You Have Data. Why Can't You Decide?

0:00 Michelle Florendo

I see a lot of people say, I need to make a good decision here, I need to be rational about it. And I'm like

Okay, and can I call you out on this assumption you're making that good decisions must be purely rational?

0:22 Sam Rogers

Welcome to Signals and Subtractions. I'm your host, Sam Rogers. You have data, so why can't you decide? That's the question of the day. Most of us have more information than we've ever had: reports and dashboards and a model that will hand us 10 options and a cited brief in a minute or less now. So still the decision sits there.

Or it gets made and then remade and then second guessed? So today I have brought in someone whose whole job is helping facilitate the deciding part. Michelle Florendo is a decision engineer and facilitator. She's the founder of Powered by Decisions, and she's trained in decision science at Stanford. She's coached leaders at some of the biggest companies you know.

She's also the host of her own podcast, Ask a Decision Engineer, back for its seventh season later this month. Very excited to have you here, Michelle. Welcome.

1:22 Michelle Florendo

I'm

excited to be here and excited for this conversation.

1:25 Sam Rogers

Great. So for the audience at home, Michelle and I go back a couple years. Here's what you should know going in. She's not here to talk about AI specifically. If that's what you want to jump in on the deep end of the pool on, check out last week's episode with Limited Edition Jonathan, which was a delightful geek fest. But Michelle is here to talk about what is upstream of that, which is the decisioning part.

one signal, one subtraction from each of us. Michelle, you're up first. So what is the signal that you're watching that you'd like to talk about today?

2:02 Michelle Florendo

I am not an expert in AI, but it has been

2:03 Sam Rogers

Yeah.

2:04 Michelle Florendo

really interesting to me to watch as all of this AI stuff has been happening, how is it that people are realizing the importance of decision skills? now that we're seeing that AI can do more so much more.

as we're offloading the doing, the deciding becomes more important. And I'm seeing clients and organizations and even individuals run into challenges around that piece, I like to call myself a a yes, decision engineer, facilitator, trainer, decision educator.

if people knew some of the fundamentals of decision science, decision engineering, decision skills, a lot of these challenges may not be as frustrating.

2:47 Sam Rogers

what was a moment that you noticed that?

2:49 Michelle Florendo

there's a couple different stories that come to mind. And so in the executive coaching side of my practice, I coach a lot of leaders in tech, And I remember one or two years ago, as things are really taking off and there's just a lot of energy around like, whoa, AI can do all these things, we need to figure out what to do.

I was talking to a senior leader and he's like, you know, I'm noticing that the way in which me, my team, the teams around us are making decisions needs to change. And so he is paying attention to, okay, like we need to be able to be more fluent in communicating how we are making these decisions and when we are making these decisions and what cadence we are using. And like in the back of my mind, I'm like, yes, these are all kind of basics.

Of decision skills, like okay, how do you frame the decision? What is the expiration date of decisions? Like, what are the different components that go into these decisions? And how do you create decision records so that as things are moving quickly, you can look back at okay, what was the process for making that decision? What has since happened? And how do we want to iterate on that process since? Because things are changing, we are learning so much as things go on.

And so anyways, those are just some of the things I'm paying attention to. Later this month, I'll be running a workshop for an engineering leadership summit for a software company, helping their teams think about, how is it that we can decide differently with a different tempo given what's happening in the world.

4:16 Sam Rogers

Yeah. Well, it certainly seems timely to be bringing more awareness to, the good work that that you and people like yourself have been doing for a long time that maybe wasn't quite as in demand because we could we could kind of shove it under the rug and pretend that we're doing, you know, data-driven decision making. Where now there's an impartial witness who will basically like bust us on it if we're not doing it right.

And having the stakes raised around that means that we we kind of need to do it for real. you've talked about on your podcast how decisions have three parts. maybe we

4:49 Michelle Florendo

Mm-hmm.

4:50 Sam Rogers

could just get like a little scratch of the surface of of walking through

4:53 Michelle Florendo

Yeah.

4:54 Sam Rogers

them.

4:55 Michelle Florendo

Right. decision making is like one of those things that I find a lot of people take for granted, kind of like walking or breathing. these are these things that we learned to do even as we were little kids. And so of course I know how to do this. Yes. And we can do it better. And so I think you alluded to one of the frameworks I love using. This comes from Professor Ron Howard, who

Was one of the pioneers in decision analysis, decision engineering. And he would talk about how every single decision has three parts. And they're like three legs of a stool. And if you haven't taken the time to examine each of those three parts, your decision or your stool topples over. So one of them is objectives. This is what is it that we want to see in the outcome? Right?

