In the past few weeks since attending a fabulous workshop in Zurich hosted by the Gottlieb Duttweiler Institute I have been even more attuned to the emerging corporate practices in which social data is informing decision making processes. A few examples:
- A retailer checking to see if your email address is active on a range of social networks as a way of deciding whether or not to clear your online order
- A credit card company that has realized that customers who have extensive and long standing LinkedIn profiles are significantly less likely to default on their credit cards
- An insurance company that is making decisions about which insurance claims to further investigate based on the social graph of the claimant
- An enterprise IT equipment company that has modified its sales lead scoring algorithm to include a variety of factors from activity in social networks and social media
- An appliance manufacturing company that has reduced the delay in knowing that they have a product defect issue by two months by monitoring online conversation rather than waiting for data from their field repair organization
The list goes on. Companies of all kinds, in every industry and region, are discovering that there is an enormous pool of information -- call it social data -- that is being created at an every increasing pace from which they can learn more, and make better decisions more quickly.
This trend will only accelerate with advanced mobile technologies. Every individual now has the capability of being a "sensor" in their physical environment, recording and transmitting physical data (location, speed, etc) but also behavioral and emotional data. When people walk into a particular store, say Starbucks, are they happier than before they walked in? How does that one store's data compare to other stores in the area?
AMBIENT INFORMATION MEETS BUSINESS INTELLIGENCE
For the past ten years we have been building out a network of sensors in roadways that can transmit data about the speed of passing vehicles and allow us to aggregate that data into a visualization (typically a map) to help us decide which roads we should choose to get from point A to point B. This is an example of data-driven decision making with which we have all become familiar.
Now every person is a "sensor" and is using their computer or mobile phone to transmit information into public (and private) databases. Businesses must learn how to build the analytical models and visualization tools to give their employees the equivalent of a map in order to comprehend this information and use it to make better decisions.
The companies that utilize these tools effectively in their industries will have an enormous strategic advantage over their competitors. The time to join the tidal wave or revolution is now.