Tamsen Webster argues that persuasion fails when audiences don't believe your cause leads to your effect. She uses the Databox example to show why "grow your business" doesn't work but "make data more usable" does, and introduces the compact case framework to scale claims to what you can credibly deliver.
One of the biggest benefits of communications is that it's usually not about math, except that it turns out it is. Okay, y'all, this was not a fun discovery for me, and yet it was at the same time. Here's what I mean. When we're talking about a new idea, when we are giving people the information about it, there's a couple things that we know are very necessary. We have to make sure that the basic building block of understanding, if-then, what's known as a conditional, won't be on the test, is present. If I am recommending my idea or my approach, then I need to make sure that I'm telling you what you can expect as an outcome from that. The reverse also works. You can set it up and say, if you want 1,000 songs in your pocket, then say hello to iPod. Either way, without both pieces, the if and the then, the idea won't make sense. And if it doesn't make sense, people aren't going to do it. People do not do long-term anything that does not make sense to them. Side note: make sense does mean both intellectually, rationally, and intuitively, emotionally. Something doesn't feel right, and I can't justify it through good rational evidence and data, then I'm not going to do it. At least not long term. But there's another problem. As it turns out, you can have both an if and a then, you can have both your cause and effect, and you still may not be successful getting that idea out there because of probability. A lot of older information about how people make decisions is based on something called the mental model theory, and also based on the assumption that we humans are perfectly logical at all times. And what's core here is that we're logical in a rational, logic, like mathy way. But that isn't what the data actually show. What the data show is that people are logical but in an intuitive way. And the way that shows up is they assess probabilities of those if-then statements. To use Vince Molinaro and the Leadership Contract's primary strategy, how likely is it that if I scale accountability, that I will and our leaders will be able to successfully execute a strategic change. Do you see how those kind of make sense together? I can start to intuitively get that accountability and scale makes sense as a way to achieve change successfully. We don't break out our statistics calculators and figure it out. We just go based on everything we already know without evidence. Does this feel like it could work? This is one of the places that I see ideas and messages break down all the time because there's too big of a gap between the if and the then. One of my favorite examples, which I can share 'cause they shared it, was my client Databox. One of several defensibly distinctive aspects of their software is that it formats data contextually based on the situation, the user, what the desired outcome is, et cetera. Now, when we first started working together, their if, the thing they said that their software could do for businesses was grow their business. That sounds good. We've been sold a bill of goods for a long time now about how we have to tie everything to revenue. But stop and think about it. Now, I love Databox. They're my client. So yeah, take that as you will. But even if they weren't, there's a big old gap between business intelligence software and grow your business. Those two have to work together in order to work well. Could it grow the business? Yes. Are there a lot of other things that have to go exactly right in order for that to happen? Also yes. So this is what I'm talking about. If someone is assessing very quickly, which they do, by the way, thanks to our automatic brain, how likely is it that what you're saying is true, that I will get this outcome from this thing? We have to make sure that we're scaling that correctly. And you may know it's true, but you don't have that luxury of time with the people that you're talking to when they're hearing an idea for the first time. So what did we do? With Databox, we scaled that question much closer to what business intelligence software can actually do. In this case, we settled on, how can I make my data more usable? Do you feel the difference between business intelligence software will grow your business and business intelligence software may make your data more usable? The more usable data piece fits better with business intelligence software. That doesn't solve our differentiation problem, does it? But this is where the prime or the core strategy comes in, where that contextual formatting piece comes in. So you see, the answer to how do you make your data more usable is yes, Databox and their business intelligence software. But it's more specifically the claim that Databox is making that contextually formatted data is much more likely to make the data usable because it's going to be formatted based on how people like to see it, who's using it, what their expertise level is, etc. Once you put those two things together, contextual formatting makes data more usable. Then someone goes, ah, that makes sense. And then Databox is in the beautiful position of being able to say, and that's what we do. So as you're thinking about presenting your idea, make sure not only that you have that conditional in place, that when you do this thing, then you can expect this to happen, but make sure that the likelihood that a reasonable human would say, "Yes, that makes sense as a possible way to do that," because the very first test that your audience is gonna put your idea through is how likely is it that those two things are actually related? How likely is it that this will lead to that? Do the test yourself first and save yourself the trouble. Make sure that you've got that if and that then working very tightly together. Best way to do that? Stop trying to reach for the moon. Name the problem you're actually solving and make sure you're describing not just your product and what it is, but the core strategy, the prime strategy that's embedded in how it does that. As always, one of your first and best tools for getting started is to figure out if you can make that compact case work. That if and the then is the first two pieces of the compact case framework for the ITBA. If, then, because, and. If you want to get started with it, you can always go to getthehandout.com and download it to get started yourself. I know this was math in the middle of messaging. But you don't have to do any special calculations. All you have to do is ask yourself, how likely is it? And more importantly, how would a skeptic answer, how likely is it that our product, our idea will lead to that outcome?
