Good morning, good afternoon, good evening.

It may be a different time wherever you are. We record these events, so who knows what time you’re watching it, when you’re watching it. But I’m glad you’re listening. I’m glad you’re tuning in. I’m glad you’re watching. Maybe you’ve downloaded this to a ex you know, who knows what. You’re listening to it, on your phone while you work out, mowing the lawn.

Who knows? Maybe you’re sitting at work. All good. Glad you’re here. I’m Malcolm. I’m gonna be your host today. I’m the host all the time.

Not just today. If you are listening to the CDO Matters podcast or if you’re watching us, you get me every time. I’ve yet to actually have anybody else, like, host on my behalf. We are I think this is episode, like, seventy eight or seventy nine.

We’re three years in to this podcast, and we’ve never had anybody else do it. And we’ve hey. Fun fact.

Fun fact. We have yet to miss we we publish every two weeks, and we’ve yet to miss a two week publish window in three years of doing this, which is, like, if I had a machine I could press, like, to make the background noise, like, the yay, like Jim Kramer with the buttons and the sell, sell, sell. I would have pushed the button that is, like, celebrate. That’s really a testament to the amazing team that I have behind me.

Shout out to Manesha.

Shout out to Ivan. Shout out to everybody who helps put this podcast together. Danielle, Haley, Kayla’s helped in the past? Alexa’s helped in the past?

We’ve got a team. It’s not just me. I am like the Vanna White of the CDO Matters community and the CDO Matters podcast. I just turned the letters.

I show up in the spokesmodel.

We can have an interesting conversation about the, you know, whether I’m an attractive spokesmodel or not. But that’s irrelevant. I am the spokesmodel, and I am literally walking on the backs of others that help my my job help make my job a lot easier easier. So, boy, I’m having a hard time speaking.

It’s Friday afternoon here on the East Coast of Florida. It is what is it? It’s early May. Kinda crazy.

I think we’ll publish this podcast as soon as we can, more than likely in a couple weeks or in three weeks, because the issue that we’re gonna talk about today is timely.

The issue today is data and tariffs.

More specifically, what should CDOs be doing?

Maybe arguably, what should they have already been doing? But let’s put that aside. There’s a lot of turmoil right now. There’s a lot of uncertainty, and I’ve got some advice for CDOs or VPs of data and analytics or directors of data and analytics or anybody in a data and analytics role who has influence over short term priorities and short term roadmaps and what you should be doing in order to buttress yourself against the uncertainty that is today’s days and time. So we’re gonna talk about what can we do.

Are there things that we can be doing in a data role to help our companies better cope with a lot of the turmoil that’s going on right now? I’m not here to talk about whether I agree or disagree. That doesn’t matter. I’m here to help CDOs and other data leaders succeed in their roles.

And the good news or bad news, I think it’s mostly generally bad news. But when it comes to situations like this, we don’t have to look too far back to look for guidance on what we should or shouldn’t be doing in times like this.

I just think of early twenty twenty.

Wow. It’s crazy to think that that was five years ago with the global pandemic, but I think back to early twenty twenty, all through the year twenty twenty, and it is just eerily reminiscent of what I’m seeing now. Things were rapidly changing. There was a big shock, a big disrupt big disruption, particularly to global supply chains.

Everything just pretty much stopped. Shipping stopped. Manufacturing stopped. Everything stopped. If you’re more than, I don’t know, fifteen years old, you’ll remember.

Everything just kinda ground to a halt. So we have a playbook here. But what I saw in twenty twenty, folks, was a lot of waiting and seeing, a lot of sitting on hands, and a lot of, well, we’re not entirely sure what’s gonna happen. Let’s just wait this out.

You know, things will probably sort themselves out sooner rather than later, and a lot of people stood on the sidelines.

A lot of people ended up and a lot of companies, a lot of data leaders did end up acting eventually. They started to act based on the conversations I was having while a Gartner analyst, and that’s a pretty good bellwether to me. That is a pretty good indicator of, you know, CDO and data leader sentiment.

Early twenty twenty, there was a lot of just apprehension apprehension. By late twenty twenty, it became clear that things were probably settling in for a while and this there was a new normal and that we would need to react and take some actions to try to combat the negative impacts of the global pandemic. And I certainly saw that while I was a Gartner analyst, but there was a good six month span there, maybe even more for a lot of companies, where there wasn’t anything happening, and they weren’t doing anything for the exact same reasons as now.

Now don’t get me wrong.

Some of the things I’m gonna recommend and some of the things that I think that we should be doing as data leaders are cost will cost money. And I do understand that there’s a lot of apprehension right now. There’s a lot of companies saying, time out.

Stop. Stop spending. Stop investment. Stop everything. Let’s just wait and see.

But if you are in a senior leadership position at any organization and you suffer from some of the things that I’m about to talk about today, I would strongly urge you to go make a business case to your leaders that you should be taking action. Because frankly, if you didn’t do some of the things that I’m about to talk about today in twenty twenty, you you know when looking back, you you will honestly be able to self assess and say, Sheesh, we should have done something. Right? We had the opportunity in twenty twenty.

