June 10, 2026 • 24 mins
Data is quietly becoming the most negotiable asset in business and the easiest one to misuse. We sit down with Charlotte de Brabandt, Ph.D., an expert in procurement, digital transformation, and AI-driven sustainability, to make sense of what it means to treat data like an economic engine rather than a pile of reports.
We walk through Charlotte’s AI data economy model and the four forces it balances: 4G generative AI, 4E ethical AI, 4M monetization, and 4C democratization. From there, we get concrete about data monetization in two practical lanes. Direct monetization is selling or licensing data (often anonymized). Indirect monetization is using data to improve performance: tighter internal processes, smarter sourcing decisions, better customer experiences, and new products that are built on real behavior signals.
AI is the accelerant and the risk. We dig into how AI raises data value through automation, predictive insights, and personalization, while also creating new problems like bias and unclear accountability. We also cover trends procurement and supply chain teams should watch right now, including data mesh and decentralization, AI-powered decision making, and sustainability in AI. Finally, we take on data privacy and consumer trust, the influence of GDPR and CCPA, and why transparency with vendors and stakeholders is becoming the new normal.
If you want a clearer, more realistic playbook for competing in an AI-driven data economy, listen now, then subscribe, share the episode with a colleague, and leave a review.
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SPEAKER_00 (00:04):
For real stories on how global business gets done.
This is Supply Chain Unfiltered,presented by the Institute for
Supply Management.
SPEAKER_01 (00:17):
Hi, so glad you decided to join in today.
I'm Melanie Stern for ISM andSupply Chain Unfiltered, and
today's episode is EverythingData.
Our guest today, she'sconstructed a new way of looking
at data, how we perceive it, howwe can put it to use, and at the
same time monetize it.
(00:38):
So let's uh introduce Dr.
Charlotte de Brabant.
She is an expert in procurement,digital transformation, and
AI-driven sustainability.
And she has developed a Kamar deBrabant AI data economy model,
and it's shaping a new waycompanies can understand and
(00:58):
monetize data.
Hi, Charlotte.
Thanks for being here.
SPEAKER_02 (01:02):
Hi, Melanie.
Thank you for having me, andalso thank you for this
wonderful introduction.
SPEAKER_01 (01:08):
There's so many, so many great things to share about
you.
But first, um I'd like you, ifif you would, give us kind of a
high-level overview of what yourum economy model is all about.
SPEAKER_02 (01:23):
Absolutely.
So the the model that mycolleague and I um designed, I
would say it takes this holisticview of data's role in our
modern economy.
And especially as procurementand supply chain professionals,
we data is king, right?
(01:43):
Without data, our negotiationswouldn't lead to anywhere.
And understanding data, but Ithink especially over the last
months, literally data hasevolved with all of this
generative AI and and data beingso easily accessible um all
(02:03):
around us.
That's how we created uh exactlythe Kuma de Brabant um AI uh
data economy model.
And it it traces at the end umthe whole data's evolution from
uh the early electronicprocessing devices that we had
(02:24):
in the 50s uh to you know toliterally today's AI-driven
landscape.
And the model is actually itsounds a little complicated, but
it's really simple because it'sit's built literally on four key
frameworks.
We have um framework number one,um that's uh 4G generative AI,
(02:51):
then we have um so generative AIdriving AI's um creative and
analytical capabilities, andthen we have uh 4E ethical AI,
ensuring um responsible andsustainable AI practices, and
then we have 4M, um there whichis then the monetization part,
(03:13):
so structuring economic valuefrom data, and then 4C, so
that's the wholedemocratization, enabling access
to data and and fostering allthis um collaboration with with
all the stakeholders.
And by combining theseframeworks, we can then create a
um like a balanced ecosystemwithin our procurement supply
(03:37):
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.
This day, this model, it's notit's not just for for frameworks
because it's constantlyevolving, constantly building.
(03:59):
So it's just a littleintroduction for you.
SPEAKER_01 (04:02):
Thank you.
And I I have to I have to umshare that um when you and I
originally spoke about you knowdoing this episode, and I you
know, I'm seeing the phrase uhdata monetization, you know, my
ears perked up like, you know,oh what's that?
