Matching Data to Outcomes

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Ladies and gentlemen, we're happy to have you with us today and very grateful that you took some time to be with us here at JLC Media. This is a series of podcasts on data literacy and data fluency, and I'm really looking forward to it. In preparing for this podcast, it helped me remind myself that so much of what we do involves us thinking data, making data part of our daily process of thought as we make any decisions that are going on. So today we're going to do a kind of an overview of how to position yourself so that you can use data most effectively. And before we do that, we're going to talk a little bit about what data means to us so that we have a common understanding about the word data, which is in the English language, a plural word, a datum is a point. Data is a bunch of points. So I'll be very cautious to watch my language so I don't slip back and forth into the more common use of data is versus data are. So expect me to stumble around that on occasion as we go forward, but today I think will be really a lot of fun. So here's our kind of intro. Now that I've kind of said that what we're going to do here, I have with me today Colleen Sullivan, the chief operating officer for JLC and one of our highly used associates in developing people's capabilities personally teams and also helping people with change management, change leadership. That's Vince Starks. So they're both with us right now. I know if you've listened to us, you already love these people as I do, so we'll get started with them right now. So just from 30,000ft, gang, what are we talking about today in this first podcast? And there will be at least three, but in this first one, what are we talking about today? From your vantage point, who'd like to start?

Sure, I'll go ahead. I think what I heard was we're going to be talking about data literacy and data fluency and really developing a common understanding of what data is and what those two terms are to help people really be able to use data more effectively. So to make decisions and to really inform them whether they are using it professionally or personally or leading a team.

I love it, love it, love it. Vince, anything to add to that?

No, my colleague was very comprehensive. I just think that one of the things that really stood out to me was just a way of when you talk about fluency and literacy, it's an acknowledgement that data can mean different things to different People. And so it's important to understand that both individually and understand what those impacts could be to your team.

I love it. Both of you, thank you. We are awash in data. Data are everywhere. We are so awash in data that different companies have designed methods to figure out what Vince cares about most, to figure out what Colleen cares about most. And they actually narrow whatever platform you're playing on based upon your interactions with that platform. So those of you that use LinkedIn or Facebook or. Or any of these. Any of the social media platforms that they pay attention to you, they recognize your face when you put it on there. So they actually have an algorithm, a method to identify you, and they actually connect you to people that look like you, and then they notice what it is that you're doing with your time online. Oh, they like to look for ice cream. Oh, this person is looking for clothes all the time. Oh, this person loves sports. What happens is when you interact with the platform and you make comments or search for things, these companies use methods, algorithms to find out, oh, this is what Vince cares about. This is what Colleen cares about. And they narrow that down a bit. It's interesting to me that they do that simply based on our interactions between. In the platform and between the people that you talk with in the platform. And so, Colleen, have you noticed that yourself as you're playing on different particular platforms?

Yeah, I mean, I have. It's funny because we redid our bathroom last summer, and literally I was looking for mirrors, and just on Amazon, and the next thing you knew, when I got on Facebook, guess what was popping up? Mirrors. So I think that happens frequently, and that happens all the time, because to your point, they're looking at the what is of interest to me, and then they're bringing that forward. So, you know, it's in the advertisements and it's in different platforms as I just kind of pop through my phone and open up different apps.

Thank you. Thank you. Have you had similar experiences, Vance?

Oh, absolutely, man. So, as you know, I'm in the process of purchasing a new home, a new construction for the first time. And so along the way, you know, I'm looking at, hey, what about garage floor doors, epoxy floors, you know, and, hey, I got this new kitchen counters, you know, and, man, getting Wayfair. Every garage door epoxy company in Northern Virginia has been sending me emails on their products, and I need it. But that's exactly what's happening because I began six months ago doing searches on new homes, new construction.

