Malcolm Hawker

Hi, I’m Malcolm Hawker, and this is the CDO Matters podcast. The show where I dig deep into the strategic insights, best practices and practical recommendations that modern data leaders need to help their organizations become truly data-driven. TuneIn for thought provoking discussions with data. IT and business leaders to learn about the Cdr. Matters that are top of. Mind for today’s chief data officers. Hello everybody, welcome to CDO Matters live. I’m Malcolm Hawker I’m the head of data strategy with prophecy software. And some of you. May have seen the podcast before. I hope you’ve seen the podcast before we’ve had. Probably 15 or 16 editions. By the time this goes to press. And we’re glad to have you here today, so we’re trying something a little bit different. We’re going to do a live event. Of the podcast. And I am joined by my partner in crime today. The pride of New Orleans, LA. Ben Bourgeois, who is my partner here at Prophecy and Ben will be helping facilitate things. Then will be the Andy to my Conan the the Ed McMahon to my Johnny Carson, which is a really real really, really old reference that people probably won’t get. But anyway, with with that fanfare, Ben.

Ben Bourgeois

Welcome, yeah, thanks Malcolm. Thanks Malcolm. Yeah Malcolm said I’m the director of digital marketing and prophecy. We work really closely with them on all things CDO matters, including the podcast and our new monthly live edition. So good to see everybody I’ll be helping facilitate and see what you will. We will be taking questions so please drop your questions. On the Gold cast chat or in the Q&A or discussion tabs, and we’re also streaming on LinkedIn Live. If you drop your questions in there, we will. Do our best to collect those. And answer them a little later in. The event we’re going. To let Malcolm kind of go off a little bit here at the. Beginning and we will. Collect all the questions for a little later. So now you wanna.

Malcolm Hawker

Get started, yeah, go go off. It’s kind of what I do right?

Speaker

Go off.

Malcolm Hawker

Yeah, I like I I like to rent so anyway, for those who have seen this.

Speaker 3

Before love to kind.

Malcolm Hawker

Of talk about things that are front of mind. But but I I will. I will veer into other areas as well. Friend of. Mine for me is something. I’ve just posted in LinkedIn. A couple of hours ago. Related to data versus analytics and the. Question that I. Asked in LinkedIn was why do we separate analytical uses of data from operational uses of data and and when I say operational uses of data, I will kind of broadly. And of, say, data management, the management of data. The data is state. Applications of data data being used in CRM systems. ERP systems. Operational uses of data. Using data for things versus reports. And we do it all the time. We even do it in the label that we use to describe our own industry data and analytics like these are two separate things. We have chief data and analytics officers. We even have this bright shiny new thing called the data mesh. Which is a yes sociotechnical approach that is beyond the data architecture. I get that I know there’s a lot of mesh acolytes in there that will will be holding my feet. The fire with the data mesh is a analytical approach to managing data. It’s all about analytics and it actually doesn’t even. Speak to the operational uses.

Speaker

Of data.

Malcolm Hawker

So if we agree that there is at least this mindset of separating data from analytics and these are two different worlds, Mr. Here a little wax on wax off. Action with my. Hands if these are two separate worlds, well why this? Perplexes me because data. Leads to insight. Well, what was it? Analytics would lead to. Insight and insight would lead to decisions, meaning actions, right? So, so things need to be ordered, purchased, configured, procured stuff needs to be done. Decisions need to be operationalized within operational systems. Go figure. Like CRM applications like any other tools that are used internally and so if we kind of draw a distinction here, I don’t. I don’t get it right, I don’t. I don’t get it, and what I’ve seen through my career is that when we draw a line between analytics and between operational uses of data. It kind of opens the door for a lot of freedom on the analytics side. OK, all right, that’s that arguably is a good thing, and this is this is the data mesh right? It it is operational or I should say analytical freedom around the data domain driven freedom business function? Control over analytical uses of data and you could argue, OK, well that’s that’s a good thing. Maybe democratization of data is a good thing. Maybe that’s a good thing way back in the day we used to call them data marts, we would build these little stand alone solutions for for people call them data.

Speaker 3

So, so far so good like.

Malcolm Hawker

OK, that’s that’s good. Give the business more freedom over their analytics. OK, but what ends up happening is that the business, when they have control over their own analytics and have control over BI, will start to define their own business rules for how they want that data to appear in reports. So they will start to define their own data. Quality rules they will start to define even things like their own data definitions that are appearing. Those reports. In theory, if you had a common foundation of data governance that spanned analytical uses, an operational uses, everything would be fine, right? There would be harmony in the world. There would be angels singing everything. Would be fine. But that’s not what happens. What ends up happening is that from those kind of business units in the domains, they start to define their own rules. They start to define their own quality standards. They start to define their own things and this leads to a lot. Of problems when? Data needs to be used cross functionally, right when, when, when, when data needs to. Move from sales. Into finance, when a contract gets executed right when when product data moves from manufacturing and into marketing. When you go from the finished product to a a product that is being marketed and sold in some e-commerce channel. So when when data moves, cross functionally if everybody’s looking at things differently and lacks a common definition lacks a common structure. Lacks common quality measure. That really creates a problem and I think a lot of this has to trace back to the idea that somehow we can compartmentalize data, data management, operational uses of data versus analytical uses, and it starts even in our name data and analytics. So that’s my. Rant du jour. I don’t know why we do it. Honestly, I think Gartner, my my previous employer has a lot to do with this. They they kind of, you know, kind of went with data and analytics a few years ago and that was actually believe it or not, largely a reaction to their their own internal organization organization and less to do with how people were actually using. But I think I think it’s problematic, and I think we need to kind of break some of those barriers. I see analytics. Forgive me, some people may react to this and there may be a kind of a backlash, but I see analytics basically as a use case of data, right? It is a way to use data as an application of data and we should be looking at applications from an analytics perspective or applications of data from an operational perspective with equal weight and not draw a distinction between them. I think drawing this distinction is is a real problem so. So then that is my my my rant dujour. What was that six minute rant? That’s pretty good for me.

