#178 Making SMARTER Decisions with Lori Silverman, author of Business Storytelling for Dummies

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Data is a tool of persuasion. Persuasion only works if you look at the research. Persuasion only works if someone cares if they're giving you 100% of their attention. They have no distractions and this is the most important thing to them. So we have to use a tool of influence. Story ins the number one tool of influence because it increases likability. And likability is what's important when we're trying to influence other people.

Welcome to Data Framed. This is Richie I'm a big believer that one of the biggest advantages an organization can get is by doing less stupid stuff than its competitors. That is businesses that can consistently make good decisions find it much easier to make money. One of the recurring themes on Data Framed is data driven decision making, where you use data to assist in your decisions. Using data is absolutely necessary to improve the number of good decisions you make, but it isn't the end of the story. On top of this, there are decision making processes that you should follow to get the best results. Our guest today is Laurie Silverman, a consultant and educator who spent three decades working with C suite teams to improve corporate decision making and transform businesses. She's also the author of several business books, including Business Storytelling for Dummies, and she's taught at the University of Wisconsin Milwaukee and Golden Gate University. On top of this, Lori is not shy about speaking her mind and is unafraid of throwing out a controversial opinion or two. I must confess, we don't agree on everything related to data, but there is one thing we wholeheartedly agree on and this is why I've been desperate to get her on the show. That thing is, if you want your organization to be good at making decisions, you need to have a framework for decision making and roll it out to everyone. And it just so happens that Laurie is the co creator of the Smarter Decision Making framework that we're going to discuss today. Let's hear what Laurie has to say.

Hi Laurie, really excited to have you on the show. Welcome.

Thank you so much for the invitation.

Excellent. So let's dive straight into it. So, to begin with, what do you think are the most common problems in business decision making?

I actually think there are six, but the first one is probably the biggest to me. So I'd like to kind of go back in history a little bit. Do you remember a time or maybe in classes that you've taken over the years where people felt that the entire solar system revolved around the Earth, Right. And then people like Copernicus and Galileo and others said, no, no, no, no, no, not the way it is. Everything revolves around the sun, at least in our solar system. That mindset shift took 100 years to be accepted. And my sense is that what I'm about to talk about with you today is that the mindset that I come with is radically different than most people in the field of data analytics and data science. I believe that we're too focused on the data and that what we need to do is we need to focus on the outcome, which is decision making and making better, more accurate, faster, smarter decisions. But what I've realized the last 10 years in communicating this message is that the way that technology firms are heading in general, are not to embrace that because the money isn't helping people with the data. And I'm just being quite frank about this because I've talked to CEOs of many technology companies, and we haven't yet kind of stepped. Stepped back and said, how good are we at decision making? So, for example, we haven't said to ourselves questions like, what's the cost of making a bad decision? Or what's the cost of making a decision and not implementing it? Or what's the cost of delaying a decision? Or what's the cost of sweeping it under the rug? We haven't addressed those questions yet. And so to me, the first issue we have to do is do this tremendous shift in mindset, tremendous shift in mindset to saying data serves decision making. Decision making does not serve data. Data is meaningless. It is meaningless in and of itself. It has no intrinsic value unless, unless you're selling it, unless you're harvesting it, unless you have a way to take that data and provide it to others and they're willing to give you something in exchange through licensing or bartering or other sorts of things. And when I think we make that shift to saying that decision making is the thing that we need to focus on, then I think we will actually leap forward light years in terms of the results that we have in organizations and our desire to embed data, at least a data informed mindset into all people in the organization and the DNA of the enterprise. And so I think the comments I'm going to make next in terms of what I think some of the common problems are, are because this hasn't happened yet, if that makes sense. Because this mindset shift hasn't happened yet. So I want you to think about the following decisions. Just like problems are all connected to business processes. Now there are three sets of business processes in organizations. There's the daily workflow that work teams own. There's, there's cross functional processes which cross a number of different parts of the organization. And then there are strategic processes within organizations. I remember saying to a CIO one time a couple years ago and my government client, he had brought in a firm to map all their business processes. And I said, are you mapping the decisions that are made in each process within these process maps? And he looked at me and he said, laurie, that would be too much work to take on right away. And I said to him, mark my word, if you do not do that, you will not be able to embed this mindset shift about who's responsible for making what decisions and getting employees to take ownership for their own decisions and their own data and making decisions real time with the data that they have. And I think that's where most organizations are today. I would venture to say that if I went into any organization or I said to anybody who is listening to this right now, we're taking it in advance. So I can't do that. How many of you have mapped the decisions to the business processes so you know where decisions are made and who should be involved? Nobody would raise their hands. That's just me. That's suspect. I don't know what you think. Instead, what we're doing is we're kind of separating data analytics and data science from the organization. We're making it like add on work. I just put out a post this weekend and I said, what sorts of decisions are best served by data analytics and data science? And except for one person and maybe two people, almost everyone to a T told me about the tool, not the decisions. Like multivariate regression analysis could be used for this or predictive and descriptive analytics could be used for revenue forecasting. They didn't tell me about the decision that needs to be made. So we're still focused like on tools and data and use cases. To me, kind of take the work that we're doing and we're Projectizing it. We're not embedding it in the DNA of the organization. We're like projectizing data analytics, projectizing data science. And then we wonder why we don't have data literacy throughout the enterprise. Well, how can we? How can we? I even said to someone this morning on the post, I said, does any business leader. Maybe you could answer this for me, Richie? Does any business leader use the term use case?

Maybe not so much.

Maybe not so much. But would leaders be talking about problems and decisions they have to make?

