The “Where” Dimension of Business Intelligence

A few months ago, I attended a school board meeting where the principal and teachers of my children’s elementary school, along with parents and others, voiced their concern about the growing enrollment at the crowed school. Simply put, we can’t fit any more students in the building. Several ideas were proposed to alleviate the problem, including redistricting–i.e., sending some incoming students, especially Kindergartners with no siblings at the school, to nearby schools.

As you might imagine, this idea was met with much debate and uncertainty. Among the questions: Where would the redistricting lines be drawn? One of the teachers, however, came prepared and did something clever that helped to focus the discussion. She mapped the addresses of all the incoming Kindergartners on Google Maps, along with all of the elementary schools in the city. Now everyone in the room could easily see the clusters of kids who live near the district borders and close to other schools.

This simple exercise gave credence to the adage “A picture is worth a thousand words,” and although the crowding issue wasn’t resolved that night, I believe the teacher’s “pushpins on a map” presentation set the course for future discussions that ultimately led to redistricting.

I was reminded of this experience yesterday when I read SAP’s announcement that it is collaborating with Google “to enhance its business analytics software with location-based data capabilities, allowing people to interact with real-time information via Google Maps™.” In the press release, SAP highlights some hypothetical examples of how customers could use the integrated solution:

  • A telecom operator could use Google Earth and SAP BusinessObjects Explorer™ software to perform dropped-call analysis and pinpoint the geo-coordinates of faulty towers.


  • A state department of revenue could overlay household tax information on a map of the state and group it at the county level to track the highest and lowest tax bases.


  • A mortgage bank could perform risk assessment of its mortgage portfolio by overlaying foreclosure and default data with the location of loans on Google Maps.


  • With SAP StreamWork, a team of customer support representatives in a consumer packaged goods company could collaborate and pinpoint the location of consumer complaints within specific geographies and make a decision regarding how to address and prioritize resolution.


  • A theme park operator could use the Google Maps API Premier and get real-time traffic information on attractions with SAP® BusinessObjects™ solutions to send rerouting messages to customers in order to improve satisfaction rates.


  • U.S. census data could be overlaid on a Google map of the country, grouped by state and drilled down on at the county level.

The “Where” dimension of business intelligence facilitates the mash-up of different information, which can open the door to new, perhaps non-intuitive, insights. What happens, for example, when you map sales of a particular product and overlay it with property values, median age, ethnic backgrounds, average income, average temperature and precipitation, crime rates, location of competitors, location of train stations and bus stops, and whatever else you can display on a map? The answers might surprise you.

Sure, companies have been doing this type of “data mining” for years, but like my school example, using a tool like Google Maps to place the data in a visual, geographical context is certainly a more powerful and easier-to-see approach than looking at dots and lines on a correlation chart.

For the past few years, we’ve been highlighting how mobile solutions and location-based technologies are driving innovation in supply chain and logistics processes (see “Apple, Google, and IBM: Different Takes on Location Tracking,” which includes a listing of other postings too). And I’ve also commented on how mobile and social media are driving supply chain innovation. So, I think it’s time I update my formula to bring all of these factors together:

Mobile + Social Media + Business Intelligence + Location Data = Supply Chain Innovation

Of course, poor data quality—my “soap box” issue for more than a decade—remains the Achilles’ Heel of supply chain management (see “A Decade of Insights (My 1-Page Logistics Book)”). Simply stated, without timely, accurate, and complete information, the equation above will yield the same answer as always: garbage in, garbage out.

So, before you dive into the sexiness of these new technologies, you first have to tackle the very un-sexy issue you’ve been ignoring for years: fixing your data quality problem. Otherwise, you’ll just be wasting your time and money, or at best, underutilizing the full potential of these solutions.

(Note: SAP is an ARC client)