Ben Bourgeois

And you know, I know you’re saying it, it can come from a few different places, but I wonder, do you think it’s just it comes from maybe the the ownership? And maybe just kind of the mindset of. The two, so maybe. From a see an organization the data itself. Well that’s an IT thing. That’s something that they have to own and maintain, but oh analytics. If I’m a leader or if I’m a CFO, I can relate to that I want. Ownership over that.

Malcolm Hawker

Well, yeah ownership, this I I find that the the notion of ownership, a curious notion when it comes to data. And but it’s life, it’s everywhere, right? There are people out there talking about establishing data ownership as a best practice in this space. But you need to define your. Data owners what? Does that even mean? Right like I I know and and again I know I could be opening my my my my DM back right and and and and and my data management book of knowledge from from Donna and I would. Open it and would see. Well, this is data ownership and data ownership is. Really important and this is. How you define data ownership? But I don’t really it. In practice. In theory book great. So in theory I seem to get it. But in practice that’s not what actually happens. In practice, data ownership is really, really about two things. It is about the. Definition of policies and procedures. The rules the laws. As it were about data, those can be defined by a lot of different groups, particularly master data that is shared cross, functionally, product, customer location, assets, thing, employee doesn’t matter, data that is shared widely across the organization, the rules, the laws of that data, the policies and procedures as defined by governance. Organization there can be many many people involved. In defining those rules, so that’s one aspect of ownership, the rules. The other aspect of ownership is the care and feeding implementation execution. Support of those rules. And again, that can happen in. A lot of different places. You can define a rule for customer data related to. Data quality and that rule could be actually enforced in a CRM system. It could even be enforced outside of IT. It could be enforced anytime customer data is created edited. And on and on and on. So the idea that there. Could be this one anointed. Person who is the owner, owner, owner sorry Echo. Of my customer data, when in reality there are. 10 and 15 people involved in defining the policies and procedures and equal number of people that are involved in actually maintaining and supporting and executing and implementing those policies and procedures. The idea that there’s one owner? I mean to me that. Seems like a recipe for failure.

Speaker 3

Right if you trying. To say hey.

Malcolm Hawker

You are responsible for. Owning this data, the only time that’s really ever going to work is when data lives completely in a silo and it doesn’t go anywhere else. It just lives in one place, right? In one application in one table in one, anything else. And you could say all right, you own that data. And if it doesn’t go anywhere, it’s not shared. It doesn’t show up on, you know, reports all shared across the organization. Well then I could, then I think. Data ownership could could work, but. In theory that you know it, just it’s. In theory great. Assign a data owner. There you go. In practice, no doesn’t happen.

Ben Bourgeois

Might work for incredibly small organization or some very solid. Just taste mentioned, but I think a lot of people who listen to to your stuff. Are trying to move some some bigger blocks and do some bright challenges in that.

Malcolm Hawker

Yeah, it’s funny. I just said in theory and it activated Siri on my phone. Maybe, maybe I’ve. Developed the list but I didn’t know it. That’s funny, I was looking. At my phone like it’s. Flashing it’s like Siri in theory. Anyway, that’s that’s that’s that’s that’s that’s my perspective on on data ownership and tying back to the to to the previous kind of discussion of data versus analytics. Yeah you can say well, you’re a you’re a you’re an owner of this report. Well, OK, if that report doesn’t go anywhere else, it only stays in one organization and you have complete and total control over the definition of that report. The business rules used to make. Great, but if you need to share that report outside of your organization and have it make any sense whatsoever, chances are you going to be in facing with other people who think that they also own that report or they also own that data field or that object or that domain.

Ben Bourgeois

Absolutely, so it’s. A little bit about about data and data perspectives and kind of why we silo and talk about things the way we do. Kind of off of that you had answer the podcast recently you talked to Rashad Dengra about product management to data. What what’s the value of bringing that perspective to it? What, what? What was your your? Take on that.

Malcolm Hawker

Well, great question. What, why right, what, what, why why? Do we need? To be talking about data as a product. I think most of what I see in the world today about data as a product is misguided. Because I think most people are taking that approach. Because of the ownership issue. Right they they they they. Are struggling with governance. They are struggling. With data quality. They are struggling with a lot of data management related tasks and the natural reaction to that with a lot by a lot. Of organizations is to say OK, I need an. Here, right? And they they people who are struggling with these things kind of turn to the kind of the data Illuminati up there and LinkedIn and other places to see. OK well what are people doing with this? Oh wait a minute there’s this thing called data as a product and one of the things that it advocates is to assign domain ownership. This is this is a core tenet of the. Data mesh right like? OK, domain own it it’s owned at a functional level and and and data as a product. It is kind of a a core tenant. It’s a it’s. A what some would say is one of the first principles of of. Of of the data mesh. These things all come together. Organizations say, OK, I’m really struggling. That means I need to have data as a product that means. I need a data product owner. Right, and that is really. I don’t think that that in and of itself, in a vacuum, at the very least, is is really going to help very much at all for all the various reasons that I just talked about. But there’s a lot of people. That are that are. Kind of turning to the idea as. Data as a. Product because it is being held out. As a solution to. All of those problems that I’m that I talked. About before Now what I see as well is. This kind of bottoms up, kind of. Like we we do this so. Much in the data world. We we we do this like because we’re we’re analytical types where we are. We are engineering types and we like to break. Things down into component pieces. And we start thinking about data as a product we say, oh hey, this. Sounds pretty good. And and I’m going to have ownership over and I’m going to. Assign a product owner or he or she. Will have control over all of these things and and it’ll be one person on the racing matrix that I. Can name to to establish. All these policies and procedures and they’ll get to. Do all their own analytics.

Speaker

And it’s going.

Malcolm Hawker

To be great oh OK, well how do I define a? Product right or what are the products that I can? Build and oh I guess I need to go take a catalog of all of my of all of my data and I need to go. Take a profile of all my data to figure out what’s out there. And and it’s kind of like it makes me kind of reminds me of. When I was a little kid. I was big into Lego and I had this giant box of Lego right and I would take the box every. This was like my my starting point for any of my Lego projects. I would literally dump the box out onto the floor. And that they’d be Lego everywhere. And then I would sit and look at the Lego. And I would say, OK, well, what can I do with all the Lego, right? What can I make out of it? And it was pretty much always a boat. Or spaceship or something I mean. You know I have my templates, but.

