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Big data


Context brokering - how do you apply it?

To better understand what context brokering is and how it can be applied in decision making, it’s worth considering the following hypothetical example:

A CEO of a large UK multinational organisation specialising in mobile phones has asked the business development manager what the international strategy for engagement in Africa is.  This happens in a board room and, as often happens, the BD manager knows nothing about Africa because he’s worrying about Brexit and Donald Trump, like everyone else.  The CEO isn’t happy about this, so she asks the BD manager to prepare a full briefing on the strategic options for improving their role and relationship in African Markets.  After this, the BD manager goes away and runs through a few options.

Option 1: Expert Literature Review

There is the ‘tried and tested’ option; commission an expert on Africa to produce a paper that tells them a range of strategic issues.  Once the paper has been delivered (probably at considerable expense that directly relates to the urgency) someone in the BD Managers team will condense them into a powerpoint presentation, perhaps with a detailed report of research that they can reference if challenged.  Is this good, is this bad?  Well, it’s good as it does give you answers that can be put back to the board (arguable in a linear, bulleted powerpoint format).  This traditional approach also suffers from limitations as it depends on the scale and the process through which the data has been assessed (often the biggest value has been given to the analyst who compiled the report and learned the associated knowledge in its production).  Such reports can easily be biased and often based on a small range of reports that are limited to the number that the analyst can comfortably process in the time available to them.  Also, if its based on a small number of people and papers, the assessment is at greater risk of being biased toward particular issues or outcomes.  

Option 2: Produce a context map  

An alternative option to commissioning a single expert is to produce a context map.  At present,  this does represent a significant cultural change to how many organisations currently conduct their strategic planning.  Context brokering works on the principle that the best thing to do early in your planning, is to define and gather as much data as possible and then summarise what you believe the insights and themes around an issue could be with some kind of qualifier for how valid you think the data could be (relating back to the source data to illustrate where the insights came from).

So going back to the considering the future of Africa, using data visualisation and mapping tools a context map (or topic model) can be produced.  Such a map summarises the data behind an issue and provides a start point for strategy making.  This produces a map that is a lot more engaging and derived from a wider range of sources (there is theoretically no upper limit to the number of reports that can be analysed and mapped, although at present our own experiments at Simplexity Analysis are around 1000 documents). Such outputs are less static than bulleted lists and can be used in facilitated sessions with experts who can then interact with the context and add their own insights as required to further enrich our understanding of the context. Have a look at the one below produced to provide a context for future strategic issues surrounding Africa.


Mapping the data around an issue in this way can be daunting.  What was the domain of traditional research and literature reviews is now increasingly contested with data scientists and analysts talking in numbers and code and arguing in shades of technical purity around who’s process for mapping is more accurate (is it a complete reflection what’s in the data) or quantifiable accuracy (if you take qualitative data, is it worse than hard number predictions)? Perhaps this is why its challenging for decision makers to interact with such new techniques as context brokering does represents a cultural change - the best way of addressing this, is probably to be open and honest in the data used to make the assessment, the assumptions behind it and the limitations in the development of the context.  In the past, that’s what the weight of a large volume of research would convey.  Now, it’s probably the scale of the data that has been analysed.

Which option works best?

Concluding again with the Africa example, what’s better - a bulleted powerpoint presentation of ideas, referenced with a weighty research tome (that, lets face it, few people are going to read).  Or a map, summarising a range of options that can be discussed and assessed by the board, or through associated activities that equate to action for the board to sanction and the associated data available for analysts to reference further as required?

For more information detailing differences of approach for mapping and analysis, please see the following presentation that outlines the differences between conventional analysis and data driven approaches.