Customer Equity Accelerator Podcast

Ep. 74 | Teach Your Team to Communicate Insights w KeyBank’s Kathleen Maley

 

"Most analysts are trained to communicate the validity of their answer, but your business partner only wants to know what she can do with this information." Kathleen Maley

 

This week Kathleen Maley, Sr. Director of Consumer and Digital Analytics at Key Bank joins Allison Hartsoe in the Accelerator. Through first-hand experience Kathleen wrestled with the analyst’s “data pulling” problem but then she found a better way. Her process turns a typical analysis on its head by asking the right questions both up front and once the data is in-hand.  A former teacher, Kathleen educated her team on this highly effective process and now she shares her discovery with you this week in the Accelerator.

Please help us spread the word about building your business’ customer equity through effective customer analytics. Rate and review the podcast on Apple Podcast, Stitcher, Google Play, Alexa’s TuneIn, iHeartRadio or Spotify. And do tell us what you think by writing Allison at info@ambitiondata.com or ambitiondata.com. Thanks for listening! Tell a friend! See the full transcriptView all episodes.

 

Setting Expectations on Data Science Projects: What am I doing and why am I doing it? - Kathleen's 12 question method to help you help your partner get the answers they are looking for.

 

If you want clearer insights from your data, check out some of our services:

Predicted CLV Calculation

Customer-Centric Reports

Campaign Tracking

Behavioral Segmentation

Ep. 75 | Retail Reimagination with Forbes Contributor Steve Dennis Ep. 73 | Marketing Analytics Evolution with Jim Sterne

Show Transcript

Allison Hartsoe: 00:01 This is the Customer Equity Accelerator. If you are a marketing executive who wants to deliver bottom-line impact by identifying and connecting with revenue generating customers, then this is the show for you. I'm your host, Allison Hartsoe, CEO of Ambition Data. Each week I bring you the leaders behind the customer-centric revolution who share their expert advice. Are you ready to accelerate? Then let's go! Welcome everybody. Today's show is about teaching your team to communicate insight and to help me discuss this topic is Kathleen Maley. Kathleen is the senior director of consumer and digital analytics at KeyBank. Kathleen, welcome to the show.

Kathleen Maley: 00:49 Thank you, Alison. Thanks so much for asking me.

Allison Hartsoe: 00:51 Yeah, tell us a little bit about your background and how you are kind of attracted to this topic.

Kathleen Maley: 00:57 So I would say it brings together two of the careers I've had. I've always loved math. I fell in love with statistics. I started working as a modeler, actually was my first job. At some point, I moved into analytics, which I do see very differently as is predictive modeling, moved into analytics and absolutely fell in love with the work that I was doing, and the value that I was able to create. As I work through my first sort of role as a working analyst I learned a lot that I was able to translate into then as a manager, being able to communicate to my team because I was no longer responsible just for the project I was working on. I was responsible for the project my team was working on too, and over the last, I would say five years especially what I've come to appreciate is how important it was then and even more is now to help my team with those skills that are required not just in doing the analysis, but and then communicating to our partners in order to get the value of the work that they've done. I was a teacher in my former life. That was what I did.

Allison Hartsoe: 02:01 That's why you're good at this.

Kathleen Maley: 02:02 Well, yes, I think it is. And so now I've landed in this very sweet spot that I love, and it's all about bridging the gap from the analysis to the value creation. And the only way to do that is through communication. I still cannot be responsible for every single project that my team is involved with. I have to make sure that they have the skills and the training so that they can do it themselves.

Allison Hartsoe: 02:23 Oh, how big is your team?

Kathleen Maley: 02:24 I've got about 25 people on my team right now and I work very closely with almost all of them.

Allison Hartsoe: 02:31 And are they all analysts or do they do different functions?

Kathleen Maley: 02:34 Everybody on my team is an analyst now. We support the consumer and the Consumer Bank and our digital team. So we support all of our product lines. We support all of the traditional channels to include digital as the traditional channel at this day and age. And so while we're all focused on different topics or function as really the same, and that is uncovering mysteries, exposing new information, solving logic puzzles. And sometimes it happens to be focused on a checking account. And sometimes it happens to be focused on what clients are doing inside of a brand.

Allison Hartsoe: 03:05 It sounds like the mystery machine in the Scooby Doo, the Scooby Doo group.

