Ep. 14 - Your Supply Chain Data Is A Hot Mess...But There's Hope

Justin Dillon: Welcome to the responsible supply chain show where we explore the world of responsible sourcing and resilient supply chains. I'm your host, Justin Dillon. And in each episode, we'll dive into real stories from some of the world's best business, government, and thought leaders protecting people, planet, and profits. Let's get it. Alright.

This is episode 14. Can't believe we got here. Four one 14. Arguably, the worst year of my life. That was my first year of high school.

I had recently moved back to California, Bay Area, San Francisco Bay Area from New Mexico where half my family is kinda pretty much cowboys. Was kind of formative years, grew up in the desert, then moved back 14 years old, freshman in high school coming in. I didn't know who I was, who does, but I had a speech impediment, had a lisp, and didn't really know how to dress. So I had like flannel shirts and a cowboy belt with a buckle on it. I think it was Miller, Miller High Life.

I mean, I would just, you know, I just did what I knew. Just went to school in the Bay Area in California and, you know, walked in with a lisp and with the champagne of beers around my waist and didn't go well. Did not go well. I'm hoping this episode will go much better than my fourteenth year. Things worked out, obviously.

Dropped the lisp, got a great speech therapist, and realized that beer belt buckles just weren't my jam. So I found my way out of it. It could be your it's look. People are bringing it back now. I mean, I kinda wish I had them still.

Go to a Post Malone concert and fit right in. More important, more pressing things, around responsible supply chains. Just a few days ago, Reuters reported that Qatar or Qatar, I can never pronounce that like you know what? I'm okay with with not being able to pronounce certain countries. I just can't get it.

So I'm just gonna let it go. But Qatar sent a letter threatening to divert LNG exports away from the European Union. For those of you who don't know, LNG is natural gas. They provide somewhere between 12 to 14% of the liquefied natural gas to the EU. And the reason for cutting this off is they just don't like where their supply chain due diligence law around human rights and climate is going, specifically the EU's Corporate Sustainability Due Diligence Directive, otherwise known as CSDDD, which is a law mandating that companies manage human rights, environmental risks throughout their supply chain, including a binding climate transition plan and Qatar said, yeah, no, we don't want to do that.

We're not really interested in in any kind of binding plan. We have no plan for net zero, even though probably look into that. It is the desert by 2050. Qatar is gonna be a little rough to live in, given the fact that all of their water is desalinated, which takes an enormous amount of energy. But nonetheless, what we're seeing is companies and countries taking advantage of the trade war to push back on supply chain due diligence laws.

The CSDDD has been having a heck of an MMA fight in EU for the last year. Who knows what it's going to be for those of you who follow it? It will be a a mere shadow of what it was intended to be. I kinda hold these things loosely. I look at the macro trends, what's really happening, not just around the, articulation of laws, but also just what's happening in the world around geopolitical and trade.

And I think the big takeaway we can take here is that ESG risks, human rights risks, geopolitical tensions, trade risks, tariff risks, they all kind of go together now. And we can't look at any of the things that we're dealing with through one lens. You need to be a little bit more adaptive and have a wider view of how some of these challenges are showing up. And look, people are gonna take advantage of a trade war. They're gonna take advantage of any opportunity they can to make life work better for them.

So we can't really sit in in any kind of judgment. We just need to be paying attention and moving the ball forward as best we can. On today's show, have Stephanie LaPierre, the founder and CEO of Tealbook. Tealbook is a leader in procurement technology, has been chosen by Spend Matters as one of their 50 vendors to know, A highly coveted supply chain thought leader, Stephanie, has been recognized as one of the top 100 most influential women in supply chain. That's no joke.

I am pleased to have Stephanie on the show today because she's talking about a problem that everyone listening to the show is dealing with in some way. That is supply chain data being such a hot mess that it's almost impossible to get any value out of it. Stephanie's here to help you, to soothe you, to inform you, to inspire you. Here's our interview. Stephanie, good to see you.

I haven't seen you in a long time. Thank you for coming on the Responsible Supply Chain Show.

