“Big Data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”
– Dan Ariely
This quote from renowned author and behavioral economist Dan Ariely may draw a chuckle, but it also may summarize how data is approached within the nonprofit visitor-serving industry.
“Everyone talks about it.” Indeed, there seems to be a great deal of discussion among museums, zoos, aquariums, botanic gardens, historic sites, and performing arts organizations acknowledging the importance of data. And data is important! It allows these organizations to focus on the expectations, behaviors, and preferences of the people that they aim to educate and inspire without needing to guess about the best approaches. Try as they might to think like their audiences, cultural organization leaders have skewed perspectives. (Hey, they are only human!) Informed by data, solutions become “I know” answers instead of “I think” guesses. Data-informed cultural organizations make informed decisions based on what’s relevant to their audiences. These organizations are eager to learn about the people who walk through their doors—as well as the people who don’t!
At the same time, though, it seems “nobody really knows how to do it,” when it comes to using data to make data-driven decisions. In my experience, some cultural entities think they are data-driven simply because they collect information or work with a partner who collects it on their behalf, not because they’re actually using it to inform strategic decisions. Simply having data does not make an organization data-informed. Data collection is only one step in becoming a data-informed cultural organization. Data interpretation, acceptance, and integration can be even more important than data collection. Being a data-driven organization means not only collecting – but actually using – data to effectively make key decisions.
To inspire your organization on its journey to effective data use, here are fifteen more of my favorite quotes that relate to data. They are from economists, academics, scientists, writers, and business leaders. These quotes, along with Dan Ariely’s words at the beginning of the article, are compelling to me because they lend wisdom to some of the biggest challenges standing in the way of becoming a data-informed industry.
“To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.”
-Sir Ronald Aylmer Fisher
Data helps inform strategy so that organizations may better engage audiences. Too often, data is used as a post-mortem assessment of a program with the aim to validate that program’s use of funds. This is a mistake. At best it misses the learning opportunity, and at worst it feeds our cognitive biases, manipulating outcomes to justify past decisions to external stakeholders. This is misuse of data.
“Some of the best theorizing comes after collecting data because then you become aware of another reality.”
– Robert J. Shiller
How much should an organization invest in research on the outset to ensure the realistic outcomes of a major, expensive project and make sure that it will reach its goals? A meager 1%. And yet, many entities build new wings or take on multi-million dollar exhibitions without considering if the immediate impacts in attendance are sustainable. Often, they aren’t. The most innovative and successful projects are enabled by market research – and they may not always be what leaders would have theorized as solutions without data.
“In God we trust. All others must bring data.”
– W. Edwards Deming
To be sure, expert opinion can be important and it has its place. But when creating and cultivating a culture of curiosity that aims to make the most informed decisions, data matters.
“I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.”
– Sir Arthur Conan Doyle
As insider professionals, we suffer from cognitive biases such as confirmation bias. This is the tendency to search for and interpret information so that it conforms to our existing beliefs. When we theorize before we have real life information, we risk making our biggest mistakes and missing the benefit of the information in the first place. Theorizing is guessing.
“He uses statistics as a drunken man uses lamp posts – for support rather than for illumination.”
– Andrew Lang
Good data illuminates opportunities that help organizations reach their goals. Using data primarily to support things that the board or executive leaders have theorized is a manipulation of data in that it can be riddled with ulterior motives and cognitive biases. Market research – in particular – is best used when it informs decisions rather than when it is used to validate them.
“A point of view can be a dangerous luxury when substituted for insight and understanding.”
– Marshall McLuhan
As insider experts, cultural leaders are not representative of target audiences… unless theirs is a museum aiming to reach that specific museum’s leadership team. We can make unintentional mistakes when we forget this. It’s a leader’s responsibility to understand that their point of view is of a sample size of one, and that is not statistically significant. When aiming to create programs that educate and inspire people, those people that we aim to educate and inspire matter most.
“Most of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong.”
– Suhail Doshi
When we don’t have reliable data, we’re guessing. When we guess, we move forward without all of the information that we may need to be successful.
One accurate measurement is worth a thousand expert opinions.
– Grace Hopper
Three cheers for the incredible Grace Hopper, an American pioneer of computer programming! Expert opinions are guesses, and they are often inaccurate. “One accurate measurement” can shine a light on the reality of a situation.