We should have done something. We didn’t do anything. Those companies that didn’t, by the way, that didn’t do anything in twenty twenty, twenty twenty one, twenty twenty two suffered far, far more than companies that did. There are a nontrivial number of companies that were taking some pretty significant actions in twenty twenty, twenty twenty one, twenty twenty two that we’re we’re still seeing the impacts of those today.

Whether those are good or bad, we can have an argument about that, but a company like Nike that it was in the middle of pandemic, made a pivot away from b to c sales or b to b sales and pivoted towards b to c sales. Nike’s been in the news recently. Some of their some of their performance is is down, But that was still a significant pivot. That was still a significant shift.

And in the time of the of the pandemic, that was a huge difference. McDonald’s was already in the middle of a shift towards automation. This was happening twenty twenty, twenty twenty one.

The pandemic just accelerated a lot of that, and a lot of those efforts continue to this day.

There are there are many other examples where companies were adjusting to the new normal of the pandemic, and we’re still seeing some of that new normal now. My point here, folks, is that it’s never too time it’s never too late to act particularly on the things that I’m gonna talk about today. It’s not too late to act.

And if history is any guide, then the longer we sit on our hands on these things, the more deleterious the impacts are going to be. I don’t know how long this tariff thing is gonna is gonna last for. I don’t know how the disruptions are how long the disruptions are going to be. I I honestly, if I I don’t have a magic forward looking hat, or else I’d be wearing it right now.

So I don’t I don’t know how long they’re gonna last, but the things I’m gonna share with you, I would argue, my friends, are evergreen that we should be doing.

We’ll get into some of the action steps here in a minute. So time, I would argue, is most certainly of the essence. Time is of the essence. If you didn’t do these things in the pandemic, you need to do them now. And if you didn’t do them you didn’t do them in the pandemic and you hadn’t done them before, these are the this is what I’m gonna share with you today is just, like, good nutrition.

Right? Exercising more, eating well, getting enough sleep. The things I will share with you are basics. One of them maybe they’re they’re hard to do.

Don’t get me wrong. That’s why a lot of companies avoid them and and haven’t figured this stuff out. But they’re gonna benefit you. They’re gonna benefit you when times are good.

They’re gonna benefit you when times are tough. They’re just gonna benefit you because they are data nutrition, data management nutrition, perhaps. So what I will share is not a, okay, it only works now and it’s only worth you know, it’s only useful now and then when things go back to normal, it’s no good anymore. No.

These are evergreen, best of breed practices best practices that we should be doing as data and analytics leaders.

So timing of the essence. Get on it.

You know, it’s never a good time for these types of disruptions. However, however, there is again, there’s a precedence here, and my hope is is that what I will share with you today motivates some data leaders to go to their senior leadership, to go to their board, to go to their c suite to say, you know what? We need to do this, and we know that times are tough. We know that things are extremely uncertain.

But here’s the reality.

We saw what we saw in COVID is the companies that got their data house in order prospered or at the very least were not excessively impacted.

Right? When people got their data house in order, good things happen. And when companies sat on their heads, bad things happen. Right? There there there were absolutely feedback effects here. There were exponential impacts.

Better you were, the better you got, and on and on. The worse off you were, the worse off you got.

So that’s the teaser for our discussion today. What don’t you have time for?

So what are the things you should be avoiding right now?

What did we learn from the pandemic that is probably not that you know, tactics that are probably not that helpful right now?

Well, if time is of the essence, and I would argue it most certainly is, then a few things to think about.

Pardon me, friends.

I got a tickle at the back of my throat. Allergy season.

C’est la vie. So you don’t have time. What don’t you have time for? Well, here’s gonna be something a little heretical.

Governance committees, decision making by committee. Don’t really have time for that.

I know that sounds heretical, and I know that is contrary to pretty much every best practice when it comes to data governance. Data governance best practices would say, hey. You know, if you’re going to be doing things with your customer data, your supplier data, your product data, you’re gonna be making some decisions that impact your analytics. You’re going to be making investments in these things. Well, they need you to run that before your data governance committee. Well, this is again, this is gonna sound heretical.

In this situation, my friends, in this situation, I would rather seek, approval later. I would rather seek you know, I’d apologize later, but have a bias for action now. The time for action is now. There should be and needs to be necessarily must be a bias for action, and I am all for governance. Huge believer in governance, but you don’t have time to defer some of these decisions to the committee. You just don’t.

When you start talking about things like customer definitions, you start talking about things like supplier definitions, you start talking things about, like, you know, financial reporting, contract level reporting, you start talking about some of these things in the committee.

We need our data governance committees, but right now time is of the essence and we don’t have time for a lot of these things. If you disagree, I would love, you know, hey, put a comment in if you’re watching this on LinkedIn, if you’re watching this on YouTube, put a comment below and say, hey, you’re crazy.