Stephany Lapierre: Yeah. Thanks for having me. It's good to see you again.

Justin Dillon: For those who don't know who or what the awesomeness of Tealbook is, can you give a little bit of a quick origin story and a bit of your mission? Because I think your mission is quite compelling.

Stephany Lapierre: Yeah. So, I mean, the mission is to enable any organization to have clarity and visibility into who they do business with. And that comes from having clean data that can be leveraged across the organization. It doesn't matter the size, it doesn't matter the industry or the technology stack that's been implemented. Every company deserves to have better understanding of better ways to optimize their supplier base.

There's billions of dollars for most companies that go through the Source To Pay process, like billions of dollars. And that process has been really fragmented and disjointed between finance, procurement, supply chain, compliance, third party risk, ESG teams, even revenue teams in some cases, who all need good quality information on who the suppliers are. And shockingly, still today, the majority of organizations don't really have a clear baseline on who their suppliers are. And it's been Why?

Justin Dillon: What's that? Why is that problem?

Stephany Lapierre: It's amazing. I think that's one of the challenges I had when I raised capital in the early days, because people didn't believe this was an actual thing. You just assume that companies would have a really good handle on the business they do business with. And it's just not the case. And, when you take a company, the majority of our clients have anywhere from 5,000 to say 140,000, 150,000 suppliers globally.

It's a lot of relationships. And a lot of the owners of the relationships sit across different places around the organization. And so, there's one person or group of people that know more deeply what the suppliers may do and the circumstance in the context of the relationship, but it's not easily transferable. And they only know their relationship. They don't know all the other information about that supplier.

What else do they do? What other entities they may own? What are they certified for on things that may not be relevant to them, but may be highly relevant to the organization. So, you know, that's one thing is just the sheer amount of relationships and information about those relationships. And then there's a lot of change that happens.

Daily, there are changes around ownerships and capabilities and companies that go out of business and certificates that get expired. And so with all this change, it's really hard to maintain. And so traditionally, have implemented software as a way to say, Hey, I am company X. The suppliers are going to come to my intake process and they're going to put their information in my portal because they want to do business with my company. And the reality is that that's usually a function of a team that's implemented a software for a very specific use case, and then multiply that by all the different functions that implement their software to manage their use cases.

So there's an enormous amount of disparity in the intake process, and there's a lot of software that are not connected. So that's a high demand on suppliers, right, to come in and put information in a bunch of places times the number of customers. It's just not sustainable.

Justin Dillon: Yeah. So would you say Tealbook is aiming to be like a network or more of a data hydration?

Stephany Lapierre: I'd say, you know, in the past, we've always been a data company, and there was misunderstanding as we built and tried to commercialize the data where it was at with software to resolve specific use case. And so I think that the market was a bit confused as seeing us as niche solutions and having a bunch of niche solutions. Meanwhile-

Justin Dillon: I wouldn't know

Stephany Lapierre: anything But about at its core, it's always been about the data. In the past couple of years and even more now as we've unwind, being focused on niche problems and really focused on being data infrastructure. And if you compare data like a Databrick or Snowflake to a Workday or Salesforce, we're much more on the Snowflake Databricks than in Salesforce. We're really data infrastructure, but really, really specific to vendor data.

Justin Dillon: I've heard you say, you know, I actually think for such a difficult to explain problem, I think, I've heard you explain it well. And it's been fun to watch you over the years because it's become more and more clear. Maybe that's because you're explaining it better, or maybe that's because the problem is becoming more salient or more real, or both, which is ideal for a startup like yours. But I've heard you often say, use the term supply chain maturity. Could you just, for the listeners, explain how you define what supply chain maturity Sorry, supply data maturity, not supply chain maturity.

Supply data maturity. Can you explain that for the-

Stephany Lapierre: Yeah, so, I mean, what we find is that four level of maturity that we see in our customers. The most mature typically resides in highly regulated companies that operate globally. And because they're highly regulated, they had to become fairly good at understanding their supplier base. The second one would be one that I've identified that they need data. So they probably have implemented quite a few solutions, especially with AI right now.

