Using Data in Decision Making | Kevin Hanegan | Episode 228

In today’s fast-paced and constantly evolving business world, making informed decisions is crucial to success. Decisions that are based on guesswork or hunches can lead to costly mistakes and missed opportunities. That’s where data comes in – it provides a powerful tool for gathering and analyzing information to inform decision making. By using data, leaders can gain a deeper understanding of their business, customers, and market trends, allowing them to make more informed and strategic decisions. In this episode, we’ll explore the importance of using data in decision making and how it can lead to better outcomes for your business. Whether you’re a small business owner or a corporate executive, understanding the value of data-driven decision making is essential to achieving your goals and staying ahead of the competition. So, let’s dive into the world of data and explore how it can transform the way you make decisions.

Kevin is a senior leader who likes to use data and analytics to transform, innovate, and continuously improve organizations to make them the best they can be. His passion is the intersection of business, technology, learning, and psychology. Kevin believes the world is constantly evolving and we should always be evolving and improving ourselves in business and in our personal life. Through many years of working in a variety of businesses and industries, Kevin has been able to leverage technology and psychology, along with data and analytics, to improve organizational performance and transform businesses into high performing organizations. Kevin frequently speaks and writes on topics of data-informed decision making, the future of learning, and growth mindset.

Topics

During this interview Kevin and I discuss the following topics:

• 00:04:19 Kevin on data and decision making biases.
• 00:07:29 Data insights improve decision-making for customers.
• 00:10:55 Innovation, technology, analysis, and uncertainty in data.
• 00:15:43 Missing context leads to incorrect puzzle guesses.
• 00:19:21 Confirmation bias, what it is and impacts.
• 00:22:08 Risk aversion, survivor bias: military budget decision.
• 00:24:24 Surprising data reveals son’s valid behaviors.
• 00:29:31 Assuming, adjusting, data-driven decision-making process explained.
• 00:32:47 Apply common sense, perspective, intuition, diverse perspectives. Disprove, decide, execute, announce, assess, learn.
• 00:34:27 Lack of questioning and communication hampers effectiveness.
• 00:38:34 Trades, servant leader, facilitating, coaching, learning, growing.

Guest Resources

If you are interested in learning more about Kevin’s resources be sure to check out the following links:

• Kevinhanegan.com
• Kevin’s LinkedIn Profile –linkedin.com/in/kevinhanegan
• Twitter KevinHanegan
• Buy “Turning Data into Wisdom” on Amazon

sc name=”transcript” ][/sc]

Scott McCarthy [00:00:01]:

On episode 228 of the peak performance leadership podcast, we speak to data expert Kevin Hagan. He’s gonna tell you the importance and how to get data informed decisions. It’s all about data, folks. Are you ready for this? Alright. Let’s do it. Welcome, 1, welcome all to the Peak Performance Leadership podcast, a weekly podcast series dedicated to helping you hit peak performance across the 3 domains of leadership. Those being leading yourself, leading your team, and leading your organization. This podcast couples my 20 years of military experience as a senior Canadian army sir, with world class guests bringing you the most complete podcast of leadership going.

Scott McCarthy [00:00:56]:

And for more, Feel free to check out our website at movingforwardleadership.com. And with that, let’s get to the show. Yes. Welcome 1. Welcome all to the Peak Performance Leadership podcast. It is your chief leadership officer, Scott McCarthy. It’s so good to have you here yet again. And if it’s your first time listening, then welcome to the guest leadership podcast going as far as I’m concerned, and that is a very unbiased opinion.

Scott McCarthy [00:01:30]:

But, hey, Thousands of people, 150 or 60, I can’t remember now, countries and growing every day. You, the audience, don’t lie. So thank you for all your support, and thanks to you for tuning in because You’re the reason why I do this show every day, day in, day out, week in, week out because I love being of service to you. And if you want more, if you wanna be served more by me, then feel free to check out our growing mastermind community. And as the leader growth mastermind, we’re in there day in day out, you know, leveling up our leadership and leveling up not just Our leadership but ourselves, leveling up ourselves so that we can lead our teams better and our organizations better, and we’re having some Incredible times in there lately. We have people who are starting new businesses for themselves. We have people who are getting new positions created for their team because their team is getting burnt out. We have people taking better care of themselves because they realize that without that, they can’t take care of their team.

Scott McCarthy [00:02:50]:

So if any of this resonates with you, check us out at lead don’t boss forward slash mastermind, and that’ll bring you to the landing page for the leader growth mastermind. We have weekly cure, calls, curated content, a soon to be a new area, which is super exciting just for the members. A complete coaching platform for you, the members of the mastermind, which I am ecstatic about so check us out. Anyway, lead don’t boss forward slash mastermind, and that is where you can check us out. But let’s talk with today’s episode, and you’re probably thinking great. Data. I hate numbers. I’m tired of data.