That’s not right. That’s not cool. It’s not good. But I would argue you really don’t have time to go before committee.

Now that doesn’t mean you don’t need to have your customers engaged. On the contrary, you do need to have your customers engaged. So one of the things I’m gonna recommend is that you take a very use case specific approach or you take a use case driven approach to solving for some of the problems we’re gonna talk about. That necessarily requires you to engage your customers and to have them working hand in hand with you.

Pardon me.

Oh my goodness.

Pardon me.

I told you. Allergy season.

When the throat starts tickling, it’s like, oh, here it comes.

Forgive me, for sneezing in the microphone. Hopefully, it wasn’t, like, you know, eighteen times the volume and you’re listening with earbuds and you get to hear hear me sneezing.

Governance committees don’t really have time for that.

You don’t have time for fancy governance either. You know, I’m I’m a huge believer in adaptive forms of governance. I am a huge believer in taking a content centric approach to governance. I’m a huge believer in having a very flexible governance model where you apply this this set of governance policies to this use case and this set of governance policies to this use case.

I’m going to recommend exactly that. But, again, we don’t have time to run this before committees because these are very complicated models. These are very advanced forms of governance that and if you try to do this and you try to get maybe ahead of your skis on governance at a time when speed is absolutely paramount and when speed is of the essence, again, we’re going to be taking an MVP approach here. I would argue perhaps even not even an MVP because an MVP necessarily, when you’re talking about some of these things in normal days and times, would require a lot of buy in and consensus and kumbaya.

Don’t really have time for that.

I would argue we really don’t have a ton of time for long drawn out consulting engagements either.

To think that you are going to go higher particularly strategic consulting. Now there are roles for consultants to play in more of a staff augmentation perspective, butts in seats type perspective. If there are roles in your team that you are missing or if you believe that there are roles that need to be sourced in order to do some of the things that I’m talking about, hey. Great. That’s fantastic.

But going in doing the six to nine month BCG engagement, Deloitte, McKinsey, Accenture, whatever, these are wonderful companies. Don’t get me wrong. They provide great insight.

But if you have to wait six, seven, eight, nine months for a recommendation, that’s probably gonna take a year to implement. Well, who the heck knows what’s In two years? We don’t have two years to wait, my friends. We don’t have two years to wait. Your companies are already feeling the impacts of these tariffs. You already are.

The the time for action was yesterday, and the time before that was the day before yesterday.

So the idea that we’re gonna go and get into this consulting engagement to help come up with a recommendation in order to deal with tariffs, forget about it. I’m here to help. Right? And and I’m I’m, you know, I’m free.

People used to pay a lot of money for my insights when I was a gardener.

But there are resources out there to help you move quickly on some of this stuff. There are some consultants, a limited number of consultants. You know, they tend to be kind of, you know, individual proprietors who are extremely talented experts in their given field who can help, who certainly can help. So I’m not saying just avoid all consultants, but I am saying, you know, the classic, hey. We’ll come and, you know, you know, do the as is evaluation. As a part of the as is, we’ll do a maturity assessment, and then we’ll come up with our road map, and we’ll come up with our priorities, and we’ll We don’t have time for that.

Don’t have time for it. As much as much as as as valuable as thing those things may be, we don’t have time for it. Speaking of data strategy.

If you’re out there, if you’re reasonably new CDO, and many of you are, many of you are, more than fifty five percent of you are your company’s first CDO, and many of you are in the job for the first time within the last eighteen months.

If you’re one of these CDOs and you’re saying to yourself, okay. Well, I gotta figure out my strategy before I can figure out how to make sure that we, you know, protect ourselves from these tariffs.

Nope. Don’t have time for that either. I I I would argue this is kind of a Defcon five or Defcon one.

Five alarm fire. This is a five alarm fire that requires action right now. And, again, the things that I’m gonna recommend are Evergreen.

All the things that I’m going to recommend to you today are best practices that should be happening Monday to Friday every day, every month.

They should be just kind of baked in everything that you do. So the things that I’m going to recommend today will necessarily and should necessarily be part of your data strategy. So this idea okay. Well, I’ve gotta go figure out my strategy first before I make an investment to try to make sure that we’re best positioned to weather the storm for these tariffs.

Don’t bother.

Don’t bother. I mean, you should be working on your strategy in parallel. Right? If you’re reasonably new to the role, you should be working on the on on the strategy.

But if you listen to any of my advice and any of my other podcasts or anything that I post online, while you’re doing that, you need to be doing stuff in the short term to drive value now. That’s what I’m talking about. I’m talking about what is the short term or what are you doing to drive value now. I would argue that if you suffer from the things that I’m about to talk to you, you should be figuring these things out now.

That is the short term, that your short term should be figuring out all of this now, including figure this stuff out that I’m gonna talk about in advance of AI, in advance of data products, in advance of anything else.

Keep that in mind.

Data cleanups. You don’t have time for data cleanup.

