If It Matters, It’s Observable [Outcomes Lab]

Every measurement is a reduction — a simplified picture of something more complex. That’s what makes it useful. But having the richness of our work compressed into something legible — a number, a category, a verdict — can feel like a threat to an identity or an imposition on expertise. Measuring a museum’s outcomes can make people uneasy because we naturally want to protect our work from anything that would reframe its value. If you measure belonging and find it’s weaker than you assumed, that’s uncomfortable. Calling something immeasurable keeps it safely aspirational — beyond the reach of accountability and evidence that might demand you change course. Douglas Hubbard — a risk-management consultant who spent his career making organizations better at quantifying things they’d written off as unquantifiable — addresses this resistance in his book, How to Measure Anything. He says that if something matters at all, it must have some observable effect on the world. If it didn’t, in what sense would it matter? And if it has observable effects, those effects can be detected and recorded in some quantity — even imperfectly, even with wide margins, even with small samples. That’s measurement. Most decisions we’re trying to make (and measurement is only useful to the extent that it supports an actual decision) don’t require a great degree of certainty or precision. They just need less uncertainty. We need to know more, but not everything. Say it matters for people to feel a sense of connection with their companions when they visit your museum (a Social outcome). Start with what you’d observe if it were happening: they return together, they bring someone new, they describe the experience in relational terms rather than informational ones. Now ask what you could detect — return visit frequency among groups, referral patterns, the language people use in exit comments or interviews. You don’t need a validated instrument. You need a small number of observations where you currently have zero. Even a rough estimate from a handful of weekends is an infinite improvement over the nothing you’re working with now. Hubbard teaches us that the absence of measurement doesn’t mean the absence of decisions. You’re already deciding which programs to fund, where to allocate staff time, and what to tell your board. You’re just deciding with institutional habit, and whoever argues most persuasively in the room. When you refuse to measure what you say matters most, you hand those decisions over to the things you can measure — attendance, revenue, social media impressions — by default. The metrics you’re comfortable with quietly become your actual priorities, regardless of what your strategic plan says. Not measuring means abandoning what matters, not protecting it. What are you currently treating as unmeasurable — and what would change if you stopped? In this event, we’ll spend twenty minutes reading Chapter 3 of How to Measure Anything, then use the remainder to work through that question together. — Kyle Apologies for the messy scan — If I had known back when I read the book that I’d be sharing my copy with others, I wouldn’t have marked it up so much! About Outcomes Lab Outcomes Lab is for MaP participants who have completed our Outcomes Assessment and are working through what their results mean for practice — how to act on what the data revealed, where to focus, and what to try next. We meet periodically to explore the ideas and research behind outcomes work in museums — each session stands on its own. If you’re interested in joining, use the link above to request membership. Sessions are recorded for internal reference, but recordings are not shared.