Absolutely. That's kind of interesting that the language is going to be very different from a data practitioner then to a leader. So actually you mentioned a moment ago just the idea that you want to employees to take ownership. And what it sounds like you were talking about there is that the data practitioners are trying to come up with analyses that will support decision making, but they're not the decision makers themselves. Do you see that as being a gap between practitioners and decision makers? Like the different people?

Well, I have to go back in my own history. So in the late 80s, I used to supervise groups of statisticians and organization development consultants who would go into organizations and try to improve the quality of various businesses. That work is not much different than what people are trying to do today. But what we did that was different was we embedded it at the front line of the enterprise. We didn't say, well, let's go set up a department and the department will do all this work with these experts. If we set up a department, those experts were meant to embed that thinking throughout every single business function, throughout every single employee's work. So the employees at the front line were involved immediately. Give me an example of an organization today that's done that in data analytics or data science.

Sort of bring everything to the front line.

You mean first? First, first. Without setting up a chief data office, without setting up a data analytics function, without setting up a data science function. Because what I see is kind of the opposite. And I've talked to a lot of people, I've interviewed lots of people around the world about this. They'll say, what happens is one person gets hired into an organization to do this work and then they go to the C suit and say, there's too much work for me to do, so I need to hire a few more people. Then those few more people say, well, but the work has specialties within it like data management or data strategy or data quality. And so now we need to create these like little mini functions under this little bit of an umbrella. And we start growing this function, we're not thinking about embedding it at the front line of the organization.

So are you suggesting that there ought to be more data capabilities or decision making capabilities within perhaps commercial teams then? Is that, is that your suggestion within frontline work teams?

Frontline work teams own their business processes. They are the ones that we should be serving, meaning that we should be teaching them within their business processes, with their leaders, how to make better, smarter, faster decisions each day with the data that they produce within those processes. And I've done that. I've set up whole organizations like that 30 years ago, and I don't see it happening today. I just, it's very frustrating to me. For some reason we just seem to think that we can set up these departments or entire fields of study that are completely separate from the business itself. And I'm not quite certain why, but it's causing us huge problems.

It does sound to be like a bit of a problem. If you have like data being completely separate from business, there should be some sort of integration there. So maybe you can talk me through. How do we get towards that?

Well, for me, it has to do with having a robust method within the organization that's documented for how to make better, smarter, faster decisions that are informed by data in a collaborative manner. And I don't use the word driven by data. And the reason I don't use that word is because we know through brain research that decisions need emotions to be made. Now, I'm not talking about routine decisions that a business process might process like a thousand or a million times a day. Right? Those are kind of like transactional decisions. I mean, you can automate those sorts of things. So let's just leave that off to the side. But there are a lot of decisions that people themselves have to make within an organization, and they're making them hundreds of times on a daily basis. We just don't think in that way. And so to me, in order for us to bring what I'm talking about to an organization, first of all, we need to map decisions to business processes. And second, we need to be able to then say, documented, what's the process that we're all going to agree to? And you tell me this, you've been in probably in more meetings than I have. If I were to go into a team that right now has a use case situation and they're sitting around the table using data science, data analytics, whatever, and I work to say to each of them, on the piece of paper in front of you, write down the steps in the decision making process that we're going through and what step we're in right now. How many people do you think would have the identical information on the paper in front of them?

I think it's going to depend on whether this is your day to day kind of thing or whether this is a more niche situation.

Right.

If it's something that everyone's doing on a daily basis, probably people are going to come up with a similar idea. If this is a one off project or something new, then you're going to get.

It would be a little bit different from what I hear from audiences. When I've asked this in front of audience I was in April, I was user conference for a tech company and the CEO on stage for the same presentation in front of him. I said to all the people in the audience, how many of you have a documented methodology for collaborative data? Not one person raised their hand. And I said, how many of you think if you're a colleague and you were to sit down and say to them, you know, here's the process I think we're going through that it would match with them and people didn't raise their hand either. And that is consistent. That has been consistent for me ever since I started doing this work in 2014. That people, unless the group that says, you know, we're going to use we're data science, we're going to use the OCM approach or we're going to use the scientific method or we're going to use something else and we know that we're going to talk about what step we're in. People are oftentimes not in your point. They might have a generalized understanding that's similar, a generalized. But they probably will disagree on the nuances of the steps themselves. Yeah. So for me, I think you have to have a documented methodology and it needs to be robust because as I said team, they can be automated. I'm not concerned about decisions. What I'm concerned about are either the day in and day work decisions that people are making. Is there something going wrong in the process? Can I catch that in advance? Is there development which is a more strategic decision or we're looking at revenue and for some reason revenue is going down, but we don't understand why. By the way, just as an aside, one of the other issues I see in all of this is I cannot tell you how many people are working in the field of data that don't understand the fundamentals of statistics. And if you don't understand the fundamentals you don't know how to interpret data. Because if you're not, if you don't understand the difference between special cause, common cause, and vary what variation is and know how to do control chart, you're not plotting your data correctly. If you have data over time, That's. I just, I just want to add that piece in here. A huge, huge. That's a huge issue for me.

Yeah. Actually, that's something we see at datacamp is that a lot of people, when they're getting started learning data, we don't teach statistics first is more difficult. But at some point, if you're going to be a data professional, you really do need to get the hang of statistics and understand things like causation. Otherwise you're going to make a mess of things.