Your data is a your data is a mess. Figure out a way around it.

Figure out a way around the messy data.

You don’t have time for perfection.

Don’t have time for that.

What you’re gonna be going for here is sixty, seventy, eighty percent of a solution, and that should be good enough.

And it’s not it’s not that it should be good enough. It’s what you’re gonna be able to do in the short term, and it will necessarily drive incremental value. Now is it gonna be drive as much value as it could if your data quality was better? Of course.

I mean, if your data quality is better, you’d you’d get more value, but you don’t have time for that.

You don’t have time for business process changes. You don’t have time to fix the fact that you’ve got data silos per se. Right? You don’t have time to opt to fix all the operational problems that got us to the to to where we are.

Right? So we don’t have time with that. We don’t have time. We don’t have time to go and sit and try to convince our customers in the business that they need to change how they onboard customers, how they onboard suppliers, or how they do apply due diligence to anybody. We don’t have time for that.

We need to be doubling down, doubling down, tripling down, quadrupling down, and some of the basics we’re gonna talk about.

So what are these elusive advices?

What are the things that I keep referring to but not speaking of?

Well, I think it’s pretty simple.

In my experience as a Gartner analyst, in my experience as a CEO, in my experience in in the data and analytics world, most companies, most, dare I say all, most suffer from data silos.

K? It’s just it’s just a reality. You’ve got data in CRM. You’ve got data in ERP.

You’ve got data in a supply chain system. You’ve got data in the HR system. You’ve got data on an Excel spreadsheet. You’ve got data written on your hand.

You got a silo. You got data silos.

What you need to be doing at a high level right now, if you haven’t done this before, you need to be doing it now. You need to find a way to break those silos to come up with holistic analytics to show you the total the tote or as close to the total as possible as much of the data possible for a given relationship that you have that is critical to your business. What do I mean? Well, customer relationships, supplier relationships. You need as much insight related to your core materials, your core products as possible.

If you’ve got product data in silos, you need to have a holistic view of that product data. If you’ve got supplier data in silos, you need to find a holistic way to have a a holistic view of that supplier data. Customer data, same thing. If you’ve got customer data all over the place and it takes you two weeks to run a consolidated customer report, then you need to fix that. And you need to get as close as you can, I will say, dare I say, to a three sixty?

This this is still a used term. It’s still a valuable term. People generally know what you say when you say customer three sixty or supplier three sixty. So, yes, it’s a little bit of an overused term. Yes, it’s a little pithy, but hopefully you get my point.

If your CEO asks you how much business are we how much are we buying from Acme Incorporated?

K? And let’s assume Acme is one of your core suppliers.

Acme sells you the stuff that you need to make your goods.

Right? If your CEO asks, how much business are we doing with Acme Incorporated? How much risk? Because act we we know that Acme is based in China.

How much risk do we have with Acme Incorporated? If it takes you a long time to answer that question, what do I mean by long? Anything other than pressing a button or running a report. If it takes you two or three days to cobble that data together, if it takes you two to three weeks to cobble that data together in an accurate, consistent, trustworthy way, this is what I’m talking about.

What you need to be focused on right now, I would argue, if you are concerned about tariffs, if you have exposure to tariffs, I would argue we all do.

Whether that is direct or indirect, we all do.

We all do. Right? If if tariffs negatively impact the economy for a prolonged period, right, the the the hope here, of course, is that manufacturing is spurred in the United States and and that local sources get of goods get to the point where where you could easily switch between. I think it’s pretty much it’s obvious that that’s gonna take some time. Right? Manufacturing plants just don’t spring up overnight.

Right? So this is gonna take some time, and everybody will be impacted because even if you’re not creating stuff, even even if you’re not manufacturing goods or if you’re not wholesaling or distributing or reselling goods from from China, this is most or or any other country for that way. It doesn’t matter if it’s China. It could be Canada.

You could be getting stuff from Canada. You could be getting soft woods from Canada or steel from Canada. It doesn’t matter. If you’re getting your goods from anywhere else, right, and you can’t get them and your prices go up, well, your demand is gonna go down.

If your if your demand goes down, there could necessarily be a drag on the entire economy on on a on an on an industry or economy wide basis.

So there’s many people out there talking about potentially a recession that is triggered by these tariffs. I don’t know whether that’s true or whether it’s not true.

My point here, my friends, is that I think every company will be exposed and will be impacted.

The question is, how much will they be impacted? I don’t think we necessarily know. Don’t think we know.

But again, returning to the high level advice, the high level advice is if you cannot quickly and easily and consistently, repetitively produce what I would just loosely call three sixty insights related to your core master data objects, supplier, product, customer, material, maybe even location. If you cannot do that quickly, if you cannot do that confidently, if you cannot do that accurately, these are the things that we need to be focused on in the short term.

Your leadership needs these three sixty insights to understand how much is our business exposed from the demand perspective.

Right? How much should we expect that our consumer demand will go down? Who are our customers? How often do they buy?

