WEBVTT
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00:00:07.839For real stories on how global business gets done.
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00:00:14.480This is Supply Chain Unfiltered, presented by the Institute for Supply Management.
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00:00:20.160Hi, so glad you decided to join in today.
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00:00:26.879I'm Melanie Stern for ISM and Supply Chain Unfiltered, and today's episode is Everything Data.
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00:00:38.159Our guest today, she's constructed a new way of looking at data, how we perceive it, how we can put it to use, and at the same time monetize it.
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00:00:40.320So let's uh introduce Dr.
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00:00:41.600Charlotte de Brabant.
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00:00:49.119She is an expert in procurement, digital transformation, and AI-driven sustainability.
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00:00:59.759And she has developed a Kamar de Brabant AI data economy model, and it's shaping a new way companies can understand and monetize data.
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00:01:00.640Hi, Charlotte.
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00:01:01.679Thanks for being here.
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00:01:03.039Hi, Melanie.
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00:01:07.519Thank you for having me, and also thank you for this wonderful introduction.
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00:01:11.599There's so many, so many great things to share about you.
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00:01:22.400But first, um I'd like you, if if you would, give us kind of a high-level overview of what your um economy model is all about.
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00:01:24.400Absolutely.
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00:01:36.159So the the model that my colleague and I um designed, I would say it takes this holistic view of data's role in our modern economy.
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00:01:42.719And especially as procurement and supply chain professionals, we data is king, right?
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00:01:47.599Without data, our negotiations wouldn't lead to anywhere.
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00:02:04.640And understanding data, but I think especially over the last months, literally data has evolved with all of this generative AI and and data being so easily accessible um all around us.
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00:02:11.439That's how we created uh exactly the Kuma de Brabant um AI uh data economy model.
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00:02:31.599And it it traces at the end um the whole data's evolution from uh the early electronic processing devices that we had in the 50s uh to you know to literally today's AI-driven landscape.
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00:02:42.319And the model is actually it sounds a little complicated, but it's really simple because it's it's built literally on four key frameworks.
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00:03:28.080We have um framework number one, um that's uh 4G generative AI, then we have um so generative AI driving AI's um creative and analytical capabilities, and then we have uh 4E ethical AI, ensuring um responsible and sustainable AI practices, and then we have 4M, um there which is then the monetization part, so structuring economic value from data, and then 4C, so that's the whole democratization, enabling access to data and and fostering all this um collaboration with with all the stakeholders.
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00:03:50.080And by combining these frameworks, we can then create a um like a balanced ecosystem within our procurement supply chain organization, I believe, where data is not just an asset, but also a force for decisions, for innovations, and um and more to come.
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00:03:58.560This day, this model, it's not it's not just for for frameworks because it's constantly evolving, constantly building.
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00:04:02.560So it's just a little introduction for you.
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00:04:03.360Thank you.
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00:04:17.920And I I have to I have to um share that um when you and I originally spoke about you know doing this episode, and I you know, I'm seeing the phrase uh data monetization, you know, my ears perked up like, you know, oh what's that?
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00:04:26.240Um so I could you share with us a little bit more about how companies can make money from the data that they have?
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00:04:28.480Yeah, absolutely.
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00:04:34.319Um I think they are simply speaking, two main approaches.
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00:04:36.639Um when we look at this topic.
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00:04:40.480We have direct and indirect monetization.
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00:04:48.240So direct monetization, it means companies sell or um even license data.
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00:05:14.720So, for example, on social media platforms, um, for example, selling anonymized uh user data for advertising insights, or we have indirect monetization, and it's when companies use data uh to optimize internal processes, very important, or improve uh customer experience, or um even when creating new products.
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00:05:25.279Um, like I, you know, I used to work at Amazon not so long ago, and for example, how Amazon personalizes recommendations using purchase history.
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00:05:38.800So the key is actually finding the right balance between um financial gain and ethical responsibility, and that's really where our model helps companies um to make informed decisions.
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00:05:42.480I I want to share something real quick.
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00:05:53.360I I ran across something, I think it was yesterday or the day before, um, where Google had announced that they are changing the way um searches will be engaged.
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00:06:01.839And they stated that they're gonna have a one, you know, an AI agent only communicate with another AI agent.
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00:06:05.680They're removing human interaction completely.
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00:06:08.639And I I just thought, wow, that was fast.
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00:06:11.040You know, it's all happening so fast.
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00:06:13.439I mean, it's all happening so fast, Melanie.
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00:06:15.279It's crazy.
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00:06:17.839That's why we're having this podcast, yeah.
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00:06:21.360Because we really should not underestimate data.
