Tom Redman: Be a data provocateur

Loris Marini: There's one thing that we keep talking about on this podcast and is theme of how do we as data professional become more impactful? Depending on where you are in the data team, you'll feel pain in a different way. and for engineers, as we've seen recently it often boils down to things that break and when they shouldn't.

Because we know how to build solid structures. We know how to build solid systems. We often don't have the time, we don't have the budget. And we always constantly battling between getting something out of the door quickly and building scalable systems and designing them properly. why does that happen?

It happens because people don't have the space, they don't have the right support to do that. There's always a missing link, at least from my perspective. And is the link of leadership and communication. How do we get the business to understand the value of what we do? How do we get them to see us as partners, not just as a technical function. And what kind of organizational transformations do we need to create to make our job more effective and easier to do? To be honest, so today I learned from Tom Redman, the data doc. Tom has a. Extensive career in the data space. He's an expert in data quality, data culture data transformation and data leadership.

And just extracting here from his LinkedIn, which I strongly recommend to have a look at because to be honest, there's too much there and I wouldn't possibly summarize it here in 30 seconds. Tom fundamentally helps companies see the big picture and get the right focused leadership structure and people in place and.

Data quality head on and use data to develop a competitive advantage. Long time in the making. Tom, I'm absolutely honored to have you on the show. Thank you for taking the time.

Tom Redman: Thank you for reaching out, Loris. I'm looking forward to our discussion today.

Loris Marini: All righty. So Tom, help me understand what is data leadership? It sounds very often as a bit of a wishy-washy word. There's a lot in there. It's like the catchall term for all the things that are hard and we dunno how to solve. How do you see it

Tom Redman: I look I think there's a plain, simple definition of leadership. A leader is any person, or it could be an organization, right? Sort of he, she, they, or it that are out in front. setting a path and providing direction for those around them and entire company, entire teams, entire divisions, entire companies to follow.

And the data space is crying out. For leadership there has never been greater opportunity for anybody, and I don't really care what your level is to, to show that leadership, to set a new path and frankly, create opportunity for yourself or your company and and have a lot of fun along the way.

By the way, when I say have a lot of fun, I don't mean there's not gonna be some hard days cuz there's gonna be some really hard days but never has the need or the opportunity for data leader, for people to emerge as data leader has been greater.

Loris Marini: Yeah, I couldn't agree more. And how do you see leadership though? Is it like a set of skills? Is it a mindset? does it tie in with seniority? Do you have to be 20 years in the data space to be, to call yourself? For data leader, you have to write books like what? What makes a leader versus a non leader?

Tom Redman: Look, I think that's a very good question. I don't think there's a script for leadership. I think it helps to know a little and not too much. And the reason it helps to not know too much is you get. Set in the ways we define problems and think about problems and attack them as opposed to if you don't know too much, then maybe go, eh, why are we doing that way?

I spend most of my time on, on data quality and and here's the sort of way most companies attack data quality. I mean it'll be sound a little funny, but it's really what happens is they make mistakes in one part of the organization that then they try to correct in another part of the organization.

and there's a cottage industry of tools to help identify errors better. And, we're seeing AI now and so forth. so one of the things that's, it'd really be good to do is ask, Well, gee, does that make any sense at all? Why don't we quit making so many errors in that first part of the organization, right?

Why don't we change the way we're going to attack, attack data quality and the more you have invested in the old way, the more difficult it is to ask that question and see that possibility. And I haven't run into an organization that is not an opportunity to say, we're going to change the way we attack data quality.

You don't have to do the whole company at once. And in fact, by the way, this is what leaders do is they start in one small part of the organization and they develop a success. They have an idea.

Loris Marini: Uh 

Tom Redman: a part of the organization, willing to try it with them.

They work on it, they demonstrate success. They have a simple before picture and after picture, and by the way they they're not running around carrying signs and complaining about how broken the organization is or anything. In step one.

They're simply making things better. And then those who make things better and say, look at this, here is a script that the rest of the organization can follow. Those people are leaders, right? Those people are leaders. And they are so important. I suspect they're important in everything, but in the data space.

