Museum interpretation professionals are creating content for people who generally know less than them. Getting the right amount of content requires understanding the visitor. Tools like content mapping can help organizations get their content right. But, all museum professionals need to remember that their visitors have different baseline knowledge levels. Onboarding is a classic corporate word that encapsulates the idea that people might need a bit of aid to get connected to an organization. I always picture a ramp when I think of the idea of onboarding. Some ramps are short, when there is little small between two elevations. Others are long. The ramp is a good metaphor for the onboarding needs of visitors. People who know a great deal about the collection area will need little onboarding. (But, these people are also the ones who are the power users of your content.) Casual visitors are often also people with greater onboarding needs; they have less pre-knowledge. Keeping the issues of onboarding in mind as you develop content will help you create content that meets the various needs of your visitor-base. Remembering that everyone comes in with different needs and pre-knowledge, also helps center the visitor in the customer experience.
When planning content, interpreters need to perform a weird type of math. After they formalize their process and create their goals, they then need to edit their desires to meet the visitor desires. Getting just the right amount of content is challenging to say the least. Part of the program is that the majority of visitors use very little information, but then there are the frequent visitors need a high level of information (partly as they come frequently). Additionally, relative or power users are super keen to access information, and they are often donors. Firstly, go back to your goals documents. Tailor content needs to make sure that visitor desires are addressed in the interpretation. This is a great moment to do research. In almost every instance, museums will still deliver more content than visitors need/want. Evaluation can help organizations get better (over time) at creating the ideal amount of content.
Helping visitors engage in collections is a primary concern for museums. Museum professionals often partner with various vendors, consultants, and partners to do this work, for example commissioning firms to develop interactives for exhibitions. Mounting these installations can be exhausting and rife with interpersonal challenges. Visitors walking into spaces, ideally, have no idea how contentious and challenging mounting installations can be, thankfully. Even if the customer experience appears alright, the staff experience should not suffer to mount such installations.
What causes interpersonal challenges in mounting spaces and installations?
I have always loved the phrase lock-step and turn-key. Both phrases scream efficiency, ease, simplicity, and replicability. None of these adjectives would be useful in describing the mounting of a collection space. Collections managers and database administrators work had to make systematize collection data. But short of digital systems, most things about collections are complexity and nuance. Objects come to museums for their rarity and complications. Installations are meant to help people with little background knowledge fall into love (like) with an object. Collectively, the work of the people mounting an installation/ exhibition is to bewitch/ bemuse the public.
Getting visitors from 0-60 about collections is a tall order and its one about which every person (either on staff or on contract) feels passionate. Emotions can run high, and the stakes can feel enormous. People on the teams come with different expertise; each person seems the DMZ and faultlines in the process differently and through the lens of their own professional role. For example, while a curator might understand the nuance between using certain phrases (say artwork vs artifact), others on the team see these as unimportant arguments. Everyone on the team is often placed in the position of arguing their corner, and everyone can come out of the process feeling bruised.
How can these challenges be mitigated?
Everyone on the team is hoping to get an interpretation for installations that is interesting and easy to use without compromising the museum’s reputation. This sweet-spot is a bit of a holy grail. But, diminishing inter-personal challenges and developing better systems is essential to improving interpretation. Sound systems result in superior products, and broken systems result in subpar products. Think of how a broken conveyor belt will not be able to create wonderful chocolates.
The first step in developing a good working process is to agree that ideal interpretation and installations need to be easy to access, understandable, and grounded in research. Like a three-headed dog, these three elements have to work in concert to go forward. Often museums allow their legacy to serve an anchor preventing action towards innovation and excellence. Museums can also be fooled by the newest fads to skew too far away from their core competencies.
After agreeing to collective and balanced actions, teams need to determine more practical issues, such as work plans, sign-offs, and tone. Underlying these practical issues the teams need to decide and articulate the no-go zones for their institution. Every institution has issues that cannot be discussed easily. Donor issues and collection histories often top these lists. In working with teams, I like to put these issues on paper. This process can feel uncomfortable. But, these lists are also freeing, in that one person on the team is not required to be the guardian of these verboten topics.