5:38 Sam Rogers

Mm-hmm.

5:38 Michelle Florendo

we can feel swept.

Into this current of, there's a lot of urgency, I need to move fast. but we need to know where we are going. this becomes your compass, objectives. What is it that matters to you and the outcome? What is your vision for the future that you're trying to head towards? And it's really interesting to see how people will dive into decisions without yet even articulating what is it that they're trying to achieve. So that's the first one.

the second component of every decision is options. this is the part of decisions we are usually very familiar with. We know we have a decision to make when there are multiple paths that we can go down. But I think one of the mistakes that people make is sometimes they either fall into a binary. Do we do this or do we not? Go, no, go, to be, not to be, right? And they forget to take even just a a little bit of time.

To explore what options exist beyond the obvious. And this becomes easier, especially once you've defined what is it that we are trying to do, what is it that we want in the outcome. And then the third one, and I think the third leg is the one that gives people the most feelings, is information. you talked about how we live in an age where there seems to be so much more information at our fingertips than ever before. And so the key is.

really understanding what information is relevant, what information would actually change our decisions. So it's really what information do we have at the intersection of those options and objectives? And then also what is our strategy for dealing with the cases where we don't have information? we can't wait for certainty. Like waiting for certainty is a decision in itself and often like is one that does not lead to

great outcomes. And so how is it that we can manage incomplete information or absences of information in our decision processes?

7:31 Sam Rogers

That's great. just a few callbacks to previous episodes of signals and subtractions, in episode 12, getting really clear on that objectives part. Our guest Omar Ladak was fantastic at doing that with really reframing where I am trying to go, what am I trying to accomplish? how clear can we make those stated objectives?

the more explicit we can make it, the more partners we can gather, be they human or agentic or however, when that vision is really clear, then it becomes much easier to bring more resources into that and align them and maintain alignment.

with the information piece, I think it was episode seven, Douglas Hubbard applied information economics perspective, kind of a Bayesian

thinking kind of

8:20 Michelle Florendo

Mm.

8:20 Sam Rogers

way to approach things. and what information is relevant. So it's true that we have way more information at our fingertips than ever before, but there's other places to derive information.

That aren't out there and aren't our fingertips.

8:34 Michelle Florendo

Mm-hmm.

8:35 Sam Rogers

could you say just a little bit about that, Michelle?

8:37 Michelle Florendo

Yeah. this is another thing that's been interesting to track because when working with AI, it can be a partner, a great partner in any of those three legs, right? Like it can help you generate more options, it can do a lot of research for you. it can be a thought partner to help you hone what your objectives may be. but yet it

There are still things that it may not yet have access to. And one of the things, one of the traps that I see people fall into is thinking that, relevant information needs to be rational, easily measurable. like when you think about data-driven decision-making, like hard data type of stuff. But I'm seeing increasingly like what we humans need to be well versed in is tapping into the other types of data that exist.

like what is happening emotionally for the humans that are involved in this decision-making process? What are some of the like bodily sensory or people might call it gut instinct inputs that exist that may need acknowledgement and deciphering for what relevant data and information exists there that needs to be folded into this process.

9:47 Sam Rogers

That's great. so jumping over to my signal and

9:50 Michelle Florendo

Mm-hmm.

9:51 Sam Rogers

reflecting on something that I think we already know getting it a level

deeper, which is

9:55 Michelle Florendo

Mm.

9:56 Sam Rogers

that AI has made the analysis part really cheap. Like the

10:01 Michelle Florendo

Mm-hmm.

10:02 Sam Rogers

so much so that like deciding is basically the real job now. Options and information, the the second two legs of your stool are like nearly free at this point, but nobody's objectives necessarily arrive any faster. And

10:17 Michelle Florendo

Mm.

10:18 Sam Rogers

And I was reflecting on that when I was making the takeaway for today's episode. I did make something that is I think supportive of your work, pointing back at some of your resources

having a way to take what we're talking about today and make it actionable. there's a temptation to use

older technology like maybe a pro con list or, you know, things that

10:42 Michelle Florendo

Mm-hmm.

10:43 Sam Rogers

we can do better these days. Like there's there's more there's

10:44 Michelle Florendo

Yes, yes. The pro con list

is like two hundred plus years old. We can upgrade our tools for decision making.

10:50 Sam Rogers

Yeah, yeah, it's

time for like a a next version of that. what I'm showing on screen here now is at SigSub.show/takeaways And it's a way to leverage AI to help you identify not just what is information that usually makes it into

The analysis, but like eliciting that extra level of information that's maybe coming more from inside and getting clearer and clearer about those objectives. I was using this for a real decision just this morning to test it out, I was looking at my own startup because it's been a year.