Scott McCarthy [00:03:41]:

And, Scott, you’re going to have an episode where we’re just gonna hear about different charts, different, you know, ways to use data, regression analysis, and so on and so forth. Nope. Not a bit of it. Not one bit. In fact, we didn’t talk about that stuff. In fact, we don’t need to talk about numbers. What we do talk about is why it’s important, how to avoid analysis paralysis, in the big one, how to use data to make data informed decisions. And that is where we went with this episode.

Scott McCarthy [00:04:19]:

Kevin and I talked about, you know, the good and bad about the hunger that’s going on right now for data, how to avoid data analysis, paralysis, different biases in data informed decision making, and you heard me and enter with the bias right out of the gate. Right? That was planned, by the way. How assumptions are crucial planning and proper data analysis, which is something people don’t think about, and we’re a leader’s fault in applying the model that he has, which is his 5 phase process to data inform decision making, and that’s really nuts and bolts of today’s show. It’s all about decision making if you think about it, and data is just one of the tools that we’re using. So who are we talking to today? We’re talking to Kevin, who’s a senior leader, and he really likes to use data and analytics to transform, innovate, and continuously improve organizations. Sounds a bit like the podcast now. Alright. His he has a passion of business, tech, learning, and psychology.

Scott McCarthy [00:05:26]:

He believes the world is constantly evolving. Hello. Again, sounds all similar. And, anyway, through his many years of working in priority of businesses and industries. Kevin has been able to use technology and psychology with data and analytics to improve organizational performance and transform businesses into high performing organizations. That falls directly in line with our goals here. So that’s today’s show, and let me tell you you’re in for a treat. And I think that’s enough for me.

Scott McCarthy [00:06:07]:

So why don’t you sit back, relax, and enjoy my conversation about using data and decision making with Kevin Hagan. Kevin, my Friend, sir, welcome to the show. So good to have you here

Kevin Hanegan [00:06:33]:

today. Thanks. Pleasure to be here.

Scott McCarthy [00:06:35]:

We are talking about Data and just literally as I hit record, I said to you, that was a I’m a bit of a data junkie. I I I I like data. I like playing with data and figuring out stuff through data. But at the same time, I don’t believe data is the end all be all to, you know, decision making and and, you know, leading leading our teams and our organizations in this this point. So From your standpoint, you know, what’s the good, what’s the bad around our data hunger that we have today?

Kevin Hanegan [00:07:10]:

Yeah. That’s such a great question. We could probably spend hours just on that. And I’ll I’ll start by saying, to to me, data like, There’s obviously, people think of numbers and, like, the quantitative, but then there’s so much around it. So sometimes I just use the umbrella term information. It could be surveys. It could be customer reviews. It Could be unstructured data.

Kevin Hanegan [00:07:29]:

And the benefit of that is there’s so many nuggets in there of insights. The goal to me with with data is to uncover insights that help you make better decisions. And you can do that sometimes on your own if you just have a couple pieces of information. Like, Here’s something someone’s talking about, you have that moment. But now with the amount of data and data that we we get through The Internet of things and everything. It it’s hard to do that. So there’s tools that allow us to do that. But to your point, I think we’ve over relied on the tools So the the the benefits are we get to know about our customers better.

Kevin Hanegan [00:08:06]:

We get to know about our business better. We have the opportunity to do more with it. The downside is I feel like sometimes we focus so much on the data that we lose our common sense And we forget about everything else. And so I always like to say it’s helpful, but you don’t start with the data and you don’t end with it. It’s in the middle. It’s like the data sandwich. Right? Is you have to start with a problem and a question. There are some people that do exploratory data analysis.

Kevin Hanegan [00:08:35]:

Here’s my haystack. Give me a needle. Doesn’t really work that way. It’s what is the problem you’re trying to solve, and this goes for business or for personal life. What information is there to help you? But then more importantly, how do you critically evaluate that? How do you think laterally about a solution where you might be Having a confirmation bias, you see the data. It’s like, Look. I was right. In reality, you probably weren’t right.

Kevin Hanegan [00:09:00]:

Right? It’s it’s misleading. So Your your your initial point is spot on. It’s a double edged sword. There’s a lot of potential, but if we don’t use it right, and some of those ways that we use it is not technical. It’s Soft skills like critical thinking or creative thinking, a lot of times it’s about we have underlying assumptions about things. So if if we don’t balance that, then it actually can do more harm than good.

Scott McCarthy [00:09:25]:

Oh, I like the data sandwich analogy. You know, we start with something soft. I okay. What’s the problem? Let’s define the problem. Okay. What data do we have to support some kind of analysis, you know, to further explore the problem, look for solutions, etcetera. But then when you get to decision making, you have to actually, you know, use your thinking hat and Use your brain and say, okay. Am I using this, you know, as a confirmation bias? Or am I use only looking at one side of this data? Because, you know, that has 2 sides.

Scott McCarthy [00:09:53]:

Right? Or even more than that

Kevin Hanegan [00:09:55]:

sometimes. More sometimes. Yeah. Yeah.