Finally, any good plan needs some follow through. Often, the best-laid intentions are destroyed because there is no big stick. Museum staff managers are rarely given training on deescalating emotional conflict; a fear of conflict is epidemic in many museum senior staff members. With so much work and so little time & money, who can fault these managers. The result is a culture of conflict-avoiding people finding ways to step around and then crashing into challenging personalities. When I have worked on successful installation and interpretative teams, there is a person who is judge, jury, room mother, and traffic controller. (Ideally, the team has been set up so that everyone is on their best behavior and everyone understands they are in this together FOR the visitor, so challenges don’t bubble up.)
Interpretative work is basically like all human to human communication, prone to emotions and challenges. In installation work, the bigger challenge might be that the people starting the conversations about the collections (the staff) are not actually present with the receivers (the visitors). The installations, from signs to interactives, need to speak to visitors on their own. When the systems create these installations are smooth, the conversations can go singingly.
On Thursday, we will talk about questions teams can ask themselves to hit the ideal sweet spot for interpretation.
This topic also ties in with a previous post about the relationship between interpretation and research.
The best writing is complex. Persuasive text needs to inform in order to convince the reader. Inspiring texts often grow from a kernel of fact. Enjoyable texts are the best way to feed people information. While creative writers have more latitude to move their readers, every writer needs to understand how to balance these aspects of the written text.
In informational or interpretive text, non-specialists have a low threshold for information overload. Entertainment is a wonderful way to engage people information, like a spoon full of sugar. Convincing and inspiring people is much more challenging in interpretive text than in creative text. Convincing people with ideas is often about arming them with relevant ideas. Inspirational texts are, perhaps, the hardest types of interpretive texts. Inspiration often requires empathy and emotional engagement, a tall order for most interpretive text. But, some of the most successful types of inspirational text balance information, persuasion, and inspiration.
While each text needs to balance the different elements, overall, when working on interpretative content for an exhibition, the writer should be aware that each element has a different weight. Think about reading heavy, emotional text; you can only take so much. On the other hand, humorous or entertaining text can be read by the ream. Therefore, be thoughtful when constructing an exhibition to weigh the various aspects.
Thinking systematically about content creation requires having a facile ability to navigate between communicating the overall idea and articulating the component concepts. The ideal systematic thinker is both a big picture and detail-oriented person. While some people seem naturally able to employ systematic thinking, practice can help anyone become more capable of working systematically.
Why Systematic Thinking for Content Creation?
We all think differently with varied knowledge bases and ideological beliefs. Good communicators are able to frame their ideas in ways that address the cognitive complexity of humans. Strong communication frames complexity simply.
Every writer who creates a paragraph that communicates an idea has practiced systematic thinking. Good writers develop themes by knitting together persuasive, satisfying sentences into a compelling, cohesive message. Writers focus on the parts as well as the whole when they ply their craft. Each sentence matters as much as the paragraph as a whole in order to ensure that the message is communicated.
Content-creation requires the same type of systematic thinking. Exhibitions, labels, interactives are just like that paragraph–tools to share a complex message simply.
Just as writing takes practice, content planning is a honed skill. Putting together ideas is not like simple math. Rather than a simple jigsaw puzzle, most messages need to be communicated using a series of complex and overlapping ideas. When interconnected in a certain manner, these ideas come together to express the message.
Just as writers are usually big readers, good content creators explore how others share messages. Be a purposeful consumer. Notice how the ideas are combined to express a message. Make value judgments about the efficacy of the message communication. This type of thoughtful communication, paired with actual practice with content creation, will improve your ability to communicate well.
Customer/ Visitor Experience basically encompasses connection your visitor has with your organization from the signs on the street to the moments in the galleries. CX overarches both onsite and offsite; physical and digital. Experience is, therefore, a huge concept. As with all large concepts, considering constituent aspects.