They are so important that I give them a special tie to provocateur, right? They

Loris Marini: Right. Tell me.

Tom Redman: provoked the organization right by demonstrating that there is a better way. Now by the way, there's a lot of people who complain about how poorly companies are run or how right, this or that is, is dumb, but don't have the courage to actually go out and create a success story.

Go through all the pain of creating a success story and demonstrate it on their own. And believe me, it takes real courage.

Loris Marini: Yeah. And it takes real work, as well. And the thing is, it's not transferable, at least in my experience. Like you, when you join a new organization, you might have a, fantastic resume. You go in, you. Interview and they give you a job, and the first few weeks you're onboarding, then you start working on the actual projects and you are still running on borrowed trust.

The business believes there is a, there's a reasonable probability that you will indeed succeed, that you will deliver in improving systems and improving that. The overall data quality, making, systems smoother, more reliable, whatever it is that you're trying to do, but, It's not until you demonstrate that you can actually do it, not technically, but that people adopt your solution.

That there is a step change in that domain that the business actually goes okay. They know, they not only know what they're talking about conceptually, they know how to build it and they know how to deploy it within the organization. Then you can have a much serious, more interesting conversation or I think it's, a lot of times we get stuck on frustration is step one, oh my God, I can't believe systems are so broken.

And, but we gotta do something about it. Now, if we try to shoot for the moon, we are never gonna get there. So often is reducing the scope and just getting a small little project delivered through the door and we're like, we were able to do that. Now let's talk about the other 5 billion things on the punch list.

Tom Redman: Look, I'm I wanna build on what you're saying and. First thing is it's not just about changing systems, it's mostly about changing organizations and changing the way people think, right? So in the example we went through about data quality, right? Building better systems is not going to change the fact that people over here are still creating errors that people over there need to deal with, right?

Real change, real sustained change and real leadership. Comes from changing the way people think about things and the way they approach their work and the way they see their jobs, and not just, not just systems. Leadership is not simply doing stuff in your narrow space. Leadership has to get beyond that, right? It has to get out into the organization.

And so if you do, if come up some way, To better integrate two databases, right? And it's okay. It's clever, right? It saves a little bit of money, but nobody in the business sees it, then you're not gonna get any points for it. 

Loris Marini: Mm. 

Tom Redman: It, these successes have to be visible.

They have to make people's work easier. They have to change the way they think about things. And in the data space, look, let's look at some of the problems we have. Quality in most companies is awful, right? Technical debt is out of control.

Loris Marini: Through the roof. Yeah.

Tom Redman: Yeah the failure rate of data science projects and AI projects, it's, it's north of 80%, so 80% is the published stuff, and some people count as well.

We were successful cuz we learned things right. Things are not going well in, in the data space, and it is apparent to people in the business. They may not be able to wrap their arms around what the problems are precisely, but they know things aren't going well.

people with data in their title who can reach out people in the business and understand the pain they're feeling, and help address their pain, that's where you're gonna earn the mantle of leadership. I'll just give a specific example. Again, I mentioned the term provocateurs, but one of the first ones I had. The opportunity to work with, I mean he worked in this, in incredibly technical thing on bill payment. And it's a particular category of bills. They set up this verification system to verify that the bills were coming in properly and they never really knew how it worked.

And it took a long time and they spent a lot of money doing, and this is a big company, kind of thing. But you just recognize that okay, play that movie forward. There's, we're doing more business. The bills are getting bigger. Verification's getting bigger. The returns are uncertain.

We can't manage the books. We're not certain of what the books look like until, eight months down the road. If we continue to go down that path in making incremental improvements, are things ever. Gonna get better. And he had the courage to ask the question, right? Is there a better way of doing this?

And again, the, the answer was gee, the supply of other things we bring into this company, right? We have an active supplier management program. Why aren't we applying supplier management? To the invoices that are coming in kind of thing. And boy, once he had that, then he had an idea.

But as he talked about that idea, there were lots of people who thought it was the dumbest thing they'd ever heard of, right? And so instead he had to make it work in some narrow area. Yeah. 