Scott McCarthy [00:09:57]:

Right? So it’s like, am I am I looking at it holistically? And and I like the part that, you kinda hinted that analysis paralysis. And and data could feed that. Like, I’ve seen leaders stuck because they’re like, well, how would data from this aspect and and that aspect and this other aspect? Oh, let’s not forget about, you know, let’s do the function of the thing, but the thing you know, do the, you know, square root of pi and all suddenly, you know, get that data. How can we avoid that as

Kevin Hanegan [00:10:29]:

leaders? Yeah. It’s a great question. Right? So I I think there’s a misconfusion out there at a high level of What’s uncertainty and what’s risk? Right? Risk is you’re gonna roll the dice. Right? 1 out of 6. You know your odds. That’s that’s the known known. It’s The the uncertainty is things change. And and, unfortunately, we or fortunately, depending how you look at it, we live in a world where what was yesterday is not true today.

Kevin Hanegan [00:10:55]:

I mean, you think even my my parents’ generation, they did the same thing for their entire generation. It didn’t change. But we have So much technology innovation, digital transformation that sometimes we’re doing the analysis paralysis, but we will never have The right data because it’s historical data. We’re trying to move forward. We’re trying to innovate. So it’s that old adage. If I’m just looking backwards, I’m not looking forward. So how can I use the backwards to predict looking forward? A lot of it is is how do you deal with uncertainty versus risk and realize that With uncertainty, you’re never gonna have the right amount of data.

Kevin Hanegan [00:11:31]:

It it’s probably about aligning a culture and a process of How strategic is this decision? How risky is it if we make the less than ideal decision? And do we have a culture to learn and assess from and learn and and adjust quickly. And those organizations that do that faster are gonna be the ones that innovate more and make the The better long term decisions doesn’t mean their 1st decisions. Right? Most times their 1st decision isn’t right, but they learn from it faster.

Scott McCarthy [00:12:01]:

I I I love that uncertainty versus risk. I think that’s key as leaders because, you know, there is no crystal ball. We but yet, we all have hindsight 2020 vision. Right? And I also liked, you know, the part that you talked about, you know, looking backwards. And, just a quick, annual story. So, by day, I served in the Canadian Army as a senior officer. And, I was in command of a squadron of 200 folks, and we’re, you know, operations. And we’re looking at our budgets and stuff like this.

Scott McCarthy [00:12:32]:

And and one of the guys is like, well, let’s just take the average cost over the past 5 years. I’m like, time out. Like, if we take the average cost of the past 5 years, we’re just gonna get the cost of it 3 years

Kevin Hanegan [00:12:44]:

ago. Yeah.

Scott McCarthy [00:12:45]:

Right? I’m like, no. We need to actually think about this guys and look at the data and do some trend analysis. You know, which direction It’s going has it been increasing? What’s the average increase over the past 5 years? Because that’s actually gonna give us more of an indicator of what our costs are gonna be instead of this. It actually took a fair bit of education because people get stuck into averages and looking backwards vice trying to extrapolate that data and use it to look forward.

Kevin Hanegan [00:13:10]:

Yeah. I always tell people it’s like you have to go back to 3rd grade math sometimes where you learn this, but then you never really apply it. And I I think a lot of us remember, like, yeah, there were differences, like mean, median, mode, but we didn’t I don’t remember learning that in, like, high school. I I learned in primary elementary But we don’t really have that many chances to to apply it. So your your point, I see that in every organization, is they will mismatch the right one and, unfortunately, Make strategic decisions because of

Scott McCarthy [00:13:40]:

it. So that begs the question, you know, how can we actually leverage Data and and get it to help us with our decision making process, and and how do we avoid these pitfalls that, you know, we we’re just

Kevin Hanegan [00:13:57]:

discussing. Yeah. I mean, you hit on one of them, right, as education. Is education there’s the education on Not trying to be a data scientist, but understanding data, understanding aggregations, understand, what the the outliers, the of it is. But beyond that, it’s it’s educating our process. I am a huge fan. 2 of my favorite words are systemic and systematic. And they they sound similar, but systematic just means it’s repeatable.

Kevin Hanegan [00:14:23]:

Right? And and systemic means I am thinking of the entire Organization or the system as a whole. So the the opposite app would be I make a decision on the sales side that completely misaligns with marketing, Or I make a decision in the product that misaligns with our marketing message. Systemic would mean that everything’s in alignment. There’s none of those unintended consequences. So one of the ways that that I like to educate leaders on on increasing their decision making is is following a process that fits into their organization. It the same process globally, but it it you follow it. It’s repeatable. The other key component of that is ensuring At all levels of the organization, you’re getting diverse perspectives.