Um so I could you share with usa little bit more about how
companies can make money fromthe data that they have?
SPEAKER_02 (04:27):
Yeah, absolutely.
Um I think they are simplyspeaking, two main approaches.
Um when we look at this topic.
We have direct and indirectmonetization.
So direct monetization, it meanscompanies sell or um even
license data.
(04:48):
So, for example, on social mediaplatforms, um, for example,
selling anonymized uh user datafor advertising insights, or we
have indirect monetization, andit's when companies use data uh
to optimize internal processes,very important, or improve uh
(05:09):
customer experience, or um evenwhen creating new products.
Um, like I, you know, I used towork at Amazon not so long ago,
and for example, how Amazonpersonalizes recommendations
using purchase history.
So the key is actually findingthe right balance between um
(05:30):
financial gain and ethicalresponsibility, and that's
really where our model helpscompanies um to make informed
decisions.
SPEAKER_01 (05:40):
I I want to share something real quick.
I I ran across something, Ithink it was yesterday or the
day before, um, where Google hadannounced that they are changing
the way um searches will beengaged.
And they stated that they'regonna have a one, you know, an
AI agent only communicate withanother AI agent.
(06:01):
They're removing humaninteraction completely.
And I I just thought, wow, thatwas fast.
You know, it's all happening sofast.
SPEAKER_02 (06:11):
I mean, it's all happening so fast, Melanie.
SPEAKER_01 (06:14):
It's crazy.
SPEAKER_02 (06:15):
That's why we're having this podcast, yeah.
Because we really should notunderestimate data.
Before they when we when we inprocurement thought about data,
when I started my procurementcareer, you know, 17 years ago,
it's kind of finance department,finance, finance.
But actually, no, it's it'sreally it's us now.
SPEAKER_01 (06:36):
It's everything.
Yeah.
It's everything.
So so um, being that everythingis transforming so so quickly,
um how how would you say thatthat AI really fits into the
data monetization equation?
How do we distill that down?
SPEAKER_02 (06:57):
Okay.
Um thank you for that because II I do like this question
because AI really enhances ourdata value.
And I think the way it itchanges the value is through
automation, so um AI-drivensystems, right, that analyze
(07:19):
massive data sets faster andmore efficiently.
And I mean, we have so manyexpert vendors out there right
now, especially in procurementand IT procurement, IT sourcing.
So many of these vendors thatare really experts when it comes
to AI-driven systems, analyzingall these massive data sets and
(07:40):
helping us as procurementindividuals then just get one
created automated dashboard.
And um lows happening there.
But secondly, also predictiveinsights.
So we have companies uhcurrently vendors, many vendors,
they use AI to forecast trendsfrom customer behavior to supply
(08:03):
chain risks.
And I have a very good friendworking in that field.
He had literally created acompany for us procurement
professionals on uh predictiveprocurement.
So for the ones listening, I'mnot going to make any
advertisements here, but I thinkmany people will smile because
many would know the company.
Okay, and then number three, um,personalization.
(08:26):
So AI-tailored uh userexperiences and making
data-driven businesses a lotmore competitive.
Uh, but I do want to add,Melanie, that we need to be a
little cautious because AI uhcan be also biased or misused if
(08:47):
we just don't apply it umaccording to ethical standards.
And that's why having the um thewhole 4E framework for ethical
AI is is then critical tobalance all of this.
SPEAKER_01 (09:04):
Yeah, we have to be mindful.
Um but it's hard, it's hard towant like want to take the time
to be mindful and take thatpause because the innovation's
happening so fast and you knowyou don't want to lose that
competitive edge, right?
So it's it's an interesting,interesting to try to find the
right balance.
So you mentioned trends in AI.
(09:24):
Um excuse me, is there anythingin particular that you think
businesses should be watchingfor as far as the trends, either
what's current or what you feelis coming in the near term?
SPEAKER_02 (09:39):
Uh yes, absolutely.
Um when it comes to to trends,we we need to take into account
um decentralization.