This week, since I started building PAICE.work it's a time to reflect on that and see what it is that I want to do from here.

11:38 Michelle Florendo

what I love about what you put on the screen is that part of improving our decision processes is making the implicit stuff that's happening inside of us more explicit. And I think that, you know, external tools, whether it be AI or simple, you know, pen and paper, can be really great for that process. and even just giving people permission and an opportunity.

to sit with their decision process. I think that's something that people don't do enough, but now that people are starting to see, this is a critical skill it's important to build supports around.

12:11 Sam Rogers

let's get back to the original question that I was opening with just a little bit

12:16 Michelle Florendo

Okay.

12:16 Sam Rogers

which is you have data. Why can't you decide? Why, why, what are the sticking points that you see often? maybe take a little bit more of the subtraction angle here, what are the things that we can remove that

make

12:31 Michelle Florendo

Mm.

12:31 Sam Rogers

deciding a little easier that decrease that friction or conflict.

12:35 Michelle Florendo

I wanna name the words that you just used friction and conflict, because I think that is at the root of a lot of indecision and it's just a matter of like figuring out what is going on there. when I think about what are the things that keep people from moving forward with decisions, even if they do have data, I've seen some patterns around types.

of decisions. And so like one of the patterns I've seen are people who won't decide because they have a fear that something bad might happen.

13:04 Sam Rogers

Mm. Mm-hmm.

13:05 Michelle Florendo

And if that bad thing happens and they were the one who made the decision, then there's all these other secondary feelings about that process, whether it's like guilt or blame, who knows what it might be. but I think in there what needs to happen is okay, like again

Emotions point to needs. And so that's why it's useful to tune into, what's going on here? I'm feeling a tightness. What's that about? Like, is there an emotion attached? is it fear? What is the fear of? Is it the fear of something bad happening? okay, interesting. Well, how do we fold that back into the process? Going back to our objectives. Well, what is it that we are really trying to achieve here? okay, you know.

You're a business owner, I'm a business owner, there is risk or like possibilities that bad things might happen. That's a given.

13:48 Sam Rogers

Yeah. Yeah.

13:50 Michelle Florendo

And so I think when we're thinking about, okay, given the many different objectives that we may have, can we remind ourselves of what are the bigger, more important things here? I may have this fear of something bad happening and like this need of like not feeling too much guilt, blame, embarrassment, But is that bigger or smaller than?

the objective of being able to bring value into the world, being able to find a way to make this business sustainable, right? And then to the subtraction, well, okay, understanding what do I care more about here? And can I let go of the thing that is less important in service of pursuing the thing that is more important?

So that's just one pattern in indecision where people are afraid of something bad happening. I also worked with a lot of high achievers and a lot of engineers and they love optimization and maximization and their maximizer mindset. And so their biggest fear is not actually that something bad might happen. Their fear is that something better might come along.

14:50 Sam Rogers

I think a few of those people are listening right now.

14:52 Michelle Florendo

Right. So that it's it's not FOMO, it's FOSB, fear of something better. And so if you

14:56 Sam Rogers

Okay.

14:57 Michelle Florendo

suffer from fear of something better, again, there's the okay, you have this like attachment towards maximization and whatever better and best looks like. But again, bringing it back to well, what are the other objectives in play? I going back to the the workshop I'll be facilitating for that engineering leadership summit. That's where the high level leaders that I'm working with.

to put on this workshop have been talking about like, yeah, we see a lot of our engineering leaders get stuck in the what is best, but really we just need to move and learn. and like take that type of approach. And so again, it's you know seeing, okay, what's on the page, what what is in conflict, and can I let go of the thing that might be less important? Like finding the best solution in service of what is more important.

Just making a decision and moving the ball forward so that we can learn and iterate.

So there's that. That's just two of I think there's like four different patterns of indecision I've noticed, but those are the most prevalent ones that I'm seeing.

15:57 Sam Rogers

Well, I have a question that did come in from the live stream here,

people ask better questions before heading toward a solution, and answers up front skip that a bit, don't they?

16:09 Michelle Florendo

Mm.

16:10 Sam Rogers

there's a study cited here, MIT went through 106 experiments. On average, people plus AI did worse than.

the best of either one of them alone. And the decision tasks was where they lost. Like though those were the parts that were the weakest. do you get people to frame the question before they see any options?

and the question is coming from one of the co-hosts of the show, Markus Bernhardt.