Kevin Hanegan [00:15:08]:

You hit on it when you said data has 2 sides of the coin. I I kinda think it has, like, 10 different sides. And I don’t know if you remember or your listeners remember, there used to be an old game show in North America called Classic Concentration, Where it was like a memory game. It was on TV, and it had boxes. And you answered questions, and boxes would come off, and there was a puzzle behind it. But the puzzle wasn’t words. It was like a it was a visual, and you had to guess what the visual was saying. And to me, that Data is the more puzzle pieces you expose, the more likely you are to have an understanding what it actually is.

Kevin Hanegan [00:15:43]:

So people would always look at the Hop. They get the top part of the puzzle, and they buzz in. Say, I know what it is, but they missed the whole bottom part, which had that context of the puzzle was completely different. And There’s some funny answers where, like, it looked like a pitchfork, so someone was saying a devil, and it wasn’t a pitchfork. It was like the mother baking cookies or something because they were missing the part of the mother, on the other side of the picture or the father or whoever it was. So being able to get those different perspectives, The data for me might mean something different to you. It might mean something different to someone else. And you have to do that in a repeatable process so that you can do it quickly.

Kevin Hanegan [00:16:21]:

We don’t wanna, you know, draw out these decisions and say, let’s all think about it for 2 years and come back to it. It’s gotta be kinda codified into the culture of, I’m a leader. I am going to democratize decision making, and I’m gonna have everyone be able to have their say. At the end of the day, you know, ultimately, I’ll make the decision, but I want their input. Those are a couple strategies I use that are highly effective, Not in the beginning because sometimes people are nervous. Like, wait. You want me to question my boss? You want me to, you know, challenge them? You want me to tell them Something that they don’t agree with. And until that organization says, yes.

Kevin Hanegan [00:16:58]:

I want you to, it’s gonna be a challenge for them.

Scott McCarthy [00:17:04]:

That last bit, I would say 2 things. First, it takes a high level of psychological safety, for an organization to do that. I had a guest on the show once, Tim Clark. He wrote actually wrote the book on that, and that would be stage 4, challenger safety. And then Yeah. What I would, what I would offer to you is, yes. That’s exactly what I want as a leader. Actually, I I want you to challenge me because I don’t know my blind spots.

Scott McCarthy [00:17:30]:

I can’t see them, hence why they’re called blind spots and you need to expose them for me. Tell my team this on a daily basis. I you know, I I have a team of, 25 right now. And I I tell all of them. I’m like, You even the lowest, you know, lowest ranked person, you have the right to challenge by challenge me in a respective manner, of course, but you do because because you see things, I don’t see things. And if I’m making a expertise. I need to know that so that I can actually make a better informed decision.

Kevin Hanegan [00:18:06]:

Absolutely. And easier said than done. Right? I I think

Scott McCarthy [00:18:08]:

one of the things

Kevin Hanegan [00:18:10]:

I I tried because I understand that. I’m like, why is that? And to your point, you need to have some capabilities as a leader, but then the individuals too. I I do a lot of relating what happens in business to what happens when we’re like kids. Well, when we’re kids and we ask we challenge the teacher, we get detention. So we’re kind of ingrained through our entire educational university not to challenge a teacher. And then all of a sudden you go to work and you get a leader like yourself who who wants to see that, people aren’t just gonna all of a sudden drop their habits and be like, okay. Let’s let’s open up and challenge we’ve been ingrained for how many years we are in school. Don’t challenge the teacher.

Kevin Hanegan [00:18:48]:

There’s only one right answer. It’s seen as showing them up. So I I think the leader needs to be open to to that, but individuals still need to unlearn some of those bad habits that they’ve gotten through

Scott McCarthy [00:19:00]:

schooling. No. You’re so right. And, actually, as you as you talk with that reflect. I’m even doing that as a parent with my sons. Right? Like, no. Right? Like, every day. Like, no.

Scott McCarthy [00:19:10]:

No. Now there’s there’s 7 and 4. So, they’re kinda in the age where I kinda need to be that way. If not, they may kill themselves or seriously enjoy themselves. Safety first, of

Kevin Hanegan [00:19:20]:

course. Yes.

Scott McCarthy [00:19:21]:

Right? But but still, it it’s very much that way. It’s like, no. You will do what I say when I say it because, you know, this is how it is. However, I do try to do make an effort to explain to them. So let’s let’s talk about data. Let’s talk you you talk a lot about biases in your book and how they affect decision making. And you mentioned 1 earlier, the confirmation bias, which is a solid bias that we see all the time. So So can you go into, 1, what confirmation bias is for the listener in case they don’t know exactly what that is and how it impacts us as leaders in our decision making process? And maybe another 2 or 3 that are common that you you see often as well.

Kevin Hanegan [00:20:02]:

Absolutely. So so, Bias in general, and then I’ll get confirmation bias, so that the brain, it’s a supercomputer. It is really good at storing information. But we are exposed to, what, millions of of pieces of information any second through the different senses. So if the brain had to consciously spend cycles thinking about every decision, then we’d overheat. We’d sleep for, like, 24 hours a day. We’d overheat. So the brain makes these shortcuts we call heuristics.