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00:06:32.879Before they when we when we in procurement thought about data, when I started my procurement career, you know, 17 years ago, it's kind of finance department, finance, finance.
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00:06:35.920But actually, no, it's it's really it's us now.
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00:06:37.439It's everything.
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00:06:38.079Yeah.
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00:06:39.360It's everything.
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00:06:54.639So so um, being that everything is transforming so so quickly, um how how would you say that that AI really fits into the data monetization equation?
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00:06:56.319How do we distill that down?
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00:06:57.680Okay.
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00:07:07.120Um thank you for that because I I I do like this question because AI really enhances our data value.
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00:07:22.720And I think the way it it changes the value is through automation, so um AI-driven systems, right, that analyze massive data sets faster and more efficiently.
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00:07:32.079And I mean, we have so many expert vendors out there right now, especially in procurement and IT procurement, IT sourcing.
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00:07:46.879So many of these vendors that are really experts when it comes to AI-driven systems, analyzing all these massive data sets and helping us as procurement individuals then just get one created automated dashboard.
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00:07:50.000And um lows happening there.
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00:07:53.439But secondly, also predictive insights.
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00:08:04.160So we have companies uh currently vendors, many vendors, they use AI to forecast trends from customer behavior to supply chain risks.
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00:08:06.959And I have a very good friend working in that field.
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00:08:14.160He had literally created a company for us procurement professionals on uh predictive procurement.
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00:08:23.040So for the ones listening, I'm not going to make any advertisements here, but I think many people will smile because many would know the company.
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00:08:26.800Okay, and then number three, um, personalization.
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00:08:35.759So AI-tailored uh user experiences and making data-driven businesses a lot more competitive.
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00:08:52.080Uh, but I do want to add, Melanie, that we need to be a little cautious because AI uh can be also biased or misused if we just don't apply it um according to ethical standards.
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00:09:04.000And that's why having the um the whole 4E framework for ethical AI is is then critical to balance all of this.
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00:09:05.919Yeah, we have to be mindful.
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00:09:17.200Um but it's hard, it's hard to want like want to take the time to be mindful and take that pause because the innovation's happening so fast and you know you don't want to lose that competitive edge, right?
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00:09:21.600So it's it's an interesting, interesting to try to find the right balance.
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00:09:24.000So you mentioned trends in AI.
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00:09:38.639Um excuse me, is there anything in particular that you think businesses should be watching for as far as the trends, either what's current or what you feel is coming in the near term?
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00:09:42.000Uh yes, absolutely.
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00:09:51.279Um when it comes to to trends, we we need to take into account um decentralization.
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00:10:03.679So uh data mesh is is changing how companies structure data and moving away from centralized uh data warehouses.
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00:10:04.960Oh, okay.
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00:10:10.799Also, another trend is AI-powered decision making.
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00:10:29.440So um, you know, we have so many tools right now where AI is helping us to create these dashboards and and as I explained earlier, you know, taking this large quantity and and through AI making helping us to make these decisions.
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00:10:38.080So more businesses are actually relying on AI for these real-time business insights.
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00:10:58.399And then number three, sustainability in uh in AI as another uh trend where companies are using AI to reduce the carbon footprint and optimize um energy usage and and support environmental efforts as good as they can.
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00:11:03.600So um I know many companies you know are going back and forth.
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00:11:06.559What are what standards should they use?
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00:11:15.039Um, but I think we are just entering an era where data is not just power, but it's responsibility.
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00:11:19.600And it's up to us to decide how to best proceed.
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00:11:39.279And I I want to um kind of step back into something you mentioned earlier, you know, um security, ethical standards, and I know a big concern for many of us, you know, on the consumer level and um within uh the business environments is data privacy.
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00:11:53.759And do you think it's possible for us to really achieve that balance between data monetization while we are able to maintain consumer trust as far as data use?
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00:12:04.799Yeah, uh that that is that is a very good point, especially remaining uh the the consumer trust.
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00:12:20.879And um, and that's why I do believe that as a company or a procurement or supply chain individual, I think transparency is key here when you speak with your vendors or with your stakeholders.
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00:12:34.480Um, I think businesses they must continuously, consistently, um, clearly communicate what data they collect, how they use it, how they protect it.
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00:12:52.960Um, and I know that I'm also going through so many audits, um, not driven by my company, but are literally getting audited also by other vendors, where they are reaching out and asking me, how are they protected, how are we using it?
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00:12:57.200So it's really a it's interesting, it's it's kind of a new trend I'm seeing.
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00:13:00.159Um so they're asking the right questions, which is great.
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00:13:01.679Yes, absolutely.
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00:13:02.879Like literally.
