The Doppler Quarterly Winter 2017 | Page 55

The Halo Effect
Order 4th 3rd 2nd 1st
Purpose
Single use case for data access and analysis implemented by the IoT provider
Multiple IoT provider use cases , derivative values from 4th order
Use cases beyond just the IoT provider
Community created use cases and analytical models of the data
Ecosystem of Data Availability
Within IoT provider
Within IoT provider and limited partners
IoT provider is integrated with ecosystem partners for shared data access and integration
Everyone is able to consume & integrate the data
Figure 2 : Fresnel Lens Order Applied to IoT
4th Order – Tracking and analyzing feature usage and failures . Enables the provider better visibility into client satisfaction and proactive efforts to increase adoption .
3rd Order – Evaluating channel watching patterns to better engage with clients purchasing marketing and providers of content .
2nd Order – Selling or exchanging usage data with external parties that aggregate the information with other marketing mediums .
1st Order - Allowing availability and exchange of data in public markets , enabling the free flow of data , access and integration between unrelated parties . This use case will produce large quantities of information about consumer behaviors that can be made available to product companies looking to better tune their products and features for a changing market .
Agriculture Technology – Field & Farm Operations Data
As the agriculture market expands to meet the needs of the world ’ s growing population , connectivity and data are key to enabling growers and providers to make better decisions and increase crop yield .
4th – Enabling farmers to simulate their fields with real world satellite imagery and weather data , paired with specific cultural practices .
3rd – Enabling a single farmer to access his or her own data and compare that data to nearby farmers and fields .
2nd – The ability for growers , retailers and suppliers to seamlessly communicate by accessing data sets that span the organization and modeling crop yields based on this integrated information .
1st – Enabling commodities and stock markets access to data , so real-time changes can be seen in buying patterns , mid-season applications and anticipated yields .
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