Kevin Hanegan [00:20:36]:

Like, you’re walking down the street and you see a bull running at you. You don’t assess the probability. Is it gonna hit me? Am I wearing the right color? Am I gonna no. You run. You move. Right? You you don’t think about it. It’s unconscious. So a lot of times when we make these unconscious or subconscious decisions, these heuristics, the the brain is looking at past experiences.

Kevin Hanegan [00:20:57]:

It’s looking at patterns. It wants to make a connection in the data and the data is what you’re seeing in the real world versus what you have in your long term memory. When it doesn’t make that connection, It tries to make the connection. So it tries to do that in a couple ways. Confirmation bias would be, I have an opinion. I have an answer to a decision, And I see a dataset and I say, see? That proves my answer. I’m right. But it’s a shortcut.

Kevin Hanegan [00:21:25]:

That doesn’t mean you’re right. There could be misleading things. So you you juxtapose that to, scientists. They use the scientific method. Their their Systematic and system systemic approach is I’m gonna have a hypothesis. And rather than looking at looking for data To prove my hypothesis, they should do the opposite, intentionally. They look for stuff to disprove it. It’s only when they can’t disprove it.

Kevin Hanegan [00:21:50]:

But, again, the way our brains are wired, the confirmation bias example is I see the data. My brain says, boop, I’m right. I move forward. Now it’s important to say it’s not intentional. It’s not deliberate. We don’t know we have it. It’s just innate in how our brains work. Many other types of biases.

Kevin Hanegan [00:22:08]:

I mean, there would be 1 risk aversion I see a lot where you’re trying to Avoid risk at all costs. And then there’s also the opposite kinds where you’re just trying to stand pat. One of my, favorite ones is survivor bias where you’re looking at data, but you’re basically in your head taking out or Filtering out things that you might think are not relevant. So actually, you’d mentioned here in the military, one of the famous examples Way back when was it one of the world wars? I can’t remember which one. One of the governments had a certain amount of budget, and they were trying to fortify Plains. And so they asked the scientists, we’ll get the planes, find the bullet marks, and tell us where you would fortify it based off the money we have. That was the second.

Scott McCarthy [00:22:54]:

Story short,

Kevin Hanegan [00:22:55]:

They did. What’s that?

Scott McCarthy [00:22:56]:

2nd World War.

Kevin Hanegan [00:22:58]:

2nd World War. Perfect. Thank you. I knew it was 1 out of 2. Right? So I but I, Turns out they looked at the dataset was only the planes that had not been shot down. Completely relevant. You see that, to look at the planes that were shot down because those are the ones you wanna fortify. You see that in finance where you’re looking at stocks.

Kevin Hanegan [00:23:16]:

You might be looking at organizations and looking at the data, but leaving out the companies that have gone bankrupt that time period. It’s absolutely relevant to look at them. Again, unconscious, not deliberate. We all have bias. It’s all subconscious. We need to kinda kick our brain into those quick pattern matching that it does. We need to pause it and say, okay. Let’s reflect.

Kevin Hanegan [00:23:41]:

Is there a scenario where this isn’t true. Is this a scenario where this isn’t telling me, the right answer? Many times, it it it Comes down to not even a bias, but a faulty assumption. So I’m gonna give you a personal story, which which I Think the readers will appreciate it. It’s nothing to do with business, but highlights you can do everything right with the data. You can have the right processes. But what could fail is you just make an assumption that’s wrong, and your brain’s kinda focused on that. So long story short, one of my kids I have 4 kids, Has, some disabilities and some mental health challenges. And a long time ago when I was in school, they were taking data because he was having behavior issues.

Kevin Hanegan [00:24:24]:

And they pulled us in a team meeting and they showed us their nice spreadsheet and couple nice graphs and they showed the behaviors are spiking. You know, we have to do some type of interventions. They didn’t know I work with data every day or visualization, so I asked them some questions about the trends, you know, what time of day is it happening, you’re just organizing them, What time of the the week? Because, you know, Mondays would tell me, you know, it’s off of a long weekend, whereas Fridays would mean something completely different. Long story short, they add all that stuff in and they come back to me and say, your behaviors continue to grow. We’re gonna have to Do some type of serious intervention. And I looked at the data again in the meeting, turned to my wife, had this big smile on my face. The data they were collecting was not just the behavior, but what my son was doing before and what the consequence was. All of the data was valid.

Kevin Hanegan [00:25:17]:

Nothing was fudged. The what I realized was the the consequence for majority of the behaviors was they sent him to the principal’s office. And logical, rational, obviously, everyone’s different. Right? Most kids don’t like on the principal’s office. My kid loves adult stimulation. So I thought it was intentional. So I came home that night. I’m like, hey.

Kevin Hanegan [00:25:40]:

You know, what happened? He’s like, dad, it was Great. I kicked the teacher. They sent me the principal. She read to me for an hour. I think I’m gonna punch someone tomorrow, dad. And everything they did about their decision making process was right. They had the right data. They did the right visualizations.

