Tuesday Email: The Experiment That Doesn't Need to Succeed

Happy Tuesday!

Every Tuesday I'd like to offer strategies for the week ahead and a thought to fuel your action.

The experiment doesn't need to succeed.

We have spent our careers managing risk. Accepting that something can fail probably feels wrong, unsettling, uncomfortable.

We are trained on outcomes, on providing positive outcomes. That's what we're hired to do. But it's also what keeps us from exploring what may need to be done in the future.

The advisors who never experiment, who never allow themselves to deal with uncertainty and potentially fail, are the ones building a future on the assumption that what works today will also work tomorrow.

That assumption gets more dangerous every year. It may not be completely visible yet, but underneath the surface that crack is expanding. It doesn't mean that what we do today won't exist in the future. The question is how we do it. And I don't believe the how will stay the same.

Which leaves us with this: do we react when the shift arrives? Or do we start shifting before the expectation does?

We assess and manage risk every day for the clients we serve.

When you think about financial risk, we look at a financial plan: the risk of not having enough to retire, the risk of running out of money. What makes that risk manageable is that we understand the levers:

• Savings rates

• Withdrawal rates

• Asset allocation

That clarity feels like control. Even though the outcomes are uncertain, because we understand the levers, they feel more knowable.

We are trained on that. So when we move into territory where we don't understand the levers, we feel out of control. We try to fit everything into the box where the levers are known, where we can apply what we understand to an uncertain outcome and feel like we have a handle on it.

The reality is not every experiment can fit in that box.

When I started Benjamin and went out to raise money, I ran into this everywhere.

I talked to smart people, inside the wealth management industry and outside it. Most of those conversations came back to one problem: they couldn't get past the cash flow model. Financial analysis meant discounted cash flows. They needed to see positive cash flows to justify the valuation I was raising at. They saw negative cash flows, and they couldn't get there. Their only lens was public securities and established businesses. They wanted a pro forma so they could project out and apply the levers they already understood to something that was genuinely unknown.

What they actually needed to ask was different:

• What experiments have you run?

• What hypothesis are you testing?

• What's the next step to reach cash flow positive?

• What are the risks and how are you tackling them?

That's the right set of questions for uncertainty. Pro formas are the right tool for risk.

There's this concept known as Knightian uncertainty, and it's simply put: risk is something you can model. Uncertainty is something you cannot.

Most advisory firm decisions about new services, new technology, or new business models live in uncertainty. They haven't been done before, at least not by us. We try to apply probabilistic tools built for the world where we understand the levers, and they give us false direction.

An experiment in science doesn't come with probabilities. It comes down to one question: did we meet the hypothesis or not? The beauty of that is we learn something either way. That new information lets us move to the next hypothesis with better data, better insight, and we build from there.

If we can think more scientifically about certain innovations we want to try, we don't have to be perfect. We can accept failure, knowing it's the building block to something bigger.

There is no better data than the data we generate ourselves. When we read about someone doing something successfully and try to replicate it, we are starting at day zero. But when they're telling us about it over coffee or in an article, they're sharing from day 100.

Their perspective has been shaped by everything that happened between day one and today. For us to take that information and get to where they are, we haven't gone through the steps to earn the same lens.

The only way to get that insight is to learn by doing. The doing is the data. It's the most personalized, most unique information we have, and it's what allows us to build something truly differentiated in how we serve and how we grow.

I love the concept of single-loop and double-loop thinking. Single-loop is best understood with a thermostat. The thermostat shuts off at 74 and turns on at 68. It doesn't ask:

• Is anyone home?

• What's the weather outside?

• Are the windows open?

It just reacts. It has one response for every situation.

In wealth management this looks familiar: AUM drops, we get on the phones. Leads are slow, everybody asks for referrals. Those are single-loop responses. We see a problem and we create an action to try to resolve it. No deeper question gets asked.

The double-loop question is the uncomfortable one. It's not "how do we fix the output?" It's "is the model still valid?"

AI note takers are a single-loop adoption.

The industry sees AI coming and wants in. The lowest-friction, lowest-disruption answer is an AI note taker. Now we can say we're part of the shift and feel comfortable.

The double-loop question is harder: if you could redesign how you serve a client from scratch, using the capabilities that exist today, what would that look like? That question requires experimentation. It requires us to challenge what we're doing and get uncomfortable, because the honest answer might mean more work on top of an already full plate. That's the point.

Here's the thing: humans are master rationalizers. I'll raise my hand on that one. And that's a problem when it comes to experiments, because what happens is we start something and we rationalize why we should keep going.

That's the sunk cost fallacy. We've put money, time, and effort into something, so we must continue. Why would we kill something we spent a year and a half on? The research is clear on this: the sunk cost fallacy isn't an irrational character flaw. It's a process failure. It's what happens when you don't set kill criteria before you start.

Without kill criteria, the judgment is left to your gut, and your gut will rationalize. Kill criteria give you a metric. Something to actually analyze against. Cut and dry.

The challenge: when you're doing something uncertain for the first time, you don't know what good looks like. You don't want to set the bar too high and give yourself no chance. You don't want to set it too low and keep going forever. So you get paralyzed, set nothing, and the sunk cost spiral starts.

Instead, just show minimal progress. Does it get one click? Move on to the next version. Maybe the next version needs five. You set bands: minimum is one click, three is solid, five is a win. If you land in the low band three experiments in a row, maybe that's your kill signal. If you never even hit the low band, kill it immediately.

You're giving yourself room to learn and iterate while protecting yourself from the spiral. But you have to set this before you launch. Once you're in it, the rationalizing has already started.

As advisors, being analytical is both a gift and a burden. It's a gift in the work we're doing today. It becomes a burden when we're trying to figure out what we need to be tomorrow. If we only allow ourselves to operate in the lane of analysis, we get held back.

Johnny Ive, one of the creators of the iPhone and one of the most creatively gifted people of this generation, shifts multiple times a day between curiosity and conviction. Between playing dumb and executing with precision.

As advisors, we get on an automatic railroad track and we stay on it. We don't let ourselves move between analytical and curious.

The Futureproof advisors are the ones who know when to be each. What gets us success in what we do every day is not what will get us success in figuring out what we need to do tomorrow. That point can't be pushed home enough.

In our own firm, we've been fortunate to grow fast.

Multiple channels, real results. And that success created an expectation problem. New experiments got killed because they couldn't produce at the same rate as established channels that had years of momentum behind them. We canceled things that would have gotten us $2 million in new AUM in a year because the time and effort didn't justify it against what we were already doing. The bar was set by channels that had compounded over a decade.

I kept pushing anyway. Using analogies, talking about it, making the case. And over time, as some of those channels slowed and others sped up, the perspective shifted. We're now more open to understanding that the payoff on a new experiment might not come in one, two, or even three years. It might take five or ten or fifteen, just like the channels we rely on today took that kind of time to build.

There's a study I can never find the original source for, but it's stuck with me. Two groups of people are walking and talking. One group is having a normal conversation. The other is talking about getting older. The ones talking about aging walk measurably slower. What you're immersed in shapes what you do. Surround yourself with high growth, that becomes your only frame. It can be both a motivator and a trap.

The experiment doesn't need to succeed.

The reality is there's no such thing as staying the same. We are either declining or we are learning through action.

If we try to keep the business exactly as it has always been, we are slowly, sometimes unknowingly, creating greater risk underneath the surface.

The only way to find out where we need to be in a future that is uncertain and unknown is to learn through action in the present.

That's what the Futureproof Advisor does.

The best is ahead!

-Matt