Here are top 5 reasons to use tech tools instead of guessing museum decisions.
#5 — There’s a Museum Data Crisis Coming. You Can Avoid It.
Most museum professionals make audience decisions (marketing, programs, events, etc.) based on anecdotes, guessing and limited data results. However, new technological advances have created a gap between Global Museums that can spend money on tools and resources to make data-driven museums decisions and the remaining cultural institutions that still use anecdotes to guide decisions in an increasingly data-driven world. The latter group is enormous and blindly heading towards a museum data crisis.
The size of the oncoming museum data crisis is based on industry facts. According to an American Association of Museums (AAM) report, over 40% of U.S. museums have less than 15 full-time staff members and about 60% have annual budgets under $3M — the report only factored museums that have completed the rigorous AAM accreditation process.
Out of the estimated 33,000 U.S. museums, only 1,065 have AAM accreditation. Simply put, over 30,000 U.S. museums lack the professional development and financial resources needed for accreditation. This is the current museum landscape in America. Now include the reported 68% of U.S. museums that lack dedicated staff researchers for collecting, analyzing and processing audience data — this is a silent crisis that no one wants to discuss.
Now if your cultural institution is part of the elite group of AAM accredited museums with an annual budget over $15M (less than 10% of U.S. museums) and over 100 full-time staff members (less than 6% of U.S. museums), there’s a strong chance a staff person or a whole team is focused on museum data analytics. But what about the overwhelming 90% of U.S. museums that lack the technical staff and financial resources? The first step to avoiding the museum data crisis to start developing a data-driven museum culture now. It can be as simple as setting up a Google Analytics account or creating a dedicated data team that meets bi-weekly to discuss audience trends and then shares insights with all internal stakeholders.
#4 — Big Budget Museums are Already Hiring Data Scientists
Global Museums are defined as well-endowed cultural institutions located in major cities such as NYC, Los Angeles, Tokyo, Shanghai and London. These museums have the institutional power and financial assets to use data analytics to grow their revenue and instantly respond to audience trends. Many have annual budgets starting at $100M and use their resources to take full advantage of data analytics to generate insights from their donors, change their admission pricing or predict visitor attendance based on factors ranging from weather, public school schedules and local tourism events.
Here are some examples:
- The Asian Art Museum in San Francisco just hired a data scientist.
- The British Museum recently paid a team of data scientists from Microsoft to analyze audience data to shape experiences that visitors really want.
- The Smithsonian hired its own internal team of data scientists to use big data techniques to generate insights from their visitor data.
- Remember when the Met changed its ticketing policy? Hate it or love it, the new policy was the result of expert data scientists providing support for a data-driven decision to increase revenue.
Global Museums might have more resources at their disposal, but smaller museums can also benefit by learning more about big data. Basic research on data analytics shows the enormous value it brings to museums — ticketing, development, membership, shop sales and audience engagement are all areas that have been integrated with data analytics to deliver astonishing results.
#3— Museum Funding is Increasingly Tied to Impact Numbers
Major funders are now demanding quantified evidence of social impact. Members and donors expect both transparency of operations and a digital presence. Data-driven impact numbers are not a luxury, but a requirement for any modern museum that wants to remain relevant.
According to former president of the American Alliance of Museums, Ford W. Bell, “Younger philanthropists and donors today are looking for measurable results,” Mr. Bell said. “It used to be you gave because it was the Metropolitan Museum of Art. But today younger donors have a lot of things they can give to. They ask what the impact is going to be and how you’re going to measure that impact. The Rockefellers gave, but they weren’t looking for specific metrics.”
Since the majority of museums 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 used to support community impact. Being able to measure community impact is a crucial advantage for gaining reoccurring funding from government agencies and large foundations. The Oakland Museum of California showcases a great example on how to measure and demonstrate social impact. For smaller museums, here is a visual layout on how to create a social impact framework for your museum.
#2 — Using Personal Anecdotes to Make a Museum Decision is Dangerous
Technological updates are happening faster than ever, leaving older models practically useless. Ten years ago, staff members at Global Museums and smaller local museums both made decisions based on personal anecdotes and limited data results. Nowadays, not one staff member at the British Museum or Louvre would guess upcoming visitor trends or suggest to stock a museum shop item because it’s “cool.”
Museum professionals can no longer avoid the use of technology and digital operational tools in preparing for long-term sustainability. Truly, data analysis is the best method for understanding, evaluating, and changing organizational practices. The Art Institute of Chicago which has an annual budget over $300M, is using data analytics to predict visitor attendance based on over 20 factors such as weather, Chicago public school schedules, tourism events etc.
For smaller museums, the most important step is evaluating your current data analysis process and then reviewing the report to see its relation to the museum decision making process. The good news is that most museums interested in data analytics do not need a complicated technical solution. Rather, the data needs of most regional museums are very straightforward and can be solved by learning basic data management skills.
#1 — Museums are Becoming Less Relevant to Modern Audiences
Museum professionals must face the challenge of creating social meaning and maintaining relevance in an age of unparalleled access to the internet. This challenge also includes the oncoming museum data crisis. The majority of museums lack the tech infrastructure and staff resources required to fully integrate basic digital tools with their mission, resulting in lackluster experiences that can fail to engage modern audiences on a significant level.
According to a 2018 National Endowment for the Arts (NEA) report on arts attendance, audiences in the 18–34 age range — commonly referred to as millennials — still have proportionally lower visitation levels compared to other demographic cohorts. This group is the second largest population after the baby boomers — a group that is biologically disappearing every day.
Museums can gain relevancy only if museum professionals decide that the modern museum experience should be vibrant and inclusive. This can only happen with structured and accessible data. Museum data can help weave compelling narratives at your cultural institution and share the stories that make your museum special. Challenges to developing a data-driven museum can be overcome by training staff in basic data analytics practices, outsourcing to a professional consultant or creating a staff position specifically for data analysis. Depending on the size and financial status of your museum, each of those options can be a good solution.