Kevin Hanegan [00:25:56]:

They Made a rational conclusion where their bias and where their assumption failed them is they assumed every kid doesn’t like going to the principal. And they made a very strategic decision without including us. Because why would you say, hey. I wanna send your kid to the principal. You’re okay with that? It It just seems like that’s the standard norm. But when you don’t do that in business, you go down these paths where you make these decisions and you have those, Oh, no moments where it’s everything’s right, but it’s the assumption that’s wrong.

Scott McCarthy [00:26:28]:

That story is Phenomenal. Well well well done. I I like the the point though. You know? So with me in military planning, assumptions are crucial. We we we have to make it we have to make assumptions, on order to plan. But we also track the assumptions, and we try to either validate the assumption or disprove the assumption as we continue throughout the planning process. So the in this case, they they did they failed to do that. Right? But

Kevin Hanegan [00:27:03]:

And that’s the key thing is that the the The takeaway is everyone makes assumptions, but when they’re and there’s implicit and explicit. Explicit are the ones like you said, you state out loud. This is my assumption. This Very common strategic planning. These are my 5 assumptions. If these change, the model’s gonna change. It’s the implicit assumptions like the the invisible ones. Those are the ones that are scary.

Kevin Hanegan [00:27:25]:

So the processes that we try to follow is make sure you go through a step to to surface all of your assumptions. And and I mentioned before, I like to equate a lot of the things back to to schooling. That’s you know, in school, when you do your math homework, You you get points deducted when you don’t show your work. And I always was like, why? Why do I have to show my work? Like, I know the answer. I’m just gonna do it. Well, now I’m at all. I can reflect. It’s because if you make a mistake, they wanna know where your logic went wrong so they can course practice.

Kevin Hanegan [00:27:58]:

So In business, you do it in the military at high risk. In most businesses, they don’t share their assumptions. So they’re not showing their work. So how can we tell people where their thought process went wrong before it’s too late unless they verbalize those assumptions?

Scott McCarthy [00:28:16]:

That’s a that’s a really great point out there. And I can see, especially for leaders out there, because, it it almost comes across as a sign of weakness that you’re making assumptions. Oh, you don’t know. Well, it’s not that yeah. I don’t know. But can I know? Like, really, I I I it’s impossible for me to, you know, know this, or it’s impossible for me right now to know that. But am I trying to figure it out? Yes. We’re trying to find out the answer to it.

Scott McCarthy [00:28:41]:

How you know, to either prove or disprove it, as I said earlier. So to me, it’s more of a sign of strength that you can show it by a sign of weakness that you don’t know something.

Kevin Hanegan [00:28:54]:

It It also comes back to what we said earlier. Like, sometimes there’s uncertainty. So, you know, an assumption in a business setting could be The global economic climate is going to be stable or is stand is gonna be the same it is right now? Well, that’s an assumption. Right? As soon as that changes, the model changes. You have no idea. Right? You don’t know if it’s going to. You don’t know if there’s gonna be another Environmental disaster or political disaster. So part of it is, yes, is you there are some certain assumptions you have to make.

Kevin Hanegan [00:29:25]:

Some of them is you just can’t know because you can’t predict the future. It’s uncertain.

Scott McCarthy [00:29:31]:

Yeah. You gotta make you gotta make an assumption on what the future holds, and then adjust as it actually unveils to you. Kevin, I I feel like we’ve been kinda, you know, hitting different parts of my next question. I’d like to wrap it up into a nice ball here for the listener, and that is you you have a a nice process for using data and making data informed decisions. Yeah. You know, you know, you refer to them as phases phase 1 through, 5. I’d like for you to just give the listener there an, you know, a nice overview on what these phases are, what goes on throughout the phases so they can have better understanding how they should be using their data to make better informed decisions moving

Kevin Hanegan [00:30:16]:

forward. Yeah. Absolutely. So as I mentioned earlier, it starts not with the data So data center, it starts with the decisions we made or the questions. So first step is asking. Like, what are you trying to solve? What is the business problem? And from a business perspective, one of the things that drives me crazy is we we get asked a lot what I call business questions. A business question is not answerable with data and analytics. A business question is a vague subjective term like, How’s my sales campaign doing? And going back to what we talked before, a lot of times we don’t know how to question.

Kevin Hanegan [00:30:54]:

We We lose the art of questioning. So we need to go back during the ask phase and say, okay. Sales campaign compared to what? Last year’s campaign? Compared to The month before we had this campaign, what demographics are you looking at? What channels are you looking at? In turn, it almost like we have smart objectives. You need smart analytic questions. So the ask is all around understanding the reason someone’s asking the question. In statistics, we have these errors that are false positive, false negative like type 1 and type 2. There’s another error called type 3, which is You answered the question, but it was the wrong question. Those happen all the time when you don’t in the ask phase clarify what you’re trying to do.