What did they buy? When did they buy? What products did they buy? Do they prefer the products that are gonna be impacted by these tariffs, relationship with your customers.

Right? You need to understand that. Demand side. Supply side, you need to understand the complete picture of everything that you’re doing on the supply side of your business.

If you depend on importing goods from somewhere else, if you depend on raw materials from other places, you need to understand your product life cycle. You need to understand where those goods come from. You need to understand, are there suitable goods that we could be using otherwise? Are there are there alternatives?

Are there substitutes here? And on and on. These are all everything that I just talked about are all predicated on the idea, the assumption, the belief that you have a consistent and accurate and holistic three hundred sixty degree view of those things that matter the most, your shared master data assets, supplier, customer, product, location, material, ingredient.

If it takes you a long time to run reports, if you don’t trust those reports because largely because you have data silos, and we all do, then those are the things that you need to be focused on. You absolutely need to be solving for that. And I would recommend, my friends, that it’s do not embark what I was talking about before. I was talking about perfection.

Forget perfection. You’re not going to achieve perfection.

Can you get to sixty, seventy, eighty percent of that three hundred sixty degree view? It’s not gonna be perfect. Can you do it?

Can you do it? Can you provide a better report to your chief procurement officer about your exposure to Acme Incorporated from a supplier perspective? Can you produce a better version of that report that shows how all of your products are being consumed across your various geographical regions or across various product lines? You name it.

Right? How do we improve that and how do we improve that quickly? I would argue, my friends, that if we take a very MVP driven, very time sensitive, biased to action approach to solving for some of these problems, we can make meaningful improvements in weeks and not months or years. What are some of the tactics to help accelerate these initiatives?

Well, you know, obviously, not all data is created equally. Right? But let’s start first with third party data. So if you are talking about your customer, whether that is a b to b customer, whether that’s a b to c customer, if you are talking about your suppliers slash vendors, you know, again, doesn’t matter what industry you are. If you are dependent on other businesses and you’re trying to understand how much business are we doing with Acme, less so from the perspective of products, maybe if you were dependent on reference data, maybe you’ve got reference data all over the place.

Can you turn to third party providers of data to help you create reference datasets for those key shared master data assets? What am I talking about?

Well, as a part of this journey, understanding how much business you’re doing with Acme Incorporated, you need to establish what is accurate from the perspective of Acme. Right? A great way instead of going to a governance committee and saying, what are the rules for how I define what Acme is? What are the rules for defining when the data related to Acme is correct or incorrect?

Right? How do even gets into simple things like defining what is a company or what is a customer.

Instead of falling down those rabbit holes and trying to answer those questions on your own, can you can you defer to third party providers of industry standard data that say this is what a company is and here’s the correct information for Acme Incorporated? Or maybe even necessarily on the consumer side, buying data from one of these a a large agency or a large data provider like an Acxiom or an Epsilon or others to help you understand who are you doing business with, how many unique customers are you actually doing business with. Third party data providers can drastically accelerate some of the governance decisions you need to make quickly.

I’ve you’ve probably heard me say this on this podcast before, but I’ve literally lost days of my life sitting in workrooms arguing about customer definitions.

You don’t have time for that. Or company definitions. You don’t have time for that either. This is this is why it can be valuable to partner with some of these third party data providers because at the very least, for better or worse, a, for example, a an Experian or a Dun and Bradstreet or a Harte Hanks or an InfoUSA or ZoomInfo even when it comes to people, they’re not gonna be perfect.

Their data’s not gonna be perfect. Is it ninety percent accurate? Is it eighty percent accurate? I I mean, I don’t know, but it doesn’t matter.

It’s still it’s still at least a standard that you’re able to apply your data to, and you’re able to actually kinda defend it. Because you put a report in front of your c suite and says, okay. Here’s how much data we’re here’s how much data. Here’s how much business we’re we’re doing at Acme Incorporated.

They’ll go, oh, well, okay. That information from Acme, where did you get that?

Right? How did you how do you know you know, how are you confident that this is how much we’re doing? Well, we’re we’re using an industry standard like a Dun and Bradstreet. We use the Duns number as the key for matching.

Right? So instead of taking days and days and days and days to try to get to consensus internally on how to define a company and whether that come and the rules related to defining whether that company is a going concern, you can use a third party data provider. We’ll significantly help accelerate those efforts.

Technology. Yes. Of course, I work for an MDM provider. I am I am biased here, but I think MDM technology can go a long way in the short term to help you do these things.

It can help match at scale. It can help you do some data stewardship at scale. It can help you understand and manage hierarchies at scale. Hierarchy management is a big part of all of this, folks.

This is another area where those third party data providers can significantly help.

You may think that you’re not doing business with China because you are working with ABC Inc.

Maybe ABC Incorporated is just some holding company based overseas somewhere, not China, but based overseas somewhere. Maybe they’re just a holding company. Right? And all of their operating units just happened to be in China, but you didn’t know that because you didn’t know all the operating units of ABC Incorporated.