So that's Excellent. So you just are now making the first of three points I want to make in this particular conversation that we're having today. There's so much data available, we sometimes start looking at the data before we decide our intent. Now, you both decided an intent, and because of your interaction with the platforms, they started giving you more information. What I'm going to do is suggest very strongly to you that the very first thing we need to become is outcome or goal centric concerned about this situation in our organization. I'm concerned about quarterly sales. I'm concerned about the necessary tactics that are going on. I'm concerned about the amount of antibiotics that are available and the amount of antibiotics that are needed. I'd like to first figure out what is the big theme or question that I'm trying to answer. And here's the edge that I see happening. Somebody will say, tell me more about antibiotics in the clinic. Okay, that's not a very clear question. It's just tell me about them. So, okay, I'll tell you everything. We have 10 trillion of this and 5,000 of that and 100 of these and 200 of those. And here you go thinking that this person who asked for the data has some other expectation. So the very first thing when you begin to become literate and then fluent in using data is to be exceedingly clear on the outcome that you're trying to accomplish. So I suspect for your both experience so far, the algorithms figured out your intent. Maybe, maybe there was something more than that going on. So the very first piece, when we say, listen, we want to become literate and fluent in the use of data, the beginning point is to clarify, what's your question? What is your interest? What is the goal you're trying to accomplish? If we don't do that, we have a tendency to just get all kinds of data from all different spots inside the system that may or may not be, and here's a very important word for us to grab onto actionable data. We want the data that we receive to allow us to make a decision, to make it actionable. If we are just getting page after page and page of data, it's wonderful, and I can make my own interpretations of it. I'm not so sure they are the variables or the key performance indicators that are necessary.

So.

So, Vince, what are you hearing me say and what are you thinking right now?

Yeah, so what I'm hearing you say, Ray, is that it's important to understand outcomes and let that be the driver of the data that you seek. But more importantly, what it meant to me was the importance of developing a common or shared understanding of what the desired outcomes are within the team. People generate data, could be very analytical people at your table, and they love it. They love the numbers and the dashboards, and that means something to them. And they are bright and they're showing you just how deep you can go. But to me, as an end user, if that's not my skill set, if I don't understand how to apply that data towards a shared understanding or desired outcome, then it can hurt myself and the team as much as it can help. So as you were talking, those are the things that were really, really resonating with me.

That's brilliant. I don't expect that every commanding officer or every CEO needs to be a data scientist. We need to learn how to use the data sets or the variables that matter most to us moving forward. That was really well said. Colleen, something to add?

Yeah, just really thinking about that, what you said around. We're in the information age and there is so much data. If I don't have situational awareness or, to Vince's point, a common understanding of what it is we're trying to accomplish, then how do I know what data sets are most important? I don't. I'm just bombarded with stuff. And now I get into a space because we talk a lot about creative tension. We've talked about it before. I'm in emotional tension because I'm overwhelmed now. It's very, very difficult for me to discern between what are the data sets I need to be aware of and what aren't, because you're not going to be looking at everything in every situation. If I don't understand the desired outcome, if I don't understand that piece, if everyone around the table and my team doesn't understand that, or the people that are providing the reports and the data sets and creating the dashboards. If there's not connection there as well, then I'm going to get a whole bunch of stuff. But is it really going to be the information I need to really move the organization in the desired direction?

Yeah. So there's something really powerful here where whoever is your team, your audience, so to speak, that you're going to look at this particular data set or sets of data. If I don't have a common understanding, to Vince's point, between the audience, the people I'm working directly with, and the intent, I'm gonna get all kinds of stuff. My best example of that was I was working for a company that builds big Buildings, Big, big structures. Right. And they asked me to come work with a gentleman data scientist inside this organization who was going to give a presentation to potential buyers, someone that was going to buy their services to build a huge structure. While I was there for about 35 minutes with this gentleman doing slide after slide explaining stress factors, the size of the pieces, the kinds of materials that would be most useful, how to rule out these features and rule in these features and about the materials and the structural piece that's going to unfold. At the end of this 35 minutes, he stopped, I think, to get a glass of water and a woman team of about 12, 14 people he was presenting to. Woman raised her hand and he said, yes, ma', am, how can I help you? Do you have any questions about the presentation so far? And she said, no, not really, but I would like to know whether the building will be pretty. And he was stunned. He was like, whoa. So there we are. I have intent to share information with this audience. I didn't really know what they really wanted from me. We didn't take the time to build that agreed upon common, commonly centric outcome of this particular meeting. So when the leadership team finally gets that together. Now, Vince served in a situation where there was a triad, there was a commanding officer, there was an xo, and there was a chief. Master chief. Right. And those three have to have a conversation about, we need to learn something about X. And the question has to be beautifully positioned so the data scientists, the people in the system, can go ahead and bring it back. How does that story land on you, Colleen, in that little piece I just did?