Kevin Hanegan [00:31:39]:

So it’s all around doing that. Obviously, part of it is classifying the decision. If it’s strategic decision, you’re gonna spend more time then if it’s an operational decision. Once you do that, you then go into acquire which is give me all of the relevant data. Let’s sift through the noise and find the signals. Let’s look at our quantitative. Let’s look at our qualitative data. Let’s bring in everything and make it analytics ready to be able to answer the questions systemically.

Kevin Hanegan [00:32:08]:

Then you go into the analytics phase, which is depending on the question doing some type of analytics. It could be the average like you mentioned. It might just be descriptive. I just need to show the the median of over the past 3 years. Or I might need to do some kind of root cause analysis. So I might have to do some type of comparative diagnostic analytics, compare This trend versus that trend, try to understand what’s driving those trends, look for correlations. So that whole phase goes through any level of descriptive all the way up to predict analytics. The key one for me which most organizations miss is the next one, which is we call the apply phase.

Kevin Hanegan [00:32:47]:

This is applying your common sense, applying your perspective, applying your intuition, applying diverse perspectives, Applying your assumptions, everything that comes to the human element of decision making, apply that to what the insight told you, Try to disprove it. And then at the end of the apply phase, you have a decision, then you’re gonna move on to to executing on it. You make your decision. You have a change management plan if it’s a strategic one. But you don’t stop there, then you move on to Announcing it to everyone and then assessing the viability of it, assessing the ROI of it, taking what you learned and then feeding it back into the beginning of Process. Sounds complicated, sounds long, but you can use it for decisions like, what where do I wanna go on vacation this summer? Or you can use it in business decisions as well.

Scott McCarthy [00:33:42]:

Yeah. No. I could definitely see how you can, you know, easily apply this to almost, you know, almost any scenario, really. And I kinda you kinda I think there’s a part of me that intuitively already does a lot of

Kevin Hanegan [00:33:53]:

that as it is. Exactly. That’s what I wanna that’s what I wanna hear. I I like when people are like, well, that that makes sense. I probably into it because it it’s all about just codifying it so you don’t forget. Right? It shouldn’t be anything earth shattering like you’ve never done this before. It should all be things you do, but now it’s just in a formal process that you can follow.

Scott McCarthy [00:34:13]:

Now from your experience, where are leaders making the biggest hiccups throughout this process? Is it that they’re relying too heavily on the data or they’re spending too much time in one area or they’re ignoring an area?

Kevin Hanegan [00:34:27]:

It’s a good question. I believe very strongly, a lot of us spend 90% of our time. If the whole cycle is a 100%, We spend 90% of our time on the acquire and the analyze phase, and the other 10% are on the ask And, obviously, the applying and then the announcing, we don’t do a lot of good communications as The why from a change management, very rarely do we assess. But just starting at the beginning, a lot of times we’re not asking the right questions. We’re not thinking critically about business problem to be able to get at that and the the less specificity you have, the harder it is to find relevant data. Because relevant to what? If you don’t know what you’re searching for, what the goal is, you gotta start with the outcome and then work backwards. And I think a lot of times people just ask a business question, And then they try to get an army of data scientists to go do some data mining and give them an answer, but not always aligned when they do that. So I think holistically, Spend more time questioning up front just like you build a house.

Kevin Hanegan [00:35:33]:

Right? You don’t start hammering. Right? You design. You design the question. And then spend more after that trying to apply your intuition and your human element to to, like, those assumptions that we talked about the example with with my son. That was the apply phase.

Scott McCarthy [00:35:50]:

Yeah. I I we are we use, I should say, backwards planning in the military all the time. That’s Exactly how how we do it. And then we spend the bulk of that time at the front end of what you basically said, you know, asking asking the questions. And I say often on the podcast that leaders now, our job is not to know the answers. It’s not to have the answers anymore like it was way back in the past. Yeah. You know, people looked up to you because, oh, they have the answers to everything.

Scott McCarthy [00:36:23]:

Therefore, I’m gonna follow them. No. That’s actually it’s actually inverse now. The world’s so complex, so so diverse, changes so fast. It’s impossible for you to have the answer on everything. But what you can do is, you know, be the one asking the questions and having your team members, you know, the specialist to answer those for you or seek the answers for you. And the more quality questions you ask, the more quality answers you get, And, therefore, the better you are set up for success in, you know, identifying and then solving the problem ahead.

Kevin Hanegan [00:36:59]:

Exactly. And one thing you said that I just again, it ties back to schooling and education. You think about the the ways of communication. Have you ever taken a course on questioning? I haven’t. Right? I you ever taken a course on listening? No. Like, those are the 2 things leaders need to do probably more than anything else. We spend hours doing writing. We spend hours doing reading, and they’re valuable.

Kevin Hanegan [00:37:22]:

But I never took a course in questioning. I never took a course in active listening. And, yeah,

Scott McCarthy [00:37:27]:

those are

Kevin Hanegan [00:37:27]:

the schools I use every day.