Well. And you're going to use the wrong data visualization tools. I mean, right. A control chart that I'm talking about is not a trend chart, a control chart. I can look at historical data and I can see when something's gone wrong. Now, hopefully I'm looking at data real time. See, I'm used to working in organizations where data was looked at real time. And I'm talking 30 years ago, people did this. We didn't need the automation and the tools that we have today to be able to do it. We had other methodologies that we could use to look at this every day. And people could make decisions every single day about how things are going. We somehow seem to have forgotten how to do that, and we're trying to recapture that in organizations. And so where we focused is we focused on forecasting now instead of. Because that nobody's kind of doing. When the work groups actually are making decisions daily which influence those forecasting decisions, we need to be looking at having them look at their decisions as well. But in terms of a methodology, I mean, so what kind of happened to give a little bit of a historical perspective here is in 2013, my colleague Karen Dietz and I wrote a book called Business Storytelling for Dummies. And we put a chapter in it called what to do with Data. If I had the chance, I'd rewrite that whole chapter today with what I'm going to talk about here. But that's beside the point. So if you get the book, everything but that chapter you can read. And we've updated the brain research that was in it too, in 2014, because the book came out in December of 2013. In the beginning of 2014, I printed off every single article I could find in the data analytics field because I'm a strategist and futurist by background, so I look for gaps, and that's why the book was written. It's like there was a gap in the industry. I've written a couple of other books in business storytelling, but there were more gaps to be filled. But I sat down with all these articles and I said, whoa, there is a huge. There are a couple huge gaps in this field. Number one, nobody understands brain science, which. And the short and the long of it is that the brain hates data. Brain hates data. There's tons and tons of research. One of the articles that I've recommended that people take a look at afterwards is this one. I just printed out the COVID page of it. In it, for the first time, I actually wrote down all the research that we look at in the field of business storytelling that impacts decision making and data. But the brain needs data.

Can you expand on that a bit? Is there a particular type of data that you think the brain hates? Like I can imagine, just staring at tables of numbers?

No. The brain shuts down immediately. The brain shuts down literally when people say it goes in one ear and out the other, they are telling the truth.

Okay, but something like visual data that's a little bit more amenable.

You see an image, then no data. Visualizations are still data. The brain, the human brain prefers narrative story with no data in it.

Okay, go on, talk me through this.

Let me give you a study that talks about this, and it's been done, replicated over and over and over. And if people have heard me before and they've heard me talk about this. So I want you to imagine that we're all part of a research and we're in college because this is where this research has taken place. So we're students who need to make money. So we sign up for these science experiments, right? And they're going to pay us at the end of it. And the gist of what happens is not important. But what happens at the end of the experiment is really the true experiment. At the end of the experiment, the group is divided in three. The first group gets in an envelope, five US $1 bills and a letter. That letter is a story about a little girl in an underdeveloped nation who has no clothes, no food, no education, no lodging. Would you please donate? The second group is given an envelope with five US dollar one bills and a very different letter. That letter says, here are the statistics around organizations that serve the millions of children around the world that have no food, no clothing, no Education, no housing. Would you please donate? The third group has given an envelope, five US dollar one bills and they're given a combination letter. The story about the little girl and the statistics about the organizations that can serve her and others like her. Would you please donate? And the question I ask everyone in workshops and keynotes that I give is, which group do you think gave the most money? The first, the second or the third? What do you think?

Almost certainly the first one. Where it's just the story about the girl.

Absolutely. I mean, anytime you add data, even to a well constructed story, brain shuts off. Now what's happened is there's been an entire field of data visualization that has risen in the technology industry that doesn't embrace narrative story. So quite frankly, I gave up a few years ago, I gave up trying to teach people how to do this separate from what was going on with technology companies because I said, I'm a single person, my colleagues are individuals as well. It would take us 100 years to try to change this mindset, let people go off. They will not be successful. They will almost always say, hey, I've got this great insight and nobody's listening to me. Or I've got this great insight, it's not being implemented. Or I've got this great insight and the senior leader changed his or her mind and did something different. And I'm like, I'm not surprised, I'm not surprised. You're trying to use persuasion. Data is a tool of persuasion. Persuasion only works if you look at the research. Persuasion only works if someone cares. If they're giving you 100% of their attention. They have no distractions and this is the most important thing to them. Now you tell me if those four things exist in people who are listening to data all the time. The answer is no. They're distracted, they're looking at their phone. This is probably not their top priority. They might not really care about this. All these other things are going on. So we have to use a tool of influence. Story is the number one tool of influence because it increases likability. And likability is what's important when we're trying to influence other people. So that's a huge shift in how we currently, today even do we collect stories up front in the decision making process. And when we have a data visualization, a data visualization is great at suggesting what the insights might be to us. That's it. Then we need to add another step that says, here's the narrative story. What narrative story will best communicate that Insight. And it's either a story I'm going to tell or I'm going to use a story prompt and I'm going to pull that story out of you. That's what we'll get change and action to happen.

This is interesting. And maybe you're going to get to this one. I mean, I'd love to talk about like the, get into the methodology of how we do this. But before that, just a question. So you're talking about using stories to persuade people to influence people to influence people in a way that data doesn't really work. But it seems like there's a difference between using data to try and understand what's happening and data to influence people and influencing and understanding. Are they two different steps?

Well, actually there's a difference between data sense making and meaning making. Now those terms might not be familiar. So when people see data they go huh? When you give them new knowledge, they go, oh, I understand. It's only when you give them a story that they go, oh. So what you want me to do is X, Y, Z. And where the field of data is right now is we're at the data. Huh? Okay, I see that, I see that. And then we get into debates about whether the data is the right data or the wrong data or did we use the right analytical tools or the right analytical techniques. We debate, we debate over and over and over again. That's what data does. Data causes debate story, which is about causing meaning inside of people in the unconscious brain because. Cause that's where the meaning making takes place, moves us to action. So my question is what are you after? Are you after debate or are you after dialogue and action?

What are you after and how do you make sure that your story's the right one because you don't want to influence people to have the wrong action.