Kathleen Maley: 03:11 I often think of us as private investigators, and that is a large part of what we do. We just try and figure out what in the heck is going on and how can we create something of value and put it into perspective for partners so that they can actually use it to make better decisions or make more money.

Allison Hartsoe: 03:25 So I'm actually gonna call out something that you're saying that the listeners may or may not realize, but oftentimes when I talk to people who are running large teams, the common complaint is, Oh, we've got a land data and we don't have enough time to really do insights. But your avenue is a little different. You're saying you're spending your time really investigating the data and producing the insights. Do you think your particular way of finding those insights and your sharpness at how you look at that is what's driving that instead of spending all time on the ETL side?

Kathleen Maley: 03:57 Well, unfortunately, it is also true for us that we spend about 80% of our time just getting up the data.

Allison Hartsoe: 04:02 Ah,

Kathleen Maley: 04:03 yeah. I mean we haven't felt that puzzle either. We still deal with that, but I think the differences, I don't want to rush to create a whole bunch of summarized data sets that nobody can do anything with. I would rather produce less, but ensure that we actually pull the thread all the way through to our business partners can do something with it. So I have a lot of conversations with my team and with our partners to say, tell us what's really most important. Where do you want to spending our time, highest and best you? We can rush through to produce all of these data sets, good luck understanding them. Or we can really focus on helping you understand this question that you're trying to answer. And inevitably they choose, okay, help me understand, help me do something that will take action. Taking action is in one place as much better than having some information about three different things, but not actually being able to do anything.

Allison Hartsoe: 04:54 That's perfect. Now so I'm going to play the devil's advocate here for just a second and say, why do I have to care about teaching my team to communicate insights? You naturally had this background in statistics, and you're able to communicate insights. These insights just kind of fall naturally out of the data?

Kathleen Maley: 05:12 I think absolutely they do not. Unfortunately, that is way analytics has been positioned for the last many years, right? Is analytics that sort of as a discipline is gain traction, and people said, okay, I'm hearing about this analytics thing. We need to be doing analytics. There was a rush to hire all of these people who were very well technically trained. Great place to start, but I think now what we are realizing across the, I'll talk about the analytics industry, of course, this fields that can be applied to in banking, it can be applied in Pharma. It can be applied at any number of places entertainment, but for analysts, there's this, in anybody who's using analytics, there is now this emerging understanding that the analysts are very well trained in the math, in the statistics and the methodology. They have not usually ever worked in business, and they have almost certainly not received any training on defining a problem.

Kathleen Maley: 06:02 What are we actually working toward or communicating that answer? In fact, the training they receive on communication is all about communicating the validity of their answer. They talk about the objective, right? They talk about the methodology. They talk about their sample. They talk about what type of model did they use, right? It was it, uh, unsupervised learning, was it supervised learning? But the problem is you're not talking to another statistician to convince that individual that your results are valid. You're talking to a business partner who just wants to know what she can do with this information, how this information is useful and relevant to her and her decisions. And so if we don't augment and supplement the training of our analysts, then they produce great work that is very valid, and we can write interesting white papers. No one will ever be able to take action on it. And that's just not what my job is. My job is to improve the ROI of the company, to improve the revenue, to reduce the cost. That's our job here. And so being, recognizing this missing skill and augmenting it means that we can be effective.

Allison Hartsoe: 07:10 Now how did you recognize this in your team? Was there an example of how you kind of stumbled across this or how you realized that there was this giant gap?

Kathleen Maley: 07:21 So it took me many years to really figure out how to articulate what I think I was already doing to some extent, what I had figured out for myself as a working analyst and much of what I share with my team now, I learned through very painful experiences. I won't call them mistakes.

Allison Hartsoe: 07:40 Yeah.

Kathleen Maley: 07:40 They were experiences from which I learned, but I would say that the one that was really most magical for me, the one that sort of lifted the veil, the one that caused the light bulb to turn on, even though I couldn't really articulate it at the time, it changed the way I approached this work. I was working with a very senior business partner who made a considerable investment in his contact center, and he created a specialty gate so that our most valued clients were routed directly to this specialty gate. And when he came to me, I had just taken a role as client experience analytics leader. So I did have a team of people working for me, but in this case, I was taking the work on myself. He came to me, and he said, okay, I need the data that shows that client experience has increased because of this investment and change I made in the context center.