Speaker 3

But that’s kind. Of what I see with with data. As a product today, which is hey I?

Malcolm Hawker

Need to go find all of my Lego. And and then I need to kind of take inventory of the Lego so I can understand you know what? What my product catalog is going to be? That’s backwards and I was doing this backwards as a kid shocker, but that’s backwards, right? What you need to be doing is talking to people out business owners who have problems who cannot. You know who are being held back by their data, who are not hitting their annual bonuses because of data or who are not delighting the customers. Because of of data related problem. That’s where we need to start and work backwards, so I’m excited about data product management being applied to data. I’m not excited about the notion of data products because I think it’s misguided, and I think most people are taking this. Bottoms up dumping the Lego box out on. The floor approach and it. Is counterproductive because people are spending a ton of time doing. Data inventories and data catalogs and data glossaries, all with the idea of trying to figure out well what can I make out of my toolbox, right? What are all the great things that I can make and how do I even define a product?

Speaker

Is that a?

Malcolm Hawker

Is that an API? Is that a field? Is that an object, is that? A table I I. I don’t know this is all seems very confusing here, but if I just keep working through my my my data catalog and my data profile and my lineage and all this other stuff, I’ll eventually. Get to it, right? No, that’s not the right. Way the right way is to talk. To business users and have them say here’s the. Problem I’m trying to solve. And if you can go solve. That problem with data? Well, there’s your product. So product management is the latter. Product management when applied to data is understanding customer needs. Understanding what’s going to solve their problems, understanding pain points and developing customized solutions that will solve those problems. In this case, using data, that’s awesome. That is goodness that is pure goodness. Product management, when applied to data management in that way. We’ll yield to great great things and great outcomes. Data as a product bottoms up no bueno.

Ben Bourgeois

Right, it’s it’s kind of like you mentioned. It’s a product manager, you know that they look at P&L. They look at impact. They look at end results, you know, and taking that mentality and trying to say well, what’s what’s the actual outcome? We’re we trying to achieve and let’s not kind of get mired caught up in the. Like you said, data governance, loss rate, operational kind of process of it.

Malcolm Hawker

Yeah, total it. See it all the time.

Ben Bourgeois

So switching gears a bit, you know we talked a little bit about, you know? Enforcing a data standard and data ownership and that could be in a CRM. That could be anywhere. You had a post kind of blow up on LinkedIn last week about how you know. Can you just manage customer data in Salesforce? Can you do an MDM light in Salesforce? Can you do? Some of these things that I think a lot of companies out there are trying to do as far as enforcing data quality and maintaining standards in Salesforce. You know you and I use Salesforce all the time. It’s a it’s. A good tool what can?

Malcolm Hawker

Every day.

Ben Bourgeois

You do and what’s it? What’s it? The some shortcomings.

Speaker 3

Yeah, yeah, so so that that post was.

Speaker

And then the.

Malcolm Hawker

A reaction to questions I’ve been getting for the previous three years as a Gartner analyst. I it was. It was a recurring drum beat of can I use Salesforce as my MDM and it was it was interesting. The the the drum beats. Would get louder and louder and louder. Leading up to Dreamforce events would kind of peak the week after Dreamforce, and then they would kind of Peter Peter out within like three or four weeks after Dreamforce. The short answer here? You know when looking at if if you consider MDM through the lens of? Critical capabilities and and and I would go again. Go back to Gartner in terms of how does Gartner define MDM as a competency? How do others define MDM as a competency and and and what you would learn is that there are a list of things. That you need. To do to be considered enterprise class. Yeah right there is. You know, data stewardship. There’s data quality. There’s data integration, there’s workflow components. There’s data persistence. There is multiple implementation styles of data like camera just flashed to me. That was weird. Multiple implementation styles, multiple deployment styles.

Speaker 3

On and on.

Malcolm Hawker

Right, there’s there’s 13 capabilities that you need to have in order to be considered enterprise class MDM. When you compare that to what Salesforce can do. So I I I put out this graph. Kind of doing a chart with the Harvey Balls comparing Salesforce to enterprise class MDM solutions. What you’re going to find inevitably is that Salesforce considerably falls short across just about every metric or every critical capability that you would need in order to be considered. Surprise class NPM. Now we could have an interesting conversation about. Well, what about some lighter form of MDM, right? If I’m just trying to create, let’s say a marketing 360 and and I and I and I said marketing 360 by design because that is different than an enterprise wide 360. But if all I’m trying to do. Is a single view of my. And my my data universe is marketing. Salesforce can do that. It’s it’s really actually. Very good at. That that assuming you. Have reasonable controls over your data. Maybe you’ve implemented some app exchange tools and bolted on some tools for kind of dedupe on entry, and there’s others. There’s great tools out there that I’ve I’ve bought over the years, demand tools. These types of things that that help you make sure that the data that you’re inputting into Salesforce, they Salesforce itself has even got some. Here for marketing 360 you you could use Salesforce for that, but again, if you’re talking about enterprise class MDM where where that data needs to be shared across multiple functions, right and available across multiple patterns of consumption. Whether that is a Kafka stream or a file or anything else across multiple use cases analytical. Operational across multiple divisions departments. The Salesforce is just not built for that. It’s built as a. CRM right and enterprise class MDM are built. Or to support all of those use cases, because that’s that’s what MDM is. So you’re going to get some MDM capabilities out of sales force. Are they comparable? No, not even close. There’s a few. There’s a few areas that are really kind of. I would say really kind of problematic. One is the data model within Salesforce itself. Kind of the object based data model. Is really really. Limiting, especially when it comes to some of the kind of the very complex relationships. The complex hierarchies that exist naturally within within master data, right? So it doesn’t do that very, very well at all. It’s very limited. As well, key capability what we call ad resolution AKA complex matching. Algorithmically driven matching to understand if Acme Acme Inc. Acme Co. Is one thing or three things Salesforce does. Does not do that very, very well. There are other things that it really kind of struggles with when it comes to CRM. It’s it’s world class. It’s absolutely world class. But the reason why M games platform? Exist is is because Salesforce doesn’t do it. By the way, more to CDP’s. So Salesforce has the CDP. There are plenty of other CD’s of their customer data platforms. Again, they don’t have anywhere close to the the the level of functionality that MDM’s do and CDP vendors at least the honest ones will tell you that right half the problem here is that you know Salesforce salespeople are really good. And the. They are rather aggressive if you if you own sales force, you know they they they they are out there pushing for renewals and upgrades and and spending more money every year with sales force. So, so they’re. Out there pitching their CDP, they’re out there, pitching. Neosoft which is. Their integration product? They’re out there telling they’re out there, telling the. World that they can be used. To maintain a single version of the truth, which is true if you’re only trying to serve people in marketing. Right, but people hear. That, oh, it’s. A single version of the truth. That means I can use. It for everything, not just for my so buyer. Beware around Salesforce and amazing world class CRM platform, but when it comes to MDM, chances are pretty good if you really need MDM, you’re going to need a lot more. Than what Salesforce yeah?

