Legese, Zeryihun, Donnelly, Sean, Kottasz, Rita and Bennett, Roger (2024) Data fragmentation in fundraising nonprofits : problems and possible solutions. In: ISTR 16th International Conference : Crisis After Crisis After … : What About the Third Sector?; 16-19 Jul 2024, Antwerp, Belgium. (Unpublished)

Abstract

Although data fragmentation has been recognised as a significant problem among commercial businesses (see Smith and Brown, 2020; Sharma and Tayal, 2021), little is known about the effects of data fragmentation within fundraising nonprofit organisations. Data fragmentation involves disjointed data scattered across different systems, platforms, and/or databases within an organisation, making integration and analysis difficult (Smith, 2020). It leads to duplication, inaccuracies, inability to understand donor behaviour, and wasteful spending on marketing initiatives (Scott, 2019). The present research sought to identify the views on the causes and consequences of, and possible solutions for, data fragmentation of fifteen key professionals from diverse UK charities who were actively engaged in data collection, fundraising, donor engagement, and marketing activities. The research was undertaken as the first step in developing software solutions designed to generate accessible and actionable data to optimise fundraising efforts, to provide personalised donor support, and to help a nonprofit to allocate resources efficiently. The interviewees (who were selected purposively) described problems arising from legacy systems unable to integrate with modern data technologies (cf. McNulty, 2020), siloed departments maintaining separate databases hence perpetuating data duplication (cf. Alam, 2018), systems upgrades and technology changes (cf. Santos and Varajao, 2019). Certain overarching themes were identified, including resource-intensive data management, supporter journey complexity, and budget considerations. Data cleaning and updating consistently emerged as a top priority, unsurprisingly as clean and current data is the bedrock upon which effective decision-making stands. The solution proposed was to abandon manual handling of supporter data (which diverts valuable human resources from productive fundraising activities) in favour of automation. By adopting automated data handling solutions charities can free up staff to focus on strategic fundraising initiatives. As regards budgetary considerations, the interviewees advocated measuring the value of data automation solutions in terms of long-run return on investment rather than mere cost savings (which is often the metric employed). A consensus emerged regarding the need for data visualization and data warehousing systems within charitable organisations, which were necessary to provide a unified and comprehensive view of supporter data. This perspective aligns with relevant literature emphasising the power of data visualisation in simplifying complex data for decision-makers (Chen, Preston and Xia, 2017) and the role of data warehouses in centralising and integrating data from diverse sources (Kimball and Ross, 2013). These insights will inform the development of a new software product tailored to address charities' data fragmentation challenges. The software is being designed to automate data collection and cleaning, to simplify data collection processes, and to provide a centralised and holistic data overview platform. An integrated donation reconciliation system will automate the matching of donations received across platforms with all other donor information. The aim is to seamlessly combine customer relationship management, marketing, and operations and to facilitate access to complete and consolidated data (Fricker, 2018). Integrating data from disparate sources into a unified and consistent format ensures that decision-makers are equipped with up-to-date, reliable information, guarding against erroneous conclusions from outdated or inaccurate information. References Alam, M. M. (2018) data integration challenges in UK charitable organisations. Journal of Information Systems and Digital Technologies, 1(2), 54-66. Chen, D., Preston, D. S. and Xia, W. (2017) Data quality and data governance: A framework for information systems research. Information Systems Research, 28(2), 320-335. Fricker, A. (2018) Data fragmentation in UK charities: Risks and benefits. Charities Security Forum. Accessed at: https://www.charitiessecurityforum.org.uk/wp-content/uploads/2018/12/CSF-BriefingData-Fragmentation.pdf [Accessed on 15 June 2023.] Kimball, R. and Ross, M. (2013) The data warehouse toolkit: The complete guide to dimensional modelling (3rd ed.). John Wiley & Sons Inc., Indianapolis. McNulty, T. (2020) Legacy systems and the nonprofit sector: The case for modernisation. Nonprofit Quarterly. Accessed at: https://nonprofitquarterly.org/legacy-systems-and-the-nonprofit-sector-thecase-for-modernization/[Accessed on 18 June 2023.] Santos, M. Y. and Varajão, J. (2019) Assessing the impact of IT infrastructure changes on data fragmentation and business performance. Computers in Industry, 109, 1-13. Scott, C. (2019) The challenges of data fragmentation in charity marketing. Charity Digital News. Accessed at: https://charitydigital.org.uk/topics/topics/the-challenges-of-data-fragmentation-incharity-marketing [Accessed on 12 June 2023.] Sharma, R. and Tayal, D. K. (2021) Data integration techniques and their role in enterprise data integration. International Journal of Computer Applications, 181(39), 1-5. Smith, P. R. (2020) Marketing communications: An integrated approach (8th ed.). Routledge. Smith, E. and Brown, K. (2020) Impact of data fragmentation on financial analysis. Journal of Finance and Accounting, 24(3), 45-59.

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