Kathleen Maley: 08:27 Now up to this point, almost every question that came to me came in the form of, Hey Kathleen, can you get me this data? I need year over year client satisfaction of this type of clients. And I would say, okay, sure I can get you that data. How do you want to cut? Do you need it trended or a snapshot? Okay. And you know, but he came to me as luck would have it with just politely different wording. I want to show them there's been some benefit based on this change. And so that just triggered some questions in my mind. Well, okay, what did you do? Why did you do it? When did you do it? What did you expect the outcome to be? And we were able to start actually investigating the effects of what he had done, not let me give you the data that shows you this difference in sat scores.

Kathleen Maley: 09:09 There was a difference in sat scores, but what was the effect of this thing that you did and what we discovered. I also had a very, very good manager during this period who taught me a lot about how to navigate this situation, but ultimately after asking a series of questions and looking at the data from a very different perspective, what is the question we're trying to answer? As opposed to what is the data that the person wants? What we discovered is it actually didn't have anything to do with the financial investment he made. I'd had everything to do with his talent selection, and so once he understood how he could continue to grow this gate, he was actually very receptive to the answer. Right. I could have given him the data, and he would've seen, okay, great. Satisfaction is higher than it used to be. I'm going to make another considerable investments, several millions of dollars, and I'm going to grow this gate.

Kathleen Maley: 09:58 It's going to be even better, and because it wasn't the money. It was the talent selection process. We were able to say, don't spend the money. Let me help you identify your next set of agents so that you can grow this in a responsible way, and it just, because the outcome was so perfectly exactly tied to the analysis and because the analysis was so perfectly tied to the way we approach the question. All of this just sort of was revealed for me in terms of how we need to think about the questions we're working on so very differently than I had previously.

Allison Hartsoe: 10:28 Oh. What I think is unique in that, and maybe it was partly the role of your manager at the time, but you didn't put the other person on the defensive when they asked for, just give me something that proves acts because I want to make more investment here.

Kathleen Maley: 10:43 I would say my manager was a big help in that, he understood sort of the politics, the psychology. This is the leader who had already done something. He had already spent some money. How do we make sure we take him the answer in such a way that he can do something very positive with it. We're all still human beings, and so it is important for my partners to trust me, and in order for that to happen, it's important that I make sure that they are positioned for success whenever possible. Everybody wants to be able to stay face. Nobody wants to be called out, and the fact was none of us could have known in advance, so now it was all a question of where do we go from here? How do we make better decisions from here?

Allison Hartsoe: 11:22 Did you already have a pattern of trust with that particular partner or was this part of the process?

Kathleen Maley: 11:27 I was absolutely brand spanking new, and so it took, this project did not happen overnight certainly, but there was a lot of dialogue, and there was a lot of time with me and my manager sort of strategizing how do we actually get this on paper in a way that is going to be received positively but on the project as well. Again, the way this leader brought me this question set me up well because I was able to ask a whole series of questions so that I could really get it what it was he was trying to solve. And so I think this is a point I want to highlight, which is at that first step when we're defining the question, I learned, okay, I need to have context, that exercise taught me, I need to have context. I don't have context. I don't know really what question I'm answering.

Kathleen Maley: 12:07 I have no hope of delivering anything meaningful. So how do I get the content? And again, it was brand new to the job and brand new to all these individuals in these personalities. And I would say things like, why? What are you doing? What decision are you going to take? And my intention was good. My intention was to really understand what they were trying to achieve. So I get to help them so I could get it as close to right the first time as possible. But the tone of that language often put my partner on the defensive. Who are you to challenge me? I know what I need. I had to develop a new language over time. How do I actually have a conversation? I'm an analyst. I love math because math is black or white. It is where it is not, and it is the fact, just the fact.

Kathleen Maley: 12:50 And why do people have emotions around fact? Um, but the reality is most people do. They have emotions around facts. And so I had to learn how to approach these individuals using a language that actually demonstrated my intention. And one of the things I learned how to say, anytime somebody comes to me, Hey Kathleen, can I have this data? I immediately say, help me understand what you're trying to achieve so I can better meet your needs. It is nonconfrontational. It sets out exactly what I'm trying to achieve. I need to understand because I want to help you. Not because I'm asking you to prove or justify the work you want me to do, but because if I don't understand what you're trying to do, there's no way I can help you effectively. So be my partner in this. Help me understand what it is you're really trying to get at so that I can go away and do good work for you and bring back an answer to your question. So there was the backend, but the front end is more important in terms of knowing what I'm trying to get at.