You and I could talk about that for hours. I think that's a separate show. How do you decide that's a phenomenal. No, I just want to say it's a phenomenal question and it's the question that people do not ask. But when you find the right story or stories, because each stakeholder group might need a little bit different story to hear, you will move people to action.

We'll park that one then like worrying about the wrong story. Let's get into methodology. So talk me through, like why you might want some sort of methodological framework for decision making.

So to me, if you don't have a step by step methodology, there's no way you're going to be able to improve decision making. It's no different than for those people in the audience who are foodies and love to cook. You might have a recipe, but almost every person, if they've made that recipe more than two or three times, improves it in some way for their taste, so they're making changes to it. If you don't have a documented methodology for decision making, you can't improve decision making because each person is going about the process differently. We actually call the process that Karen and I developed smarter. So it's an acronym for seven different phases in the process itself. The first phase is what we call seek context. And what we're doing here is we're looking at things like what's the business value? What's the decision that you're trying to make? And I'm not talking about a decision that's as generalized as we need to how do we improve productivity? But I'm really talking about how do you take that question and actually refine it so it's actionable? I have an actionable decision for us to make. And as a part of that, we're also wanting people to talk about what's the level of pain and urgency for this decision to be made. Because if I have a business leader who says to me, I need to have made this decision yesterday, I don't have six weeks to clean up the data. I just don't. So I then have to think about, well, what do we have available to us and what can I provide you immediately? And I also want to understand how urgent this is on their to do list. If it's not urgent, then I'm not going to prioritize it either. But we oftentimes don't talk about that piece. So what I'm doing is I'm embedding the organizational change process up front in trying to understand what it is that we're trying to do now within a work group that owns their own decisions, they're already going to have set the context. Although probably from a change perspective, not so much. Because if there's a group of 30 employees who work together, there's probably a couple people who are like, no, I don't know. I know the date. That decision might be an important one. But if you actually make a decision about that, that might impact my job, and I really don't want to have the answer to that. So there is. There are some organizational change pieces there too. We're also talking about who's the target audience for business value, so who needs to be involved, right up front, who are the people who own the decision, who are the people who have input into the decision and who are people who have to implement the decision? So those are the stakeholder groups I need to involve up front and I need to, if we're doing this as a team, I need to get them involved right away, at least get their input.

This is interesting. This sounds like a lot of these questions like design, who the stakeholders are and what the sort of the scope of this is. These sound very much like project management questions to me. Is there some sort of overlap here in the.

Well, they're just good business questions that you need to ask all the time if you're interested in making change happen.

And are there any common mistakes that people make at this seeking context stage?

Yeah, they skip it.

Okay.

Or what happens is. And I've seen this happen with, I've worked a lot with CEOs and teaching them this methodology. And what CEOs will often say to me is, I already know the answer. I might be asking the question, but I don't really want the data. I know the answer. I want to know that in this step, if someone already believes they know the answer, then don't waste my time, go implement it now. You have to make certain that it's a decision that can be changed if it's wrong. Like you gave me a wonderful article from Jeff Guizos where he talks about there are some decisions that are non changeable, like increasing people's pay or union bargaining decisions. You're not going to change those once they're in place, they're in place. So you better be really, really clear what they are. But if I have a business leader who's bent on this is the way it needs to be done and I don't. Yeah, I'm having you give me the data because everybody tells me I have to do this over here. Just go do it, go do it now. Maybe I'll make a pact with them. And I have done this with business leaders. I'll say, and this is going to sound funny because this is just me. I'll say, pinky swear with me. You think you have the answer? Give me three days. Give me three days or give me whatever. One week. Can you hold for one week? Let me see what I find in one week and I'll come back. And then if my answer is different than yours, will you be willing to listen to the insights that I find? Yes or no? If they say no, I say just go ahead and do it. But that's what's different. And that's one of the mistakes, is that we skip this conversation.

Okay. I'm now really curious as to whether doing a pinky swear with a CEO actually works.

Yes, and for me, it does. I'm a woman. I can. I'm sorry. I have really good relationships with the CEOs I've worked with over the last 35, 40 years. But I'm just saying it's kind of like it's this. Well, how do you have. How do you say to a business leader? Because it has to be funny. It needs to be a little humorous here, right? Like, humor me. I might even say, humor me. What if you were wrong? They might say, lori, I'm never wrong. Yeah, well, maybe you were once in your lifetime. You know, can you afford to be wrong right now? That's that. Can you afford to make a wrong decision? Can you afford to be wrong right now? And can you wait a week? Can you wait a few days? Can you wait a little bit of time and have me get you some insight and see what I find? But that's predicated on a mindset that says the decision is more important than having clean data. The decision is more important than having all the data. See the difference in this? So a little bit of a shift.

Absolutely. So definitely you need to make sure that there is actually a decision there. All right, so that's S and seeking context. What's the M in smarter?

The M is manage the data. So really it's all about collecting and organizing data and answering the question, do we have the right data? I think the hard part for people here is going to be that intuition is a form of data, and you need. You probably would have gotten a little bit upfront from whoever is the stakeholder, but you need to listen to people's gut and what their gut is telling them. If you tell me which is what people do, that we have to take all intuition out of this, then what you're saying to me is tribal knowledge does not matter. And tenure in the organization does not matter. That your learnings over time or your gut feel makes no difference. All of us in our life have examples when our intuition has served us well or when we haven't listened to our intuition and it's served us badly. I want that data so you can take this tangible data that you all, everybody who's on this video uses, and I want you to find out what this is, and you need to merge them together. Nobody's doing that right now other than the people. I mean, I'VE done lots of workshops over the last 10 years. So people that I've trained, I pray and hope that they are combining those things together. But I don't know of any decision methodology that combines those two things together.