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00:13:13.759It's uh it's and it seems to be the new norm that uh companies, or the larger ones at least, are actually coming and asking those questions.
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00:13:24.480So uh regulations like um GDPR and CCPA, um, they do influence uh the whole data protection.
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00:13:39.919But companies they need to go, I think, just beyond compliance, and they should embed privacy into their culture and AI ethic uh panels and secure data sharing agreements.
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00:13:41.600Um, these are all the great steps.
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00:13:51.919And I'm literally having vendors asking for these uh agreements, and it's unbelievable to what depth I'm being questioned.
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00:14:12.879And I'm I'm wondering too, like when you're getting these questions, um or or maybe not you directly, but what you've heard um within the industry, do the questions kind of differ depending on what um where geographically speaking a company is coming from?
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00:14:15.120Oh, that's such a good question.
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00:14:22.799Yeah, I just I'm like as as you're talking, it's like I'm like, well, wait a minute, or do we all have the same concerns or is it different?
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00:14:24.639I love this question.
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00:14:41.679Um, and I have to say that I would say before, if you would have asked me that four years ago or five or a bit longer when GDPR got introduced, I think then it would have been different because GDPR was first pushed by Europe.
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00:14:48.639But now we really have these global trends, and I am getting okay, a lot still in Europe.
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00:14:57.759So I think I don't want to make any conclusion here, but I do think it it's it's maybe a bit more stricter regulated in Europe.
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00:14:59.120And then that's surprising.
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00:15:22.559Yes, but I I do see this trend, but these companies are also global companies, so we need to keep in mind that they um I'm sure they will somehow communicate it then to their head office in the US or not really Asia, but I think it's it's a lot driven in Europe for these questions.
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00:15:25.039It's it's a really interesting trend I'm I'm seeing.
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00:15:30.639So I want to I kind of coming on the heels of that, I'm wondering too.
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00:15:54.639So when we look at what ethical standards would be in our use of AI and um integrating it into our data practices, do you think um are you seeing maybe by the questions you're being asked, or just a feeling in general, a consensus across um, I'll say the supply management profession?
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00:16:00.879Do you think these businesses are becoming more ethical with their data practices?
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00:16:05.120And is is there differences in that based on geography?
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00:16:14.080Yeah, so I do see businesses becoming more ethical, um, but there is still a lot of a lot of work to do.
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00:16:22.639So companies are, I think, waking up um to the fact that uh trust equals to value.
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00:16:26.639And if consumers don't trust a brand, then they won't share the data.
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00:16:27.200True.
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00:16:49.120Um, and one exciting innovation is like the uh data marketplaces where companies buy and sell data ethically, and these platforms, um, for example, they use uh blockchain for transparency uh or to ensure um all these secure um traceable transactions.
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00:16:51.679So that's just one example.
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00:17:07.279But um, but in terms of to make it more ethical, and now you asked about geography, I think just because it's still kind of at beginning stages where companies are creating this awareness, um, it is it is too early to determine.
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00:17:07.839Okay.
00:17:08.079 -->
00:17:14.880But I would predict, yes, it would differ from geography, just because globally we have different ethical standards.
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00:17:15.920Exactly.
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00:17:25.920Yeah, and that's always that's always an interesting conversation just to see how we look at things differently from business perspectives, just based on where you do business.
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00:17:32.559Melanie, I would have the best podcast partner for you in mind if you ever want to do another one on that.
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00:17:43.759Oh, yeah, I think it's uh a subject that none of us get tired of just because it's always it's like it's a topic that massages the brain constantly.
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00:17:53.200Because just when you think you have, you know, you're set with the one perspective you have, someone will share something else with you, and you'll just then your mind will open up even more.
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00:17:56.640And so, yes, we should talk about that at some point.
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00:18:14.640Um so if if we can pivot this conversation to um, let's say the leaders, leaders in the profession and other professionals that are navigating this AI-driven data economy, and you know, that's that's here to stay, right?
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00:18:20.960So, Charlotte, what what's the advice you would want to share with them on how to get through this?
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00:18:33.279How to be more um not just accepting of it, but um fully embrace it and uh be comfortable with the change that is going to continue.
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00:18:42.000Um well, I have I would say maybe a couple of tips I could share to my fellow colleagues.
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00:18:42.480Okay.
00:18:42.720 -->
00:18:52.640Um definitely staying adaptable because technology is just evolving so rapidly, and leaders they need to be open to change.
00:18:52.799 -->
00:18:58.000At this stage, we cannot even, it's not even a wish anymore, a wish list.
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00:18:59.759It is really a must.