Allison Hartsoe: 13:43 And the phrase was, help me understand what you're trying to achieve so I can better meet your needs. Right? That's right. It reminds me a little of Jerry McGuire like you help me, help me help you.

Kathleen Maley: 13:55 Right? And you know my team laughs because I say all the time, I don't care what your partner says to you. I don't care if it's an email. I don't care if it's a pin, I don't care what it is. I don't care that they tell you it's a fire drill. I don't care that they told you that it's coming from the CEO. You do not start pulling data unless you have had 10 to 15-minute conversation. And it always starts with help me understand what you're trying to achieve. Ignore them, whatever they have said, ignore them. Help me understand what you're trying to achieve. Every question,

Allison Hartsoe: 14:27 What if the analyst has a 10 to 15 minute conversation, but maybe they don't really ask enough questions, or they end up with kind of a very weak piece that comes back on the context or into the context itself is weak, and so for 10 to 15 minutes, they basically get, it's a fire drill, and I need it for the CEO. How do you help them get deeper?

Kathleen Maley: 14:46 Sometimes it really is a fire drill, and it really is for the CEO, and it's hard to say, okay, we're just, you don't call it the CEO and say, what you're trying to achieve. You just build that. That's with the reality of the world in which we live. But what I have found is nine times out of 10 isn't really the situation. Right. And it comes down to, well, so and so called me and so and so was in this meeting and it came up that act, and now we're trying to see why. Okay, that's interesting. How can I get somebody who was actually in the meeting and actually heard the dialogue? So getting to primary sources, critical, I'll probably never get as close to the CEO. In fact, sometimes it happens, right? Hey, I thought our average age was this. No, I thought it was that, okay, well there's a right answer. Let's figure that out and let's put it in context and put it to that as quickly as possible, but if I can get closer to the primary source, ah, he saw this number on a page and he's reacting because it looked different than this other, but now I know the page he was looking at was actually a subset of clients, so there isn't anything wrong. It was just a different group that was defined somewhat differently. Getting to the primary source is extremely helpful in doing that.

Allison Hartsoe: 15:55 I can see how that would be. That's fantastic! And do they need to do more on the front end or is that enough and then you start working with how you communicate the answer on the backend.

Kathleen Maley: 16:02 You asked the question, what if they have the 15 or 20-minute conversation, 10 to 15-minute conversation and it's very weak context. I actually give my team a starter set of questions. It's literally a one pager. It's got 12 different questions on there. What are the sorts of questions you can ask to get the dialogue happening? Very often that the hardest thing is how do we even start the dialogue? How do I go beyond weak contexts? And it seems like, hey business partner, what's your hypothesis? Are you worried about something? Has something changed? Just always getting at where is this coming from? So one of two things happen, right? Either they have no idea what the context is, and I say, okay, I need more information before I can start on this because again, I'm not helping anyone if I'm working on something that isn't leading anywhere.

Kathleen Maley: 16:44 So if it's really that important, you got to come back to me with something, or it kicked off a dialogue, and it's that dialogue that becomes meaningful. And so one of those two things will happen when it comes to, and one of my favorite things, if I've done this really well, my business partner will say, okay, here's what's really going on. Don't share it because it's confidential, but here's what's really going on. And it's when we get to that point of view is what's really going on, then we can actually start to get into the work and answer the question.

Allison Hartsoe: 17:13 That's fantastic! So basically they have this set of 12 questions and what they're trying to do is get them to kick off the dialogue with the business partner that uncovers the primary source of what happened, the why and when you hear the magic phrase of, well, this is what's really going on and keep it confidential. Then you know you've struck gold.

Kathleen Maley: 17:31 Yes, absolutely. And it happens all the time. Nobody can do anything without data. I mean it really, we really are in a very fun spot. Very often, the analysts in your organization are the only people who know every single facet of a problem that the business is trying to solve because everybody has to have data. Then we ended up in a very important position we see across, and we can connect dots where others can't just because we have a broader perspective because everybody is coming to it.

