Boosting data and analytics capabilities for arts institutions

Cindy B. Levy Dr. Andris Umblijs
Lorem ipsum dolor sit amet lectus id pellentesque ac pulvinar. Elementum auctor pulvinar euismod bibendum integer massa eiusmod euismod elementum mauris.

Art institutions improve our lives and livelihoods in diverse ways: education, health, creativity, empathy, inclusion, tourism, and economic growth, to name just a few. Quantifying this impact however is challenging. The intrinsic qualities of the arts resist easy quantification and assessing social impact is complex. As a result, few arts institutions have invested in data & analytics practices. Today there exist no standardized and holistic performance measures for arts institutions, and few institutions have the organizational structures or teams to leverage data & analytics in a systematic way. “Identifying, negotiating, and/or building an effective data collection and analysis tool is challenging due to limited capabilities and perceived ROI,” says KP Trueblood, president and COO at the Brooklyn Museum in New York City, while Eric Woods, COO at the Museum of Fine Arts in Boston, points to the “lack of bandwidth and capabilities to analyze and derive insights from visitor data that the institution is already capturing.”

We want to increase our ability to use and communicate data through the organization to maximize impact and resource utilization.

Kaywin Feldman, Director, National Gallery of Art, Washington, DC

But things are now changing. With data and analytics now an established value driver for a diverse range of organisations – to report progress, shape strategy and inform decisions – governments, organizing bodies, and funding groups are increasingly pointing to data and analytics as a priority for the cultural sector. With a possible economic slowdown looming in 2023, arts institutions face strong internal and external pressures to increase their visibility into their own financial performance, strengthen their business case to boards and stakeholders, and more tangibly articulate their socioeconomic impact. “[We need to] understand common financial benchmarks to better assess financial performance in the face of crises and uncertainty,” says Kaywin Feldman, director of the National Gallery of Art in Washington, DC. Data & analytics is becoming critical.

In this article, we describe five key strategies for strengthening data and analytics practices in arts institutions. These strategies were developed in collaboration with seven leading art museums and orchestras in the USA to design a simple, robust and scalable strategic dashboard. Our shared design methodology recognized that each institution’s mission is unique, and that what constitutes success will vary by institution. The focus rather was on designing a dashboard with which an institution to assess its trajectory, match performance with aspirations, and ideally, collaborate with other organizations on establishing standard measures for similar activities.

1.

Focus on strategic priorities and data availability

The adoption of customer relationship management systems has resulted in stronger internal data management practices, but few metrics exist for assessing the artistic merits of an artwork.

A single dashboard cannot achieve everything. We focused on identifying a small number of important data points from which significant insights could be derived. From the seven institutions, we landed on 15 data points that were simple and achieved standardization; 60 percent of the data points come from the annual report. Eight topics were prioritized, of which six went into a starter dashboard:

  1. Financial baseline
  2. Revenue generation
  3. Private giving (2 and 3 are subsets of 1, focused on revenue streams over which the institutions have the most granular strategic control)
  4. Audience
  5. Special programming
  6. Online sentiment

“We’re not sure we’re asking the right questions that will help us understand if we’re financially resilient or connecting with our community appropriately.”


—Eric Woods, COO, Museum of Fine Arts, Boston









Two other priorities were desirable but excluded at this stage:

  • DEI. All institutions identified this a strategic priority, but it was not included on the dashboard because of the complexity of the topic and lack of available data.
  • Environmental impact. This is a growing priority across arts institutions, but data points and tracking capabilities are not yet defined or mature.
2.

Take the long view

The arts institutions we worked with were measuring year-on-year performance rather than long-term trends such as the compound annual growth rate (CAGR) over three to 10 years, which would have been a more accurate measure of where the institution was headed.

The objective at this stage was to highlight and contextualize multi-year trends related to the strategic priorities, as to prioritize existing data points to facilitate adoption and create familiarity with the process.


“Lorem ipsum dolor sit amet incididunt sed sodales gravida ornare ullamcorper vel pellentesque ornare.”