“A person who is gifted sees the essential point and leaves the rest as surplus.”
– Thomas Carlyle
Not everything that can be measured should be measured. Vanity metrics – such as Facebook likes or website page views, for instance – are examples of data for data collection’s sake. They muddy the water for focus on more important metrics, such as an organization’s reputation, ad awareness, visitor satisfaction, and intent to visit. These key performance indicators actually matter. So much of what entities collect and report today does not – and thus dilutes the efficacy of efforts to become a data-driven organization. By focusing on what matters, we can be inspired to make changes that matter.
“The alchemists in their search for gold discovered many other things of greater value.”
– Arthur Schopenhauer
Collecting good data can result in findings that lead to greater insights. This happens regularly in my own work with data. Here’s an example: In aiming to uncover the top reasons why millennials become members to cultural organizations, we found that supporting an organization’s mission matters to this audience. We were intrigued! We added new questions to the National Awareness, Attitudes, and Usage Study and found that mission-motivated members are more satisfied with their memberships and more likely to renew – regardless of their generational cohort. Now, we have multiple other data points related to this motivation to inform conversations with cultural organizations. In sum, asking one question on behalf of one client organization resulted in our looking into national data and spotting a major trend generally impacting cultural organizations on the whole.
“If statistics are boring, you’ve got the wrong numbers.”
– Edward Tufte
We say at IMPACTS that if data challenges you, then it’s a good sign! It means there’s a possible opportunity to change your organization for the better. If data keeps showing over and over that everything is hunky dory, then you may not be collecting the most helpful information. After all, why collect data that doesn’t help you evolve? If you’re in the “safe zone” with your findings, it may help to look into additional information to find areas for improvement.
“Facts do not cease to exist because they are ignored.”
– Aldous Huxley
We can cover our ears and our eyes and pretend certain realities do not exist because they are inconvenient, but that doesn’t make them any less real. Last week, I wrote about some economic realities that cultural organizations willfully ignore. There are many, but that article focused on three: Price-quality heuristics (“people value what they pay for”), the reality of having likely and unlikely audiences, and the cost/benefit of marketing.
“The value of an idea lies in the using of it.”
– Thomas Edison
It’s not enough to collect data or have data. Data must also be interpreted, accepted, and implemented in order for an organization to gain its benefits. These tasks can be just as important as having the data in the first place.
“Things get done only if the data we gather can inform and inspire those in a position to make [a] difference.”
– Mike Schmoker
The data and analysis that an organization or its partners collect (and the large-scale market research that I share here) may only be helpful if its necessity is understood. It may only be helpful if leaders are willing to put healthy organizational evolution ahead of their egos, and it may only be helpful if an organization’s mission (and related financial solvency) is truly central to a team’s motivation. When used successfully, data can inspire us all to grow as effective leaders, challenge our unintentional biases, and lead cultural organizations to success.
“Not everything that can be counted counts, and not everything that counts can be counted.”
– Albert Einstein
Let’s be clear: Data is helpful insofar as it helps us understand people and behaviors, and how organizations can grow and evolve to best meet the needs of their audiences. My favorite findings are the ones that tie to emotions. There are ways to measure things like awe, relevance, and inspiration – but these are human emotions, and humans are messy. We aren’t always aware of our emotions in the first place! Heretofore – in a world without data that was as accessible – running a cultural organization may have been approximately 90% art and 10% science. I posit that the answer isn’t to become 100% data-driven (including on those fuzzy “matters of the heart”) or be stalled, but to make way for science and consider it a necessity in strategic decision-making. Let’s aim to at least even out art and science in our strategic decision-making. (We are very far from this as a sector, and have a great deal of cultural shift to carry out.)
We’re not short on fuzzy, feelings-based guesses about how to run cultural organizations. In fact, that may be how cultural organizations necessarily had to make decisions in a world wherein audience research was less commonplace and market research was even less accessible. Arguably, leaders had no other choice! Today, it’s our responsibility to our audiences and our missions to make the smartest, most informed choices possible.
Data can be difficult to integrate into decision-making processes, but data can also inspire leaders, and – most importantly – data helps cultural organizations most effectively educate and inspire the world.