Having that depth of insight related to these from these hierarchies is so, so important.

They’re so important because they’re gonna show you where there are second and third degree risks related to the business you may be doing with Acme. We saw this in COVID, friends. We saw this where there are plenty of people that didn’t think they had any supply chain exposure, any supply chain risk. Lo and behold, what happened is is that they were doing business with one company. They thought they were doing business with one company. Turns out they were doing business with fifteen companies because company a was dependent on all of these other companies.

The interconnectedness, the interdependencies within our global supply chain are very, very real and starting to build out and manage these hierarchies and understand relationships between corporate entities.

A good starting point is legal relationships between them, things like owner and subsidiary or franchisee.

Understanding some of those legal relationships is a good first step. Second, third step as you progress in your maturity here, will be to understand some of those operating interdependencies that may not be abundantly obvious, where there are operating agreements or trade agreements that you didn’t even didn’t necessarily know about. But again, using third party data, focusing on some idea of master data management, probably through the use of the tool, probably through the use of software.

Is that going to align to this get ‘er done quick? Some better than others. Some better than others. You know, if if you’re if you’re thinking about, you know, nine to twelve months to implement MDM, you don’t have that time.

You need to be working with a provider that’s gonna be be able to help you be up and running in days and doing some matching in days, maybe a couple of weeks tops. You can start throwing some data into taking data out of your CRM and your ERP and your procurement system, dropping it into an MDM and doing some basic matching, using some basic matching rules to see, okay, how often does Acme Incorporated showing up across these three sources of data because we need to understand our relationship with Acme Incorporated whether Acme is a supplier or a customer. Same thing is true from a product perspective.

You need to understand your products. Where are materials being used across your products? Do you even have that visibility today? Maybe you’re global now multinational and you are building products all over the world and operating in use across the globe.

Can you start to produce some of those insights where you can see, we’re building something in Canada that is highly dependent on tariffs, but we’re building something over here that is not. Could we start trading some things internally necessarily within organizations?

So you get my point. Hopefully, you get my point. Master data management here is all about busting silos.

My recommendation to you in the short term is to find ways to bust silos.

If you didn’t do it during COVID to come up with these three sixty degrees of views of something, you need to do it now.

Because, again, this is evergreen. This is evergreen, friends. This isn’t going away. Nobody is going to argue. If you make an investment right now to come up with a single view of your relationship with Acme Incorporated, nobody is going to argue that’s a bad thing. Nobody.

These things arguably should have been happening five years ago if they weren’t. We need to get them done now. And, again, perfection is the enemy of progress on this stuff. It most certainly is. Now I’ve mentioned MDM as a discipline, master data management, and in technology as well.

There’s a lot of people that incorrectly assume that MDM necessarily is this two, three year long initiative. It’s not. Doesn’t have to be. There are two forms of MDM.

One is what we call an analytical style where all you’re trying to do is link things together.

Acme, Acme Inc, Acme Co, Acme LLC, Acme and Sons.

Is that one thing or is that four things?

Analytical styles of MDM are answering that question.

They will they will help you answer that question. You’ll be able to configure some basic rules for for how I define a corporation. This is where a third party data provider can help you accelerate that.

You will implement some basic rules and configure some basic rules and configure some basic data quality standards for what you expect to see on the record for ACME. You’ll define some essentials around what are the attributes of Acme that matter the most.

Right? Maybe, obviously, their location. Their address is gonna be one of them. Their industry could be another one, revenue, number of employees. Maybe you need to understand what the risk is of Acme going under because of all this. Maybe you don’t even know that you’re doing a lot of business with extremely small companies that may not be able to weather the storm in the short term.

Right? If the shipments stop, right, you’re dependent on Acme as a manufacturer for your stuff. Is Acme going to be around in three months?

If Acme is a forty, fifty billion dollar company and you know that because of a robust supplier due diligence or supplier onboarding process, if you know these things, okay. Well, great. Acme is probably gonna be around. They’re probably gonna be able to weather the storm for the next three to four months. But if Acme is an extremely small company, and maybe you don’t know that, maybe you don’t know that, maybe you were sold a bill of goods when you established your supplier relationship with somebody, Maybe you made a choice to do business with them because they were the lowest cost provider.

It’s these types of insights that I’m talking about, my friends. I’m not you know, yes, I’m talking about a three sixty, but I’m talking about it in a little bit more of a holistic view as well. Again, this is where third party data can be very, very helpful because you don’t have to sit and Google who is Acme Incorporated and try to figure out how much how big Acme is, how long they’ve been around, what their creditworthiness is.

Another great justification to use third party data to help understand and augment your complete view of Acme Incorporated as a supplier or a customer. These things are absolutely positively necessary. We need to be doing this.

Most companies most companies, again, have silos.

They they they they have they have silos.

So so this is a pervasive problem. Anyway, two forms of MDM.

