While institutional philanthropy is in a boom-time, foundations have not monopolized such growth. The renewed interest in donor advised funds (DAF) since the pandemic has triggered meteoric growth in the amount of assets stored in DAFs, with recent figures showing over $229 billion stored across 2 million DAF accounts, receiving roughly $86 billion in annual contributions, and granting nearly $52 billion in 2022.
The use of generative AI (GenAI) tools is becoming increasingly prevalent in marketing, particularly for smaller organizations or nonprofits seeking innovative ways to engage audiences and improve workflow efficiency. This article dives into data collected through a survey that was sent out to museum professionals in Pittsburgh and Cleveland to better understand how and if they are utilizing generative AI tools in their marketing strategies.
This month, music and film are at the forefront as each battles with the future uses for burgeoning tech. While AI-generated film visuals seem to be coming up short, progress toward realistic AI-generated music is starting to send shockwaves. On the consumer side, music streaming tools are being released to allow more listening experience customization. Across the industry, artists are celebrating ways that some these new tools can enhance their work, while speaking out against potential impacts on jobs, compensation, and creative freedom.
Generative AI (GenAI) has become increasingly integrated into marketing and communication careers, and even our daily lives, with the rise of various text-to-image, text-to-video, & text-to-text tools. As digital marketers find new and innovative ways to keep up with the trends, and specifically GenZ in a quick-changing popular culture scene, how are they reacting to the rise of GenAI?
Arts and cultural organizations are becoming increasingly aware of their climate impact, and many are taking action to reduce harm. Tracking, reporting, and offsetting emissions may seem like an overwhelming feat for small or mid-sized organizations, but emerging blockchain technology may help make the process more efficient and reliable.
As the need for website privacy policies grows, how are arts organizations keeping up? From a sample of 100 nonprofit arts organizations across the United States, this article evaluates how many organizations have accessible privacy policies on their website and why that number should be higher—both to show their dedication to protecting patrons’ personal data privacy and to keep up with changing policy requirements.
In a survey of 467 nonprofit professionals, EveryAction and Nonprofit Hub found that 90% of nonprofits are collecting data, but that 49% of surveyed nonprofit professionals did not know how it was collected. While data clearly plays a large role in nonprofit arts organizations’ operations, few have concrete policies and procedures that guide its collection and use. In the context of changing policies about data privacy and increased risk of cyberattacks, this is a dangerous place for nonprofit arts organizations to be in. This article will summarize considerations in areas pertinent to these organizations.
Digital technology is becoming a standard tool for the collection, preservation, and dissemination efforts of arts and cultural heritage worldwide. From 3D configuration of ancient artifacts to applying artificial intelligence to shed new light on how we perceive the lineage of humanities, cultural heritage is headed toward a digital future. This article will examine the ways in which digitization and artificial intelligence – two of the most widely used or relevant forms of technology in cultural heritage – are applied through global cases of innovative initiatives happening in the field in recent years.
More than a trend or a buzzword, data analytics are here to stay. Newcomers to arts management may find themselves asking, what does data analytics mean for me, and how and why does my organization need to use it? If you are new to arts management, or the data world in general, this two part series is for you!
This article is Part II of a two part series. Part I is available here.
Donors and other major funders typically seek quantitative evidence of mission-related impact in communities therefore nonprofit organizations are making data analytics a standard part practice in daily operations. However, the transition into data-driven decision making hos occurred quite slowly, with over two-thirds of nonprofits reporting that they are only in the beginning stages of implementing data analytics. Furthermore, the majority of nonprofits report that they are not using external data for mission-related analysis; it seems that there is a lack of knowledge or disconnect about how big data can be captured for future community impact. In general, larger nonprofits are more likely to implement data analytics in tandem with improved strategic planning for the mission and programming. Smaller nonprofit organizations, or even arts organizations that wish to place on emphasis on people rather than numbers, have access to many of the same data analytics tools as larger counterparts—so the present concern is why are some organizations not implementing these accessible strategies which can have an immediate impact?
Graph of reasons for not doing data analytic cited by nonprofits: Image credit: IBM, Leap Before You Lag (2017)
Numerous barriers, ranging from internal to external environmental factors, are frequently cited as contributing to an organizations the lack of data analytics use. Particularly for smaller or newly founded organizations, the lack of proper technological infrastructure prohibits even the most basic data analytics collection. Similarly, some organizations cite their limited financial resources. Others are concerned about potential resistance to using data as a primary tool for decision making from major funders and financial decision-makers, such as government supporters and board members. A the perceived lack of expertise within an organization’s staff may also present a barrier.