There's a higher demand for high quality data. And so they would be looking at investing or they've started to invest in their data infrastructure. And then I'd say the third bucket would be the ones who have implemented now, multiple digital solutions and have still probably a bias towards workflow and dashboards. They may not have still come around to think that a lot of the dependency on those investments to be good is coming from having good quality data. And so they're still going to focus on software resolving this.

So we see companies have implemented SLP from Ariba and already may have had Aravo and may have had Apex Analytics and Hicks and all these different solutions, maybe are also jumping on the intake orchestration hype, but they're still resolving data with software. And then the fourth bucket, it's still the tactical team and usually less mature. It typically stemmed from leadership not investing necessarily as much in procurement or not really understanding how to leverage those investment to drive more value. We're letting those companies come along a little further before we would even interact with them. They would not know what to do with data.

Justin Dillon: I feel like in some ways, in the ways we try to describe our companies, we're trying to help people avert pain. But the pain isn't necessarily on them this second, this quarter. But for us, we're a risk management company. And what's risk management? It's like, well, something might happen, or you might see something.

And it's a tougher sell. It's like selling insurance, right? And do you find yourself having to educate customers on the pain of bad data? You're almost like educating them while you're also trying to create a transaction?

Stephany Lapierre: I think, as you said earlier in the conversation, the data problem is definitely more acute than it used to be. Back in the days, like when we used to talk about using AI to scrape data, scrape websites and database was like really scary for procurement. So that's now evolved. I do think COVID was a huge accelerator at understanding, sure, have spent analytics, it's a very small, and even spent analytics requires good data. And I'd say with AI and the demand for data quality, I think most procurement teams now would know the problem.

So they recognize the problem. It's sort of how to fix it. What's the solution and how to go about it?

Justin Dillon: Maybe you can share a little bit about, you know, maybe an example you've seen where immature supply data directly contributed to a disruption or a risk or a cost to the business?

Stephany Lapierre: I mean, so many, right? I mean, thinking about COVID, just the evolution of everything. I mean, there's always been disruption,

Justin Dillon: lack of visibility in supply chains, has that been something your customers have problems that your customers have brought

Stephany Lapierre: to you? Yes. Yeah, understanding where you have most exposure is really important. Where are your suppliers based? What's the biggest exposure?

How can you shift your supply chain if needed? And it's not easy, right? If you have suppliers that are meeting certain compliance requirements and took six months to onboard and suddenly you have to shift your supply chain. So having access to good data, one to understand your baseline and where you have the most exposed risk and then where to ship it to, and then be able to use that to also prepare some scenarios. And I think with tariffs specifically, it just kept changing.

So try to stay on top of what's happening.

Justin Dillon: Would you say, yeah, would you say to that end, because we've heard a few stories like that on our side as well, where it's not an I shouldn't say it's not important, but it's not needed until it's absolutely needed. Like, risk information we'll get our customers will tell us it's like, I needed it, and it was there, and I went in and, you know, did a, you know, a review with my boss or with our shareholders or whatever, and and the information was there. And it's almost like this, you don't need it 99% of the time, but that 1% of the time you need this information, it's a 100%

Stephany Lapierre: we talk a little bit differently about, like when we talk about the data foundation, it's less reactive. It's much more about when you're thinking about building, you're digitizing procurement and you're looking at how you build your technology stack, where does the data flow to and from is what we're talking about to customers. Then it identify where you have gaps. You're not getting the ROI that you expected on the investment of a certain system because of data quality issues. So all these regulatory requirements, which will not end, all the complexity, it'll just get more.

And so how prepared are you, right? And if you think software will prepare you or make you position us in a way that you're gonna be able to get in front of those disruptions, it's not gonna happen. And so it's definitely a shift in mentality versus like trying to resolve. But to your point, when someone, there's a huge migration happening and there's a failure in the implementation of this new system, or there's a regulatory demand that suddenly no one has the answer, it does at least raises the question. And then we can work back towards like, why is this happening?