You know, it's funny, because what I was thinking about is going back to, you know, just even I know, Vince, you mentioned you were an ER nurse for a really long time. So can you imagine if you were in the ER and the doctor's like, just give me a tool. Give me something, and you had no idea what he was trying to accomplish. It's like, okay, well, we got a lot of stuff over here, boss. Which one do you want? Right. And so how. Unless to your point, that's a very simple, simple story, but it just kind of popped into my mind because it goes back to if I don't understand the end state, I'm not quite sure what it is you need to get the job done.

Yeah, I'll just take anything. Sure. So I need a scalpel, but actually he handed me a wrench. It's not helpful. So there's so much possibility in this particular space where the team And I like the idea of an operating room where the team is clear on the intent. They're clear on it. They have a common understanding. The space is so psychologically safe that they can ask for anything they need. Or what's happening with blood pressure. Well, right now it's 120 over 80. However, 70 seconds ago, it was 190 over 110. That would be good information for the surgeon to have moving forward. But if we aren't clear about the need for the very important variables. There are significant variables. Notice my language. Significant because this is the language of data fluency, which we're going to come to in a second. Vince, how did those stories resonate with you?

Yeah, I thought those stories, man, were spot on. And I thought it was, you know, the presentation and information that the guy was talking about building structures was absolutely important. Right. There was a safety factor in what he was doing. Absolutely qualified. But the question that came from the partner at the table was about design and the end product and what was it going to look like and how was it going to feel equally important. But again, to your point, man, they didn't have a common understanding of where they were. And so you had these two different data sets that were incredibly powerful, incredibly important, but they were not linked. And so I thought that story really, really captured and brought that picture home. Beautifully well stated.

Love it. Thank you. Thank you so much for that, Vince. So intent and audience really matters. Intent and audience. You know that we work with some Fortune 50 companies that do a lot of sales. We need to have clarity about what's happening this quarter, what's happening the past two quarters, what are the indicators that we're moving forward. Those things all matter when there is a shared feeling and a shared meaning, common understanding about the intent of the conversation. Without that, we have a 10 tendency to get very drifty and start telling about single datums. And at one point, as I said, about blood pressure. So my friend had a problem the other night. He thought he was having a heart attack. And so what happened was when they finally hooked him up to some material, the emergency gang, they could actually watch his heart rate over time. Now, when I got there, I did a quick assessment, but all I knew was here's his pulse rate right now at 11:27. Right. And here's his blood pressure and eyes are equal and reactive right now. I did not have an expanded set of data points that would allow me to make a better determination as to do we need to transport this guy. Is this really a heart event? What is this? And of course, One of the EMT's biggest deal is don't let them die. So they're going to hook them up and get them to the place. It can take some more time and look at a broad perspective. But the audience arrived, there were five people in the room, not counting me, all emergency medical people, sharing the data with one another. The intent being we need to make a determination as to whether we transport him or not. Is he going to be okay or not? So they had a clear, very clear intent, and the audience was very interested in hearing one another's perspectives. So as we start this game forward, the two big points will fold it. One, we have to really be outcome and goal centric. We really got to think about that, what are we trying to accomplish and make sure that the audience is with us on that intent, otherwise we drift someplace else. So that's probably the big piece for this first few minutes in this part of the podcast that I want you guys to get your arms around. And in the next session, we're probably going to shift into what's the difference between literacy and fluency? I think that is a very important piece when we start thinking about data and data sets. So let's close this one out right now, but let's close it out with events. Playing your role as commanding officer and your triad was very interested in getting data about wait times. Why did you care about wait times and how did the three of you go about taking care of it? What would you tell the audience about that?