Allison Hartsoe: 18:00 And because you see across, does that also sometimes cause a little friction with the business partner where maybe they're asking for something that's fairly narrow, but you can see a better way to approach it. How do you deal with that?

Kathleen Maley: 18:14 Well, it's interesting that you would call it friction. I don't see it as friction at all. I see that as a very positive thing that I would say generally, not always, but generally that observation is very positively received. Now there are cases where that may not be the case. Every individual product line is responsible for his or her product line. That is what they're 100% most focused on. I have the luxury and the obligation of thinking not about any individual product line, but how our products come together to serve the entire need that of the clients that bank with us. So it is sometimes we do ask our partners to take a step back and think about this more broadly like, yes, I can do this for you if we're only looking at this one product, but if we're looking from the client's perspective, does it make sense that we have one set of definitions on this product, a different set of definitions on this product and a third set of definitions on this product.

Kathleen Maley: 19:11 So I don't necessarily have to make the decision on what we're going to do about it. In fact, I don't think that's my responsibility to make the decision. What is my responsibility is to reveal, to make observations, and to ensure that any decisions the business partners make are informed decision. Okay. You now see that we have three sets of definitions that clients have to navigate in order to manage their three different product sets, right? Check, call, checking savings, and borrowing a mortgage or a car loan. Think about what you're asking them to navigate. If you're okay with that, you can make that decision. If you're not okay with that, let us help you decide what is the best definition to cut across all three of these product lines. Ultimately, it's the business partner's decision. My obligation is to make sure the decision they make is an informed decision, and very often, the answer is obvious. What makes the most sense is obvious, and when the right people are brought together to have that conversation collectively, which is what our data enabled, it makes it much easier to come to a logical and best answer for our clients.

Allison Hartsoe: 20:11 And are those 12 questions something that you can share with us? We can put into the show notes.

Kathleen Maley: 20:16 Yeah, I'd be happy to do that.

Allison Hartsoe: 20:18 Oh, fantastic!

Kathleen Maley: 20:19 In fact, I have a whole sort of, this is one of the talks that I've shared with my team and l for that sort of goes through this process of how do I define the question up front and what are the things I need to think about and how to communicate after the fact. Again, I work with really, really smart people who've received a lot of training on predictive modeling and using R and python, to create summarized data sets that can be analyzed for meaning, but we don't typically have the training on the front end defining the question, the backend communicating, so this is something I've actually tried because I've been teaching it to my team for so long. I thought wouldn't it be useful to put something down on paper.

Allison Hartsoe: 21:00 Oh, Kathleen, that's fantastic! You got to write a book that would be gold for so many analysts. So let's switch to the back end because I think part of the communication is setting it up correctly in the front end. If you don't do that, you're really dead on arrival when you try to do the backend. But I imagine that with all these technical people who are trying to talk about the model and the academic approach, that when they go to communicate insights, you've got to teach them to come away from that. How do you approach the back end?

Kathleen Maley: 21:26 So typically we think about our work and the order in which we do our work, right? First, we define the question, well, how do we do that? Define the question. That's sort of what we've been talking about. And then it's time to do the work. This is the part all the analysts are super familiar with. You pull the data, you summarize the data, you analyze the data, and you have to be able to draw conclusions. So there's a whole lot we could talk about in terms of drawing the conclusion. But let's just say we've drawn a conclusion and we sort of, we know what it is we want to tell back to the partner, right? So here's an example of, hey, do I need to worry about the impact of the government shutdown? Well, now, I know my answer. I can draw my conclusion based on all of the work that I've done.

Kathleen Maley: 22:01 How do I communicate this back of partner? I like to actually work backwards. When I am talking to a business partner, I do not want to have them walk my analysis path with me. My analytical path it is irrelevant. What I did to make sure I have confidence in my conclusion is absolutely critical. Really important. When I'm talking to another analyst, absolutely irrelevant to the partner, you just feel the trust that I know how to do my job. So when it comes time to talking to the partner, I literally work backwards. I start with my answer. I look back to my conclusion, and I ask myself two questions. What is my conclusion? How do I know? And the how do I know comes out of all of that analysis and summarize data that I've worked through. I have to study that stuff, and I said, Aha, here's what's happening.

