Welcome to our new podcast!
April 3, 2024

The Data Consultant Triage

The Data Consultant Triage

On today’s episode of How I Met Your Data, Sandy Estrada & Anjali Bansal dive into the heart of organizational challenges and triumphs in the realm of data governance, technology adoption, and the ever-evolving landscape of Gen AI.
 
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How I Met Your Data

On today’s episode of How I Met Your Data, Sandy Estrada & Anjali Bansal dive into the heart of organizational challenges and triumphs in the realm of data governance, technology adoption, and the ever-evolving landscape of Gen AI.   With excitement still buzzing from our launch, we’re tackling the surprises and insights that have emerged from our conversations over the last couple of weeks.  From the dual-edged sword of policy and change resistance in data governance to the shadows where Gen AI is being forged, we’re unpacking what it means to navigate the complex tapestry of modern organizations.   We also explore the nuances of consulting, the human side of data projects, and the intricate dance between business and IT. Expect tales of change fatigue, the quest for effective communication, and the occasional need for data therapy.   Whether you’re a data veteran or new to the field, this episode promises a blend of reflective insights, practical advice, and a touch of humor to lighten the load.

Chapters

00:00 - Welcome to How I Met Your Data

01:09 - Surprises and Themes

07:27 - Understanding Human Reactions

13:02 - Simplifying Processes with Automation

18:56 - Struggles with Trust and Communication

23:04 - Over-Communication and Meeting Users Where They Are

24:07 - Enabling Stakeholders and Understanding Needs

25:57 - The Impact of Building Relationships

Transcript
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Hey, everyone. Welcome back to How I Met Your Data. Sandy here.

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You know, this whole podcast adventure has been a wild ride so far.

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And honestly, I'm just so thrilled you're all here for it.

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We've got a lot of love since we kicked things off. And it's been amazing to

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see how many of you are really into our chats about data, life and stuff in between.

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So what's on the menu today? Well, Anjali and I are going to be diving into

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some of the stuff that really caught us off guard lately.

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We're also going to chat about what what it's like being in the trenches as

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consultants, you know, the whole dance of navigating company dynamics.

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Plus, personally, I've been pondering a lot about the human side of all of this.

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It's not just about the tools and technologies, but the people behind them.

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And sometimes I feel like we're all in a little need of therapy,

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maybe data therapy, perhaps.

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So grab your favorite snack, find a comfy spot. If you're driving,

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that's fine, too. And well, let's get into it.

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Music.

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You can always edit things out sandy correct

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that is correct it's been a week huh it has

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been a week it's been quite a week actually we launched

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our podcast to a bunch of excitement which was was amazing to hear how many

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people enjoyed hearing us banter and chat about data and life and how excited

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they are to hear us keep talking. Is there anything that surprised you this week?

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I think one of the things that surprised me is I'm seeing the same themes just

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come up again and again as I work with more and more people, right?

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So looking at different policies, of a data governance, we see kind of this two-pronged approach.

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Either organizations and individuals will over-index on a policy or kind of

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sweep it under the rug and say, you know, we'll deal with it when we deal with it.

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And then the other thing, it's just kind of like a twofold thing,

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is as we see organizations take on policies, there's also a resistance to a change.

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It's the whole organizational construct, right? You never know what's behind

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the veil because you're dealing with maybe one layer or two layers of the organization,

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but there's other things going on around them that sometimes we're not exposed

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to as consultants, right?

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I think that's a great segue into our conversation today.

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For me, the thing that surprised me the the most this week is that I didn't

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expect Gen AI to become a thing that is created in shadows.

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I've had multiple conversations between last week and this week of organizations saying.

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Yeah, people are building stuff and we need to control it.

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It reminds me of when folks were buying Tableau and Power BI and some other

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tool in pockets across the organization and couldn't get a hold of it because

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it was just happening and procurement was allowing for it.

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But what's interesting about the way technology is shifting right now is that anybody can do it.

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There's so much information out on the internet, right, in terms of how to do

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things that almost everybody's an expert.

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That shocked me, I think, more than I expected. I did not expect it to take that route.

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That says more about me, I think, than the people out there.

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I don't blame them for going that route. I think that's fantastic,

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right? That's what tools and technologies are for, to enable people.

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I didn't expect people to find all this free time to get their hands dirty like

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that because it's a leap from Excel to building a model, right?

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That's really interesting. And I'd love to to spend some time uncovering,

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why do we need to get a handle on it?

