Amongst the challenges that many find within mobile, the idea of making sense of the amount of data that comes in is one that gets many people. Usually because we end up trying to answer the questions around return on investment (ROI). Yes/ there’s that challenge of identifying the data that we use, but what about after we get that data? What can we expose our understand better in order to change our approach or perceptions to what makes for effective ministry practices?

The MIT Technology Review recently published a piece looking at how data from mobiles changed bus routes. Here’s a snippet:

…Mobility data is created when someone uses a phone for a call or text message. That action is registered on a cell-phone tower and serves as a report on the user’s general location somewhere within the tower’s radius. The person’s movement is then ascertained as the call is transferred to a new tower or when a new call is made that connects to a different tower.

While the data is rough—and of course not everyone on a bus has a phone or is using it—routes can be gleaned by noting the sequence of connections. And IBM and other groups have found that these mobile phone “traces” are accurate enough to serve as a guide to larger population movements for applications such as epidemiology and transportation (see “Big Data from Cheap Phones.”)

Cell-phone data promises to be a boon for many industries. Other research groups are using similar data sets to develop credit histories based on a person’s movements and phone-based transactions, to detect emerging ethnic conflicts, and to predict where people will go after a natural disaster to better serve them when one strikes…

Read the rest of African Bus Routes Redrawn With Cell Phone Data at MIT Technology Review

The MIT Tech Review has also pointed to a slew of other mobile research data that will presented at an upcoming conference.

Knowing some of the folks who read here, this kind of data mining or analysis sounds probably too specialized, or at the least too intensive to be useful quickly. But I want to wager that is something that can be done on smaller, more informal scales by starting with observation.

For example, back with the Kiosk Evangelism Project, one of the initial theories on implementation were that people would be willing and able to put their mobile or memory card from their mobile into a machine and get content. I had my partner in the project go to the mall and observe how people were sharing content, and then go into various phone does and look at how the devices that sell the most were not used towards that manner. We had to look at distribution differently in light of that data, then come up with methods of access and discovery that worked for that kind of target audience.

Yes, you can go a lot further, as the MIT Tech Review piece shows. But, you have to be willing to look at the data differently, and be willing even to let the use of mobile disk to you, rather than making it say what you want it to.