Kathleen Maley: 22:50 And I know that this is happening because I thought Xyz, everything else falls on the cutting room floor. What is my conclusion? How do I know everything else falls away? None of the other stuff is relevant. It was all supercritical and me getting to the answer, it is not at all relevant communicating the answer. The only thing the partner needs to know, here's the conclusion and here's how I know, that's it. And it's got to be in a language they understand, which isn't about repeating data point. It's connecting the dots. This is this way because of this. So it is a sentence. My answer is never a table. My answer is never a chart. My answer is a sentence that is written in English.

Allison Hartsoe: 23:29 Wow. Okay. So I'm going to ask you for an example of that because it seems very powerful. And when you produce that sentence that's written in English, are we talking about 40 PowerPoint slides? Are we talking about 10 are we talking about a pitch deck? We're talking about one. How do you present it as well?

Kathleen Maley: 23:47 So my general rule of thumb is one slide. So we're in banking, we use a lot of powerpoints. One side, that's it. If I cannot say it in one slide, I don't know what I'm saying. That's the bottom line because it's usually one or two meaningful sentences. Right?

Allison Hartsoe: 24:03 So, Kathleen, let's say you have the conclusion, and you get one PowerPoint slide that communicates one or two meaningful sentences. What's in the rest of the presentation? Is it just like a five-minute presentation? Here's the point, and everything else falls away.

Kathleen Maley: 24:18 Oh, it's interesting. I don't really think of the work we do as being about the presentation, right? Somebody asked the question, we bring them back and answer that is usually in the form of a sentence, and they're usually a little bit of data or some visualization that support that. Right? Cause there will naturally be some follow-up questions. I know I've done a great analysis. If the focus is on me for about five to seven minutes and then it's about what's next, what's the action we're going to take? Do we like the answer? Do we not like this answer. So if all I'm talking about is the analysis itself, we're not really getting anywhere. If I've put the information on the table to drive a business conversation, then I know I've done a good job. My favorites are when in fact this was again around the government shuts down the analysis we did around the government shutdown, and that was one of those ones.

Kathleen Maley: 25:07 You have a day and a half, two days to pull something together. People were very worried naturally, it's a big risk. So in this case, we just submitted our findings by email, made sure all the right people were copied, laid it out, which by the way, when you submit findings and writing, it has to be crisp. It's actually harder to do than most people think it should be, but what came back after it was digested by leadership was, Hey Kathleen, thanks. This is really helpful team. What are we going to do about x, Y, z? That is perfect. That means we hit it. He understood what we were communicating. He understood the magnitude of the risk, and he was immediately able to turn to his team and say, if this is where we need to focus, what is our plan for doing it, that is what success looks like.

Allison Hartsoe: 25:52 Wow. That's fantastic. I love that metric.

Kathleen Maley: 25:55 Yes. It's very simple. Are they doing something, are they now in a position to do something.

Allison Hartsoe: 26:00 exactly five to seven minutes on me and then the balance of the time on the action, what are we going to do? And it's almost like an 80 20 rule, right?

Kathleen Maley: 26:09 Yeah. It's so interesting because decks will be brought to me. Hey Kathleen, I'm getting ready to share this. What do you think? 10 12 15 pages long, and I look at chart after chart after chart after chart. Okay. Let's have a quick conversation. What is all of this really telling me? Well, what it's telling me is that actually there's a lot of office opportunity with clients who are already banked with us. Okay. That is your one sentence at the top. There's a lot of office opportunity. Now give me the two or three data points that show that and here they are and now we're done. Do you want to leave the 15 pages in the appendix? That's fine, but we just the 50 pages of the summarize data, the analysis, that active analysis is what gets me from 15 pages of data, to there's a lot of office opportunity when we should go after it and here's one way we could do that.

Allison Hartsoe: 26:51 I love it. Do you think the heavy focus on data visualization is a crutch where we're trying to communicate with chart after chart after chart, but we're not getting to the root of the problem.

Kathleen Maley: 27:00 I don't think I would describe it as a crutch. But with data visualization is for me the start of my analysis. The analysis is the hard thinking part. It's the drawing of conclusions, and if all I'm doing is putting all of that visualization in front of my partner, I'm asking them to do my job. Now again, early in my career, I didn't think that that's what I was doing. I thought I was sharing with them all of the data that they asked for, and I was because that's the form of the question. Hey, Kathleen, can you get me this data? They don't really want the data, right? I no longer hear the question is they asked if I hear, hey, Kathleen, I need your help with something. And the help that I owe them is an answer based on the analysis I've done and the analysis, the active hard part of the analysis is studying the summarize data, not creating the summarize data. Creating the summary data is easy. It's annoying. That's where we spend 80% of our time. But it's not hard making sense of what we see that part, and that's where they need us. That's where we can be of highest and best use.