Loris Marini: Yeah. 

Tom Redman: once he made it work in one narrow area, then he had the before and after picture and he said, look, we can attack this whole thing, we can take this for all our invoice. And he never did get to all the invoices, but he got to a significant fraction. And he saved the industry a quarter of a billion dollars a year, and he saved his company 150 billion billion a year. And. by the way, it started out with an open mind, right?

An open mind to, to, you know, to new ideas. And then the next thing was that, the courage to, to try something new. And then, I don't know, maybe it's marketing. I don't know the right way to, but to step it up, right? Here's the script. We can copy this script. Persistence was a big deal.

I think if you wanna be a leader, it's really helpful to have a thick skin. Because no matter what you want to change, then, You 

Loris Marini: gotta get a lot of No. Yeah.

Tom Redman: I'll tell you why it's not gonna work kind of thing. 

Loris Marini: Yeah. 

Tom Redman: Sometimes I tell people, if you wanna be a leader, you're gonna have a lot of bad days.

the reason this is so important is, Things in the data space are not working right. We need to change the way we need open minds in it. For me, it is most apparent in the quality space and that's what I work in. But similarly, when I dive in into data science and I look at the way data science, Projects are done and I look at, we sit these data scientists off in an ivory tower and we ship 'em a bunch of data and say, have at it, And we the company or they don't say what's the real problem here? What is it gonna take to solve this? What is the full end to end solution? I may come up with, interesting. How am I gonna build that into, in, into the infrastructure? How am I gonna get people to use it? all over, we see these opportunities, we see these opportunities to, to think about, right?

What is it gonna take and think about things in a different way and more powerful way. And I think, I mean from my perspective, like this business of courage. It's a, people ask me about it all the time and I point out look, 80% of the projects are failing anyway. If you try something new and I fail

right? You put it yet

You don't even make the stats. And then the other thing sometimes I point out is how are you gonna feel about yourself? Now by the way, I know there's a lot of organizations where people get punished for making mistakes. And if you work in one of those organizations, I do feel sorry for you.

But most organizations are not that way. Most organizations people have way more power and way, way more flexibility than they give themselves credit for. And if you happen to work for a manager that you know is not giving you much, find a different manager.

Right. Find 

one. 

to me, this is the key thing. Leaders set a new path all right. The head, Leming is not a leader, right? The head leming is just, driving people over, over the edge. The leader demonstrates that this is a better way, this is a better vision.

This will benefit the organization, it'll benefit us all.

Loris Marini: Tom, I love this. I really do. It's touching on so many, things, stories that are lived stories that I'm living right now and. I'm here to change this to be honest. That's why it's six 30 in the morning in, in Australia and we here recording this conversation. Cause I could have slept I woke up at five and the what gets me outta bed is quite honestly is the the potential why I see the potential if we change this, if we get 1%.

More people in a data role when even in non data role as we talk soon enough data is for all, not just for data people to actually embrace these concepts and build habits around this. Five points you mentioned, right? Open mind. You start with an open mind. You have the courage to try something new and to challenge the status quo.

You you step it up. So you know enough about communication and persuasion and marketing to, take that message, that new path that you can see and make sure that all the important stakeholders around you see it as well. And they're able to tell the story and the new path to other people so that the idea propagates through the organization.

Very hard to do. It's a bit of an art, but surely there are skills that can be learned and spaces that we can create, teach people how to be better marketers, . But the marketing leaders, then there's four persistence. You gotta get there, you gotta stick to it, you gotta keep doing it.

It's not gonna happen in one day, it's gonna happen in a week. You're gonna have a lot of bad days. Deal with it if you don't like the idea. Don't get in data leadership because you gotta have many pushbacks and five develop a thick skin or find ways to channel that frustration and those emotions that inevitably.

Bubble up in other ways because you are, keep the eye on the ball. The focus is transform the organization, do more with data, and they unlock the really the potential that information has to get people to go home with less headaches and spend more time with their kids or doing the activities they love to do, they kids, rather than just stare at that spinning wheel or look at those databases that you can't join or be frustrated if you're a CEO because you're just asking.

