Informed Decisions: Big Data and Positive Change

October 10, 2019

Informed Decisions: Big Data and Positive Change

We live in the age of data. More information is being generated, tracked, quantified and analysed now than ever before. The much talked about statistic at the moment is that data is now even more valuable than oil as a commodity. So the concept of Big Data is one that many businesses and organisations are interested in, as they want to find ways to make use of the information they have access to – whether it is to improve their services, understand their users better, or simply sell more stuff to more people. It’s not one specific technology, however, but rather a description for the overarching field and approach. Whether you use Natural Language Processing or the Internet of Things to gather it, or AI and Machine learning to make sense of it, it simply refers to this quantifiable world we now live in.

In this post I want to drill down and focus on one specific use of Big Data, namely to instigate positive change. When you have access to large volumes of behavioural information, you can shape broader systems to either reinforce desirable behaviours or hinder negative ones. This can be in the form of small nudges – for example your Apple Watch encouraging you to move when you’ve been sedentary for too long – or large structural shifts – like Google’s now-retired project to analyse search trends to track flu outbreaks and provide models to better deal with public health.

Incentivising Input and Quantifying Output

Locally, brands like Discovery have played into this space through offerings like their Vitality programme. By encouraging users to track their health-related activities to get rewards, they’re able to gather data around behaviours like healthy eating, medical check-ups and exercise. This is an example of Big Data that incentivises positive behaviour by gamifying the collection of information. It serves the two aims of getting (a) more data and (b) more relevant data – both of which are vital for better decision-making. The issue in this space, however, is making the gamification engaging enough for people to want to actually participate. Back in 2012, consulting firm Gartner saw this a main issue for what was then a new concept, predicting that 80% of gamification projects would ultimately fail because of poor design (and therefore low uptake). For us as a business, this highlights both the potential benefits and pitfalls of this space. So much comes down to developing systems that are actually relevant enough to people for them to see the value in giving their data to a third party.

There are also larger-scale ways to use data to make systemic decisions that can benefit the broader population. The Bloomberg Data for Good Exchange is one example of this happening at a thought leadership level. The yearly conference brings together data scientists and related experts to solve social issues around a specific theme. Similarly, earlier this year, the Rockefeller Foundation announced a joint, $50-million investment over five years to build the field of data science for social impact. One of the funded organisations, DataKind, applies hard data science to help address social problems across the developing and developed world. One project, for example focussed on identifying corruption in the UK through an analysis of open data around company registration to track ownership back to tax havens or disqualified directors, sanctioned individuals or senior political figures. Another proof of concept used satellite imagery and building typology recognition to identify severely poor villages in Kenya and Uganda to help philanthropic organisations quickly identify potential areas to invest in.

So Where to From Here?

The main reservations around this kind of technology lie around the areas of data security and the motives of those making use of the information. As with any security issues, the robustness of a system helps to address concerns in that space. When it comes to data use, however, the issue becomes more complicated. Big Data can appear to be a daunting subject in the public imagination, mainly around concerns of surveillance and manipulation. The fact however is that this data is being collected, and if it is being used for good, all the better.

At Swipe iX, we see our role in this space to be around the conceptualisation and development of Big Data systems that are inherently for the greater good. A system doesn’t have to be in the NGO or social space to change behaviour positively, and we like to use this as a filter for our work rather than a specific technology to necessarily integrate. Big Data is simply an approach to making use of the kinds of information available to us at the moment, and as a strategic and human-centred organisation, we believe this should always be inherently positive.

Leo Redelinghuys

Managing Director

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