So uh data mesh is is changinghow companies structure data and
moving away from centralized uhdata warehouses.
(10:04):
Oh, okay.
Also, another trend isAI-powered decision making.
So um, you know, we have so manytools right now where AI is
helping us to create thesedashboards and and as I
explained earlier, you know,taking this large quantity and
(10:25):
and through AI making helping usto make these decisions.
So more businesses are actuallyrelying on AI for these
real-time business insights.
And then number three,sustainability in uh in AI as
another uh trend where companiesare using AI to reduce the
(10:49):
carbon footprint and optimize umenergy usage and and support
environmental efforts as good asthey can.
So um I know many companies youknow are going back and forth.
What are what standards shouldthey use?
Um, but I think we are justentering an era where data is
(11:12):
not just power, but it'sresponsibility.
And it's up to us to decide howto best proceed.
SPEAKER_01 (11:20):
And 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 formany of us, you know, on the
consumer level and um within uhthe business environments is
data privacy.
And do you think it's possiblefor us to really achieve that
(11:44):
balance between datamonetization while we are able
to maintain consumer trust asfar as data use?
SPEAKER_02 (11:55):
Yeah, uh that that is that is a very good point,
especially remaining uh the theconsumer trust.
And um, and that's why I dobelieve that as a company or a
procurement or supply chainindividual, I think transparency
(12:15):
is key here when you speak withyour vendors or with your
stakeholders.
Um, I think businesses they mustcontinuously, consistently, um,
clearly communicate what datathey collect, how they use it,
how they protect it.
Um, and I know that I'm alsogoing through so many audits,
(12:40):
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 theyprotected, how are we using it?
So it's really a it'sinteresting, it's it's kind of a
new trend I'm seeing.
SPEAKER_01 (12:57):
Um so they're asking the right questions, which is
great.
SPEAKER_02 (13:00):
Yes, absolutely.
Like literally.
It's uh it's and it seems to bethe new norm that uh companies,
or the larger ones at least, areactually coming and asking those
questions.
So uh regulations like um GDPRand CCPA, um, they do influence
(13:22):
uh the whole data protection.
But companies they need to go, Ithink, just beyond compliance,
and they should embed privacyinto their culture and AI ethic
uh panels and secure datasharing agreements.
Um, these are all the greatsteps.
And I'm literally having vendorsasking for these uh agreements,
(13:47):
and it's unbelievable to whatdepth I'm being questioned.
SPEAKER_01 (13:52):
And I'm I'm wondering too, like when you're
getting these questions, um oror maybe not you directly, but
what you've heard um within theindustry, do the questions kind
of differ depending on what umwhere geographically speaking a
company is coming from?
(14:13):
Oh, that's such a good question.
Yeah, I just I'm like as asyou're talking, it's like I'm
like, well, wait a minute, or dowe all have the same concerns or
is it different?
SPEAKER_02 (14:23):
I love this question.
Um, and I have to say that Iwould say before, if you would
have asked me that four yearsago or five or a bit longer when
GDPR got introduced, I thinkthen it would have been
different because GDPR was firstpushed by Europe.
But now we really have theseglobal trends, and I am getting
(14:46):
okay, a lot still in Europe.
So I think I don't want to makeany conclusion here, but I do
think it it's it's maybe a bitmore stricter regulated in
Europe.
And then that's surprising.
Yes, but I I do see this trend,but these companies are also
global companies, so we need tokeep in mind that they um I'm
(15:12):
sure they will somehowcommunicate it then to their
head office in the US or notreally Asia, but I think it's
it's a lot driven in Europe forthese questions.
It's it's a really interestingtrend I'm I'm seeing.
SPEAKER_01 (15:26):
So I want to I kind of coming on the heels of that,
I'm wondering too.
So when we look at what ethicalstandards would be in our use of
AI and um integrating it intoour data practices, do you think
um are you seeing maybe by thequestions you're being asked, or
(15:47):
just a feeling in general, aconsensus across um, I'll say
the supply managementprofession?
Do you think these businessesare becoming more ethical with
their data practices?
And is is there differences inthat based on geography?