We can resolve, you can give the answer, but let's talk about the root cause of the problems. You have no idea.

Justin Dillon: Well, yeah, speaking of moments in data foundation, we're certainly living in a moment around AI. And what a perfect time for a company like yours, because I've heard you say that AI needs clean fuel. And you've also said that AI is only as good as the data it learns from. So maybe you can share a little bit about how business has changed for you or how, in whatever way you wanna share, with this this demand on. Everyone's getting excited about AI, but the secret is your data's probably crap.

It's probably really bad. It's a bad it's very difficult to train your supply chain data on AI when you've done three M and As in the last five years and you've got 16 different systems. It's just gonna hallucinate. I mean, I'm answering your question for you, but I'd love to hear

Stephany Lapierre: what Well, it's you're interesting because we're an AI first company. We've been since '16, right? So we use AI. Been using AI to create digital profile of businesses. And when we completely replatform, which we've been doing for the past three years, this new architecture has a lot of AI embedded into it.

And so we leverage AI in the way that we've built our technology to make it more scalable, to make it faster, to get it smarter. So one example is we have an AI match playground that allows a vendor master to process and match the right legal entity. So that's getting better and better over time, and it makes it easier to match at a higher rate and match the right legal entity without using humans to do it. And so we're AI first, but it does play, right? Our clients are looking at leveraging these AI tools and there's a plethora coming from DPW, like every company sounds the same.

They're all kind of building either they're layering AI tools on top of their existing technology or they're AI native, right? They're building applications that are more niche. But when you can't match your vendor master to the right legal entity, and you're trying to pull data to enrich it or do something with it will create a lot of misinformation and it sounds great, but it's not real. And to have the confidence to put a tool like this in the hands of your sourcing team and then in the hands of your stakeholders, like you have to have confidence in your data.

Justin Dillon: Well, it makes sense how you're using AI to create value for customers. But I would imagine one step beyond that, correct me if I'm wrong, but the value that Tealbook brings in cleaning up and enhancing and hydrating their supplier data improves the customer's use of whatever AI they want to deploy across that to solve lots of different procurement, including risk problems like the ones that we solve and are the the people that are listening to this show, data data clean data is a big, big, big blocker to being able to comply with laws, to map supply chains, to understand who owns what and who's connected to what. And I would say it's had, for our customers, bad data has had a real cost, like literal cost, for instance, importers into The US who are doing business with sub suppliers they're not supposed to, but have no idea how to connect the dots. And that has material costs because their goods get detained at the border. And soon those similar goods will be detained at European borders.

So there just seems to be a real need in the market for clean databases. What's keeping companies from just cleaning their sock drawer when it comes to

Stephany Lapierre: data? I think it's the oversimplification, right? I've heard now from multiple procurement teams who have invested. One company implemented nine software, right? So they want to do this big digital transformation.

They assess all these software, the sourcing intake orchestration, blah, blah, blah, right? Analytics. And when I asked about data, they said, well, it's too messy. Like we're not gonna address this upfront. We're gonna implement and then we're gonna look into data.

And it's so backwards, right? Because you have the right data. One, you may not need all the software. You will need some software, but you may be able to consolidate. The other piece is that you shouldn't depend on the software for data, right?

You can have a more interchangeable ecosystem that's connected and the time to value, the compliance, the ROI of those systems that they've implemented would be so much better if they had this data foundation upfront.

Justin Dillon: Most companies don't know what they bought from a supply That for me, I think, you've been in supply chain a while. I guess I can't say I'm new to it, but I'm still blown away that there isn't, it's somewhere in the system you must have known if you bought a tractor or, you know, consulting service, but you can't tell me based on the vendor. Blows me away with that.

Stephany Lapierre: No. It's and then that's the problem is the information resides within people across global companies, right? And so actually it's when the first idea of Tailbook was twenty something years ago when I heard a client talk about this company she wanted me to meet and look into Binder to find their contact information. And I knew that the company was going through a huge consolidation exercise to reduce their supply base by 50%. Remember those days, like we're going to reduce our supply base by 50%.

