Context Brokering

Context Brokering supports the development of strategic insights.

It is a machine-learning based research and analysis process specifically designed to help identify and effectively use data in order to more comprehensively understand the context of, or around, a particular issue or theme.

As an approach in futures work, this capability is crucial to establishing the current characteristics of the wider environment of interest and context brokering offers a number of key advantages, including:

• It allows us to more fully interact with, and understand, highly complex systems
  
• It can better reveal the working assumptions and biases that human analysis may miss or not consider exploring
• It has the ability to handle large volumes of data, especially important given the increasing range, scale and multiple sources of data becoming available
  
• It helps us to better identify issues of data ‘timeliness’ and ‘relevance’
• It provides versatility in structuring data, so allowing improved research gathering and network understanding
• It offers better methods for visualising data, so promoting ease-of-use and facilitating engagement

Context brokering can be used to both enhance the capabilities of our horizon scanning service (providing increased depth and breadth to the range of information already collected), or as the basis for standalone futures analysis projects directed towards exploring a particular evolving domain, a new research question or a set of pre-existing scenarios.