Tell me how many of that product we sold in that region. I wanna know a number and I want to know one number, not five different ones. I wanna have one single number, and I'm expecting that to be true.

Seems to be impossible.

Tom Redman: Let me add one other thing to that and and this is a trait of some of the provocateurs it's been my privilege to work with is I think they're able to, they're able to think long term and they know how it's gonna turn out, right? So right now in the data quality space almost everybody is attacking it.

but you know that sooner or later they're gonna begin to attack it. And it's sometimes it's just to ask yourself, do you wanna be on the right side of history on this stuff? And so maybe, not in detail, but. But look, things are coming in the data space.

Quality is going to get better. Ways to monetize are going to get better. We're going to figure out how to increase the success rate of data science, right? And fundamentally you have a choice. You can either be at the head of that pack, you can be, sticking your finger up and figuring out which way the wind's blowing or you can be behind it kind of thing.

those are your choices. There's a full spectrum there but most people, when they think about it that way, they say, yeah, I think I'd rather be on the, I'd rather be leading than following kind. And the last bit is well certainly if you're not gonna lead, then quit complaining get out of the way, and at least help those who are trying to lead, lead.

Loris Marini: Yeah, be helpful. At the very least. I am fortunate to work now in a company where there's a lot of people that are willing to help. What's often missing based on my prior experiences is that, Vision for the new path, the better way. And when the vision is there, it is often disconnected and it's far fetch.

It's like some, something like, hey, we should create, a central brain that processes all the big. Business problems we have. Yeah, that's 20 years from now, what can we do? So that's the thing with vision, right? Like it's gotta be something that obviously you want to do, has to be appealing, but it also has to be attainable if it's too far in the future.

Like you're talking about running a marathon and you don't even know how to hold the balance of your body in space. Maybe we should first work out how to stand before, before we even start walking.

Um, 

Tom Redman: exactly right. Look, there's intermediate deliverables and there's things you need to do. First I wanna say one other thing, Loris. And this just entered my mind. I find a lot of people, right? They have a ready made complaint that our senior management doesn't.

Loris Marini: Yeah.

Tom Redman: Okay. And by the way, ultimately if you are going to tackle things like culture and you're gonna transform a whole or organization, you're gonna have to get a lot of senior people involved, right? It is very easy to duck behind. Our senior leaders don't get it. I found all of them.

It's, and I don't know, I haven't worked with hundreds, but I've worked with dozens kind of thing. I've found all of them are very eager to help. And by what I mean is if you come in and you say, we just did. This transformation and we looked at, 90,567,319 rows of data, and 19,000,242 of them, 371 had an error in them.

Don't you think that's terrible? They're just gonna throw up their hands. And too many data. People take things to senior business leaders that senior business leaders simply do not understand, right? Instead of saying, Look, I am trying to do, make this change in the way this organization does the following things, and I need help.

I need you to help me connect with this person, or I need a little bit additional budget, or I need this, or I. I need that. and rather than expecting, senior leaders to learn everything you've learned in 20 minutes, come with a specific ask, explain why the ask is important. Make it something that they can do. An enormous fraction of those people of senior leaders are really willing to help. And I want you to think about that when you're trying to get traction. You don't need senior leadership to understand what you do need their help. You may be, you may need their connections, you may need a lot of money, you may need them to have a talk with somebody who's getting in your way.

I think that too many people in the data space misread senior leaders and deny themselves the benefits of what senior leaders can do

as a result. 

Loris Marini: Yeah. I love this. Asking for help. I'm gonna put that as an additional point number seven in the habits list. And we are not really good at that. I personally am still struggling with that. To be honest. I have to remind myself every time I. Realize that there's, the obstacle is too big for me to overcome with what I know and with the immediate sort of stakeholders that are around me, the people that are involved somehow, but they're not my like manager or the manager of my manager.

And I try, I tend to have this feeling of avoidance. I'm not sure why that is because I know my stuff and I'm pretty sure that I could walk in the room. Paint a picture for the future of the business, but somehow it feels way more safe and like it's not, I don't have to put my face out there, I can just fire my, my code editor, my ide, write some code, try to automate it, try to find myself out of the task.