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What does that mean from a responsible AI perspective and responsible usage

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perspective as well? It's exposure.

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If you're building a product in isolation from the rest of the organization.

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It's a matter of exposure.

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And then what are you going to do with it once it gets out of hand?

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You're going to hand it off to some centralized group that then has to deal

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with however you you band-aided this solution together and they don't want that.

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They want something that's scalable, that they can maintain, that they can grow with.

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That's ultimately the challenge for specifically, I think any central services

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organization within a company, they say, I need to get control.

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I need to get control of this.

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That's really what they're meaning. Cause they know they're going to end up

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with it, right? They're going to end up with that package.

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I think we're both talking about

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the same thing, right? Like organizations and how they, how they work.

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But as consultants, I'm often faced with a few things. I'm triaging them, right?

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Are you doing the same thing? You're triaging them in your mind.

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I'm constantly trying to get like a quick assessment of who they are,

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what they're dealing with, et cetera. How about yourself?

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Oh, absolutely. Absolutely. And I think one of the first things that I feel

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when I walk into a new situation is two polar opposite emotions,

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right? There's this excitement.

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There's a new voice in the room, a new team of experts here to help us get a

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handle on the things that are challenging us versus that resistance.

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Resistance, that resistance to, oh, here we go again.

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We've been down this path and, you know, it hasn't worked before.

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So why, you know, why is this time different?

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And so, you know, behind both of those, those emotions and feelings,

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there are a lot of things that we haven't yet uncovered.

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Yeah. It's funny because I think the beginning of my career,

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I cared very much about what we had to accomplish.

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What were the tasks, like very tactical approach to programs.

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And now, Now, you know, as I've spent 20 plus years in this situation,

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I immediately have this sense of trying to understand the individuals that we're

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working with, whether maybe we got engaged through a business partner,

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right, or business sponsor for the for the program.

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I'm constantly trying to assess the situation and then assessing everybody around them.

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All right, well, the business person seems okay. Like, hey, let's go over here

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to see if, you know, the technical team has been abused in other different ways

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where there's cost cutting and maybe there's other things that are challenging

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them to do the right thing for their counterparts, right?

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Or maybe they've just been there forever, so they don't even know what they don't know.

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So I'm constantly trying to figure that out because I feel that the way to success

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is truly through understanding where everybody is coming from and where they're

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entering that engagement or that program and trying to figure out, right,

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what ladders do I have to create or we have to create as a team to ensure that

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they as individuals get what they need out of this? Yeah, bad habits are really easy to perfect.

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But oftentimes when we leave, it's easy to go back to what those bad habits were.

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Yeah, I agree. I think that's another fun challenge.

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I always see our teams trying to manage how people do things with what we give them.

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You can't change who they are. You have to give them something that works within

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the ways they work and not give them something that we think is the best approach.

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Yeah, exactly. Exactly. And it's, you know, we see that miss when we're trying

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to give them the Cadillac and, you know, tell them here, go drive it,

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whereas they're really just learning how to crawl.

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So, you know, following that crawl, walk, run mentality, and we're going a million

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miles an hour when they're not ready for that. Yeah.

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I mean, we talked about a lot of the beginning of this. We talked about up feel, right?

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I guess, why do you think people feel that way when we first engage with them,

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whether they're frustrated or they're excited or curious to learn from us?

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Why do you think that's happening? Well, I mean, I think that there's a couple

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different things that are leading to that.

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One, from an excitement perspective, I think the type of personality that is

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excited is the one that has the most to gain.

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Learning a new way or unlocking something innovative that they know or at least

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believe will help their organization. organization or it's going to set them up for success, right?

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They've been given an objective from leadership and they know that they need

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to introduce change in order to meet that objective.

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So there's excitement around that because they're bringing in experts that have done it before.

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Whereas where we see the resistance, a lot of that comes from some of the things that you talked about.

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You know, parts of the organization have been underfunded.

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Others are frustrated and tired. They've been there before.

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They've seen change try to come through so many times that they've got change fatigue.

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And those individuals, I feel like is the hardest to try to overcome and bring

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them along for the journey because they've already been burned so many times.

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They've spent so much time in these initiatives that haven't gone anywhere for

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them or haven't brought them the value that they were hoping for.

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But they're going, what's in it for me? Why do I need to bother. I've already done this.

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I love how you brought change fatigue in, right? So there's like that out there

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about chief data officers changing to roles, jobs, just about every two years.

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I find that interesting because it's a hit on both sides of the equation, right?