Allison Hartsoe: 27:57 I love it.

Kathleen Maley: 27:58 An analytical math.

Allison Hartsoe: 27:59 Yes. I love it. I love the emphasis on really the hard thinking, and it is just like you described at the beginning, it's like an investigation. And so along those lines, are there, uh, particular tactics that someone should work through first, second, third, in order to do this communication style properly.

Kathleen Maley: 28:17 So again, step one look backwards, right? You do all the hard work, you reach a conclusion, you've got an answer. Now look backwards. This is my conclusion. How do I know? What's the data that supports that conclusion? That's the first step. Second step. But I think the power of this when I'm about to say cannot be underestimated. Literally, talk it out. Now you have a conclusion. You think you know what your answer is. Find somebody to talk it through using conversational language. Hey, here's what I think is going on. I'm looking at this data. I'm looking at this. Here's what I think is going on. Another analyst can be very, very useful in that. And their first question should be, what are you trying to get at? What's the answer? What's the question you're trying to answer? So it forces, and this is what I use for myself, and I encourage my team, it forces me to put the information in some sort of logical flow, and through that conversation without exception, I identify things.

Kathleen Maley: 29:09 Oh, you know what? I don't really need to talk about that. It's kind of irrelevant. It's true. It's a true fact. Kind of irrelevant to the question I'm answering here. That'll take us down a rabbit trail. Let me leave that to the side. Okay. I thought I understood this, but now that I have to lean it to you, I don't think I do understand as well as I thought I did. Let me go back and look at that. Oh, that's a really good question that I haven't looked at yet. Let me take a stab at that. Huge value in just whiteboarding it out with somebody else. High level. Here's what I think is going on. Does this make sense to you or not? Huge value in that, and if I'm doing it with conversational language, it means, and again, not this is how I pulled the data.

Kathleen Maley: 29:43 This is what it means. These are the conclusions, the connections I'm making. If I'm using conversational language, I'm already setting it up so that I can have a meaningful dialogue with the business partner. And last, I would say plenty of time. Getting something on paper is hard. It is hard to not ramble. It is hard to make a statement that is crisp, clear and concise. Pascal, everybody remembers Pascal's triangle, right? He has a quote in that. Something about I've made, I apologize for the length of this letter. I didn't have time to make it shorter, and that is how I think about the work that my team does. When they've got to get it down to a single page, you have to know what you're talking about. You have to know what's relevant. And if you do, you can get it to a single page, maybe two, maybe two if you're in a hurry, but you can get it down and so, but it takes time, and my team is doing this for the first time. They'll say it took me half a day to get that paid. Yes, it did. I'm not at all surprised, and as a result, you're going to have a very meaningful conversation.

Allison Hartsoe: 30:41 That is a significant amount of time and I imagine that the process of pulling the data when it's all loaded in, is there a rule of thumb for how long an analysis might take and I realize like depending on what they're asking, it could be shorter or longer, but let's say it's a decent question you have to investigate. How much time do you allow?

Kathleen Maley: 30:58 I think regular check-ins are absolutely critical. So what I try to do is really understand the question, and then we break it into pieces, right and really understand the question. There's lots of aspect to that not just what's the answer you would like, but okay, what I've heard you describe we'll take us six months, you probably can't wait six months, so let's talk about how we stage that, how we tackle one piece at a time. In other cases it's like, Hey, I've got a meeting in four days and I have to have this and I know I should have come to you sooner, but I didn't. Or this just came up now, is there any magic that you can work, and we say, okay, here's what I can do in four days. So it's about sizing the work, the time as opposed to, right. So coming at it from both angles and again it's about open dialogue with the business partner.