Ben Bourgeois

Absolutely, yeah. Like you said, marketing 360 much more limited. Application can certainly do some of that, but not a lot of. The enterprise wide exactly, yeah. So so speak. Speaking of marketing, you had an MDM bytes video recently. You’re talking about the importance of marketing and IT initiative or MDM initiative and the impact that can have with either getting it off the ground or getting more buy in. You know what’s something IT or business or CDO’s can learn. From the importance of marketing your initiative like that.

Malcolm Hawker

Yeah, this is. This is something I had to learn through the school of Hard Knocks. I had no idea like when I when I was first tasked. To implement MDM. Get MDM off the ground, get some form of governance program off the ground. I I had no idea right? I’m an IT. Guy, what what do what do we need with? Marketing or promotions.

Speaker 3

And this is, yeah, this is something that I.

Malcolm Hawker

That that I that I learned the hard way. It’s it’s critical, and it’s critical across all phases of a large scale data, data initiative and and this isn’t just MDM guys. By the way, this is this is data strategy. This is data governance. This is MDM if you’re working with data quality initiative right you you you need to do marketing right? And it’s not just. About advertising the benefits. That’s an important part of it. Don’t get me wrong, like if you if you move the needle. If you solve. A problem you’re going to want to scream that from the mountaintops, right? You’re you’re going to want to say look at what we did. Look at the value that we drove to the organization. Look at the complex. Problem that we solved. So that’s certainly a. Part of it, but what this is all about? Beyond that, beyond. The screaming from the mountaintops. Look how awesome we are. This is about managing and setting expectation. This is about people having people start to understand why we invest in data. Why are we doing this? How does better data connect to something that I care about in the business, right? This this is this is a huge problem for the average person who is working in a CRM all day every day or working in an ERP system all day every day. I see this all. The time you know these big programs kind of come come in like a wave and it’s now all of. A sudden this field is required. This field is required and I’m. We’re going to make it. A little harder for you to do your job. And those people are like, wait a minute, hold on a second, you’re making it. Harder to do my job. Why I don’t get it? I don’t see it. You’re slowing me down and this whole you know, data this whole MDM thing. I don’t like it. I don’t like it. Well, good marketing would would mean that even in advance of implementing a change in a CRM or an ERP or making a field required or or changing how a dashboard. Good marketing, we would say in advance of that let the people know what’s coming. Let them know why it’s coming. Make the benefits to them real as early as possible, right? So so you know, have a marketing plan. Yes, a marketing plan. For your data related. Project and again that could be as simple as. A new report? A new dashboard, maybe something as big as MDM or maybe. Something even bigger like a. Data strategy. You need to have a marketing and communications plan associated to that that tells people it gets people excited about it brings home, you know, make makes, makes data real from their. From the perspective of their day-to-day job. So it’s kind of the.

Speaker

That’s like.

Malcolm Hawker

Tell them what? You’re going to do do it. And then tell them again what you did for them and then tell them again what you did for them and keep it going and. Keep it going. Because this is marketing is so so so important to getting stakeholder engagement. It’s so important. To getting funding, it’s so important. To get the. People who are using your products products data products. Day in and day out. So without marketing it, it’s just it’s just going to be so so so so so hard to do and so hard to maintain. You know that funding so. So hard to get. The funding, yeah? I mean, and I think. Coming back to the kind of the notion about product. Product managers can just. Know this stuff.

Speaker 3

Right? Like you you would you would.

Malcolm Hawker

Never launch a. Product, right? Like I’m going to make a phone, right? Or I’m going to make a widget right? You you’d never you’d never embark on, you know, making a widget without having a marketing plan. You you you need one right?

Ben Bourgeois

Right?

Malcolm Hawker

Like if you were in the widget business. What’s the marketing plan? You know? What’s the budget for marketing? Who’s our intended audience? Who’s our? Who’s our target customer and on and on? If we implement more product management into data management and into data world, then you know you would have people asking questions like oh OK, well that’s great. We’re embarking a data quality program, or we’re we’re building a new dashboard, or we’re launching Tableau or whatever. It doesn’t matter what’s a marketing plan and something you should be asking. Kind of as a normal. Course of business because. It’s only going to yield to. Goodness, as as a result.

Ben Bourgeois

Yeah, absolutely. It’s just like you said with product management and just bring that new perspective. It’s something I’m sure you know IT, leaders. They kind of get as they advance in their career, right? Get a little. Further away from. The the practice and the looking at the objects looking at the fields looking at the kind of more tactical things doing it. It’s something they have. They have to learn and have to. Have to get into because that’s a huge part. Of it, and getting these things getting these. Things done at an enterprise level.

Malcolm Hawker

Yeah, you know it people, we’re just. We’re we’re not. Very good at. At some things there’s some things that we’re really. Really good at we’re good. At problem solving, I would say. We’re we’re good at architecture. We’re good at technical things. We’re we’re good at writing code. There’s so many. Things that you. Feel are really good at.

Speaker 3

One of the.

Malcolm Hawker

Things we’re just not that good at is marketing, right? Because and and that. Goes sales as well. And you know, obviously, I’m I’m I’m. Painting with a really really wide brush here and I’m sure that there are some IT folks that are just phenomenal marketers.

