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In various presentations, questions, and discussions at Digital Now, I've been seeing an interesting theme emerging: cause and effect are getting to be very, very difficult to pin down, and that's just something association leaders have to learn how to live with.

Some form of this question has come up several times in just a day and a half: "How do I monetize this?"

And the consistent answer has been, "Well, you don't really. You make your money elsewhere."

It came up in the session about free yesterday. It came up in a session about building online engagement today. Repeatedly, the answer to drawing financial gain from social media, publications, engagement, and many education efforts is now an indirect one. For example, you create a presence in several social media outlets, you engage with people, they build community around you, and then some of them might buy something from you. Or some of them might join your association. Or the ones who are already members become more likely to renew. Or you sell advertising to people who want to reach that market. You get the idea.

One panelist says we operate in "an ecosystem" where it's increasingly difficult to draw straight lines.

Another says he doesn't like the term ROI (return on investment) in social media; he prefers ROA: return on attention.

We touched on the indirect nature of returns on social media efforts back in November when I argued that social media evangelists have to talk to their CEOs about social media in dollar values. That was a healthy discussion, because translating social media into dollar value isn't easy, and that lack of direct cause-and-effect relationship is hard to sell to leaders or to boards.

It's why warning signs on electric fences work a lot better than warning labels on cigarette packs. The link between cause and effect in the former is a lot clearer (touch the fence, instant death) than the latter (smoke a lot, die of lung cancer 30 years from now).

Of course, you could see this all as a counterpoint to the message from Ian Ayres earlier today about the need for more statistical analysis to inform our decisions. Randomized testing is designed exactly to discern cause and effect. His point, though, is that it takes a lot of discipline and effort to track data, build samples, and test accurately, but it can indeed be done. Cause and effect, or at least strong correlations, can be discovered through data analysis.

And so maybe this isn't a counterpoint so much as it is a complement to the earlier post. As we acknowledge the increasingly complex ways in which business models for associations will work, we must grow more comfortable with a lack of direct cause-and-effect relationships. Or, if we must have those answers, our methods for connecting Point A and Point B must become more sophisticated as well.