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Because a lot of them are leaving the practice and being chief data officers.

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They're opting out. They're saying, I'm not going to do this anymore.

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And that's really why they've been changing is they've been trying to,

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it's like Goldilocks trying to find the right, you know, the right house.

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And they just cannot find the right org structure.

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They can't find the right funding mechanisms or they can't find the right culture.

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And they just keep moving from one place to another.

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Not that they're not successful while they're there because oftentimes they are.

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They do it even regardless of all those other conditions that are presented

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to them. So it's exhausting.

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It's not just about them leaving. It's about the organization they left behind too.

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Because all those individuals are now dealing with, oh, great,

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we need, we're going to have another leader come in here and have a different type of vision.

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Because leaders at this level have very vast visions. They often attach themselves to different vendors.

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They attach themselves to different consulting firms they trust and advisors that they trust.

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So they're bringing all of that with them into any organization they walk into.

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And I can't tell you the countless times where we're in the middle of a very

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large transformation for a client and they hired a new CTO or CIO or CPO or

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something, you're relitigating everything that you've done.

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Everyone's questioning what you're doing and for good purpose.

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And I understand that. But then

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at the same time, it's like that that is draining to the organization.

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Yeah, absolutely. And I think one of the other things that I've noticed as chief

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data officers move from organization to organization is they bring maturity

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bias with them as well, where if they've left a well-functioning organization.

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Large scale, fully automated, you put all the great qualifiers on there and

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they go to an organization that really hasn't gone along the maturity journey.

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They have this bias in their mind where they're saying, you should be doing X,

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Y, and Z and have expectations of a much more mature organization organization

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and are then putting those expectations on a group of individuals that aren't

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prepared to meet those expectations. Absolutely.

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I also find, as you said about maturity, right, there's different types of organizations,

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particularly when it comes to data teams.

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I do find that you have sometimes some optimal models for data teams where it

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might be, you know, development center based data, data teams are data teams,

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and they forget about all all the things that happen around the engineering.

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It's almost as if they just assume a pipeline's a pipeline and a data model is a data model.

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And they don't think about all the softer things that happen with data work.

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The design aspect, the build aspect, the operate aspect separately.

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And oftentimes those things are brought in all together in organizations.

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So the model doesn't really work because they're not thinking about how am I going to design this.

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It's designed in And in isolation, there's no good handoff of best practices,

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oversight of best practices on the builds aspect of it.

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And then when you're operating on it, that's a whole different skill set for

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handling customer issues and making sure that things are working effectively in a production model.

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Yeah, that kind of disconnect of the relationship between business and IT that

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we've seen it time and again lead to a mistrust between the two groups.

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Where the business is saying, I can't really trust that IT is going to deliver

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what I need because they're focused on these other things that matter not at

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all to me, but I don't know who else is going to use that.

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So IT is taking this, build it, and they will come back.

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Approach, and nobody comes. And yet the business is sitting here going,

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I need help with improving the transparency of my data.

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I need help onboarding X, Y, and Z, and there's nobody there to really help them.

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I feel bad. I feel like we just spent 20 minutes talking about all the horrible

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things that happen with organizations.

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I'm wondering, what can be done? What have you seen work? Yeah,

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I mean, I think one of the things is really thinking about where can we simplify processes, right?

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Where can we bring in easier ways of doing things?

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And one of the best ways to do that is introducing automation.

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How can we automate some of the what I call skull numbing activities that a

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human doesn't need to be performing?

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Because we've actually programmed computers to do that job. So how can we identify

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those tasks, those capabilities, and introduce automation?

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I think another thing I've noticed when the Data Mesh book came out,

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I got so excited about it.

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And the reason why I got excited about it wasn't actually the technology pieces.

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It was the stuff in between it all, which was communication.

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And if you think about the architecture and the components and all the ways

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organization would be able to work, that the hardest part is the communication

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aspect of it, regardless of the architecture.

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And what excited me about that book and the concept behind data mesh was that

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it was really a shift to build an application platform for data that the entire organization can use.

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And then there's more visibility because everybody's on the same kind of ways of working.

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And it just really resonated with me because it felt like this This would be

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a nice shift if people would go this route.

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The sad part is like every technology idea or methodology has gone out there.

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Folks have looked at it as a architectural Bible and that is it.

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They have lost, again, all the other things around it that need to be there

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operationally for an organization to be able to do that effectively.

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And that's really a miss in general and why I think these things never take off.

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Because everything is, give me the best tool, give me the next new architecture

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that's going to solve this problem.

