is likely that you will have your mobile device with you. Matthew can use the powerful combination of GIS and BI to measure the distance between the customer’s mobile device and the transaction. If the two are not in close proximity to each other that means something could potentially be wrong. Matthew’s company can validate identification of the customer by calling them and asking questions that can only be answered by someone familiar with the cardholder’s community and surrounding area. Some of the questions they might ask: What is the name of the nearest mall or school? What is the name of the park at the end of your block? Name of the closest hospital and which highway do you take to get there. So basically what you have is validation identification, that’s using location information from both the transaction and the location of the mobile device, that was alerted through BI reporting.
GIS and BI pinpointing low birth rates in Shreveport
While the above scenarios are simply demonstrations of how BI and GIS can combine to create insight that improves business, the following real life example illustrates improved insight for better decision-making. Ryan Bilbo with the Louisiana Department of Health is using this technology in actual real-world scenarios. Ryan was trying to identify areas of low birth rates in Shreveport, Louisiana using different types of analysis. Trends were not immediately visual. Typical BI cannot display the lower level of granularity needed to visualize hot spots, though it can aggregate and display information on the state or county level.
Ryan investigated his data by performing a cluster analysis using spatial relationships to compare birth rates of their neighboring data points. The trends became crystal clear on the map. In talking with Ryan, he further explained that using the relationships helped to further identify areas for intervention. If he did not use this technique and granularity, one area would have been divided between two census blocks and the results distorted. This type of insight would have not been possible with traditional BI. You can watch his two-minute demonstration here:
There are many more real-world cases of the BI and GIS fusion out there. Still, this is still considered a fairly new concept at least in some industries. You are going to find more people asking questions about it than using it right now. But that is part of why it is a bit exciting. It is incredibly powerful, holds so much potential, and it is just now getting started. There is no doubt that both BI and GIS are great tools for analysis. When you harness the power of these two together you can start to tame the biggest big data and provide much better insight for better decisions.
*feature images courtesy of Esri.Com