SPEAKER_02 (16:05):
Yeah, so I do see businesses becoming more
ethical, um, but there is stilla lot of a lot of work to do.
So companies are, I think,waking up um to the fact that uh
trust equals to value.
And if consumers don't trust abrand, then they won't share the
(16:26):
data.
SPEAKER_01 (16:26):
True.
SPEAKER_02 (16:27):
Um, and one exciting innovation is like the uh data
marketplaces where companies buyand sell data ethically, and
these platforms, um, forexample, they use uh blockchain
for transparency uh or to ensureum all these secure um traceable
(16:48):
transactions.
So that's just one example.
But um, but in terms of to makeit more ethical, and now you
asked about geography, I thinkjust because it's still kind of
at beginning stages wherecompanies are creating this
awareness, um, it is it is tooearly to determine.
SPEAKER_01 (17:07):
Okay.
SPEAKER_02 (17:08):
But I would predict, yes, it would differ from
geography, just because globallywe have different ethical
standards.
SPEAKER_01 (17:15):
Exactly.
Yeah, and that's always that'salways an interesting
conversation just to see how welook at things differently from
business perspectives, justbased on where you do business.
SPEAKER_02 (17:26):
Melanie, I would have the best podcast partner
for you in mind if you ever wantto do another one on that.
SPEAKER_01 (17:32):
Oh, yeah, I think it's uh a subject that none of
us get tired of just becauseit's always it's like it's a
topic that massages the brainconstantly.
Because just when you think youhave, you know, you're set with
the one perspective you have,someone will share something
else with you, and you'll justthen your mind will open up even
more.
(17:53):
And so, yes, we should talkabout that at some point.
Um so if if we can pivot thisconversation to um, let's say
the leaders, leaders in theprofession and other
professionals that arenavigating this AI-driven data
economy, and you know, that'sthat's here to stay, right?
(18:14):
So, Charlotte, what what's theadvice you would want to share
with them on how to get throughthis?
How to be more um not justaccepting of it, but um fully
embrace it and uh be comfortablewith the change that is going to
continue.
SPEAKER_02 (18:34):
Um well, I have I would say maybe a couple of tips
I could share to my fellowcolleagues.
SPEAKER_01 (18:42):
Okay.
SPEAKER_02 (18:42):
Um definitely staying adaptable because
technology is just evolving sorapidly, and leaders they need
to be open to change.
At this stage, we cannot even,it's not even a wish anymore, a
wish list.
It is really a must.
We need to be open and alsoinvest into digital literacy,
(19:04):
um, you know, with continuouslearning and um understanding
how we can somehow increase ourknowledge for digital literacy,
whether you're in procurement orsupply chain, but understanding
data is a must, you know, and wecannot just rely on finance how
(19:27):
we used to.
We are the owners of the newAI-driven data.
And we can, of course, benefitfrom automated dashboards, but I
think uh that's where ourprofession has evolved somehow,
um, being a lot more data-drivenas procurement professionals.
But also, I'd like to add uhthinking long term.
(19:51):
So data is is more than just arevenue stream, it's I think an
opportunity actually to createimpact.
And businesses that thenprioritize sustainability, as we
talked about, and ethics today,um, they will actually be the
industry leaders of tomorrow.
(20:12):
And then looking at it, youknow, from this different
international um cultural pointof view, especially in ethics,
there's still, of course, a lotto do in that way.
So thinking longs long-term,preparing uh for long-term
goals, but right now for theshort term, invest into digital
(20:36):
literacy.
SPEAKER_01 (20:38):
Interesting.
I I know I I feel like it wasn'ttoo long ago where there were
discussions um, you know, aboutyoung, you know, talking to
young professionals and wherethey want to kind of pivot their
skill sets to make themselvesmore marketable uh in the job
market.
And um it seemed as though likepeople could specialize in in
(21:03):
data and data analytics and umhow to maximize its use.
Where now it almost seems asthough everybody needs to kind
of get comfortable using this.
Are you finding that that thatshift?
SPEAKER_02 (21:19):
Absolutely.
It's um it's scary, you know.