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When in reality, you probably don't need to change anything.

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You really just need to change the way an organization communicates.

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I often push for this idea of ensuring you have data partners within IT that

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are interacting with different parts of the business and really understand the

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data needs of that part of the business.

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Yeah, I love that. That really speaks to me, especially from a governance perspective,

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because one of the first things that we really want is a clear understanding

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of roles and responsibilities.

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Who's doing what? What are their areas of focus so that you can make that distinction

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between your IT business partner and your data partner?

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When I see that IT business partner performing both the application and the

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data and analytics politics activities,

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that to me says there isn't really a clear separation of roles and responsibilities,

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that we're blurring the lines and we really do need to formalize what is required by each role.

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Talk about the communication, but so much of it is collaboration and working

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together and ensuring that as we're, from a business perspective,

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creating our roadmaps and priorities for the year, they line up with what's actually possible.

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So I'll take an example of an organization that was really excited about uncovering

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their generative AI use cases. All of their systems were on-prem.

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So trying to get that data that they needed to support their AI use cases wasn't

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going to fit into their timeline for creating their POCs and creating their value propositions.

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So we really needed to sit down and think about what is possible and how do

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you align your priorities with what is happening on the modernization side.

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Yeah. Speaking about collaboration, I've noticed a recent trend and it worries me more and more.

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This is my job, not your job mentality, where they're not sharing in the thought process.

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They're not willing to share in terms of where they're going to head or how

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they're thinking about it.

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It's kind of like, oh, I got your requirements. I'll come back with a grand reveal.

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And this could be either part where the business doesn't tell,

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they just give IT exactly what they need because they don't trust them.

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Or, you know, IT meets with the business and says, I'll come back in six months

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and, you know, I'll tell you what I'll do about that.

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Have you seen a lot of that? Because I've seen a lot of that recently.

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And I just, I look at that and I'm just like, how are you ever going to work

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effectively? Exactly. And that, to me, it fits right into that resistance to change.

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Because our recommendations, when we talk about collaboration,

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is breaking down those walls, and actually being forthcoming and transparent

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in terms of what are your priorities?

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What are your requirements? What do you need to be successful?

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And sharing that with the teams that are.

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In place to actually help you be successful. It would be awesome if there was

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like a company that just came in and said, look, we're your data therapists.

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We're going to come to you and have a conversation with the sponsors on this

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side and the sponsors on that side and maybe a level down from there.

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And we're going to have this group think in terms of why don't we share our information?

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I don't know. Maybe I'm just one of these kumbaya type people. Absolutely.

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So it's funny, side tangent, prior life, prior organization,

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I had a client that I was really, really friendly with.

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And we were encountering the same problems with people and data week after week.

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So we just set up 30 minute data therapy every week.

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And it was just a safe space for the two of us to chat about what was going

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on, why it was frustrating, just get it out of our system.

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And then move on with the rest of the day. Yeah. It was actually very helpful.

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That's fantastic. That's fantastic.

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I always feel like everyone wants to do the right thing. At the end of the day,

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everybody wants to do the right thing.

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It's just the way they get there is often mirrored in, you know,

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just lack of trust, miscommunications, lack of communication,

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why things are not coming through, etc.

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When it does work well is they have this brainstorming session together.

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They'll get in a room together as a team and have maybe a couple of days of

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a workshop and just get through it all.

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And then they go back as long as they're on the same page. And then they come

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back together and retouch on that.

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And we've done that with some of our clients and that's worked really well as well.

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Just spending some time with them in a room for a few days, because especially

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with this virtual world that we live in, no one's making a connection.

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You can't connect with somebody you've never met with. That changes everything. That really does.

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It really does. You cannot be harsh or mean as easily when somebody is two feet

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away from you. But across the screen, I've seen it plenty.

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Yeah. Or an email or a text message or a phone call.

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Yeah, absolutely. Absolutely. Actually, Sandy, as we've been talking,

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another thought came to me in terms of that unwillingness to share information, share priorities.

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And what I've been seeing a

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lot of is as organizations have gone through a reduction in force, right?

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And these data experts or experts in the organization's data have left.

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So now there's already a gap in understanding, understanding and we've asked others to fill that gap.

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And they're still learning. They're still trying to figure it out.

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So when you go and ask them for information, part of it is they may not know.

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But the other part is they're trying to keep it close to the vest as a job security move.

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And I think I'm starting to see that a little bit more as well.

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I don't know if you started to encounter that. Yeah, I have.