And. And hope that's gonna fix it. And I've seen a lot of people, highly technical people do that. They revert back to what they know best, which is writing code as opposed to have a conversation.

Tom Redman: Look, I don't think it's just highly technical people. I think that there became this ethos and management that was of the form, don't bring me problems, bring me solutions. 

Loris Marini: Yeah.

Yeah. 

Tom Redman: Okay. And, partly it was a response to people complaining all the time about, about things.

And I do see it, but a lot of times what it does is, it leads to bad behavior and but so don't be problems. Bring me solutions, is not the same as, be afraid to ask for help. You must get help when you need it.

Loris Marini: And before being able to ask for help effectively, you need to know how, what people care about. The put in a language that the business understand. And that's, to be honest, that's the easy part because the most organizations. Have periodic meetings. They talk about their strategy. So if you if you pay attention, the key targets are out there, you just have to get them and put in a spreadsheet or your, in your own knowledge management system, whatever, in your notes.

And try to tie every activity you think of doing to those targets and those KPIs. Those are already been established, accepted as a leadership team that literally their job is to come up with targets. And so if you can tie the activity to those targets, that's a way to get their attention. Hey, I wanna, I'm transforming organization to get there.

Here's why. Here's how.

Tom Redman: I, I mean, Don't go overboard on that. We tend to have targets on things we understand and a lot of times leadership is breaking through. Getting new metrics. 

Loris Marini: We touch on so many things here. I think a concept that keeps coming back is responsibility, taking that responsibility, but when you think about.

Tom Redman: Yeah. Everybody wants to state an opinion and not take responsibility for the outcome,

Loris Marini: Yeah. Yeah. It takes and encourage of course, is connected cuz if you don't, it could not work . In fact, most of the time it doesn't. So yeah, you gotta be ready to get some scars all over and then get at it again and hopefully have the great.

Tom Redman: That's exactly right. Look, things fail and a lot of times, you have a new idea. They don't all succeed organ, first of all, your idea may not be a very good one. Yeah.

It maybe's. Thinking too big. You may be thinking too small, right? You may not have the smarts to get enough people involved, but I don't know.

I it's almost would you rather have somebody who's never tried anything or somebody who's tried something pretty darn big and failed on your team, and almost people say, oh, I want somebody who's tried something big and failed that you just don't get it. The real, experiences in any.

other way 

Loris Marini: Yeah, you, we just opened so many things there. I don't even know what what is next? 

Tom Redman: Yeah let's not, blather on longer than we need to. I think we've made some really good, really good points for you, for your audience. I want to be very encouraging that people, data people and people without data in their title, we need, there has never been greater need for leadership, right?

And, see the opportunities around you. Ask if there's better ways that we can manage data. Ask if there's better ways that we can monetize data don't just go talk about it. Do it right. Go do it. And if you can only do it, on a team scale involving three people to start, great.

If you're higher up in the organization and you can do it in, with a whole department of 50 people, great. And, you're a business unit president and you can do it right with a thousand or 5,000 people, e you know, Great still, but We need leaders and they are so important, but you have to actually solve a problem and you have.

You have to create a script and you have to market that script. And those people, and again, I'm repeating myself, they're the most important people in the data space. They've been the most important people so far, and they're the most important people going forward. And look, it's a marketing term, but these are provocateurs and I love them and we need thousands of them.

And so go for it. 

Loris Marini: Yeah. Yeah. Tom, as you were summarizing the important points, something came up in my mind and is something that relates to quality, which we haven't really talked about. You mentioned the grid. The grid is essential. Everything else builds on top of it, and we don't even question it Data quality, integrity, and reliability is important because without that we can't do anything else. We can't turn it into information, knowledge, and then ultimately add decisions and actions. There is a bit of a catch 22 though. Often people get stuck on I can't really lead change if the data is so crappy.