They spend millions of dollars with Accenture and they're doing it based on spend and risk profiling with no data to understand like who's actually creating value, what are we buying, how many companies are we buying the same things from that could be consolidated. And that's where I was like, that's crazy to me that the information that this person had in her head about this one company that reside in her binder was absolutely unattainable by anybody else in the company. And corporate was making this big decision to cut the supply base by 50%, which would impact this amazing company she wanted me to meet because they would never have that information.

Justin Dillon: You think Maybe we can talk a little bit more positive about the opportunities. I

Stephany Lapierre: think it's an amazing opportunity. So, I mean, my view at least is that it's fine. I was thinking about writing something about this today because we were seeing more and more finance folks coming into our calls that are building spend data lakes. And I'm thinking, is procurement missing the opportunity right now to own this Because they can't own this. This is something that they can own and they can enable.

Absolutely. And it can help them, one within procurement function, get access to good data and make better decision, build better category strategy, expedite decision, all of that. But they can also become, and that's actually Kraft Heinz was speaking with us on August 6, is talking about how she and her team are taking ownership of the data and are working now collaboratively with supply chain, compliance, third party risk, and finance, because they're taking ownership. And they partnered with Kraft Heinz corporate data team, and together, they're building a data foundation to take ownership of the, and I think it's an amazing opportunity for procurement to do this.

Justin Dillon: Do you see that companies building supply data maturity or supply chain data maturity investing in that? Do you see opportunities and advantages for them competitively in the future? And if so, what does that look like?

Stephany Lapierre: Well, I love the idea of like, what if your data was really good? Like, what if the supplier base that you do business with was one of your biggest competitive edge? Right? And people that need to make decisions every day would be enabled to make decisions. The investment you've made in technology was actually materializing the outcome that you invested in technology.

And imagine the power of a company be able to optimize that investment. We're talking billions of dollars in opportunities, right? That's right now hidden.

Justin Dillon: Oh, it's savings or competitive edge, primarily Oh,

Stephany Lapierre: right, savings, able to capitalize on partnering with suppliers to generate revenues, mitigating risks that would be blockers everywhere in the organization, small risk, bigger risk, be able to diversify your supply chain really fast to ensure business continuity, give yourself a competitive edge by understanding your supply base and how it relates to your consumers or your shareholders. There's so many ways to leverage your supplier base. Even in the company, we're hearing all these major Apollo data lakes and data infrastructure, but vendor data is not usually prioritized. Customer data is. All the data in the company is.

But vendor data is not the biggest priority. And it's always mind boggled me as to why it's not one of the biggest investment because it is, you know, the only way you can improve your margin is to reduce your costs, right, and grow more efficiently. And by reducing your costs, it's either people or your spend. And so just that basic, you know, metrics of having better, healthier margins for the market. You know, if there

Justin Dillon: was one. Yeah, I agree. And it's and I know it's it's hard for companies to get their head around investing in a cost center, but it's about reducing the cost in a cost center. It just seems like that's such low hanging fruit and just easy, quick wins. Wins you can start to see in quarters, not If there was one misunderstanding around supply chain data maturity that you wish you could fix today by waving a wand, what would that be?

Stephany Lapierre: Just don't do it. Like, there's so many ways you can tackle this problem. But there's a lot of companies who have failed over and over again or built very expensive workaround. There's a chance to avoid that now. You don't have to do that.

So there's a way you don't have to spend a roadmap of four years to get there. The technologies have advanced so much and the solutions have been built, not just by us, but customers working with us directly in solving this problem for the market. And so that would be my advice is like, yes, think about obviously how you want to solve it and what it means for you to have a strong data foundation. But just don't do it a way that's going to be more expensive and take years because it shouldn't have to take years anymore. Should be a pretty fast win.