Speaker 3

But but as. A as a.

Malcolm Hawker

General rule, it’s it’s. It’s generally something we we don’t think about it kind of falls into the sales bucket. You know somebody else? ‘s job and that’s OK. I would argue that you just need somebody who’s good at marketing, whether that is within this the the data Analytics team. Oh look, I just felt created my own thing I I just said data and analytics within the data team. That person can be in the data team, right? It could be the program lead for MDM, or it could be the you know your lead data steward or or you could have those confidence views. Within the data team. Or they could be within your marketing organization. Go build relationships with your marketing folks with your marketing team and say, hey, listen. I’m embarking on this thing. We’re doing it. We’re executing a data strategy, and we’re implementing it. Can you help me with the marketing for it and they may come back and say well how much? Money do you have? What’s your funding right and and that’s OK and and that’s fine I would expect. Most to to do that. But you know, I’m not saying you need to go higher necessarily. Depending on your company size. Of course you need to go higher. An expensive. You know marketing person. Chances are those people are already existing, but as a data leader, whether that is in MDM, program leader, data quality, program, lead or CEO.

Speaker 3

You need to.

Malcolm Hawker

Go and interface with your marketing organization and say you know, hey, here’s the big thing. The big ticket items we’re doing this year as a part of executing our strategy, and I’m going to need your support. And if you can’t support me, then you go back to your CEO and ask for some additional funding to source those roles within your organization within the. Data organization. Or resource them. From within marketing. Right, so yeah, it’s it’s. It’s an absolute must do because because generally you know it’s it’s not something we consider often enough. I would argue within IT, you know, focused organizations.

Ben Bourgeois

Yeah, absolutely. So one thing we posted from you this week, Malcolm, you had a new blog out earlier this week on the the cost and. Benefits trade-offs. When you’re looking at data governance, right, interesting. Just because one of the things. You talk about is the popularity of kind of like this super decentralized or Federated kind of approach to governance is is that a new? Phenomenon is that just something we’re paying attention to more now and and do you think that’s a? You know the right way to go about. It or what’s your take on that?

Malcolm Hawker

Well, again, that’s that’s this. This idea of kind of super decentralized governance it it’s this pendulum, right? Like and based on my oh good Lord 30 years yeah, that’s real. That’s real great here. Yeah, I’ve seen the pendulum swing back and forth. And many many, many times and and where we are right now is the pendulum is swinging wildly towards kind of decentralized data governance. And you know the post that I made was. A theory. And I would love love to embark on some. Sort of quant. You know, research to back the theory up, but the theory is based on my experience where where as these pendulums swing back and forth, decentralized, centralized, decentralized, centralized.

Speaker 3

I would argue that that the.

Malcolm Hawker

Pendulum is an outcome. And and the pendulum, the swinging back and forth is is an outcome from the business feeling like they’re being told too much. What to do? Like the business feeling like they don’t have enough freedom? The business feeling that they can’t move fast enough. The business feeling like they’re being force Fed business. Rules or policies or procedures. That don’t well align to. How they manage their business? Right and and these things ebb. And flow like the. Hide and what we’re seeing right now is is a lot of that, with the business saying OK, you want me to digitally transform? You want business acceleration, so it’s not just digital transformation, it’s digital acceleration. You want more for less IT leaders, including CEO’s, are having their budgets continually cut where IT leaders are. Being asked to, you know it’s it’s it’s 0 funding for these major programs, including cloud migrations. Right like self. Funded initiatives so.

Speaker 3

The pressures are.

Malcolm Hawker

On leadership right? And they’re there. Whether they’re IT leadership or business leadership, right? CEO’s are saying we need more. We need it bigger. We need it faster. Business leaders are saying OK we can do that then I but but to do it I need I need freedom. Right I I I I need I need the freedom to build my own analytics and we’ve this is this has been. This has been a crescendo that’s been. Building and marketing organizations. For a while now for. I would I would argue about the last seven years. Where marketing organizations have been staffing and building out their. Own analytics groups. Right where there aren’t, there’s a marketing analytics team now within a lot of marketing organizations. So businesses are saying more freedom, more freedom, more freedom. If you want me to go faster, I need to be free, right? And there’s a certain logic to that. This is a certain attraction to that and and and I get it so that happens and then the business goes and. Starts to build up their own reports. Right, the business starts to go and build their own little data marks. They go and buy their own tools. They go there, buy their own analytics solutions, right? They’ll go and spend a lot of money with Adobe or whoever doesn’t matter. And and and start. To deploy all of these solutions what they find. Right, what they find is that when they do it, they are it basically to do it. They are defining requirements of course, because all solutions, all programs, all processes need requirements. Those are it varied. In those requirements are governance policies. They may not appear like governance policies and they may have to be called governance. Policies, but they most certainly are. Standards for data quality, right? I’m building a marketing dashboard, right? What’s the data that goes on here? What data doesn’t go on here? How are we going? To do it right, integration ETL, there are marketing organizations that are doing their own ETL right? That that are that are defining business rules for mapping of data. The minute you start mapping data and moving it from A to B. That’s governance because there are business rules that have to go in to say I’m going to move it over here to move it over here and I’m going to make some transformations to it. The minute you start transforming data or even normalizing data, rules need to be applied to that data governance. Marketing will say well, I I need I need to manage my own hierarchy. I don’t want to apply to the corporate hierarchy. I’m going to define my own. Marketing centric art. Fantastic, that’s governance right? So so so this is the pendulum swinging and it’s swinging and it has been swinging for a number of years towards business units with autonomy to give them autonomy. That’s fantastic to a certain degree, but. What ends up happening, what ends up happening is that the autonomy that has been given to that business unit, the freedom that they get, comes at a cost. The cost is is cross functional interdependence and cross functional efficiencies right where all of a sudden? Now it’s not just about marketing or procurement or finance or accounting or compliance. It’s like how do. You make them all work together. Oh wow, wait a minute. It’s taking Me 2 weeks to run a full customer report because marketing is doing different things differently than finance is doing different than every other group. And that and and then CEO’s go. Go wait a minute, hold on a second. Why is it taking? Me 2 weeks to run. A customer report here you told. Me marketing that all my problems. Are going to go away when I gave you autonomy. You told me finance all my problems are going to go away and. Now I’ve got more problems than I had before. Cue the pendulum to start swinging back the other way right and this and this just kind of happens naturally and it happens naturally as a result of of of kind of business shifts. It happens naturally from from changes of of leadership. It it it. It happens naturally from a lot of different. Reasons but a. Part of this also is is that.