How do I even know the level of quality is so low that I can't do much about it? How do we get out of that catch 22 and what do you think is the right mindset, to that we should embrace? Because if we. If we fix it here and then with whatever the means, like an Excel file asking 50 people, spending two weeks on trying to get the bare minimum level of quality that we need to demonstrate that we can do it, and we keep doing that, the business will go we don't have a data quality problem.

There's. There's Tom there in engineering that does all the magic, and all we get is reports that so far look good, but if we don't do that, the data quality is so crappy. So how do we get out of that cycle?

Tom Redman: Look I think you really, as you told the story, you pointed out what needs to be done, right? If things run through one person, then it's just not gonna scale. And we're not, we're not talking about, doing this with. Start out, do it once, but then we've gotta scale People don't understand. I think they know it by the way, in their minds, but they don't want to bring to the front of their mind how suffocating bad data is on everything. A lot of it is just the data is wrong, it's missing. It's poorly defined. Things don't line up between two systems and so forth.

And at the organizational level, we're not really gonna succeed with monetization. We're not gonna succeed with data science at scale. Unless we do data quality first and so sometimes I say all roads lead through data quality. And the fundamental problem and you can describe it in lots of ways, but at its most atomic level people in one part of the organization, Are creating data that people in another part of the organization use and that data they're creating is not fit for purpose.

Okay. And then people here are trying to accommodate that bad data and that they are falling into that trap of thinking that they can find and fix errors. Faster than people are creating them and never works and it doesn't scale, right? So the first change has to be you have to attack.

Data quality properly. And by the way, it is so much more fun to do it. It is so much less work, right? It does involve a change of mindset. We need lots and lots of provocateur specifically on data quality. Because we're not gonna get through this log jam with the quality of data that companies are dealing with now.

It is suffocating them every day and just garden variety operations and decision making and it makes everything clever. We wanna do, so much more difficult so I've done a little bit of work measure the quality of data levels and then synthesize things.

And, only about one in six managers trust the data they use every day right now. Now, what's really interesting, Loris, is only about 3% of the data is trustworthy. 

Loris Marini: Ha, 

Tom Redman: yeah, I made you laugh there, right? But we're not you can say this in a different way. And that is is we really need to be able to trust the data.

The data is not trustable. And, cosmetic things are not gonna do the trick here. Fundamentally, We have to start a building, starts with creating data values correctly. It includes building great metadata, right? We need to do a far better job building data models that are intuitive and people can understand and so forth.

And I don't know, maybe there is some magic. Around the corner, I've been hearing about things that will magically solve the problem now for a full generation, and it hasn't happened. So I'm skeptical that, that magic is gonna take care of this,

Loris Marini: Yeah. Yeah. Okay, so let me summarize and see if I understood. To break the cycle being the decision we need to often make between fixing the problem in whatever way we can. Hiding sort of the fact that the data is crappy fixing enough to be able to provide some value. And I use that as with a bit of storytelling and a bit of marketing to paint the picture.

Say, Hey, this is how we are doing stuff. It's broken, it's unscalable. We made it work. Now we have two options. We can keep doing that monkey work and still be. Where we are now in terms of quality and in terms of enabling future use cases. Or we can take care of our data and we can develop a plan to make it more reliable, more more useful.

Tom Redman: Yeah, I look, I

Loris Marini: we ha need to have that conversation. Otherwise we stack on Yeah, just fixing it. Just bandaids.

Tom Redman: it's really key. In most kind we find it doesn't cost any more money to create data correctly the first time than it does to create it incorrectly. What costs a lot of money is

Loris Marini: it's to fix it. Yeah.

Tom Redman: Okay. And so people express this in different ways, fine eliminate the root

the air.

And let me say one other thing about this. Again, it's a provocateur thing, but take a hundred data quality issues, right? And 80 of them are pretty easy to solve. And then they get increasingly difficult and maybe, maybe two or three of them are fundamentally unsolvable, okay?

But somehow organizations go after those first rather than the 80. And my advice is always well do the easy stuff first. Develop, get in the habit of doing this. Learn how to find and fix errors. Learn how to put controls in so they don't come back. Learn how to get management accountability, right?

