Technology adoption is always a challenge, especially for enterprise organizations. Disrupting a workplace with new technology, particularly when it involves solutions that are frequently used by employees, can leave people feeling confused, or with a lack of direction. The pressure for success with any new technology solution is huge, and AI adoption has some unique challenges. Fundmetric tackles these challenges such as a lack of data, fears of overhauling legacy systems, integration nightmares, and finding a use case, but the greatest challenge of all adoption burdens is organizational silos. The good news is that a graduated approach with Fundmetric can ease this burden. While many software platforms view adoption as a linear process in which you either pass or fail at each stage, Fundmetric has realized that the nature of data science which underlies AI does not follow a linear path. So a set of exact instructions isn’t always applicable, but establishing buy-in with a graduated approach has led to the most successful outcomes. The approach will depend on what your organization’s needs are and what you are looking to improve upon. A helpful way to think about this is looking at what your current state is now, what your future state looks like, and from there you can see what you would like to improve and we can assess how Fundmetric can help with those improvements.
When we partner with different organizations, they usually come to us with a specific understanding of what AI is or how exactly they want to apply it. Sometimes these are broad scopes of work and sometimes they are very narrow, but usually there are elements of the platform that organizations perceive as being outside of what they would imagine using Fundmetric for. This could be because of duplication of platforms, or organizational operations and behaviour. Fundmetric works with our clients to find a starting place where they are comfortable. Sometimes a group will start using the predicted list segmenting for a specific campaign, a project focused on using the Fundmetric platform to generate data, or working with prospect research and major gift officers to add predicted major gift donors to their portfolios. The learnings and successes of working through an initial project informs the next phase of adoption. This early traction inspires people to use the platform for something new, often this will involve another department.
Breaking down silos
AI often gets applied within silos and even though teams may use the same technology, they end up doing so in isolation. Unfortunately that can lead to the building out of different infrastructures and adoption of different workflows, which only complicates broader AI adoption. Starting with a small project that attracts cross-departmental collaboration means that people get to experience for themselves the impact that their work has on the entire organization. As people get to experience the early successes and see the potential for success in other areas, adoption starts to shift from adoption based on individual interests, to holistic adoption based on the organization’s interests. Different tools and disconnected information prevent teams from working cross-functionally. Fundmetric AI weaves a common thread of data that allows teams to coordinate their efforts and predict outcomes, increasing the collective awareness that everyone is all trying to accomplish the same thing.When collaborative teamwork becomes more natural, adoption shifts from being focused around the organization, to being focused around the donors. This does something that goes far beyond AI. Making AI adoption about donors and their experience a way of doing things that makes understanding data less of a chore and more of a natural habit, by connecting the data to being part of something larger than ourselves.
Bio: Kristopher has over 18 years of marketing experience in both Canada and the USA and 8 years experience in fundraising for Canadian charities. With an emphasis on multi-channel direct marketing, Kristopher has managed over $7 million dollars in annual donations integrating direct mail, digital including predictive modelling, face-to-face and telemarketing strategies to drive growth and lifelong donor journeys.
“The concept of digital fundraising today must include predictive modelling/machine learning. Including machine learning in the mix ensures that you’re driving down your cost of funds raised while ensuring that no donor feels overlooked because you’re providing meaningful, personalized stewardship touch points at the right time in their donor journey.”
-Kristopher Gallub, Fundmetric Fundraising Liaison