The concrete elements that express the experience to customers/ visitors are a good place to start. These elements are where the ideas of the experience come to fruition, where theory becomes action. Here are some examples:
- Word of Mouth
- Social Media
- Social Media
- Front of Line Staff
- Front of Line Staff
- Point of Sale
- Word of Mouth
- Social Media
The touchpoints should spark reactions in visitors. These reactions aren’t just procedural. For example, a common museum touchpoint is a map that should help people get to places, at a bare minimum. But, the map should also communicate welcome and ease. People should feel comfortable.
Museums often focus on the procedural element to the touchpoints and therefore miss the mark with reactions. An effort needs to be placed on understanding that touchpoints evoke attitudinal (not just behavioral) reactions. Without careful consideration, those touchpoints will strike the wrong chord.
Thinking big picture is a good improve the alignment of the touchpoints and the reactions. Start with the action you hope to evoke. So, for the map, for example, you are communicating welcome. You want people to feel ready and able. Certainly, you want them to get to each of the galleries. They won’t even want to get to your collection if they feel overwhelmed or turned off from the map.
Museums and the Web 18
Museums and the Web 2018 was hosted in lovely Vancouver. As always, friends from around the world descended upon the town for ideas and enjoyment. While the MuseWeb organization does a great job of publishing articles that expand on the presentations, here are the highlights and themes from this year’s conference:
VR/AR/R: All types of reality were discussed and debated. Virtual reality was featured in the keynote, from LucasFilms VR lab no less. The back channel, a bit of unicorn at conferences these days, got fired up, with good reason. Virtual reality, in practice, currently feels more virtual than real. And, we as a field have real problems. We need to slay our dragons before marching out onto a virtual quest. In addition, VR is about being in a new reality. For museums, this is a big challenge. We want people to explore our reality, not escape our reality. In that way, AR seems supremely promising. Augmented reality is like seeing your own world through a surprising lens. Interpretation at museums is basically augmented reality, without the tech. So, this tech feels like a natural option. That said, a few pioneers have marched into VR, eyes open. From what they say about the frontier; it is challenging but compelling if you work really hard to do the VR right and have money from the private sector. Oh, that is, if you aren’t under 13, because insurance, et al, are not into VR for the teeny, tiny visitors.
More Money/ More Problems: “Big museums get to do big projects” used to be the story of the field. Now, with a proliferation of technology options, technology is being used across the sector. Investment dollars don’t have a direct relationship with success. Leaders who lay off their ego and instead focus on their visitors will succeed.
The Thing Doesn’t Matter; The Thing Really Matters: A few years ago, the theme of tech conferences could be: its all about tech/ its not about tech. There was a real tension between the need to focus on content and the need to focus on tech. Truthfully, they both matter. One is about how the road is built; the other is about where the road goes. For the road to be useful, both its physical manifestation and its functional raison d’etre have to be considered together. This tension from conferences past seems to have been transmuted slightly. Rather than should we tech or should we not, now the field has moved into a bit more nuanced questions: how should we do this? Should it be tech?
The Workplace can be an Albatross or our Lifejacket: We are at the end of the college years in the field of museum technology. In our infancy, we could do one-off projects because everything young ones do is great. In our teen years, we showed responsibility by attempting to implement enterprise solutions. In the last few years, like college students, we did group projects better than ever by playing nice(r) with other departments and other institutions. Now, as if with new found maturity, we are aching to make our lessons mean more for the field and more our visitors. But, how? We are struggling with making the workplace equitable and reasonable. We are trying to get others to understand that tech is for everyone; and that everyone needs to know tech. We are communicating better ways for work to happen. We are hoping that our leaders grab those life-jackets; many in our field feel like they are drowning.