Speaker 3

I would I would.

Malcolm Hawker

Argue that the greatest benefits from governance, the the greatest benefits happened at those cross functional levels. So there was always a greater gravitational pull away from business units, because I would argue that the greatest benefits here are when. They are realized at above a functional level, right? So if you look at an organization largely at as three levels, right, functional cross, functional and headquarters enterprise wide, the real value starts to get exponential as you move up the the the the value chain as you go from functional to cross functional right? And that’s the value of governance. That’s the the value of more centralized governments. That’s that’s the pendulum swinging more towards the CEO and more towards senior leadership, right? And and they can say look at all this goodness here of having a single view of the customer and having this this. This large centralized governance org. And I see that, but. The costs are really, really. Still remain within the functional group because because there is people in functional groups that are doing that are doing the data quality that are doing the data stewardship that are doing the data mapping. They’re doing the basic ETL so. There was this. Constant ebb and flow back and forth. Where the benefits are at. A higher level, the costs are at a lower level. And there’s all these shifting going on and. And I would argue that. Kind of the way to break all of this. The way to break it, not all, not the only way.

Speaker 3

That a way to.

Malcolm Hawker

To to break a lot of this is to. Find a way to. To to get the incentives to better align at a lower level, right and and and a. Way to do that? Now this is getting into really kind of conceptual and really theoretical here is is that marketing organizations across companies have more in common than a marketing organization would have within a company with a finance group. Right? Like so so so can we find a way to be managing data at a functional level that delivers scale that delivers more value in a way that is beyond what we can do today. I would argue that starts to get into cross company data sharing and to some other realms that I would largely argue were are untapped. But I think there’s there’s something interesting there, so it’s separate conversation is sharing separate conversation around creating incentive structures that allow for data stewardship and data quality, and data governance to be managed in a more scalable, equitable way. But yeah, that pendulum. It it? It’s it’s constant, and it’s always swinging back and forth. It always is business freedom versus centralized control. We are living very much in a world of of business freedom. Maybe the data mesh will figure this out. Maybe the data fabric will figure this out and what I mean by this is this happy medium between total complete freedom domain centricity if if you will fine but call it whatever. This happy middle ground between complete freedom over here and still some idea of centralized control where the pendulum stops. Right, if we could do that, then I will be the greatest supporter of data mesh or data fabric or insert name here. I don’t care whatever that you’ve ever seen because if we can do that, that’s that’s what we really, really need. But it has yet to happen.

Ben Bourgeois

Yeah, yeah, I saw this a little bit kind of similar to the example you said at the beginning about. Just just the the governance standards and kind of you don’t really see that value until you get to the the board. The corporate kind of the enterprise level. Look at a company where business development like you said, spun out a sort of Gorilla analytics function within themselves because we’re healthcare organization.

Malcolm Hawker

Right?

Ben Bourgeois

The you know corporate analytics team was focused on. Healthcare outcomes they were focused on trying to manage payer relations and get Medicare Advantage plans at the payer level and all business development cared about was well. How are my sales reps performing in a certain territory certain hospital so analytics for neither group really served one another and it kind of caused this kind of spin out. And you know you’re presenting it. This is development metrics to the board, and they’re like, well, how can you roll that up to, you know, HCA across five states, and we were kind of like, oh, sorry, yeah.

Speaker 3

Exactly so we have do.

Malcolm Hawker

We have any questions. My interface has gone a little wacky. It’s completely totally blacked out. It seems like we may have some questions.

Ben Bourgeois

Yeah, when you’re talking earlier about data ownership and you know perhaps that being a bit of a misnomer and kind of how you implement that, somebody asked well, who’s accountable for the data and the data quality. If not the owner. Doesn’t the owner kind of well?

Malcolm Hawker

Right so. Right and and and and herein. Lies a little bit of the rub I get. It so for data that. Is inherently kind of cross functional, this is. This is largely master data, but it’s not exclusively master data either. Like reference data, by the way. Great great example here. Ultimately, the accountability for that data would fall within sort of some cross functional data governance organization. And I know even for me that that that’s hard for me to say, because when everybody is accountable, nobody’s accountable. I I get it. Right, But but ultimately, that’s how it has to be if data is being widely shared across the organization, right? It is. If it’s cross functional, if it needs. Both a combination of domain centricity and some sort of cross enterprise cross functional focus well, then the ownership really really needs to come down to. Some form of data governance counsel that is responsible for those two things that I talked about right defining business rules, defining governance policies, and implementing and managing and executing those right so ultimately that that Governance Committee is going to be responsible for those things now at lower levels, each of those individual. Deliverables, right? Like making sure that a field is is not null within a CRM that could be side’s job. They could be accountable for that, right? Making sure that there are metrics to quantify the impacts of of a data governance policy. That could be a steward’s job right? But when it comes to a a customer data. Let’s say customer data right, who’s responsible for customer data? Well, that is by definition a collaborative effort. There are a lot of other things that go. Into that that. Can most certainly be owned by individuals at more of a process or functional. But the idea that. One person owns customer.

Speaker 3

Data it, just it it’s.

Malcolm Hawker

Never worked, it’s never worked.

Ben Bourgeois

Right, it’s share data. Absolutely we had another question, kind of in your kind of intro. You’re talking about separating data and analytics and how that comes down to operational and analytical uses of data. I had a question. Would you like to see operational databases built on text files like a data lake and just kind of a impact of that?

