Giles Hindle, Hull University Business School
Richard Vidgen, Hull University Business School
Andy Hamflett, AAM Associates
Gavin Betts, Hull University Business School
This report documents Phase One of applied research into the innovation of food bank operations in the UK. The research is a pilot study of the NEMODE Network+ Research Call 2014. The aim of the project is to investigate the use of technology in changing food bank operations in the UK.
The context of the work is food poverty in the UK. In February 2014 the All Party Parliamentary Group on Hunger and Food Poverty commissioned a Parliamentary Inquiry into hunger and food poverty in Britain, chaired by the Bishop of Truro, Tim Thornton, and Frank Field MP. The resulting report – Feeding Britain – was launched in December 2014, based on evidence from more than 400 people across the UK (food poverty, 2014). The report estimated there are 3.5m adults who cannot afford to eat properly in the UK, 500,000 children live in families that can’t afford to feed them, and food prices have risen 47% in last ten years.
The largest food bank network in the UK is the social franchise organised by The Trussell Trust (Defra 2006, 2013). The Trussell Trust is a charity with the mission of empowering local communities to combat poverty and exclusion, and operates across the UK. Data from the Trust shows a 40-fold increase in provision of emergency food aid between 2007-08 and 2014-15. 1,084,604 people were given three days’ emergency food and support in 2014-15, though these were not all unique users (http://www.trusselltrust.org/stats#our-stats-explained). In parallel with this surge in demand the number of food banks rose from 80 in January 2011 to 445 in September 2015.
The existing or potential uses of technology in food bank networks in the UK are under-explored. In the Feeding Britain report, aside from referencing the importance of low-income households owning a mobile phone and having access to the Internet, the uses of technology were not mentioned.
This report presents findings from applied research into the use of technology in radically changing food bank operations in the UK. It is the result of an action research project employing Soft Systems Methodology (Checkland and Poulter 2006) and business model mapping (Osterwalder and Pigneur 2010).
The project was delivered with the full involvement of the Trussell Trust and followed a process of technology innovation developed by Dr Giles Hindle and Professor Richard Vidgen at the University of Hull (Hindle and Vidgen 2015, Hindle and Franco 2007, 2009, Hindle and Carreras 2009, Hindle and Dickenson 2008, Hindle 2011):
1. The current business model(s) underpinning food bank operations were examined. This focused on both individual food bank operations, and the wider Trussell Trust food bank network. Site visits and interviews were conducted – with individual food bank staff and Trussell Trust central management representatives – to develop baseline operational models.
2. Emerging technologies, cases, and relevant literature were reviewed to understand how food banks (and best practice from other industries) have used (and could use) technology to inform the process of business model and technology innovation.
3. Stakeholder workshops were delivered to develop design models of food bank operations.
4. An opportunity for technology innovation in food bank networks was identified based around the application of Data Science and analytics. A Phase Two report will document the outcomes of this work, which is ongoing.
This report is structured as follows. In section 2 we outline the research methodology; in particular the innovation framework employed and schedule of stakeholder engagement activities. In section 3 the outputs of our “business model innovation framework”, as applied to food banks and the Trussell Trust network, is presented. Section 4 details the technology leverage analysis, which explains how opportunities for technology innovation in food bank networks were identified. In section 5 the implications of the research are discussed with emphasis on the opportunity for investigating open data analytics in Phase Two of the project. The Phase One research is summarized in section six and recommendations for next steps are presented.