Okay, that's interesting. All the Bayesian statisticians probably put their hand up right now.

Yeah, yeah, I get it, I get it. And they're going to scream at the next phase of this process as well, which is assure confidence. So we've got seeking context, manage the data, assure confidence. So the question that's being answered here is, is this data valid and reliable, considering the source? Okay, okay, so let me explain this. Several years ago, I'd been hired by a technology company in the Ukraine to do some online training with their business analysts. And the business analysts included business leaders who wanted to join in the conversation. So I interviewed all of the leaders, and I had the head of. I believe it was head of sales say something to me that was just. That never left. Never left my stream of consciousness. He said, corey, my guys will call me up and they'll say, hey, we have an insight. We have an insight that'll help to solve this problem or help us to make this decision. And then they'll just, like, rattle it off. Like three or four of them on this call with me. He said, but what they forget is that the person who's giving me the information or the person who's touched the data is as important as the data itself. If I don't trust them or I don't trust the people who are collecting and organizing the data, I probably will not buy into what they're saying. There's a people component to this. And I just. I stepped back and I thought, wow, we don't think about that because that's a political issue. Right? I mean, in some ways, within an organization. So you kind of have to say, when you're looking at data, who does this person trust and not trust? Who's going to have their hands in this? Or who do we say was involved so that we can mitigate that barrier or that constraint? Because he said, most times he goes, if I trust the people, I go, yeah, go ahead, go do that. But if I don't trust somebody, I go, mm, let me think about it. He said, and that. Let me think about it. So I'm not gonna do nothing about it. So, I mean, here is. I mean, and I've worked in the field of data quality, so here is all the questions around integrity of data, data quality. How confident are we, How Much do we trust the data? All the things that everybody again, understands. But you gotta look at the people component of this too.

Absolutely. Although it is sort of worrying if you've got people analyzing data where you think actually they're probably not qualified to do this. So that suggests that you've got some definite sort of human resource maybe process issues there as well.

Yeah, that's that. Therein lies the dilemma. Right. So just know that people are using that as a form of input into their decision making process. Okay.

All right. And what's the next step?

The next step is the R in smarter, which is reveal insights for us. We believe that data sets have three different types of insights that can emerge. You can have knowledge insights, which is the reason or the purpose or the cause of something. It's really what I said earlier, it's about making sense of the data. It's like, so what's the cause and effect relationship between these two things? Well, here's what it is, by the way, that is not actionable. So again, if that's all you get out of your decision making process, you might not have had the right question up front. However, if you have the right actionable question up front, you probably are going to either reinforce knowledge or bring forward new knowledge, but just know it's not actionable. So I want to know that. The second thing I want to know is know what we, as we call current state insights. What is the most important decision that needs to be made and what's the insight around that for actioning today? What can we do today? And then the third type of insight is what we call future sedate insight and that's around innovation. Is there anything, any insights that came out of our, the work that we did that could be considered an innovative item and do we want to handle that right now or not? Or do we want to log it someplace? So three different types of insights. Again, what I don't encourage people to do is stop at new knowledge. New knowledge is going to get you nowhere. That's when people going, uh huh huh. Okay, okay, I understand.

I like the idea that you don't always just get the insights that you wanted to make this particular decision that you're trying to get to. But you might also find other interesting things as well. And that's scope for future projects.

Maybe, maybe, maybe. Right. But what I want to do is I have to have a way of logging those sorts of things because over time if we start to see some repetitive things about some innovations, then we've got the reinforcement to start asking for something new in our budget, or we've got the ammunition to say we need to reframe what people are doing, or we need to put a team together to explore this in a little bit more depth because we're seeing this too many times. And so we don't want that to be lost. But I think that the real issue becomes is that the current state insight, the change we want to make today, has got to be related back to the question from earlier. That's the meaningful insight. Because what you're talking about, the nice to have insights, are potentially the innovative ones. So we need to know how. So it comes back to a question. If I can now deal with the question that you asked earlier, because in the next step this will become important. How do you know which story to tell? It's around the insight you're trying to communicate.

Okay.

And so at least that's the first cut at it. Which ones are the most important for us in terms of actioning them today, if that makes sense. And I might have to share stories around new knowledge as well, or the reinforcement of knowledge, because we might have new employees who don't understand or new leaders who don't understand something.

Okay, so you've gone from insight to we're trying to turn this into a narrative now.

Well, the narrative actually happens in the T and smarter, which is taking a stand, but that transition is happening. So to me, what we really wanted to do with people is to separate getting the insight, which is where data visualization can be extremely helpful and where you kind of need to know statistics. Going back to earlier, using the right tool to visualize the data, that just gets you the insight. That's all it does. And it can get you multiple insights. When you go to take a stand is when you're starting to tell the narrative stories and that's where you're getting people. And we say take a stand because this is where people need to make the most important decision. That's what you're driving for. And you're driving for alignment around that decision. So there's an actual step for that. And then the E and the R of smarter are actually quite interesting because this is going to take you back to your earlier comment. Oh, this feels like project management. The E stands for how are we going to execute the decision? And the R for when we execute the decision. How are we going to collect data on the results and relay those results to show how successful we were with that decision? So it's kind of bookended in your Nomenclature by the beginning of what you call project management and the end of it. But to me those are part of organizational changes, they're not part of project management. If you want to make a change happen, you need to do the front end and you need to do the back end. It's not enough to make the decision without us then saying to each other, okay, how are we going to make this happen? Who's going to be in charge? What's the plan going to be? Do we have the resources? Because that's the next thing. We could come up with the most brilliant current state insight and then realize we don't have the resourcing to do it. And that can happen at a work group level. It doesn't even have to happen at a strategic organizational level. Can happen within a group of five people and then they're like, crap, now what do we do?