It's scary how quickly we haveto be uh uh open-minded, and
it's really an eye-opener howhow data is evolving so quickly,
and how quickly we as leadersneed to evolve.
And I I see this I see thismassive shift, especially then
(21:44):
on the impact of our profession.
And that's why we shouldn'tunderestimate data.
SPEAKER_01 (21:50):
This is true.
This is true.
I I say that to myself everytime I get an email that
surprises me.
Um anyway, no, I This has beenreally interesting.
And every time we talk aboutyour data economy model, the AI
data economy model, I I get abetter understanding of what
(22:12):
you're sharing and just a betteridea of the magnitude of all of
this and how lucky are we thatwe are here and now watching it
all unfold and being part of itand able to make a our own
impression on it.
It's just, it's um, it's reallycool.
(22:34):
That's not there's no other wayfor me to say it.
I just think it's really cool.
Um, Charlotte, for anyone thatwants to kind of learn more and
you know, kind of pick yourbrain a little more, um, what
way should they contact you?
SPEAKER_02 (22:47):
Well, I'd be happy to answer any questions either
via my website, that'sCharlotteDebraban.com, or you
can also find me on LinkedIn.
And I think I'm quite good atreplying to the messages.
So don't hesitate, just reachout.
SPEAKER_01 (23:03):
Wonderful.
Thank you.
Thank you so much for beinghere.
Always a pleasure.
And and, you know, kind of uhtalking about uh getting more
knowledgeable on data and how touse it to your benefit.
You know, that's one skill thatwe all could, you know, get a
little bit more savvy on.
But just in general, it's agreat time to upskill yourself,
(23:25):
your teams, boost yourknowledge, and you can do it by
enrolling in any of ISMcertification courses.
They've got training programs,or check out their corporate
capability models andassessments.
They're um they're reallythought provoking and um very,
very beneficial.
(23:46):
You can find it all and so muchmore always at ismworld.org.
Thanks so much for being here.
Love having you with us always.
I'm Melanie Stern for ISM.
For real stories on how global business gets done.
This is Supply Chain Unfiltered,presented by the Institute for
Supply Management.
SPEAKER_01 (00:17):
Hi, so glad you decided to join in today.
I'm Melanie Stern for ISM andSupply Chain Unfiltered, and
today's episode is EverythingData.
Our guest today, she'sconstructed a new way of looking
at data, how we perceive it, howwe can put it to use, and at the
same time monetize it.
(00:38):
So let's uh introduce Dr.
Charlotte de Brabant.
She is an expert in procurement,digital transformation, and
AI-driven sustainability.
And she has developed a Kamar deBrabant AI data economy model,
and it's shaping a new waycompanies can understand and
(00:58):
monetize data.
Hi, Charlotte.
Thanks for being here.
SPEAKER_02 (01:02):
Hi, Melanie.
Thank you for having me, andalso thank you for this
wonderful introduction.
SPEAKER_01 (01:08):
There's so many, so many great things to share about
you.
But first, um I'd like you, ifif you would, give us kind of a
high-level overview of what yourum economy model is all about.
SPEAKER_02 (01:23):
Absolutely.
So the the model that mycolleague and I um designed, I
would say it takes this holisticview of data's role in our
modern economy.
And especially as procurementand supply chain professionals,
we data is king, right?
(01:43):
Without data, our negotiationswouldn't lead to anywhere.
And understanding data, but Ithink especially over the last
months, literally data hasevolved with all of this
generative AI and and data beingso easily accessible um all
(02:03):
around us.
That's how we created uh exactlythe Kuma de Brabant um AI uh
data economy model.
And it it traces at the end umthe whole data's evolution from
uh the early electronicprocessing devices that we had
(02:24):
in the 50s uh to you know toliterally today's AI-driven
landscape.
And the model is actually itsounds a little complicated, but
it's really simple because it'sit's built literally on four key
frameworks.
We have um framework number one,um that's uh 4G generative AI,
(02:51):
then we have um so generative AIdriving AI's um creative and
analytical capabilities, andthen we have uh 4E ethical AI,
ensuring um responsible andsustainable AI practices, and
then we have 4M, um there whichis then the monetization part,
(03:13):
so structuring economic valuefrom data, and then 4C, so
that's the wholedemocratization, enabling access
to data and and fostering allthis um collaboration with with
all the stakeholders.