16:41 Michelle Florendo

Okay.

16:42 Sam Rogers

Who's asking specifically within the

16:43 Michelle Florendo

Yeah.

16:44 Sam Rogers

AI collaboration kind of framing,

16:46 Michelle Florendo

Mm.

16:47 Sam Rogers

which is something that we will explore next time Marcus is

16:50 Michelle Florendo

Yeah.

16:50 Sam Rogers

on the show.

16:51 Michelle Florendo

before we even talk about those three components of every decision, there is another component which is framing. you can probably see my books back here. there is

16:59 Sam Rogers

Yeah.

17:00 Michelle Florendo

a book up here, it's a red book. It's called Decision Quality, very popular book within the Society of Decision Professionals. And if you want to go beyond the

three components of any decision and you want to go into the six lengths of decision quality, what actually goes into a good decision, you can read that book. it's those three that I mentioned. Plus framing. Yes, framing is in intensely important. And like really questioning again, like I said, I when I see people go into decision making, oftentimes they're leading with options. That leg, that is the leg that most people are most familiar with because we know we have a decision when there's more than one option. But

17:32 Sam Rogers

Yep. Yep.

17:34 Michelle Florendo

yes, it is important to kind of go upstream a bit.

to objectives and even like maybe beyond as you're figuring out objectives to that framing piece. What is it that we are actually trying to decide? What is the the problem that we are trying to solve here? And there are various ways that you can think about framing sometimes we talk about decision hierarchies and how to frame and like play with frame from that perspective.

But yes, that is intensely important because if we go in just with the options, we come in with kind of like a narrow frame. those options are not useful if the right frame hasn't been defined in the first place.

18:10 Sam Rogers

I think there's an inherent framing kind of an assumption that often gets made around insulating us from an outcome that we don't want by using a good process. So we want to like increase the outcomes that are good outcomes by making good decisions.

But like you were saying about and everybody knows, like there's risk here, and we kind of skip past that part in our framing. Like if we just do this good enough, if we if we maximize

18:38 Michelle Florendo

Yeah.

18:39 Sam Rogers

the value here, then we'll reduce the risk that something could go differently, and we get fixated on the objective being the sole measure of the decision-making quality. And

18:53 Michelle Florendo

Yeah.

18:55 Sam Rogers

And that those are kind of two different things, but it gets rolled up in a framing that's like they're the same thing.

18:57 Michelle Florendo

Yes.

Right. Yes. that's actually when when I teach about decision making, one of the first things that I will talk about is decision quality and the misconceptions that people often have about what makes a good decision. And I think you named it. I think a lot of people think like that, a good decision is when I got all the things I wanted. and I mean, like, yes, that's a good outcome.

But decisions

and the quality of our decisions is a bit separate and distinct from the quality of the outcome because you can make a good decision Right now I'm like looking on my shelf to figure, it's over here. Thinking in bets is the book from Annie Duke.

19:39 Sam Rogers

Annie

Duke, yes, big fan.

19:40 Michelle Florendo

and I love it be I

love her because I feel like she's one of the people who has like introduced like the mass population to this concept of resulting, which is where we think that whatever the quality of the outcome was tells us what the quality of the decision was, which is not actually true because if you think about it, if you decide to drive drunk and no one gets hurt, was that a good decision?

No, still bad decision. Still bad decision.

20:07 Sam Rogers

Ha ha ha.

20:08 Michelle Florendo

If you're like thinking I'm trying to preserve life, it was just a good outcome and vice versa can happen. You could have a good decision and have a bad outcome.

20:17 Sam Rogers

let's get back to that subtraction part

given everything that we've said thus far, what no longer makes sense? You know, what should we stop doing that we have a habit of doing?

20:28 Michelle Florendo

so I I I wanna name a bias I have here. I realize that like where I operate, I'm based in the Bay Area, I coach a lot of people in tech. I do a lot of work with like people who tend to be very like cerebral. And so I see a lot of people who believe that well, like they'll say, I need to make a good decision here, I need to be rational about it. And I'm like

Okay, and can I call you out on like this assumption you're making that like good decisions must be purely rational? Because I find that like when we ignore some of the, like I said, other sources of data, we are missing key pieces that need to be folded in. you talked about risk, and you know, risk sometimes surfaces as an emotion, like fear or a feeling.