Be Analytical but not an A**hole: We are all trying to understand everything better. Data feels like the place to get answers. Numbers seem like they don’t lie. (Be warned. The people crunching the numbers might inadvertently make them do so.) We want the best museum: well-run and well-attended. But, this ideal has a Shangri-la-like quality; a foggy possible existence that is remote and unreachable. We use data to help us track a path to this ideal. We are getting closer and closer, but it is still not quite in reach.
Collaboration & Coalitions: Working together is the hardest and easiest part of work. That is, in theory, it makes perfect sense to work together towards a common goal–easy peasy lemon squeezy. However, nothing that involves people is easy. We, as a species, are erratic and confusing. Therefore, collaboration can be the hardest part of the workplace. Politics and bad behavior can cost an organization hundreds of thousands of dollars. Killing it at collaboration means everyone on the team succeeding. Collaboration gets easier with practice, though. Thoughtful action can result in being better collaborators, which will eventually lead to an easier/ better workplace situation. Inter-organization collaboration expands reach exponentially (with the commensurate expansion of challenges.)
Conclusion: These year’s MW had a sort of sedate quality, as if many in the field are in their crystallises getting ready to burst out in full flutter. So many conversations were about doing better at our work. Refinement and improvement seems like key issues in the field.
Museums might be said to be on the higher-end of the leisure world. They have cache. If not, imagine the situation associated with the phrase, “We are at the museum today.” Now imagine being in the situation to be able to say, “we are at an amusement park right now.” Both are perfectly enjoyable, no doubt. But, the former is more rarified than the latter. Amusement parks bear their mission in their name–an outdoor space to bring joy. Museums, on the other hand, as a word is somewhat out of step with the current usage. The word denotes these sites as places for people to encounter the muses. While certainly, no museum is actively discouraging convening with the muses, such spiritual-intellectual pursuits are just one of a range of experiences that the contemporary museum hopes to foster. Unlike amusement park, with only a century or so of history, museums have 400 of history. In the word of whip-fast brand pivots, museums change is glacial, but they have continued to evolve. This evolution includes slowly but surely fostering social media use by patrons about collections. These moments when the glacial change becomes apparent can confuse people. Every once in a while, the media bemoans changes to museums like the use of social in the galleries. But, hard as it is to believe, change has been part of museum culture since it began.
Change in Museums
Early museums began in Europe. A museum, as described in the Ephraim Chambers Cyclopædia of 1750, is “any place set apart as a repository for things that have some immediate relation to the arts, or to the muses”, while a repository was “a store-house or place where things are laid-up, and kept.” In other words, early museums were set apart from warehouses by the act of curating meaningful arrangements. Museums were a place “to instruct the mind and sow the seeds of Virtue” as noted by Charles Willson Peale founder of the Philadelphia Museum in 1784. These spaces were meant to be visited by the well-heeled they have the proper disposition and pre-knowledge to appreciate the nuance of museum installations. Museums were in keeping with a host of amateur activities pursued by gentlemen during their leisure. Contemplation and conversation over objects were fun for a certain class of men.
— Smithsonian (@smithsonian) November 3, 2017
The idea of museums spread quickly along the same networks that supported the colonialism of the age. By the early 19th century, museums were found on all inhabited continents. But, by this time, museums had already changed substantively. Rather than being for a select group of educated men, museums were now seen as a place for the general public. Additionally, visitors were allowed to self-guide through museums rather than taking a prescribed tour of the galleries. With the inclusion of all types of people, museums began to foreground their educational nature. In their first century, they could be assured an audience with the necessary foundations to understand the collection. But, in the 19th century, as James Smithson, founder of the Smithsonian, said museums are “for the increase and diffusion of knowledge.” Museums were a way to share ideas with anyone.
The 20th century saw a massive growth of museums. These museums maintained and augmented their educational value. Most museums developed departments tasked with education. Spaces began to reflect this educational charge. Education was diversifying in the real world and museums met this challenge accordingly. But, museums also began to offer more entertaining ways to explore collections, like classes for children and lectures for adults.