Okay, that does seem like a problem if you realize that you don't have the resources like towards the end of the project you need to have like decided, I guess upfront, like do we, do we have this to begin with? So again, that's about seeking context to begin with.

Well, so what I do up front, and I'm so glad that you said that, what I do up front is I will play with the person who owns the decision and I will say what are the potential outcomes for this decision and are you willing to live with any one of them? Because that's the front end. Now does that make sense on setting the context? That's a piece as well, but that's organizational change. But again, if I'm doing this work within a work group, the work group is probably having these conversations on a daily basis. If I'm doing this as a one off, we're sitting in this department and we've been asked to do this use case situation. That's a little bit harder thing because now I've got to start figuring out a lot about who the different stakeholders are and who's got ownership of this and who's going to execute. And it starts to get very complex up front.

So we've got to e we're executing and then we've got a final R to cover.

Right. The reveal insights is what are the results of the implementation itself and are we relaying those? Back when we actually started doing the steps to execute the decision, what results did we get from making this decision? But it really comes down to is, did we make the right decision? Yes or no?

Okay, yeah. So you're doing some kind of post Mortem, was this a good idea or not?

Right. But again, I like to see this all embedded at the front line of an organization. So because this is part of people's daily work, when you start to make this, what we're doing today with data, which is making this one off, off to the side, trying to do it, and we're not embedded within the business to do it, it makes it a lot harder to have these types of conversations to control any piece of this process, quite frankly.

Okay.

Which is why I, like, I was just talking to someone recently who took on a new job and is a data leader, a new data leader within an operational function reporting to the coo. And I'm like, yes, that is so cool. Like directly in finally, or not directly, because he's like one level away. But I'm like, that's, that's what we want to start seeing is how do we get this embedded into the core of what's going on? Rather than having it be attached to technology or IT or office's own separate function reporting in, we need to integrate it into the business itself, which would make some probably Chief Data Officers not be very happy with me.

Well, they can change their title to Chief Decision Officer. It's same acronym.

So let me tell you something. Let me tell you where that that term came from. I actually. Because you had a hint about what I was going to say about this. I was prepping for a keynote at three conferences. I think it was 2018, 2019 timeframe, I can't remember which year it was. And I was interviewing people who are going to attend the keynote. It was three conferences combined in one, and I was the opening person. And a gentleman in Venezuela said to me, if I were to buy into what you're saying, then what's the role of a chief Data officer? And in the moment I said chief Decision Officer. That's where it came from. Because the real question becomes is who has ownership of how successful decision making is in the organization. One could argue that every single business leader should have that ownership at their level. But who's improving the process of decision making? Where does that come from? Now, you could try to give this to a training department to have ownership of, but it's probably not going to. I used to head up a training department, Gobsy, years ago. That's not enough power in an organization. It needs to be someplace where someone can say, this is the process we're going to use and it's robust. So you might, you're not, you're going to do all seven phases, but the steps that you do underneath them might differ or you might quickly go through them. Like if you only have two or three days, you got to figure out like where you're going to place your time versus if I have three months of time to try to figure out something that's really a sticky wicket. Probably a much more strategic decision that could have tremendous influence on our business. Such as I had one years ago. I was working with the board of a healthcare insurance company and they had to make some decisions. They had opened up facilities in other counties in the state that they were in and it didn't appear to be going well. And that's a really hard thing to do, is to pull out of resourcing communities with health care. And that was a tough decision that took us quite a bit of time to make because we knew it was not reversible. Once we did it, you either had to be all in or all out.

So actually that leads me to my next question. It seems like there's such a wide range of possible decisions in business. So it goes from like the very simple, what should we order for lunch? Up to like, how do we do something complicated now, like a merger or something. The business, which is irreversible and very difficult. So with your smarter methodology, is there a type of decision that it's optimized for? Is it for big decisions, small decisions? What's the.

Well, that goes back to what I said earlier. Simple routine decisions. Like a customer is filling out a form to complete a purchase and if they miss the zip code, does it come back and ask them for it again, that sort of decisioning process, which is embedded right within the online system, you're not using this process. For now, if we stay with that example and we're finding that people are not completing their sale and we don't understand why, then that's a decision that this particular methodology becomes useful for. But to me, again, remember where my mindset is. My mindset is everybody at the front line of an organization should know how to make better decisions. They're making decisions daily about the work that they're doing. There are some decisions that are going to be need to be given a little bit more thought. Those decisions embody this framework. So those are what I call daily work decisions. Decisions that cross functions almost always need a methodology like this because there's too many stakeholder groups and too many people that you've got to kind of bring together and align on the decision. So things like new product development for Example might require a cross functional group to study whether or not the data is showing us that we should innovate in a particular area. I'm not talking about actually making the new product, but the decision making. I'm a strategist. That decision making process in front is a really thoughtful one that we have to do. And then there are other strategic decisions in an organization where this methodology is absolutely critical for decisions on policies. Are we going to follow regulations? How closely are we going to come to skirting legal issues? I mean, those are the realities of working in the C suite. And you really have to think long and hard and you need some sort of methodology to follow so that you know that you're covering all the steps. The interesting thing is, Richie, I've been going through all my files since I started working and oh my gosh, in the late 70s, early 80s, and the very first article I wrote on decision making with a decision making process in it that I developed with a C suite group was in 1988.

Okay, so it's, it's been being refined for a while then.

Yeah, it was kind of like, you know, I, when I went through my files, I'm like, oh, I got to keep this article for past year. But we created a decision making process for deciding on policies within the business itself. So it was specific to that. But if you look at the methodology, it mirrors many of the steps that I'm sharing with you today.