And like we need to be able to name what that is. Like, what is the fear of? You know, fear of a business no longer being viable is different from fear of being embarrassed because, you know, like I care about what other people think. Like we need to be able to decode what these inputs are because they're valuable data. And I think especially as we are living in a more uncertain world, those signals are

within us and we need to be able to articulate and make explicit like, okay, what is at risk here? Is it a risk that we can weather? increasingly I'm finding that when we approach decision making, it's more important to be resilient than to be right.

where right is, I got the thing that I wanted, or I was able to predict the future, because oftentimes like that's more and more a factor of luck. and luck is unpredictable. But you know, if we can build our resilience, if we can build our decision skills and how we're moving through the process, that is really what over time will increase our likelihood of getting the things that we want in a way that we can control. We can control our process.

we can control like how resilient we can be in the face of uncertainty.

22:32 Sam Rogers

That's great. I'll throw in my subtraction here,

22:35 Michelle Florendo

Mm-hmm.

22:36 Sam Rogers

which is specifically from the AI side, to stop using AI simply as a kind of rational advisor. to add on to what Michelle's saying. just because it's the most rational choice doesn't mean that it's the best choice.

just in a meeting last week where I see people like using AI to give the pros and cons, you know.

22:59 Michelle Florendo

Mm.

23:00 Sam Rogers

we're automating for part of what is useful information, but that doesn't necessarily result in a good decision. Like that's only half of where good decisions can come from. And

23:11 Michelle Florendo

Mm-hmm.

23:12 Sam Rogers

a model can make

Things up, but it doesn't have access to like the physical feelings like you're talking about. And for anyone who wants to go back to our episode with Sabino Marquez, episode four, I think it was, where he's speaking about safety as being a feeling in the body. And

23:29 Michelle Florendo

Hmm. Yeah.

23:32 Sam Rogers

this is the CISO of CISOs kind of guy who's working very deeply with AI

and recognizes that in order to have safety, like that's not a rational thing. It's not a matter of just getting SOC2 this and compliance that and their

23:47 Michelle Florendo

Yeah.

23:48 Sam Rogers

boom, safety. There's actually a feeling that we can access. And whether that's a purely human discussion or whether we're using.

more automated tools where we can feel that pull and that aversion, this is unsafe. Like that often shows up first in the body and

24:07 Michelle Florendo

That's right.

24:08 Sam Rogers

I I feel concerned now about this decision. Like that may not be coming from a rational place, but it is a valid source of information.

that actually impacts the quality of the decision. And

24:19 Michelle Florendo

Right.

24:19 Sam Rogers

AI can't have that for you, right?

24:21 Michelle Florendo

Right. Yeah, good decisions need to make sense but also feel right. And so we need to be able to acknowledge what is happening in the feeling layer. I think in this age of AI, like there's a lot of talk about safety. and like you said, that shows up first as a feeling usually, and also about trust. And that is also something that is not like you you can't calculate your way to

trust or like what is the level of trust that is something that shows up like in our emotions and in our body and then can be decoded from there.

24:55 Sam Rogers

Cool. so coming to a close here, where we send people and and what you'd like to see from them?

25:01 Michelle Florendo

Yeah. if anyone else wants to learn more about how is it that they can hone their decision skills, they can find me on Substack Decisionfluency.substack.com. I like talking about decision fluency again because it is a skill. It can be learned. There are different like levels to it. And the more fluent you become in these decision skills, the more like

different applications, different settings, different environments you can use it in. And I think it can be incredibly powerful, especially as technology can do more and deciding becomes like more of our job as humans. it's intensely critical to learn these skills.

25:39 Sam Rogers

I am signed up to Michelle's Substack and her podcast, both of which are excellent. And I look forward to the day when the bookshelf behind her there there might even be a book. maybe. Maybe sometime.

25:51 Michelle Florendo

Working there. Working on it.

25:53 Sam Rogers

Well, thanks so much for for being on the show, Michelle.

25:56 Michelle Florendo

Thanks for having me, Sam.

25:57 Sam Rogers

for everyone at home, one thing to do this week.

Pick one decision that you're sitting on. And before you ask anybody or any disembodied agent for like the pros and cons or whatever, write down what you actually want from it. And then for each option, write down where you feel that, what concerns you, and if that points towards something that maybe isn't as clearly expressed.

in your list. That's the part that no amount of data is going to give you. So we built this into the takeaway. Again, sigsub.show/takeaways/concern-column. And that's it for the show. Thanks to Michelle Florendo for joining us. Thanks to you for joining Signals and Subtractions. Episode is out on Friday, newsletter every Sunday.

If you're listening on audio right now, please tap follow. And Sunday is issue 72 of the newsletter. One signal, one subtraction, one analogy, about five minutes to read.

Everything on the show lives at sigsub.show. One signal worth watching. One subtraction worth making. Now go find yours.