The first decades of the 21st century have seen an exponential rise in the number of museums. Museums are no longer solely about collections but also ideas. More importantly, museums are fighting against many leisure spaces for visitors’ attention. Museum has met this challenge in innovative ways. I, myself, happily spent a career developing family guides, technology content, role-playing games, and social media campaigns. (I am the middle person in the picture :>)
And good question ! If I try to sum up : experiencied visitors (labels, art pieces (globally, details,…) first-time visitors (institution, architecture (inside/outside), visitors group). But it’s also mixed with visitors personal interests and passions 🙂
— Sébastien Appiotti (@sappiotti) November 23, 2017
Museums in many ways have returned to the roots. Rather than doing it wrong, visitors are taking up the charge of the early founders. People are enlightened by the muse in our galleries, taking and sharing photographs. Now, the question is how do we continue with the 19th-century ideal that museums should be for the broad public? Firstly, by encouraging and supporting the action of taking photographs. Social allows visitors to engage with the best intentions of museums in the language of our time.
Data seems pretty cut and dried, but don’t be fooled. There are plenty of ways to fold in bias. Here are some concrete steps to help you do your best to counteract the most common pitfalls.
Start with a clean tool/ protocol to collect data.
1. Keep data clean
There are plenty of ways to keep you tidy. First, have everyone use the same protocol. Ideally, keep your data collector pool down to a minimum. More people means potentially multiple interpretations. Train everyone the same. Take out the protocol and make sure everyone understands it. And, make sure everyone uses the same data collection tool. I used to work in a team of three data collectors. We had to agree to everything, and often huddled up to make sure we were on the same page. Be vigilant
2. Observe First, Interpret Later
Years ago, when I worked on hiring teachers for the public schools, I had to take a course on legal job interviews. The fear that the trainer burned into my soul always returns to me when I do interviews. Only write what people say–word for word. Do not interpret. This goes against your human nature. And, if you have a hard time writing, ask respondents if you can record them. Also, feel free to ask the people who provided the data whether your interpretations seem to be representative of their beliefs. Once all the data comes in, then you have the joy of interpretation. That said, once you get familiar with interpretation-free listening, you will also find joy in data collection.
3. Check out the competition.
After your initial interpretations, look to others to see how they are tackling this issue. What are their findings? What other issues might be occurring in the literature. This is sometimes called triangulation. If you can find other sources of data that support your interpretations, then you can have more confidence that what you’ve found is legitimate.
4. Check for alternative explanations.
False conclusions are absolutely the most likely place that bias comes into understanding data. Jumping to conclusions can feel normal, like finishing someone’s sentence. But, just was you can’t fill in the blanks for your respondents, don’t fill in the blanks for yourself too quickly. Consider whether there are other reasons why you obtained your data. If you can rule out or account for alternative explanations, your interpretations will be stronger
5. Review findings with peers
Don’t be an island. Unless confidentiality prevents you, let others look at your data. You will only become better at your work with critical assessments. Additionally, when you allow peers to review your work, you might find commonalities. You might even be able to augment your argument.
This is the second in a series of posts about confronting bias. These #longreads use narrative to help bring up bias in an accessible manner.
As Director of the Art Museum of New South Overthere, you are constantly being asked to make decisions based on data. Sure, you had your last math class in 10th grade, and then avoided math through your PhD. But, you are a specialist, I mean in lantern slides, but still, you got this, right?
You are dying to know how much people like lantern slides. You write out a survey for your staff to deploy. You want to be direct with your visitors so that you don’t waste their time. So, you asked the people in the Joe Bright Memorial Lantern Slide Gallery (and broom closet).
- “What do you like about lantern slides?”
- “Is there anything that you don’t like about lantern slides?”
- “What would you like to see with the lantern slide display?”
You were happy to find out that there is nothing that they don’t like about lantern slides. They also love your lantern display as it is. The only thing they want is more information, which is what you thought. They just wished they could know more about the slides! How wonderful to know what you do for a living is so relevant for people.