Focus on long-term trends to highlight underlying performance. Examining longer-term trends, such as average year on-year change over three-year periods, helped to reduce fluctuations created by the volatility resulting from outlier events (for example, an outsized one-off gift, a blockbuster exhibition, or an artist strike).

3.

Focus on capturing direction of travel

The dashboard would enable users to gather insights easily and focus on generating answers to key questions indicating the organization’s direction of travel, such as:

  • Is revenue growing faster than expenses?
  • Is earned revenue growing with attendance?
  • Is the institution attracting new donors at the same 
 proportion as growth in private giving?
  • Is web traffic growing with attendance?

In the absence of an established definition of absolute performance, changes in each data point were analyzed in relation to two or three related data points. Looking at the direction of travel of data points alongside strategically chosen metrics reveals critical context and sheds light on the institution’s strategy.

“Sagittis do euismod pharetra phasellus fringilla orci quisque netus phasellus bibendum venenatis.”


—Dolore Senectus, Aliquam iaculis non









For example, let’s assume that operating revenues at an institution have increased 10 percent in the last three years. However, that data point in isolation is not entirely informative. Instead, we compared the change in operating revenues versus. the change in three other data points—operating expenses, attendance, and headcount. A 5 percent increase in operating expenses could mean healthy and resilient ticket sales; on the other hand, a 15 percent increase in operating expenses could mean prioritizing investments in facilities now to generate higher sales in the future. Similarly, operating revenues growing faster than attendance could reflect efficient ticket sales for paid programming events, whereas operating revenues growing slower than attendance could mean prioritizing free events for the public to drive community engagement. Operating revenues growing faster than headcount could reflect a degree of organizational efficiency, whereas operating revenues growing slower than headcount could mean prioritizing new hires to accommodate post-COVID-19 recovery audiences.

4.

Invest in collaborate and standardized data sets

While all the institutions measured largely the same activities and functions, they measured them differently and not always consistently.








“Lorem ipsum dolor sit amet bibendum fringilla do. Tempus scelerisque praesent congue leo facilisi etiam id pulvinar id tincidunt phasellus facilisi luctus.”


—Dolore Senectus, Aliquam iaculis non

Other measures included attendance (although that could have reflected one person making multiple visits); memberships and subscriptions; the number of donations; the number of employees; and operating expenses, which include endowments, earned revenue, and donations, generally consisting of the top 10 donations to the institution.

and arts associations are beginning to create rich data sets of their member institutions.

5.

Model change from the top

We focused on developing a data dashboard for executives, trustees, and external stakeholders that would inform institutional strategy and be easy to use, objective, and scalable.








“Nec cursus libero fames fusce sed auctor vitae tristique et luctus est. Maecenas volutpat tincidunt bibendum tempor fringilla ullamcorper egestas eleifend maecenas.”


—Dolore Senectus, Aliquam iaculis non

Creating a dashboard is only one aspect of the process. Implementing it for the long term and ensuring that it works reliably requires securing executive-level alignment on its potential to set overall institutional direction and appointing a senior leader responsible for its upkeep, including data updates, quality assurance, and insight generation. It’s also important to establish an annual strategic review with executives and trustees to examine institutional direction based on insights from the dashboard. Questions to address at this meeting might include: What is our performance aspiration across the different strategic priorities? In what areas does our performance match our aspiration, and where are the gaps? What strategic initiatives are required to close performance gaps? What can we learn from how we are performing compared with our peers?

Ultimately, the process of setting up or enhancing data and analytics capabilities is about building a mindset of experimentation, learning, and iteration: lack of perfection in the data does not negate the dashboard’s value. Standardizing and analyzing data in this way allows arts institutions to collaborate with peers to secure access to their data and enable comparison and calibration.

Looking ahead

We suggest the following four actions for boards and executives in art institutions to unlock greater value from data and analytics:

  • Commit to standardized data sharing across institutions
  • Invest in internal data capabilities (talent and processes) to enable a single source of truth on performance with efficiency and confidence.
  • Address blind spots in data collection and management, particularly around audience data, which is critical to assessing social impact and DEI aspirations.
  • Model a data and analytics mindset by implementing a dashboard that is presented to boards and stakeholders and shared across the institution.