And by combining theseframeworks, we can then create a
um like a balanced ecosystemwithin our procurement supply
(03:37):
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.
This day, this model, it's notit's not just for for frameworks
because it's constantlyevolving, constantly building.
(03:59):
So it's just a littleintroduction for you.
SPEAKER_01 (04:02):
Thank you.
And I I have to I have to umshare that um when you and I
originally spoke about you knowdoing this episode, and I you
know, I'm seeing the phrase uhdata monetization, you know, my
ears perked up like, you know,oh what's that?
Um so I could you share with usa little bit more about how
companies can make money fromthe data that they have?
SPEAKER_02 (04:27):
Yeah, absolutely.
Um I think they are simplyspeaking, two main approaches.
Um when we look at this topic.
We have direct and indirectmonetization.
So direct monetization, it meanscompanies sell or um even
license data.
(04:48):
So, for example, on social mediaplatforms, um, for example,
selling anonymized uh user datafor advertising insights, or we
have indirect monetization, andit's when companies use data uh
to optimize internal processes,very important, or improve uh
(05:09):
customer experience, or um evenwhen creating new products.
Um, like I, you know, I used towork at Amazon not so long ago,
and for example, how Amazonpersonalizes recommendations
using purchase history.
So the key is actually findingthe right balance between um
(05:30):
financial gain and ethicalresponsibility, and that's
really where our model helpscompanies um to make informed
decisions.
SPEAKER_01 (05:40):
I I want to share something real quick.
I I ran across something, Ithink it was yesterday or the
day before, um, where Google hadannounced that they are changing
the way um searches will beengaged.
And they stated that they'regonna have a one, you know, an
AI agent only communicate withanother AI agent.
(06:01):
They're removing humaninteraction completely.
And I I just thought, wow, thatwas fast.
You know, it's all happening sofast.
SPEAKER_02 (06:11):
I mean, it's all happening so fast, Melanie.
SPEAKER_01 (06:14):
It's crazy.
SPEAKER_02 (06:15):
That's why we're having this podcast, yeah.
Because we really should notunderestimate data.
Before they when we when we inprocurement thought about data,
when I started my procurementcareer, you know, 17 years ago,
it's kind of finance department,finance, finance.
But actually, no, it's it'sreally it's us now.
SPEAKER_01 (06:36):
It's everything.
Yeah.
It's everything.
So so um, being that everythingis transforming so so quickly,
um how how would you say thatthat AI really fits into the
data monetization equation?
How do we distill that down?
SPEAKER_02 (06:57):
Okay.
Um thank you for that because II I do like this question
because AI really enhances ourdata value.
And I think the way it itchanges the value is through
automation, so um AI-drivensystems, right, that analyze
(07:19):
massive data sets faster andmore efficiently.
And I mean, we have so manyexpert vendors out there right
now, especially in procurementand IT procurement, IT sourcing.
So many of these vendors thatare really experts when it comes
to AI-driven systems, analyzingall these massive data sets and
(07:40):
helping us as procurementindividuals then just get one
created automated dashboard.
And um lows happening there.
But secondly, also predictiveinsights.
So we have companies uhcurrently vendors, many vendors,
they use AI to forecast trendsfrom customer behavior to supply
(08:03):
chain risks.
And I have a very good friendworking in that field.
He had literally created acompany for us procurement
professionals on uh predictiveprocurement.
So for the ones listening, I'mnot going to make any
advertisements here, but I thinkmany people will smile because
many would know the company.
Okay, and then number three, um,personalization.
(08:26):
So AI-tailored uh userexperiences and making
data-driven businesses a lotmore competitive.
Uh, but I do want to add,Melanie, that we need to be a
little cautious because AI uhcan be also biased or misused if
(08:47):
we just don't apply it umaccording to ethical standards.
And that's why having the um thewhole 4E framework for ethical
AI is is then critical tobalance all of this.