In this case, you have several problems. First, your survey questions are constructed with a particular slant towards lantern slides. This a situation of interview bias. It’s as they say in legal shows; you are leading the witness. When you construct survey questions you don’t want to tip the participants off to the “right” answer. People have an inherent need to please, and so they will answer in a way that seems correct.
Additionally, there is a selection bias at work here. You went to the gallery where you hope to make changes. On one hand, you are being proactive. However, you are skewing your data. You have a sampling error at play. A better study would interview not just current visitors to the lantern slide gallery but also those in the museum who are not currently going to the lantern slide gallery. In other words, you want visitors and potential visitors to draw a complete picture of the situation.
Your first meeting this morning was with the board. This nice old lady, Sweetie Monroe, heiress to the great Marshmallow Mills fortune, was hoping you could explain why you don’t have any students in the galleries. Now, you have never seen Sweetie upright before 1:00 pm in the morning. But, you also know that the school scheduling staff member, Peaches LaPew, is busy every morning. Last week, she tried to get you to do a Kindergarten tour, because you had more students than staff.
You’re not going to be able to show Ms. Monroe children in the flesh (you aren’t a miracle worker), so you ask your staff to do a little comparative analysis. Your head of Marketing/ Audience Research/ Programming & Security, Joe Exhaustino, has emailed you a super long report. Does he understand how busy you are? You don’t have time to go through this like you were in school. Luckily, it has a clear summary. You have plenty of kids coming. Fabulous.
In this case, I have bad news for me. You didn’t look too closely at your data. You used the data like a yes-man. This is an example of choice-supportive data. If you looked more closely at the data, you would notice that only 4 percent of visitors are 18 and under. Most of those are school groups. Now, I don’t know what your measure of success is, but 4 percent of total visitors seems extremely low.
Before you can get to your chance at regaling Ms. Monroe about your fabulous student tours, you find yourself stunned by numbers. You are sitting at a breakfast meeting with the directors of all the local organizations. The head of the Community Development Corporation is sharing a graphic. Apparently, the average percentage of family visitors at museums is 10 percentage. Eek. You get nervous. So, you turn to the guy next to you, the Director of Coffee Cups & Porcupine baskets. He smiles and then says, “Oh, yes, that’s just average. We are at 18%.” You leave the meeting despondent, and shoot off a quick email to your grant office/ gardener to get money right now for school tours.
In this case, the data was combined inappropriately, though you wouldn’t necessarily know it. You didn’t have all the information when you sat in that meeting and looked the graph. The number crunches decided more numbers were better. But, in doing so, they didn’t use like categories. In this case, the number cruncher didn’t separate out school groups. Only two of the four museums do school tour. This means that in those museums children are coming in though out the week without adults. They will have higher numbers of children than those who don’t do school tours. The lesson is that you need to thoughtful in combining data. There are other challenges with combining data. If you aren’t careful, when you aggregate data, you can accidentally contradict what the original data said. This is called the Simpson Paradox.
You are hoping to buy more media adds. You call on Joe Exhaustino again, but this time with your demographic numbers. He gives you the classic bell chart with mostly mid-aged people attending the new exhibition. No surprises. So, you will just use digital adds to get more young people. Finally, an easy decision. After the ads go out, you take a turn in your Lantern Slide gallery. Something odd is up. The gallery is full of really old men. You go back to Joe and ask him if his numbers are right. He shows you his numbers. He had used a good-sized sample. He crunched the numbers and he ended up with a graph that didn’t look right. So, Joe removed the outliers, the old people.
Joe has been doing numbers for years. And, he assumed that the attendance numbers should conform to a bell curve. This is called the Non-Normality bias. But, another bias was in play here. Instead of investigating the outliers, they disregarded those numbers. Joe did better on his second crack at it. Along with the quantitative data, he looked at surveys. Turns out the lantern slide gallery had become a mecca for the over 95 set. Practically, everyone in the state in that age demographic comes to the museum to check out those sweet slides, particularly on “free coffee Friday”.