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Unbound is a weekly podcast, created to help you achieve more as a leader. Join Chris DuBois as he shares his growth journey and interviews others on their path to becoming unbound. Delivered weekly on Thursdays.
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On today's episode, we're going to learn how to take data and turn it into wisdom.
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Are you a leader trying to get more from your business and life native? So join me as I document the conversations, stories and advice to help you achieve what matters in your life. Welcome to the unbound with me, Chris DuBois.
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All right, today, I want to introduce a concept called the DI kW pyramid. I am sure there are some way to turn that into an acronym that sounds cool, but I'm not gonna risk it because it sounds very inappropriate when I try it. So the DI kW pyramid, okay, what's the sample or first data, information, knowledge and wisdom? Hey, I'm willing to I'll put a picture of this inside of the show notes so that everybody can see what this looks like. But ultimately, this is the flow that you're going to get for everything you have to work with within decision making, right? First is going to be data, then we're going to turn into information, then into knowledge into wisdom. Now, moving them into each next stage requires something we have to add some sort of ingredient to this in order for it to work. And so when we have data, when you apply context to it, right, so if I'm looking at this data, I now add the context, it becomes information, information on its own, it's still more useful, then data, but we can't move it up into knowledge unless we apply meaning to it. Once you have information and meaning, it becomes knowledge. And then that knowledge once you have enough of it, and you can reinforce it with some insights, that's what becomes wisdom. Right? So really what you can break down if if you want to be the wisest person in any stage, anything you're doing in life, how can you how can you get there? Okay, well, first by having some insights, that you've applied to knowledge, because you've applied meaning to information, because you've applied context to the data. So you can use this reverse engineer, how to become smarter in anything. Hey, but the reason that we want to track inputs this way, is that it's important to know what level information is coming to us. Right? So I'm going to use probably some words interchangeably, I might say information, in reference to everything here. I might say data, just bear with me, it's hard to get this out just the podcast, hey, what data are those individual inputs, they're the facts and figures that we consolidate, that we can turn into more valuable information.
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So again, once we apply context to data, we get information information then allows us to look at multiple data points to see a line on the chart, right? This is where we start being able to identify patterns.
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From there, if we can apply meaning to it, we create knowledge. Now knowledge tells us what that line actually means is up into the right good in this instance, or is it bad, right? And then finally, when we can apply some insights into that, what are we actually learning? Right? We're going we're normally doing this through the experience of working with this this knowledge multiple times, right? That's what allows us to create the wisdom because the insights that we're able to provide are much stronger. Okay.
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Everyone's probably heard that saying, right knowledge is knowing a tomato is a fruit wisdom is knowing not to put it in a fruit salad. That's kind of same, right, you've had some insights. Here is a simple example. Data is the ingredients like flour, sugar, eggs, information is the list of ingredients and amounts that we need for whatever our recipe is. Now knowledge is understanding how those ingredients come together. If you're mixing, baking, you know, everything. And then knowing how to actually make those like cookies, say, cannot wisdom, is knowing when the cookies are baked just right, based on like the smell the look, right that you have experienced that tells you when everything is going right, give it some no matter how experienced you are in any given space, it is important to start by identifying the data. Because experience is going to let you make decisions a lot faster, because you're able to lean into that wisdom. But if you don't pay attention to all the details, you also risk making a poor decision. This is why sometimes having that novice frame of mind, right, bringing someone in to make a decision who does not have the same level of experience can be super beneficial for your team, because that individual is going to look at every single detail. Whereas someone who's more experienced might skip over some because they feel like it's intuitive to them. So they're not deliberate
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really trying to get this wrong, they've just been through this so many times that they can move quick, they don't notice.
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Okay, so when you can get good at seeing the data, then quickly applying context, so it becomes more workable, right? And then you keep doing this through every step of the pyramid. Now, that's where we're, we're starting to get really good at during this acclimation kind of phase, right, where we want to hit that speed to inform with go back previous episode 4070 rule, right? We want to collect this information as fast as possible and get to something we can use to help us make a good decision. This is that one of those steps. Okay, so where can we find the data that we need to very quickly move up? Like, what are we looking at for data sources? One of the first ones is going to be customer data, okay, you want to collect customer data, and your customer can change based off whatever you're doing, right? Like,
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who is that end user who is going to be receiving? What are the results, the consequences of this decision. So go through your CRM, your email, or chat records, like if you have a point of sale system for your business, we have web analytics, go through all of these different places, collect every bit of information you can, and keep track of it. Right? Have it stored somewhere in some database on some, whether it's a spreadsheet anywhere, so that you can use this as a frame of reference to go back to understand where you're at this the same with the next one of market data.
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You need to be able to understand those wider market trends that demands what your competitors offer. All of these things are going to guide a lot of what you're doing within your business and some of the decisions you're making. Right? If you see every other competitor in your space. zigging when you're zagging, that could be a good thing, it could be a bad thing. And so being aware of what's actually happening is going to give you the ability to actually look through it with a lens of like, okay, what do I actually need to be doing here, right?
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Hey, financial data. Another really important one, you got to know what your numbers are. If you don't know your numbers, you don't know your business, you need to keep an eye have an idea of every single number that's going through your business when it comes to money. If you are the leader, right, it is your responsibility to ensure there's always cash in the bank. Otherwise, you risk having to let people go, That's never fun. And honestly, it's probably a failure as a leader, anytime you do have to lean into layoffs,
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employee data, so your company culture, retention, productivity,
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all of those those details, they'll let you know of you, as a company, as a team are doing the right things you're jiving, right, that information is going to be really important, especially as you start moving further up in that di kW pyramid.
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Next, operations data. So things like your quality control, production numbers, supply chain status, right inventory levels, all of these things are going to guide what goes into a decision. And obviously, it depends on what the question is being asked. But like this is information that should be readily available so that you can make better decisions.
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All right, so you're going to use those. And finally, I want to close with some critical questions for all of us. So you should be asking yourself, as you're trying to collect data you're trying to acclimate very fast. A very important question that I feel a lot of people don't ask is, what don't I know? If you can ask that? And ask it to a group, right? You could sit down and look at your team and say, what don't we know right now and you make a list of all the you actually have to think differently. So now make a list of all of these different things that like, we actually don't know this. We're making assumptions here. If we knew this could actually change how we're looking at this entire decision.
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That that is something you very much need to put down.
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Getting clear, what is the core issue or opportunity that we're working on?
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Another critical question asked, What are the key facts and figures? Are there any immediate risks or constraints? These all of these things are just incredibly important, because you're not just going to sit down, take in this information, and, and be good, right? There's information you don't have and you don't know that you don't have it. But by asking specific questions, through a deliberate decision making process,
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you're able to find some of those gaps within your own data, your own thinking so you can make better decisions. So anyways, that was a brief snapshot of the DI kW pyramid. Some questions ask yourself and some different data sources that you should go hunt down for your own decision making process. I hope you're getting
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Getting things from this.
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If you want access to like the full kind of decision making course I have here you can shoot me an email Chris at leading for effect.com I can get something sent out your way. But until next time
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thanks for listening to today's episode, if you want to leave a review, awesome, but I would recommend you head over to LinkedIn. Connect with me. Join the conversation there. You find my profile in the show notes and I look forward to connecting with you
Transcribed by https://otter.ai