Scott McCarthy [00:37:29]:

No. Definitely no courses, but I can highly recommend a book, Name never split the difference by, Chris Voss, a former FBI, negotiator. Fantastic read along those 2 things, active listening and, and and talk to what he refers to as tactical questioning.

Kevin Hanegan [00:37:49]:

Yeah. He’s got spot on.

Scott McCarthy [00:37:50]:

Yeah. No. It’s a fantastic read. Outstanding. Kevin, this has been a great conversation and and, probably to listeners delight, not too nerdy. We didn’t get into, you know, different types of aggregation or anything like that, because, well, This is not what it’s about. It’s about, you know, understanding, you know, the process, understanding what it can do, understanding our biases, and all these things. Now, before we wrap up, and obviously, you’ll get a chance to to plug your book, I do got a couple last questions for you.

Scott McCarthy [00:38:23]:

That’s according the first one being question asked all the guests here at the Peak Performance Leadership podcast. And according to you, Kevin, what makes a great

Kevin Hanegan [00:38:34]:

leader. I think we talked I mean, I don’t wanna just say listening and questioning, but We talked about a lot of the trades. I I happen to be a servant leader. I like to serve the teams that I that I work for in doing that by being facilitating, asking the right questions, coaching them. So, you know, I’ve had leaders where they just give me the answer And back in the day, that was seen as a great leader. Now it’s not because you’re not growing that person. You’re just, you know, Artificially augmenting them, so to speak, is I want someone that I can learn from. I want someone that I can grow from.

Kevin Hanegan [00:39:09]:

I want someone that I’m comfortable, questioning and and kind of that give and take. So I guess summary, to me, what makes a great leader is is empathy, Active listening, questioning, and the ability to inspire the best in everyone they work with in a very in a way that’s done with integrity.

Scott McCarthy [00:39:29]:

I gotta love that last part. Definitely integrity. And a final question of the show. How can people find you? How can they follow you? Shameless plug.

Kevin Hanegan [00:39:37]:

Have at it. Yeah. Absolutely. So you mentioned the book, Turning Data Into Wisdom. You can find it on Amazon. You can go to my website, kevinhanigan.com. I am one of the few that have not gone on the social media training yet. I need to.

Kevin Hanegan [00:39:49]:

I just run out of time, so I don’t have a Twitter or anything yet. Just LinkedIn. You can just I think there’s only 2 Kevin Hagen in the world, so you’ll find one of them that has the book inside of it and connect with me on LinkedIn. Go to the website. The company I work for, Qlik, q l I k, does data and analytics. So you can go to their website, check out some of the offerings that we have there, as well.

Scott McCarthy [00:40:13]:

Yeah. And for you, the listeners always, it’s easy. Just go to lead dump boss.comforward/ 227-227, and the links are in the show notes. I’ll also like to say that I’ve gone through your book. Thank you for a copy, by the way. Fantastic. And, I run a mastermind community with, with this podcast. And each month, we go through one of my 3 domains of leadership.

Scott McCarthy [00:40:39]:

So this past this current month, we’re actually leading ourselves. We’re talking about, you know, prioritization and how to maximize, you know, being more effective at work and stuff like that. Next month, we’re gonna talk about, leading our teams and getting into team prioritization and, effectiveness and all that things. But on the schedule 1 month, we are gonna do about leading our organizations, and and data’s gonna be in there. And your book is gonna form the framework for that conversation

Kevin Hanegan [00:41:06]:

Very cool.

Scott McCarthy [00:41:06]:

With, with that mastermind community. So, for listener, if that, you know, piques your interest, please check out lead the boss forward slash mastermind, And check us out because we’re doing a lot of great stuff in there. And and, you know, we get a lot of great content from experts like yourself that that feeds into it. So thank you again.

Kevin Hanegan [00:41:25]:

Absolutely. That was awesome. Yeah. Thank you for having me.

Scott McCarthy [00:41:29]:

And that’s a wrap for this episode, ladies and gentlemen. Thank you for listening. Thank you for supporting the peak performance leadership podcast. But you know what you could do to truly support the podcast and know that’s not leaving a Rating and review. It’s simply helping a friend, and that is helping a friend by sharing this episode with them if you think this would resonate with them and help them elevate their performance level, whether that’s within themselves, their teams, or their organization. So do that. Help me, help a friend, win win all around, and, hey, you look like a great friend at the same time. So Just hit that little share button on your app, and then feel free to fire this episode to anyone that you feel would benefit from it.

Scott McCarthy [00:42:20]:

Finally, there’s always more. There’s always more lessons around being the highest performing leader that you can possibly be, whether that’s for yourself, your team, or your organization. So why don’t you subscribe? Subscribe to the show via moving forward leadership.comforward/subscribe. Until next time, lead, don’t boss, and thanks for coming out. Take care now.