So it does sound like from what I'm hearing, there are two cases where this methodology is really important. First of all is if it's a high risk decision, like there's a lot of uncertainty. Particularly you gave the example of if you've got several different teams involved or if it's high impact. This is something like the C suites involved with. And those are where having that methodology is going to give you a bit more reassurance that things are done right.

Right. But I see it being used at the frontline level. I don't want you to dismiss it. With daily work, we want people at the front line. We don't realize that a single employee could make a decision that could influence the future of our business by either doing something or not doing something. I have seen it. I have worked across 25 different industries in my career with multiple types of organizations from as small as 16 people to as large as a million people. I have seen where a single person's decision has caused wreaked havoc and everybody thought that decision was small. So I just caution you on saying that I Don't want to use it. I'd rather people embrace the mindset of it and then say, with this decision, how do we roll through this process? Again, we might not go into the depth that we would if it was a high risk, high monetary decision, but at least I want to make certain that we didn't skip something along the way, that I've got the right people involved, that we've looked at this, that we understand what the insight is. Because otherwise, what you were doing, then if we're not using it, is we potentially might just be using only intuition to make the decision, which is what we don't want to error on either. We want a marriage of the two pieces, our hard data and our intuition.

Excellent. Okay. And for organizations who are wanting to get started with being more methodical in their decision making, can you maybe give me an example of, like, what you do first if you want to implement smarter?

What I've been doing with organizations over the years, which is they just want to learn the methodology. So I say to businesses, and I've done this for professional associations as well, is give me. I say, give me what your audience would call a use case. So give me a use case situation where that maybe a company has already gone through or they're in the middle of give me all the data. And then we take that in a workshop setting and we work through it with people in the audience and we go through all the steps. Because until you've gone through all the steps and you actually are forced to kind of understand what each step is by practicing it, you don't have a really great feel. I mean, you can read. I wrote an article. I did this because I wanted to codify the methodology. So Cutter was really nice to publish this article for us. It's part of the resources that I gave people as well. And it goes through the methodology and what I've shared today and maybe a little bit more depth, but just reading it isn't going to get you very far. So I think the challenge for everybody here is mindset. You got to go find. If you think that this is worthwhile, you have to ask yourself, who else do I need to tell this to? Who else do I need to educate on this? And then. And I actually wrote a chapter on this for women in Analytics. Kind of like, how do you do the grassroots approach to this is go find kindred spirits who believe that there needs to be a shift from a sole focus on data to a focus on decision making. Go find those kindred spirits in your Organization kind of form your community of practice group. Either decide to use a methodology like ours that we've developed or create your own methodology, or find a different methodology and tweak it. I don't care what you use. And then figure out which executives in the organization you need to influence just like you would for anything else. Now people might be saying to me, that's not my job. I was hired to do xyz and I'd be like, anybody can do this. I have seen in organizations where a single person has caused tremendous transformation because they've gone and found the right people in the organization who saw the necessity and need to do something. And I think that this is the same way. But you have to have pretty savvy emotional intelligence, EQ skills. Right. You have to know how to influence people. You have to know how to tell the right stories. And the right stories might be around decisions that we have made that have caused us a lot of havoc. I might be telling stories of pain, a lot of pain in organization.

Yeah. Certainly if you're not good at making decisions across your organization, I'm sure it's going to be pretty painful. And certainly getting people to change how they're making decisions, any kind of change management, stuff like that, it's gotta be pretty brutal, right?

But I think that even more so, we don't want to admit that we're not really good at decision making.

Absolutely. And I suppose very few people make every decision wrong. Or at least like if that's happening on a corporate level, you're going to go out of business pretty soon. So I guess this is just about trying to improve your hit rate, trying to improve the fraction of decisions that are good ones.

Well, and I remember very early on in my career the first CEO that I worked with when I was a consultant, so this would be 1988, I said that the beauty of it was that he walked in one door of a meeting room with the executives in his business and I walked in the other door of the room. I was the new consultant that they had hired. And he said to me, because the business was a cash cow within the larger enterprise, huge cash cow, they were taking money out of it left and right and head for years. And he came in as the new CEO to tell them that they were about to go under, but they were no longer going to be the cash cow. He figured they maybe had three to five years, maybe three years, but that they were going to plummet and that they were going to lose everything. Now how do you tell that message to C Suite, you know, people who've been successful. Right. And when he and I met separately for the first time, he said, Ms. Silverman, I just want to let you know that for most CEOs, if they get a decision right, it's dumb luck. He said, we can't use dumb luck anymore. We can't rely on dumb luck anymore. We have to be much more methodical and rigorous. And we were in his organization, but we still could not move fast enough. And he was correct. We downsized that business tremendously. I worked with them for almost five years, tremendously, because they took huge hits. But at least he saw the handwriting on the wall and was willing to do the hard work within his enterprise, given what I'm talking about today.

Okay, Yeah, I certainly agree. Dumb luck is not a great strategy for decision making. So perhaps you can talk about what skills you need then in order to get better at decision making.

Well, I think that once you have a methodology, you don't have to know how to do the steps within the methodology. You just have to know how to facilitate the methodology with other people and teach it to them. Right. And who are experts within the organization that you can draw into each phase of this process to help you. So first of all, it's having a methodology and knowing it and being able to articulate it. Second is the ability to facilitate other people learning it and facilitate individuals in groups going through the various phases of the process, which requires pretty strong consultative or communication skills. The third thing you're going to need is strategic thinking skills. And most people don't think about this in an analytic process. See, they think everything about decision making is analytic. It's not. It's very strategic. The first part and the back part of this and even what you talked about, what story do I tell based on the insights? I find that's a strategic decision. It's not about breaking things down into parts. It's about going back and seeing the whole. So I have to understand strategic thinking. And then I would hope that people would learn narrative business storytelling, because it's going to serve you well. And when we created this methodology for every single phase, Karen and I wrote down what storytelling practices fit into every single phase, because we know that they do. And so when we teach it, we teach those skills along with it. So it's learning that as well. Okay.