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00:19:28.480We need to be open and also invest into digital literacy, um, you know, with continuous learning and um understanding how we can somehow increase our knowledge for digital literacy, whether you're in procurement or supply chain, but understanding data is a must, you know, and we cannot just rely on finance how we used to.
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00:19:32.559We are the owners of the new AI-driven data.
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00:19:46.640And we can, of course, benefit from automated dashboards, but I think uh that's where our profession has evolved somehow, um, being a lot more data-driven as procurement professionals.
00:19:46.960 -->
00:19:51.119But also, I'd like to add uh thinking long term.
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00:20:00.880So data is is more than just a revenue stream, it's I think an opportunity actually to create impact.
00:20:01.359 -->
00:20:12.640And businesses that then prioritize sustainability, as we talked about, and ethics today, um, they will actually be the industry leaders of tomorrow.
00:20:12.880 -->
00:20:25.920And then looking at it, you know, from this different international um cultural point of view, especially in ethics, there's still, of course, a lot to do in that way.
00:20:26.079 -->
00:20:37.039So thinking longs long-term, preparing uh for long-term goals, but right now for the short term, invest into digital literacy.
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00:20:39.119Interesting.
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00:20:56.000I I know I I feel like it wasn't too long ago where there were discussions um, you know, about young, you know, talking to young professionals and where they want to kind of pivot their skill sets to make themselves more marketable uh in the job market.
00:20:56.559 -->
00:21:07.440And um it seemed as though like people could specialize in in data and data analytics and um how to maximize its use.
00:21:07.599 -->
00:21:15.359Where now it almost seems as though everybody needs to kind of get comfortable using this.
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00:21:19.279Are you finding that that that shift?
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00:21:20.720Absolutely.
00:21:20.960 -->
00:21:23.680It's um it's scary, you know.
00:21:23.759 -->
00:21:38.799It's scary how quickly we have to be uh uh open-minded, and it's really an eye-opener how how data is evolving so quickly, and how quickly we as leaders need to evolve.
00:21:39.039 -->
00:21:46.400And I I see this I see this massive shift, especially then on the impact of our profession.
00:21:47.119 -->
00:21:50.000And that's why we shouldn't underestimate data.
00:21:50.720 -->
00:21:52.000This is true.
00:21:52.400 -->
00:21:53.119This is true.
00:21:53.279 -->
00:21:57.200I I say that to myself every time I get an email that surprises me.
00:21:57.440 -->
00:22:02.640Um anyway, no, I This has been really interesting.
00:22:02.880 -->
00:22:31.519And every time we talk about your data economy model, the AI data economy model, I I get a better understanding of what you're sharing and just a better idea of the magnitude of all of this and how lucky are we that we are here and now watching it all unfold and being part of it and able to make a our own impression on it.
00:22:32.000 -->
00:22:34.559It's just, it's um, it's really cool.
00:22:34.640 -->
00:22:36.480That's not there's no other way for me to say it.
00:22:36.559 -->
00:22:37.920I just think it's really cool.
00:22:38.160 -->
00:22:47.039Um, Charlotte, for anyone that wants to kind of learn more and you know, kind of pick your brain a little more, um, what way should they contact you?
00:22:47.839 -->
00:22:58.240Well, I'd be happy to answer any questions either via my website, that's CharlotteDebraban.com, or you can also find me on LinkedIn.
00:22:58.559 -->
00:23:01.279And I think I'm quite good at replying to the messages.
00:23:01.359 -->
00:23:03.200So don't hesitate, just reach out.
00:23:03.599 -->
00:23:04.160Wonderful.
00:23:04.400 -->
00:23:04.799Thank you.
00:23:04.960 -->
00:23:06.160Thank you so much for being here.
00:23:06.319 -->
00:23:07.279Always a pleasure.
00:23:07.759 -->
00:23:15.119And and, you know, kind of uh talking about uh getting more knowledgeable on data and how to use it to your benefit.
00:23:15.279 -->
00:23:21.200You know, that's one skill that we all could, you know, get a little bit more savvy on.
00:23:21.440 -->
00:23:33.039But just in general, it's a great time to upskill yourself, your teams, boost your knowledge, and you can do it by enrolling in any of ISM certification courses.
00:23:33.200 -->
00:23:39.440They've got training programs, or check out their corporate capability models and assessments.
00:23:39.599 -->
00:23:45.920They're um they're really thought provoking and um very, very beneficial.
00:23:46.079 -->
00:23:50.640You can find it all and so much more always at ismworld.org.
00:23:50.799 -->
00:23:52.079Thanks so much for being here.
00:23:52.240 -->
00:23:53.519Love having you with us always.
00:23:53.599 -->
00:23:56.000I'm Melanie Stern for ISM.