Kathleen Maley: 31:39 Is this still work for you? Because in some cases it will be fine. In other cases, no, we need to come up with a new plan. Okay. I don't ask my team to work 18 hours a day to meet a deadline, but I do ask them to shave down the work. We should be doing very often, not always because we should always be getting better as well, right? Looking for new techniques, looking to push the boundaries out a little further, but what is the absolute least that is required for a decision to be made? That is the amount of work I should do. Everything is a return on investment, and if I have done the absolute least for a decision to be made, and then I keep working, I should be asking myself why is this because I'm interested? Is this because I really think it could be a better decision? Is it going to make any difference for all of this additional work and putting in? In some cases, you have what you need to make the decision, and I'd start that with a partner. Will this change the decision you make? If the answer is no, are you sure this is where you want me spending my time?

Allison Hartsoe: 32:32 I love that because one of the challenges was really smart analysts is they don't know where to stop. They keep digging and digging. Yeah. But yet, you know, the responsibility of your team.

Kathleen Maley: 32:41 No, it helps if you know where you're going.

Allison Hartsoe: 32:43 Yes. Well, but also the responsibility of your team is to produce insights, and you can't do that if half your team is online digging and digging and hasn't found a stopping point. So it's almost like a production workflow. Right. So, Kathleen, that sounds like there are really good solid steps. I had actually five looking backward. Once you have your conclusion and understanding how do I know, talking it out and spending the time to talk it out? Finding the Whiteboard, the conclusion, the conversational language, what it means, and then making sure that you have time to, the word isn't the bare minimum, but what's the least required for a decision to be made so that you can find the ROI. I think you will use the word shaved down the work, which I thought was a really clever way, especially when you have to push back at someone. They said, oh, I only have four days. What you didn't say was, no, we can't do that, what you did say is, no, we need to come up with a new plan that we can deliver to you in four days, and I think that's a really nice approach. It makes your organization a very trusted entity for someone to come to. I'll also gently teaching them not to leave you four days.

Kathleen Maley: 33:52 Absolutely. It is my job to help my partners be successful, and ultimately it's about our clients and our shareholders, but we're in it together. We are a team, and so that means, just like, I wouldn't want to be left hanging out to dry. I don't want to put anybody else in that position. We've got to work together to make sure we get the answers that are required, so let's be smart about it.

Allison Hartsoe: 34:12 I love it. So if people want to reach you, how can they get in touch?

Kathleen Maley: 34:16 The two best ways would be , and if they searched Kathleen Maley, I think I'm the only one that comes up, but if they need the KeyBank filter they could add that in, and on Twitter, my handle is @kldmaley, and I'm very active on Twitter actually. I follow a lot of data science group, and it's just a fun way to stay connected to new trends and new pieces of information, and so I do try to retweet things that are of particular interest for the type of work that we do.

Allison Hartsoe: 34:45 Well, I will look forward to following you for sure. Fantastic. As always, links to everything we discussed are@ambitiondata.com slash podcast. Kathleen, thank you so much for joining us today and sharing all these valuable insights.

Kathleen Maley: 34:58 Thank you, Allison. It was a real pleasure to be here.

Allison Hartsoe: 35:01 Remember, when you use your data effectively, you can build customer equity, it is not magic. It's a very specific journey that you can follow to get results. Thank you for joining today's show. This is your host, Alison Hartsoe, and I have two gifts for you. First, I've written a guide for the customer centric Cmo, which contains some of the best ideas from this podcast, and you can receive it right now. Simply text, ambitiondata, one word to, three, one, nine, nine, six, (31996) and after you get that white paper, you'll have the option for the second gift, which is to receive The Signal. Once a month. I put together a list of three to five things I've seen that represent customer equity signal not noise, and believe me, there's a lot of noise out there. Things I include could be smart tools. I've run across, articles I've shared cool statistics, or people and companies I think are making amazing progress as they build customer equity. I hope you enjoy the CMO guide and The Signal. See you next week on the Customer Equity Accelerator.

 

Key Concepts:  Customer Lifetime Value, Marketing, Digital Data, Customer Centricity, Long-Term Customer Value, Marketing Leaders, Analytics, Creativity, Product Development, Audience Research

Who Should Listen:  CAOs, CCOs, CSOs, CDOs, Digital Marketers, Business Analysts, C-suite professionals, Entrepreneurs, eCommerce, Data Scientists, Analysts, CMOs, Customer Insights Leaders, CX Analysts, Data Services Leaders, Data Insights Leaders, SVPs or VPs of Marketing or Digital Marketing, SVPs or VPs of Customer Success, Customer Advocates, Product Managers, Product Developers

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