Justin Dillon: Most of the people that are listening to this work in the risk side or responsibility side of supply chains, working on ESG, trade, tariff, human rights. What type of advice would you give them in their job today that's going to help them in their you know, it's going to benefit them and their company in the

Stephany Lapierre: last Well, so again, it's very biased, but I do think having a clean baseline of your supplier base and automate as much of the data that you can attach to that entity as much as you can, because there's always going to be some work that's going to be done manually. Like there's some things you need to collect or you need humans on the ground, like auditing a cotton farm. Just going to be companies that are going to be really niche, but you don't have to buy a niche solution for every problem you're solving or every certificate you need to collect or every possible risk. Just depending on suppliers to give you information and third party risk management program won't do it, it will not satisfy all the demands. So try to automate as much as you can.

And then in the intake process, if the information is mostly automated and then you need to supplement, it removes a huge burden on the suppliers and on your team to be able to fill it and be able to make sure that the data is accurate and be able to report it with confidence. And so the more you're centralizing some of that process and then you're adding on, it'll just make it a lot easier. And over time, you can continue to automate. It will never be 100%. But even if you could automate 20%, 40%, 60%, it's so much better and faster, and it's going to relieve a lot of your employees to do more strategic things and drive impact versus being the menu of sharing data.

Justin Dillon: One of the things that I have I try to teach my son as he's a teenager and kind of thinking about the future is, you know, I try to encourage him to think about becoming great at one thing and being the greatest in that thing, whatever that niche thing is. And you have clearly you are the OG greatest voice and knowledge that I know about supply chain data maturity. You have just owned that niche. I point everyone to you. Our audience is so fortunate to get to listen to you.

If anyone wants to learn more from you or contact you, we're

Stephany Lapierre: really It's obviously steelbook.com has a lot of information. We're very active on LinkedIn, and please connect with me personally on LinkedIn, Stephanie Woodawaii. Good. And I'm always happy to have a good conversation.

Justin Dillon: Perfect.

Stephany Lapierre: Thanks for coming. Thanks so for having me.

Justin Dillon: This is The One Thing, the part of our show where we dig into one idea from interview. Stephanie's mission has been to organize and enhance supply chain data. It's impossible to miss her passion and knowledge on the subject, a subject that she has campaigned for for over a decade. Anyone who builds anything as great as Tealbook starts off with an idea and recognizes that that idea might not be understood for a very long time. It seems that Stephanie's idea to clean up the world's supply chain data is now relevant.

As she mentioned, software and AI don't work without clean data. But cleaning it up often gets deprioritized for the tyranny of the urgent. Let's be honest, we all procrastinate projects that don't feel urgent, or most likely to benefit us in the near term. The definition of procrastination is the voluntary delay of an intended course of action despite expecting to be worse off for the delay. Ouch.

Harvard Business Review published an article in 2022 called Stop Procrastinating and Tackle That Big Project. In it, it states that procrastination of starting big projects comes from three core drivers. One, a lack of effective habits or systems, which makes it really, really hard to begin. Two, avoidance of uncomfortable emotions like anxiety or boredom. Meaning, once I start this project, I'm gonna see how big it is and how difficult it is, that's gonna make me anxious and then eventually bored.

Raise your hand if that's you. Three, cognitive distortions that amplify task difficulty making it seem overwhelming. This is the catastrophizing of projects that we just don't want to get started. In order to break through this type of resistance and begin, the writers of the article offer three ideas. Start small.

Start with the easiest, lowest friction task, a basic step that you know you can get done and gradually build momentum. Two, create rewards for competing tedious and anxiety inducing tasks. And three, leverage routines like setting a week a month to focus on data transformation. In my experience, the greatest contributor to procrastination is talking or planning over doing. Creating working groups, hiring a consultant, approving a budget, building a quote unquote, air quotes, strategic plan is just that.

It's a plan. Plans are not action. If you want to be great at whatever you do, then you need to learn to do the hard and boring stuff first and I know you've heard this before. Getting a handle on supply chain data management is boring and thankless at first, but it's sure to pay dividends in the long run. Thank you so much for listening.

Please be sure to subscribe. And if this show is providing any valuable information to you at all, please give us five stars, not four, five. Just rack them up so that others can find us. Thank you so much.

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