Sure. So the first thing I would say is that the healthcare system utilized wait times, the time it took from a person to walk into you during the time they actually saw a provider getting care. That became a universal standard across the country in terms of quality of service. How quickly are you able to get people to care, to actual care? And so looking at that and understanding that was a systematic or enterprise measure, it became a central thing that we were going to use as a measure of how well we were performing across different parts of our system. So what I need to do is understand what that meant to our system, understand that measure for quality. And then I had to communicate to my team that this is something that we're going to look at. This is what it means to the enterprise, and this is what it means to us and the people walking through our doors. I wasn't going to change anything until I developed that common understanding. So I spent a significant amount of time just making sure the team understood why this was going to be important. To us and how everyone had to be on board in their own individual areas to drive us towards that outcome. And so that was a very early measure with something that we could look at. It was something that we could talk about. It was something that we can look at where we need to make adjustments. And it was something to bring the team together and get us moving in the same direction. So I tried to do that across the enterprise and that was a very good example because it's not complicated but extremely important. And the data wasn't complex data. It had to be simple enough so that the team could understand. I could have a dashboard that would blow your mind with all kinds of colors and graphs and lines, but it wouldn't mean anything to my people. I had very sophisticated, high level professionals and I had paraprofessionals and. And everyone had to understand the information the same. So I worked hard at keeping it simple.

Simplicity is so important. And when we recognize we can produce some words, some language that helps us understand the data, this matters dramatically. I will tell you guys a sub story on what Vince just laid on the table. He had a wonderful XO that became the commanding officer of a facility that I went to. And we were sharing data about wait time. And I asked a question in the middle of the conversation. I said, do you guys keep track of who goes early? And they all just looked at me. What? I said, you keep track of wait time? People that have to wait more than a moment to see a provider. Have you ever done the other side of that, which is who's in early? And it was like, oh, wow. We need to really think about the variables that we're chasing because we're chasing one side of the equation. They came to learn, and thanks to you, Vince, and your training of your xo, who is now co, he came to realize, boy, we have lots of people getting seen early, but it was hidden from us because we didn't chase it. He was great. Rob was great at that. And boy, that. That development you did with them really helped tremendously. Colleen, how's this landing on you?

I think what's landing on me is what you just shared and the fact that sometimes we can lock on to one data point and start to make decisions and say, this is actionable intelligence. I can apply this data point. However, am I really seeing the broader picture? So I think I'll go back to what we talked about earlier. Intent, right? Ensuring that everybody understands what is the intent. The audience. Who's the audience? Who are we talking to? Right. And clarity. And what other questions and what other data points will help me fully get a broader understanding and more clarity around this situation? Because if I just lock on to the one or two pieces that I like right, my boss, my boss told me are important, I might be missing a bigger, bigger picture and a bigger perspective of truly understanding the situation.

So I'll probably say this in every podcast, but I want you two to help me remember as I was studying the fluency part of data development, data literacy and data fluency. As I was studying the fluency side, one of the gentlemen made a great comment in this little mini course I was taking. He said that if data is used, data are used well, they will provoke two things, curiosity and creativity. And the stories that you guys have been telling me today have all been about that. It's not like confirming my bias. It actually allows me to ask more questions. And if we're doing data fluency correctly, we can create conversations that produce creativity. All of this is all connected to the work that this wonderful team does that Colleen and Vince do all the time in helping people have high quality conversations about significant issues. Notice my language. Significant issues, not all the issues. Because we must have clear intent, clear goal, and understand our audience. Ladies and gentlemen, thank you for being with us today. This is the first in a little series of podcasts about what does data literacy and data fluency really mean? Thank you for being with us. See you on the next one. Sincerest thanks for listening to this episode.

Of the Everyday Leadership Conversations podcast. The Jorgensen Learning center offers a variety of programs for individuals and organizations to enhance their communication and leadership skills. To find out more about programs and upcoming webinars, check out our events page@gojlc.com.