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And obviously it didn't work for the predecessors. Why do they they think it's going to work for them.

300
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Yeah, information is not job security. Even if you have a production system

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that has all the business logic and it's running or a model that you built,

302
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you actually build it for a specific request or a specific need.

303
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The angle the initial person had requested that information for is completely

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different from the one that the new person who's there in that seat is leveraging

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it for. So you have to rebuild it.

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I've seen that happen often often as well, which gives really high credence

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to the idea of not really institutionalizing. And I hate saying this because

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I don't fully believe in it, but truly institutionalizing BI.

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Because analytics is going to really be dynamic over time for organizations

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and having something quick and easy for them to go use for six months, that's good enough.

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To me, sometimes that's good enough. As long as the data is accurate,

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it's of quality, it's consistent.

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As long as all those things are there, everything in front of it doesn't really matter.

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So question for you, why do you believe or why have you seen the new user not

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using the asset in the way that it was intended?

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Is there a lack of documentation? Documentation? I mean, when was the last time

317
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you read a document? I don't read documentation.

318
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If I think about how we're streaming this and recording this right now,

319
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no, I just clicked on buttons. I figured it out.

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I think that's part of the reason is folks are moving really fast and they're

321
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not questioning what they're getting.

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They're happy to have the data. They're happy to have the report and they're

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not questioning the background use case of that information,

324
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why it was created, who created it, is the data valid until there's an issue.

325
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Yeah. Oh, for sure. I mean, as humans, one we

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hate documenting things even though we know

327
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we should but then also as humans

328
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we never really read the documentation when when it's

329
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in front of us anyways no we don't we don't yeah my favorite is when people

330
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ask for documentation and i'm like yeah sure we'll spend time doing that no

331
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problem you're not gonna read it you're absolutely not gonna read it but we'll

332
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do it we do charge by the hour. At least it's not by the page. Yeah.

333
00:23:04,865 --> 00:23:09,465
Oh my gosh. I guess if you had one piece of advice for an organization or for

334
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a consultant who's coming in and is triaging their client and thinking about,

335
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you know, how do I assess this?

336
00:23:17,165 --> 00:23:21,845
Either or. Client, consultant, you know, what is the one piece of advice you would give them?

337
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I think the biggest two pieces is really, and they do go hand in hand,

338
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but one is ensuring that you communicate to the point of over-communication.

339
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Communicate what are you trying to achieve? Why are you trying to achieve it?

340
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What's the path to get there? How do you know that you're there?

341
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And then also thinking about meeting your users, meeting your clients where

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they are, if you're a consultant.

343
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So as you go through your path of designing, how are we going to get from where

344
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we are today to where we need to go?

345
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Really thinking about, are you trying to give your clients the keys to a Cadillac

346
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when they haven't really learned how to walk yet? Those are fantastic.

347
00:24:07,445 --> 00:24:10,465
I agree with the overcommunication. conversation when we're brought

348
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into a client to finish something that is

349
00:24:13,225 --> 00:24:16,105
the only thing we're doing 24 7 that's the

350
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only thing on my mind right is those client problems what

351
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we're trying to achieve the client probably has 60 70

352
00:24:22,445 --> 00:24:25,885
other things that they're dealing with you get them for one hour a day and you're

353
00:24:25,885 --> 00:24:29,645
communicating to them they're not going to retain that information they may

354
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not be listening they may be multitasking especially now in the virtual world

355
00:24:33,705 --> 00:24:37,305
so you have to over communicate you have to do it in writing you have to do

356
00:24:37,305 --> 00:24:40,345
it verbally and you have to do it it six more times so they get the message.

357
00:24:40,525 --> 00:24:46,525
I think for me, the big one is just realize that they're humans across the table

358
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and think about them and their needs and be open and honest and ask them questions,

359
00:24:52,025 --> 00:24:54,725
probing questions about what else is bothering you?

360
00:24:54,905 --> 00:24:58,965
How can I make this easier for you? What other challenges are you dealing with?

361
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And try to figure out how you can help them get to where they need to be from where they are.

362
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And not just for that particular client, but also for the other individuals

363
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you have to work with to get things done for that client.

364
00:25:12,145 --> 00:25:17,805
And I think that's something that people often forget is that they're dealing with a human.

365
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And, you know, even though we have a task and we have a thing we have to go

366
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get, we have to enable the individuals that we're working with as well.

367
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I think like a big piece of that enablement is also thinking about for our stakeholders,

368
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for our sponsors, right?