One is an analytical style where you’re just trying to link things together. Two is operational MDM. It’s known as operational MDM where you create a single gold master record for Acme, and then you push it everywhere. You push it into CRM. You push it into procurement. You push it into ERP, and there’s one record to rule them all.

Well, that’s wonderful, and that’s a great future state from an MDM perspective. You don’t have time for that. You don’t have time for it. That’s fine.

Part of the road map. We’ll get to it. We’ll get to it. What we’re talking about here is building a report that shows your total relationship with Acme Incorporated or the total number of products that you are selling or the total number of materials that you are using and where you’re using those materials.

I keep deferring to supplier because or customer because I think, you know, corporate entity because I think it’s a it’s it’s a normal, and we all do business with other businesses somehow, some way.

Yeah. But product is relevant here. Ingredients slash material is relevant here. Even employee is relevant here.

But I’m gonna keep focusing on corporate entities. So operational MDM sounds great. The single one gold master record sounds great. You don’t have time for that.

You don’t have time for that. What makes analytical MDM in this use case so powerful is that you don’t have to fix your source data.

You don’t have to. You just need to find a way to link it all together.

Once you create that one new master ID that links all of those child IDs together what do I mean by that? Some new master ID doesn’t exist. It will exist.

Right? When you create this new master ID that links Acme one, Acme two, Acme three, and Acme four together.

Source ID one, source ID two, three, and four. Could be your Salesforce ID. Could be your Oracle ID. Could be your SAP IDs, doesn’t matter.

All of those things get linked together so that now you can run a report using your BI platform of choice. Doesn’t matter. Whatever. You can run a report using your BI platform of choice to show you how much business are we doing with Acme Incorporated across all of our lines of business, across all of our domains, across all of our manufacturing locations.

That’s what we are going for here. And if you can’t do that today or the common thing this is what I was trying to get to a little bit earlier before I lost my train of thought.

The common thing for most companies is that creating these reports is a two, three week exercise. Not uncommon.

Not uncommon where you have to manually manually link all of those versions of Acme together.

Is there maybe this sounds really familiar. Maybe it doesn’t sound familiar, but I suspect it does. It was familiar for me.

It’s familiar for me. CEO says, hey. I’m gonna go golf with the CEO, you know, with my buddy CEO of, of Acme Incorporated. You know, how much business have we done with Acme over the last six months?

Uh-oh.

What’s our balance of trade with Acme? That’s even that’s even more fun. Right? Like, hey. You know, we sell stuff to Acme, but they sell stuff to us.

Right?

Can you tell me can you tell me as the CEO, can you tell me what that balance of trade is? Right? Are we selling more than than than we’re buying?

Right? Which is kind of the preferred scenario. But, like, in my past, when those questions were asked to me, it was gulp.

That’s gonna be a couple weeks. What do you mean it’s gonna be a couple weeks?

Well, because I’ve got data all over the place. Acme is all over the place, and I’m not entirely sure that Acme Inc and Acme LLC are one thing or two things.

And I need to go do some really kind of gyrations, some of it human based, some of it query based, some of it DTL based to try to solve for that problem.

And with I I suspect you’re there. Most companies are there. So if these are the things that you’re suffering from, if you don’t have that single view of your customers or suppliers or products or materials, if you don’t do it or you can’t do it easily, quickly, you can’t do it accurately, confidently.

If you you maybe you can produce the report, but when you look at it, you’re like, what? What?

This is what we’re seeing right now with a lot of companies that made a rush towards Databricks and Snowflake.

Right? Everybody’s rushing to Databricks, to Snowflake.

You know? Hey. Data lake. Lake house. Woo hoo. Let’s go.

My friend Scott Taylor says it sounds like the lake house. Sounds like where data goes on vacation.

All jokes aside, a lot of companies have been racing towards those analytical infrastructures because they’re very powerful. They’re very attractive. Hey. I can I can do all of my analytics workloads?

I can do my data science workloads. I can do I can do everything. You know? I can do everything out of Databricks that’s gonna solve all my problems.

Oh, and by the way, I can even do complex matching. I can run the Python libraries when I import all of my data, and I can do all the normalizations I want. I could all these things, and then you get everything into Databricks and you start running some reports, and lo and behold, you still see five Acmeys.

Sound familiar?

Right.

Right. Because maybe the stuff that you were doing in Python wasn’t multivariate, wasn’t looking across five, six, seven, ten attributes of Acme for commonalities.

Maybe there were no UIs within or maybe it’s not a maybe, there are none to get stuff in front of data stewards for your top twenty customers.

I would argue you don’t have time to steward a lot of data if you’ve got eighty thousand customers.

You’re not gonna have time to steward data for eighty thousand of them, but your top twenty, fifty, hundred? You bet.

Absolutely.

Absolutely. You’ve got time to do that. Pareto is going to apply, meaning eighty percent of your revenue is gonna cover from twenty percent of your customers. So do you have time, potentially, to steward some records? Notice at the beginning of this conversation, I said you don’t have time for data cleanup. That’s true.

You don’t.

