How 'Guerrilla Data' Is Disrupting Big Data

That was fast. No sooner did big data change the way knowledge is used to make strategic decisions faster, the cost went up.

Not for long in this tech-and-data enabled world. Cheaper alternatives to the collection and interpretation are emerging. The question is whether quality is being sublimated in the process. But then that's what the legacy defenders of the status quo always say, isn't it? Even if they, themselves, are only a year or two old. JL


Bernard Marr comments in Forbes:

For data to be “guerrilla” is to employ faster, cheaper and often less formal alternatives for data collection. These alternatives might be less costly, less formal, or on a smaller scale. Much like the warfare of the same name, guerrilla data is unconventional but effective. It allows the organization to collect meaningful data at a very low cost and/or from unconventional sources.
In many areas businesses are fighting to be the first to collect data and turn that data into value using new apps and algorithms. There is often a first mover advantage where the companies with the best data can develop new insights faster than their competitors and develop and refine their analytics tools quicker. This in turn helps them to turn their data into a valuable asset.
One agricultural data company, Springg, has come up with a way of collecting and analyzing data on the fly — guerrilla data, if you will.
For data to be “guerrilla” is to employ faster, cheaper and often less formal alternatives for data collection. These alternatives might be less costly, less formal, or on a smaller scale. Much like the warfare of the same name, guerrilla data is unconventional but effective. It allows the organization to collect meaningful data at a very low cost and/or from unconventional sources.
The company recognized that farmers in developing nations could benefit from the same data farmers in developed nation have access to, for example, soil quality.  But in rural and underdeveloped areas, the practice of taking a soil sample and then sending it off to a lab for analysis can take weeks, which can dramatically and negatively impact the farmer’s current season of crops.
So Springg developed mobile test centers with Internet of Things (IoT) devices that could test the soil remotely, give results almost immediately, and then send the data back to a central repository for further analysis in conjunction with all the other soil samples. It’s a benefit for the farmers, but it’s also a benefit for Springg who will have data on soil conditions in places no other data has ever been aggregated, which could be interesting to the commodities markets and other businesses.
Finding guerrilla ways of collecting and analyzing data will help companies get this valuable first mover advantage. This is not only true in the area of farming but more or less any area of data and analytics. Weather companies are constantly fighting for the latest ways of collecting data — and the weather channel was acquired by IBM for a lot of money because it had so much data and analysis capabilities. Fitness tracker apps are racing to be the first to collect activity and sleep data and develop algorithms to turn it into value.
Finding innovative ways of speeding up the data collection and analysis can be powerful – be it through apps (fitness data), through crowd-sourced data collection (customer reviews), or IoT devices (Google’s Nest thermostats, home weather stations, etc.). Researchers are just scratching the surface of this sort of data collection by using smartphones and wearables to gather data for medical and clinical research.
This sort of guerilla data collection in the field requires a sophisticated network of devices and technologies to collect, analyze and store the data.  It might include wireless networks, smartphones, IoT sensors, and flexible communications protocols, data preparation, and data transportation.
But companies with the foresight and creativity to build the infrastructure (physical and technical) required to collect, analyze and use this data will be rewarded with all the rights and benefits that come with collecting and “discovering” it.