369
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What's going to make them shine in the best light for their leadership?

370
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What's going to be important for them in their leadership's eyes to continue

371
00:25:41,410 --> 00:25:45,670
to justify their approach, their priorities and their objectives?

372
00:25:45,670 --> 00:25:48,830
Yeah, I still remember this. There's two things.

373
00:25:49,570 --> 00:25:57,770
Then we can kill this conversation. But I still remember I was a consultant early in my career.

374
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I did consulting and then I went to go work for a financial services firm.

375
00:26:01,170 --> 00:26:04,570
The first project I had, I had to go gather requirements from a bunch of people

376
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who were obviously abused by IT.

377
00:26:07,050 --> 00:26:11,310
They did not want to tell me anything. And I would go and spend hours with them

378
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at their desk and just kind of spend time with them, I'm getting to know them

379
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because my boss was like, you really need to get to know them as individuals.

380
00:26:17,950 --> 00:26:21,730
Don't think of this as I needed to go build a dashboard. Think about this as

381
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how do I enable their jobs?

382
00:26:23,430 --> 00:26:27,650
And that resonated with me so much because I saw a shift.

383
00:26:27,850 --> 00:26:32,390
Me just taking a lot of care about that individual and how they work and what

384
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they were trying to do with themselves and their teams changed the way they interacted with me.

385
00:26:37,470 --> 00:26:41,770
It took longer for sure, but it changed the way they interacted with me and

386
00:26:41,770 --> 00:26:45,130
that's kept me forever the other thing that i will say is,

387
00:26:45,810 --> 00:26:49,470
the biggest learning i had leaving consulting for seven

388
00:26:49,470 --> 00:26:54,870
eight years was what happens when the consultants leave that is that is another

389
00:26:54,870 --> 00:26:59,470
world i did not have an appreciation for and quite frankly it changed me as

390
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an individual as well and i think it made me a better consultant because a lot

391
00:27:02,410 --> 00:27:07,650
of times you come in you you just give them whatever right and you're walking out the door.

392
00:27:08,549 --> 00:27:12,109
Everybody has to deal with that. They have to maintain it. They have to make

393
00:27:12,109 --> 00:27:13,709
sure the end user understands it.

394
00:27:13,769 --> 00:27:16,589
They're dealing with all of that after the fact.

395
00:27:16,589 --> 00:27:23,389
Yeah, I think one of the most painful consulting experiences I had was,

396
00:27:23,469 --> 00:27:25,509
you know, working with an organization,

397
00:27:25,989 --> 00:27:31,009
setting up some great programs for them, leaving that that particular engagement,

398
00:27:31,209 --> 00:27:36,109
and then coming back eight months later to see what had happened while we were gone.

399
00:27:36,349 --> 00:27:40,049
Everything that we recommended everything we had built was gone.

400
00:27:40,209 --> 00:27:43,149
There was no evidence that we'd ever been there before.

401
00:27:44,109 --> 00:27:51,329
With this phone yeah exactly and you're just sitting there going i've spent

402
00:27:51,329 --> 00:27:55,149
all this time with you you you looked me in the eye and said you get it you

403
00:27:55,149 --> 00:27:56,769
understand you know why it's important,

404
00:27:57,549 --> 00:28:02,069
but you lied you lied to me i've seen i've actually seen the opposite of that

405
00:28:02,069 --> 00:28:06,429
yeah i do i do understand that whole yeah we left them with a bunch of stuff

406
00:28:06,429 --> 00:28:09,989
we walk away come back and check in it's completely different world the wild

407
00:28:09,989 --> 00:28:13,349
wild west yeah so bad habits easy Easy to perfect. Yeah.

408
00:28:13,469 --> 00:28:16,869
Easy to go back. So this has been fun. This is our second one down. How do you feel?

409
00:28:17,089 --> 00:28:23,089
I feel good. I feel really good. I feel like we unleashed some of our pent up

410
00:28:23,089 --> 00:28:25,749
dress, I guess, is the best way to describe it.

411
00:28:26,149 --> 00:28:31,329
Oh my God. We just sound like two miserable old lady consultants.

412
00:28:31,829 --> 00:28:34,929
I got these stories for you from a long time ago.

413
00:28:36,089 --> 00:28:40,769
It's not even fair to use the term, but we're war veterans. No offense to the

414
00:28:40,769 --> 00:28:43,749
armed forces out there. I mean, it's crazy.

415
00:28:44,720 --> 00:29:07,201
Music.