Malcolm Hawker

That’s interesting. Well, why I don’t? I don’t know. There’s there’s, there’s got to be something else to that I’m I’m maybe I’m maybe I’m missing something but. I I don’t. I don’t know why, why right like I mean I guess I guess the text file could be a really, really, really rudimentary form of a database. No, I I I don’t. I don’t think I understand the question. Answer no, I would not. I would. I would prefer that that data sits in, you know, you know data feeding the CRM or an ERP is sitting in a robust relational data store because because because it it needs to, right? Like you, you need to be able to index that that data quickly when you’re talking about CRM or ERP. You’re you’re talking about known nodes, right? You’re you’re talking about queries that are repetitive and known and structured, and this is the world of relational data. So answer no. I wouldn’t want to see it in. Text file I. Want to see it in a robust relational data store?

Ben Bourgeois

Do have one question? Uh, just talking about the change management. So how do you overcome organizational change management challenges that come with implementing an MDM? Platform MDM initiative.

Malcolm Hawker

Yeah, that’s that’s a good question, you know. Change management is is you know how how kind of you know. I guess IT folks like like to posit things, and you know inherently governance is change management. Right and we we can look at the execution and management of data governance through the lens of change management. I think that that’s fine, right? I think you can. I love to look at it through the lens of kind of more of a product lens, right? If you were, if you were going back to my widget. If you were going to change the way the widget worked, what would you do? Right and and I think, yes, that is inherently a change management function, but I love looking at it through the lens of product because a product person would say OK. What are the cost benefits of the change? What’s the business case? For my change, is the change going to? Be net positive. For the organization, what are the downstream impacts of this change going to be on? Let’s say customer service or support right? Will we increase our widget defect rates by implementing this change right so so changes would be evaluated and managed through the lens of? Of a product right starting with the business case, right? And and and working all the way through back to that marketing plan that I was talking about. Working back through what we would call go to market.

Speaker

OK.

Malcolm Hawker

As a product person and by the way I I was a chief. Product Officer I. Was the the vice president of product. I had a product team. With a software startup based in Austin, so I I come at this rather honestly. The 1st 15 years of my career was all product centric so you’d have a go to market. Plan right where? It’s OK, well, we’re implementing a change new bell. The whistle on the widget, and we’re implementing a change, so we need to educate our users. We need to educate all the people are going to do this right. We need to make sure that they understand how to implement the. Change or how to use the new bellor whistle on the widget. We like in the data world. We like to call this data literacy.

Speaker 3

I don’t call it.

Malcolm Hawker

Data literacy because I because frankly guys I think the the phrase data literacy is is judgmental and and and and and borderline condescending bingo.

Ben Bourgeois

Right, what’s the opposite of that? It’s data.

Malcolm Hawker

What’s the opposite of data literacy? Well, is data illiteracy? Right, and who wants to be told they’re illiterate, right? Chances are pretty good. I don’t use this thing the right way, right? Actually, chances are very good that I don’t use this thing right.

Speaker

You can use.

Ben Bourgeois

Siri instead of Siri.

Speaker 3

Right, right and and and it’s like.

Malcolm Hawker

OK, does that make me widget illiterate? Come on, no it it doesn’t and and I get it right. It’s like, let’s not we’re not saying data illiterate. We’re just saying that you know that the problems with data or an individual’s inability to derive value from data is a result of the skills gap. And by the way, this is the core tenant of data literacy. That the inability. To derive optimal value from data is a result of a skills gap of the users of said data. That’s it, and if it if if you we can argue all day I I’m going to stand by that one. I read Jordan Moore’s book. Got a pretty good idea of what data. Literacy is so if. You make that. Assumption that the inability to derive value from data is all about data literacy, right? Well, the opposite is data illiteracy and I would argue that that’s not always the case, meaning that it’s not always about a skills gap. Maybe the data itself. Is low quality. Maybe you built a poor product. If the widget doesn’t meet the need and. Nobody buys it. Or it’s full of defects or it gets returned to the store? Well, maybe the problem was the product, not the user. Right, and so I don’t know. I I tried very lightly when it. Comes to data literacy. We all want better informed, better skilled employees. We all want people to know. When the right tool is the right tool for a job, and. How to use? That tool right? You don’t want to use. This as a. Hammer right and you need. To train people, hey, this isn’t a hammer. I’m not sure if I’ve ever used my iPhone as a hammer, but there’s a good chance that I’ve probably used it in some sort of banging way.

Speaker 3

Anyway, you want people to know what’s the. Right tool for.

Malcolm Hawker

The right job, right? And and. That’s good and you want people. To be highly skilled, but at the same time. Maybe you need to be looking at the product. Maybe you need to be looking at your product quality. Maybe there’s other things you should be looking at before you go. And assume that the. Skills gap is the problem for. People not getting value. Out of the data.

Speaker 3

Sorry, the question was about change management and I I wound my way all the way down to the data literacy, but yes. I like change management.

Malcolm Hawker

Especially, especially when you put it through the lens. Of product life cycle management. That’s even better, right? If you so if you. If you look at changes through the lens of business cases, if you look at changes through the lens of impacts to users.

Speaker 3

If you look.

Malcolm Hawker

At changes through the lens of. Go to market and training and all those things like a product manager. Right on I’m all for change management.

Ben Bourgeois

Absolutely we have one follow. Up question about data as a product. So what if that? Data is truly your product. It’s what you said.

Speaker

Oh yeah, that’s a.

Ben Bourgeois

Good one, monetization. What do you suggest when you know an off the shelf MDM doesn’t hold the complexity of A2 tier? Kind of conventional MDM? They call it a product MDM approach. So what do you suggest when I think implementing MDM and mastering data when your data actually? Is your product.

Malcolm Hawker

What a great question. So I happened to work for a company for seven years, where that was the case. A little data provider called Dun and Bradstreet, and I had the lofty title of distinguished architect. I think it was because they they recognized all of the hair and the Gray hair, and they said, OK, well, you need to be distinguished.

Ben Bourgeois

He looks. Yeah, that’s exactly.

Malcolm Hawker

Right, yeah, and I had to wear a. Tweed jacket all the time too. It was. Really yeah elbow. Elbow beds exactly. Yeah, well when your data is the product, sorry. Yeah, when your data is the product, it introduces some interesting and unique challenges. Most of I’ve seen in the past smashed my microphone. I’ve seen in the past where you know where to draw the line from an IT perspective. That’s a good one, usually from.