Are you able to give me an example of what one of these narrative the business storytelling practices is?

Sure. So, for example, people like to ask questions the way the human brain interprets A question is it pauses because you're asking for information. And it screens kind of politically what someone wants to say and what they don't want to say. However, if I ask a story prompt, tell me about a time when XYZ happened, or tell me about the worst case situation when and I ask for a story. The brain does not filter. And when people tell the story, 99% of the time, they give far more information than they ever planned on disclosing.

Ah, so it's a good way to get information out to your colleagues. Excellent.

Exactly. So I even, in fact, I'm going to Brussels in December. This will be coming out after that. I understand, but it's to teach business storytelling skills to a group of people in Leuven, Belgium, about how to use that technique and how to use. How do you listen to stories differently? Because that practice in and of itself will serve you extremely well, because if you can pull the stories out, you might use those stories later on when you have your insights, but now you know them. And it's also a way to very quickly gain likability and trust is by asking people for their stories.

So one thing that I think you mentioned, like before, you were talking about having like cross functional sort of things. And I always find when there's lots of people involved in decision making, it can get tricky because people disagree on things. So maybe you can tell me a story about this. Yeah. How do you deal with disagreements then? How does the methodology help you there?

There is an excellent book that Robert Cialdini wrote a few years ago called Pre Suasion, which is what sort of influencing techniques do you need to do before you get people together into a room? And how do you make make good decisions about who are the right people to involve in the decisioning process? So let me give you an example that he has in his book, because it seems so small, but it's actually very powerful. So the example he gives in his book is, let's say you hire a repair person to come to your house, maybe your refrigerator or something's broken. And that person, they come in and then they look at you and they go, oh, I'm sorry, I forgot something in my truck. Is it okay? I'm going to go out the front door. Is it okay if I just leave the door ajar? Because I'll kind of come right back in. You saying yes to leaving the door ajar actually increases your trust in them and you're more easily influenced by what they say and do next because you already gave them permission that's like. So there's like these other sorts of, like, techniques and things that you can use to actually put people in a state of mind that gets them to be more receptive. And so just walking into a large group is, for me, is tantamount to risk. That's high risk. I need to know a lot of things. Either I need to have had discussions in advance with the person who owns. There's almost always one person who owns the decision. Does this person want to make the decision by themselves? Do they want to involve other people? If they want to involve other people, who are the other people who need to be involved? Who are the people who are going to execute? What if they don't want those people in the room? I have to talk through all of that with them in advance. So I have those conversations. I'm always with the primary decision owner. I'm tracking with them throughout this entire process. So we don't get to a situation that you're talking about in a group meeting. Now, remember, a lot of times the debates and the arguments are because people are showing data. Data gets debate. So you have to start thinking about how do you revise your presentations so that what you're not showing people is data? How do you start to incorporate narrative business story so that you start to get people aligned? That's a different way of approaching this. So remember, your question comes from showing people data visualizations or from data, at least I'm assuming that.

Yeah, I was trying to think. We went around a few circles there. Yeah. So I think what you're trying to say is, like, you need to make sure that is an actual single decision maker for any decision that has to be made. Like, you need some kind of hierarchical structure there. Because if it's a group decision, then it's just not going to happen.

No, it's. Well, it can happen within a group if a person chooses to be collaborative. But it's just like when you have business processes, you have process owners. Those process owners own the decisions within those processes. But I still want them to be collaborative. They have to involve other people. That's why you have to map the decisions to the processes. Because if you don't map them, you don't know who the people are. So then of course you're going to ask me this. You're going to ask me this question, who do I involve? Well, what process is this decision related to or what set of processes is it related to? That's going to be my first question to you all the time. And Then who are the owners of those processes?

Okay, so really, just make sure every decision you make is mapped to an actual process and there is an owner of that. That does sound like good advice. All right, just before we wrap up, then, do you have any final advice on how you get better at decision making?

Well, I'm obviously biased. I would encourage people to read the articles that I've given to you as resources if they'd like more information. The best way to reach me starting in 2024 is going to be through LinkedIn. And I'm happy to talk to people. And I. And I've been doing this for years offline about how you know how to bring methodologies like this into organizations, because there's a lot of challenges with doing it, because the mindset right now, as I shared at the beginning, is the complete opposite inside of enterprises. So you have to be pretty savvy, business savvy to bring this stuff in, but also how to use it on your own. I've helped people just individually do that. One of the things I've shared with you that I'll share with your audience as well is my direction is changing. 2023 was my transition year, so as of 2024, I'm going to kind of go off in a completely different direction. Not ready to announce that just yet, but I'm still happy to help people who choose to reach out to me and connect on LinkedIn and have a conversation. Because for me, this is my legacy work. I've put my heart and soul into this for a lot, a lot of years. And while I'm going off because I need to go off in a different direction and do other things to better serve, I think the word to use is my soul and to continue to bring me joy and for the next legacy in my life, I still want to be able to help other people. But you have to read about this and you really have to start thinking about how can you shift your own behavior? That's where it all starts. How do you shift your own behavior within your own enterprise?

Wonderful.

Yeah.

Change your behavior. One step to changing decision making. Wonderful. Thank you so much for your time, Laurie. That was brilliant.

You're welcome. And thank you so much for inviting me to share Sa.