However, can you clean some up?

Can you at the very least say, Yeah, that Acme and that Acme and that Acme are the same?

Because I don’t care how good your matching algorithm is. I don’t care how good that Python library is. I don’t care how good, you know, the fuzziness is of your fuzzy matching, how amazing it is.

If your source data is suspect, if you’re lacking fields, if you’re lacking attributes on those Acme records and there’s still transactions associated to them, Acme is an active customer, an active supplier, and you have no address on that, I would I I just I was just talking to a client yesterday.

Billion dollar business plus two billion plus business that doesn’t have address on on their core on their core customer data.

And if that’s what you’re pumping into Databricks, well, good luck with that Python library because you’re not gonna be able to resolve those. You are not you you will be overmatching and undermatching left, right, and center. And when you run the report, there’s still gonna be five ACMEs in it. Or the ACMEs that you’re looking at are incorrectly matched or under matched or not matched at all because, frankly, without address, you’re gonna be up a creek, at least on corporate records and company records. So this is my way of saying, I think MDM as a discipline is going to be critical here. There are things you can be doing in the short term to come up with this three sixty degree view, and I would argue they are absolutely positively evergreen.

And once you get something stood up, once you can actually produce a report to somebody that says, I’m pretty confident this is like ninety percent of our footprint with Acme Incorporated, your company can act on that. They can try to find alternative suppliers to Acme.

Right? It can understand what the business’s impact is gonna be. It can actually forecast.

If Acme is operating in a country where there’s a thirty percent tariff, that’s what I need to take action as a CEO or a CFO.

I know. And it or or that’s one thing that’s very different than we’re not entirely sure how much business we’re doing with Acme or it’s gonna take us three weeks to come up with that answer.

And maybe you’re in that situation now. If you are, we need to be thinking seriously and hard about how do we stand up one of these three hundred sixty degree views quickly that is reasonably accurate, that can be done at scale, can be done in an automated fashion without a lot of rigmarole around cleanups, changing source data, changing business processes. We don’t have time for those things, my friend. So if you didn’t do it at COVID and you’ve been kind of for whatever reason, you haven’t been investing in coming up with these three sixty views and coming up with the idea of creating some notion of a master record.

If you haven’t been doing it, you need to do it. You need to do it. And I don’t Again, this this may this may sound like I’m the MDM hammer looking for MDM nails. I understand that.

I just have a hard time thinking that everything that I just talked about.

Right? Creating some holistic, reasonably accurate view of your relationships that matter the most.

Right? Your relationships from a product perspective. Who’s buying what from a customer perspective? Who’s buying what? When? How often?

Right? Do you have do you have specific business risk to individual customers who may be hit particularly hard by tariffs? That’s another thing.

Like maybe you are a b2b provider and you’re selling stuff to manufacturing companies.

Right? Do you know how much do you know what risk is associated to company a or company b?

How much business are you doing with this other manufacturing company that just happens to source eighty percent of its stuff from China?

If that’s the case, if you don’t know, then you’re driving blind. So, yeah, I I I know I know I’m I’m kinda sounding like I’m I’m selling MDM here. But again, this is evergreen. This is best practice.

These are things that we need to do. And we may, in doing what I just suggested over the last forty five minutes, we may step on a few toes. We may make some errors when it comes to governance decisions. We may cut some corners when it comes to data quality.

And yes, my friends, we may be required to own more of this on the IT side than we would be comfortable in otherwise owning.

We may, but it’s necessary. We need to move. We don’t have time to engage the business. We don’t have time to talk about changing our supplier onboarding processes.

We don’t have time to start changing our credit processes. We don’t have time for all that stuff. Will they help? Most certainly they will help.

But we don’t have time for that. Right now, what we need is accurate insights. That’s what we need.

More accurate, more confident, more consistent, more automated.

These are the insights that we need. If we don’t have them, we need to be talking about MDM. Forget the data catalog, forget Databricks, forget all of this old fancy other stuff over here. This is basic meat and potatoes, blocking and tackling data and analytics, a three sixty degree view. Data catalog, not gonna help you with this.

Just not. So, yes, I know I’m biased. Yes, I know that I’m pro MDM, but it makes sense.

With that, my friends, I hope you have gotten value out of this gotten. Is that a word? We like semantics, do we not?

I think gotten is a word. I’m going with it today. It’s a Friday afternoon. I’m gonna give myself a pass on gotten. I hope you have received some valuable insights here. Hey, take a minute to subscribe.

Take a minute to give it a thumbs up on the content. Would love it. We do this every two weeks, as I mentioned at the top. We haven’t missed a two week span yet.

I am here to help. My mission is to extend the tenure of chief data officers and to help others who want to be a CDO to become one. My job is to make your job as a data and analytics leader easier, and I hope that’s exactly what I’m doing. We will see you on another episode of the CDO Matters, and we’ll hear from you or you hear you will hear from me on another episode of CDO Matters sometime soon.

Thanks. All by for now.