And only when you're pretty darn good at that attack, these really hard issue. And maybe, and if you can't fix it. Some, there's certain things that are unfixable, then live with those. But there is so much opportunity, with quite frankly, fairly easy stuff.

Loris Marini: Yeah, definitely. So it, it connects to that entrepreneurial mentality of fail fast, learn faster. Do you do want to start somehow though, right? Somehow you could argue that the connection is not there actually, cuz the entrepreneur is all about when startup, we're trying to create demonstrators of product market fit.

What you're doing is doing stuff really fast. Even they're not done well, they're just done. So you get some feedback in this case. That can backfire because if you don't, if you do it too crappy oftentimes it doesn't work. It's not, 

Tom Redman: Yeah, I don't know. 

Loris Marini: market fit right? 

Tom Redman: But

I don't think anybody ever comes into work and says, Hey, I need more bad data than I get to fix. I just haven't seen that yet. 

Loris Marini: Awesome. there's many takeaways here, but one thing that I will try and remember is that connection between you as an individual trying to fix bad data by yourself, thinking that you can do it faster than people can create data problems. And the reality that is you can do that.

So if the organization has 200 people and you're one there's 200 times more data, potentially problems per unit of time being created compared to those that you can fix. And plus creating a data. Quality problem is way faster than fixing it. , right? I can I can, yeah, change the name or column.

I can put an add, add the zero to a cell in a database, right? And that's a data quality problem. It takes literally one keys stroke maybe two, maybe I want to add three zeros, right? It takes really little to to screw it up. It takes a lot to find it, and it takes a lot to fix it. Yeah, don't do that. Cool. So the way to get in touch with you, Tom, data quality solutions.com and your LinkedIn, I believe.

Tom Redman: Yes, LinkedIn. I get people reach out to me one of two ways info@dataqualitysolutions.com. I've, I got a large LinkedIn following. I take all calls and Love, love hearing from people and obviously by the way, this is how I make my living is helping people and organizations think through this.

I like to think that I've made a bunch of provocateurs in my career and 

Loris Marini: since 1995. So 27 years of in the market. That's 

Tom Redman: Well, that's how long I've been on my own. I started with a data quality lab and Bell Labs in the late eighties. I've probably been at this longer than most listeners have been alive. Yeah.

Loris Marini: Yeah, I would say so. I would say it's a good it's a good bet. 

Tom Redman: I wanna say one other thing about this, by the way Yeah. 

Loris Marini: Yeah.

Yeah.

Tom Redman: Yeah This, a lot of people have the attitude that data quality's not sexy. And this is something I've been I've been fighting for a long time. But exactly the opposite is true. There is nothing more empowering than finding and eliminating the root cause of an error and making it go away.

people I've helped do that, right? They are changed individuals. They are empowered and when you come in every day, And your job is to, deal with other people's junk. It is not an empowering job, but making that go away is empowering and it is one of the reasons I think things in the data space, if we do them right, will be transformational.

Not just for companies, which companies will be richer, organizations will perform better, but it'll be transformational for people. And that's the part I'm most excited.

Loris Marini: I love it. I love it. Yeah. And just to, Narrow down the type of people that you can help. We're talking about large organizations, small startups, or anything in between.

Tom Redman: Yeah, anything. I look, people who don't have open minds tend not to come. Right? I'm most effective with those with open minds and those with courage. I'll help encourage them and I'll expand their minds further. 

Loris Marini: Yep. 

Tom Redman: who. All kinds of organizations at all levels. 

Loris Marini: So if you're listening and you wanna take a little bit of that wisdom, I believe Tom would be very happy to have a chat with you at info data quality solutions.com.

Tom Redman: thank you.

Loris Marini: Tom, thank you very much for this exchange. It's been a pleasure. It's a fantastic way to start. Today, it's seven 14.

I had my first coffee and I feel fully charged to go and be a data provocateur at my company today. So what do sincerely thank you for taking the time and being on the show.

Tom Redman: Yep. Thank you very much for inviting me and good luck provoking today, Loris.

Loris Marini: Thank you,

Tom Redman: stay in touch.