Some of these challenges may be overcome by training staff in data analytics practices, outsourcing for professional consulting, or creating a staff position specifically for data analysis. Depending on the size and financial status of a nonprofit, each of those options can be a viable solution. Staff can be trained on the more basic analytics tools, and many consulting firms offer services that are specifically tailored to the arts nonprofit sector.
Due to the lack of confidence and informative insight for the implementation of analytics, it is imperative that today’s arts managers initiate a new data-driven operations model in their organizations and make the case to stakeholders. The total digitization of information has created a business environment where institutions cannot maintain long-term success without understanding the importance of data.
Best Practices
In assessing what type of data to analyze and how to acquire it, arts organizations may benefit from partnering with other nonprofits or seeking assistance from external sources as they begin the journey of analytics-based functioning. As budget constraints are often a prevalent issue, nonprofits may consider a shared data services model and forming an insights ecosystem. This ecosystem is a combination of resources, internal practices, and external information that can help to optimize profitability and mission-focused agendas.
Visualization of an insight ecosystem: Image credit: IBM, Leap Before You Lag (2017)
As demonstrated above, collaboration is actually a key component in the process to becoming a data-driven organization.
A clear strategic plan from a lead staff member concerning the critical nature of data in the arts/nonprofit sector is central to success. There must be a steadfast commitment to using data for major decision-making and a willingness to educate staff and other stakeholders about its benefits. Further, new data practices should align with the financial stipulations set forth by major funders and board members; data analytics must be presented in a way that buttresses the development of mission-based programming for real impact. In terms of internal staff, arts managers need to ensure that “actionable metrics” are defined and the organization invests in the necessary technology to measure said metrics. Data analysis can only be beneficial if the goals are defined and accessible through proper platforms. Consequently, data analytics best practices also require organizational leaders to inform staff of new data-focused operations and empower individuals to improve on their skills in the process. Outsourcing may not be necessary if staff members can be trained on new data software and have the desire to build on their current skillsets. Most important in the data analytics journey is that the emphasis on metrics will build or alter programming in a manner that furthers an arts organization’s mission, vision, and values. The metrics that show evidence of success should be analyzed on an ongoing basis, and should those metrics that show problematic trends should be via immediate changes in budget, programming, staff productivity, or which ever means seems appropriate. Behind all of these best practices lies an individual commitment to seek change; thus, the data analytics truly rests on the “human element” for real-world benefits to be had.
Conclusion
Arts organizations can no longer avoid the use of technology and digitized operational tools in preparing for long-term sustainability. Truly, data analysis is the best method for understanding, evaluating, and changing organizational practices: “Without data, it is impossible to measure financial and operational health, identify problems and measure organizational impact.”The most valuable aspect of data analytics that arts managers should realize is the ability to make relevant organization-wide improvements in alignment with the impact they hope to bring about from their mission statement. While data analysis can effectively aid in the acquisition of donors and retention of key audience segments, nonprofits can use these tools to decide which programming elements are bringing about the community benefits they are seeking (and which are not). Given that an organization’s mission, vision, and values reflect its identity in the community, it would be wise of arts leaders to implement data analytics and become advocates for data-driven decision making.
[1] IBM, “Leap before you lag,” (2017): 1.
[2] Ibid.
[3] Idealware, “The State of Nonprofit Data,” 2.
[4] Ibid., 11.
[5] Ibid., 7.
[6] Ibid., 2.
[7] Ibid., 13.
[8] IBM, “Leap before you lag,” (2017): 14.
[9] Ibid.
[10] Ibid.
[11] Ibid.
[12] Ibid.
[13] Ibid.
[14] Cardinal Path, “The State of Digital Data,” 10.
[15] Idealware, “The State of Nonprofit Data,” 3.
Over the past decade, digital security and infrastructure have arrived at the forefront of the minds of organizations both small and large. In an increasingly digital business world organizations must remain vigilant in protecting the volumes of data they collect. This article examines the baseline considerations for Arts Organizations in relation to managing and protecting both business and patron-side data.
To understand why arts organizations have struggled to capture funds from tech billionaires, arts managers and development professionals would do well to recognize what philanthropic sectors they are losing these dollars to, and why. Armed with these insights, arts professionals can then adjust their strategies to better appeal to this new and growing donor segment.
If you told the average San Francisco resident 40 years ago that the art scene in the Bay Area would be gasping for life in 2015, they probably would have laughed in your face. But it is 2015, and that is the reality we are facing. The tech giants have moved in, and tension is building between the Silicon Valley community and its non-profit entities. In particular, arts organizations seem to be at an extreme disadvantage for a few reasons:
