Big data and the war on hunger in the UK

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The fight against food poverty in the UK is a struggle set for the long haul, if the latest figures released by the Trussell Trust, the country’s leading food bank, are anything to go by. The numbers paint a bleak picture. More and more people are using food bank services in the UK, with Trussell Trust figures alone showing a 2% increase in 2015-16 over the previous year. Ever since the early 2000s, the number of food banks has also seen a steady increase with a dramatic explosion in numbers post-2008 recession, with estimates pegging their number in the UK close to a 1000.

Food poverty is a complicated issue with multiple causes and factors involved. These could range from benefit delays, to debt, low income and unexpected payments and high living costs; all largely exacerbated by the general recessionary climate and austerity measures. According to Trussell Trust chief executive David McAuley, solutions to root out the actual causes underlying the need for food banks can only come up through a joint initiative involving all the stakeholders: policy makers, government agencies, voluntary organizations, businesses and the general public.

Recent initiatives by the Trust, in partnership with Hull University Business School and AAM Associates, a social innovation agency, have been looking at the potential of new technologies in the fight against hunger. Of the 56 technologies identified and investigated, big data analysis has shown the potential to be a game-changer.

The Trussell Trust is not the pioneers in this regard. Various charitable organizations and civic bodies across the world and in the UK have forayed into big data analysis to help make a difference. These include Friends of the Earth, England, Wales and Northern Ireland; SolarAid; Parkinson’s UK; New Orleans Fire department; Citizens Advice; Macmillan Cancer Support; and The South Carolina Campaign to Prevent Teen Pregnancy, among others.

For their data analysis, the Trust uses data regarding its food bank locations, combined with the data collected from food bank users, including their names, ages, addresses and reasons for seeking help. The results of the data analysis have enabled them to create a geographical distribution of demand for banks. Through the creation of such “heat maps”, the trust can easily identify variations in the regional patterns of demand for food banks across the UK.

Using their own data in conjunction with various census data has also enabled the trust to create forecasts of potential increase in future demand for food in specific regions. Though far from perfect, these breakthroughs highlight the potential that big data analytics hold for charities and other organizations operating on the frontlines of such crises.

But since big data analytics does not come cheap, charities will have to seek frontline associations with interested data scientists and pro bono initiatives from big businesses and organizations like the Operational Research Society, to continue this success story into the future.