Speaker 3

When you have a.

Malcolm Hawker

Widget when you sell widgets you. You can draw a hard. Line between you know IT. For internal purposes and IT for external purposes, when you’re when your product when your data is the product, you know your factory, your data and analytics factory that would otherwise exist only for internal users where it’s easy to to to allocate cost and budget to internal users. Those words those words get really, really blurry. Not to mention from an IT just kind of core infrastructure. Things get really, really blurry from the perspective of you know QA versus production and how to separate separate those those worlds for internal uses versus external uses. I actually have a podcast episode coming up. We haven’t published it yet. It may be the very next one where I introduce an interview on CNN Matters. Salim Khan, who’s one of the smartest people. That I know who is. The CEO of a company. Who makes data for a living? And in another few episodes, he’s told me he’s going to do it. And if he’s watching this, I’m. Going to hold your feet to it. I’m going to interview interview another CDO of data centric product. His name is Chris Pardo who works for a company called Apex Analytics who also manages data for a living. So I would sorry this is a shameless plug plug. I don’t usually do this stuff, but instead of me giving giving you this, I would say stay tuned. 2 episodes of CDO matters. Two within the next five are going to be with Chief data. Officers of companies that manage data where it is their product and I will ask them all the hard questions promise.

Ben Bourgeois

Awesome, awesome. Look forward to that one. We said I had a comment on your comment on the data Governance Council and who’s ultimately accountable for data. On the day of Data Governance Council, seeing never been successful without one and that data stewards are part of the part of the process but not the ones. Ultimately, you know responsible for. Maintaining it so.

Malcolm Hawker

Yeah, governance councils are tough. They’re they’re, but but absolutely, positively necessary now. What I’ve seen historically is companies really struggle with this, and they really, really struggle with creating and managing and maintaining. That’s the hard one, maintaining they generally last six months, seven months, eight months. When some edict has been issued from the top that says thou shalt attend these meetings and own. XYZ data and that will only last a. Little bit, but it. Won’t last longer than even a full budget cycle. The right way to do it is. Is as a part of that Governance Council. If if it. Could be the governance. Council, I would argue it should start with the CD. So where you do some work, some basic work to make a business case that connects better data and the management of. Data the to to the. Delivery of business outcomes right? Start high level work. Your way down, start with three or four or five or six or seven use cases. Right? Started, data governance. Committee with limited scope, right one of a difficult thing that you can do that introduces a lot of risk is to bring everybody to the table on day one right? I would argue that if you’re looking to get a governance organization off the ground if you look. Start implementing a data strategy is to focus very very, very narrowly on specific business processes. 345 of them bring those folks to the table. Work with them to put together some business cases that make a connection between investments and governance, and the delivery of business outcomes. If the stakeholders can. See that their work. Right will result in more sales, lower costs, mitigated business risk. They will keep going to the meetings. They will be engaged in the meetings they will happily. Get into the sometimes boring business of data definitions and policies and data standards and all these other things, but they’ll do it if they know that they’re going to get the there’s a pot of. Gold at the. End of all of this, that is measurable, and we’ll go. Back into their annual bonuses, right? What I see instead is, well, we’re. Going to convene a committee, we’re going to make these people attend a meeting. Every two weeks it’s not going to really be that exciting, particularly at the beginning, and we’re just going to hope. That they stay engaged. So hey.

Ben Bourgeois

Yeah, kind of folds into like you said, having a very limited set of business outcomes and being focused you know kind of your minimum viable product strategy, yeah?

Malcolm Hawker

Bingo approach Yep.

Ben Bourgeois

Absolutely, absolutely we are. We are precariously close to the bottom of the hour here. Maybe you want to close this out and say where people can find you in the podcast, and what you’ve. Got coming up.

Malcolm Hawker

Speaking of good marketing, thank you Ben for the for the reminder. So yeah, come find me on LinkedIn. I am when spelled correctly, there’s there’s only three of me on. The planet, so that’s a master data challenge right there? That’s it. It’s a disambiguation entity resolution challenge. The three Malcolm Hawkers, which of the three is me? Chances are pretty good if you spell my name right on LinkedIn, you’re going to find me even if you just start with my last name Hawker, there’s not a ton of us either, although there are a few more hawkers than there. Amalgam hawkers but come find me on LinkedIn. If you ask me this question on LinkedIn, any of these questions I’ll, I’ll I’ll, I’ll respond. I may not respond right away, but I, but I do respond. So please come find me on LinkedIn. Come keep coming to these events. We’re going to be doing this every. Month, so if you’ve. Got questions, you know? Write them down and then. The last Friday. Of every month has been kind of our cadence. Come to this event, ask the questions. Check me out on YouTube. I am we on on the Prophecy channel on YouTube. I am posting a lot of. Stuff out there a lot. Of YouTube shorts I’ve I’ve. Done five in the last week. If if you know. If this doesn’t, you know tire you of seeing my my log check me out on YouTube. We’re putting out some shorts, we’re. Putting a lot of. Content there come. Check out prophecy.com and the resources. Section of prophecy.com We’ve got so. Much stuff guys we have. We have got best practices related to RFP’s. We’ve got best practices. We’re building a business case we’ve got. We’ve got so much stuff and. So many resources out there that are practically identical to what I was doing at Gartner, but not exactly identical. At all but but practically identical with the same level of insight and the same level of goodness that I was doing it at at Gartner, that we put out on the Prophecy website as as a resource for everybody to use. Customers are not customers, just just come check it out. So if you got questions, data quality, data strategy, MDM governance, getting stuff off the ground, building a business case, the list is long. All of those resources YouTube prophecy.com the resources section here on Lync on LinkedIn. We’re on LinkedIn, live here on LinkedIn. Come to the podcast, check out previous episodes of the podcast Spotify, Google Apple Podcast, you name it. We’re out there. We’re here to help.

Ben Bourgeois

Absolutely yeah, we just dropped the latest episode of the podcast yesterday. I’m sure with Rashad dingras. So please everybody check that out and we will see you next month on the next episode of Studio. Matters live thanks again.

Malcolm Hawker

Awesome thanks guys. Have a good weekend.