SPEAKER_01 (09:04):
Yeah, we have to be mindful.
Um but it's hard, it's hard towant like want to take the time
to be mindful and take thatpause because the innovation's
happening so fast and you knowyou don't want to lose that
competitive edge, right?
So it's it's an interesting,interesting to try to find the
right balance.
So you mentioned trends in AI.
(09:24):
Um excuse me, is there anythingin particular that you think
businesses should be watchingfor as far as the trends, either
what's current or what you feelis coming in the near term?
SPEAKER_02 (09:39):
Uh yes, absolutely.
Um when it comes to to trends,we we need to take into account
um decentralization.
So uh data mesh is is changinghow companies structure data and
moving away from centralized uhdata warehouses.
(10:04):
Oh, okay.
Also, another trend isAI-powered decision making.
So um, you know, we have so manytools right now where AI is
helping us to create thesedashboards and and as I
explained earlier, you know,taking this large quantity and
(10:25):
and through AI making helping usto make these decisions.
So more businesses are actuallyrelying on AI for these
real-time business insights.
And then number three,sustainability in uh in AI as
another uh trend where companiesare using AI to reduce the
(10:49):
carbon footprint and optimize umenergy usage and and support
environmental efforts as good asthey can.
So um I know many companies youknow are going back and forth.
What are what standards shouldthey use?
Um, but I think we are justentering an era where data is
(11:12):
not just power, but it'sresponsibility.
And it's up to us to decide howto best proceed.
SPEAKER_01 (11:20):
And 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 formany of us, you know, on the
consumer level and um within uhthe business environments is
data privacy.
And do you think it's possiblefor us to really achieve that
(11:44):
balance between datamonetization while we are able
to maintain consumer trust asfar as data use?
SPEAKER_02 (11:55):
Yeah, uh that that is that is a very good point,
especially remaining uh the theconsumer trust.
And um, and that's why I dobelieve that as a company or a
procurement or supply chainindividual, I think transparency
(12:15):
is key here when you speak withyour vendors or with your
stakeholders.
Um, I think businesses they mustcontinuously, consistently, um,
clearly communicate what datathey collect, how they use it,
how they protect it.
Um, and I know that I'm alsogoing through so many audits,
(12:40):
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 theyprotected, how are we using it?
So it's really a it'sinteresting, it's it's kind of a
new trend I'm seeing.
SPEAKER_01 (12:57):
Um so they're asking the right questions, which is
great.
SPEAKER_02 (13:00):
Yes, absolutely.
Like literally.
It's uh it's and it seems to bethe new norm that uh companies,
or the larger ones at least, areactually coming and asking those
questions.
So uh regulations like um GDPRand CCPA, um, they do influence
(13:22):
uh the whole data protection.
But companies they need to go, Ithink, just beyond compliance,
and they should embed privacyinto their culture and AI ethic
uh panels and secure datasharing agreements.
Um, these are all the greatsteps.
And I'm literally having vendorsasking for these uh agreements,
(13:47):
and it's unbelievable to whatdepth I'm being questioned.
SPEAKER_01 (13:52):
And I'm I'm wondering too, like when you're
getting these questions, um oror maybe not you directly, but
what you've heard um within theindustry, do the questions kind
of differ depending on what umwhere geographically speaking a
company is coming from?
(14:13):
Oh, that's such a good question.
Yeah, I just I'm like as asyou're talking, it's like I'm
like, well, wait a minute, or dowe all have the same concerns or
is it different?
SPEAKER_02 (14:23):
I love this question.
Um, and I have to say that Iwould say before, if you would
have asked me that four yearsago or five or a bit longer when
GDPR got introduced, I thinkthen it would have been
different because GDPR was firstpushed by Europe.
But now we really have theseglobal trends, and I am getting
(14:46):
okay, a lot still in Europe.
So I think I don't want to makeany conclusion here, but I do
think it it's it's maybe a bitmore stricter regulated in
Europe.
And then that's surprising.
Yes, but I I do see this trend,but these companies are also
global companies, so we need tokeep in mind that they um I'm
(15:12):
sure they will somehowcommunicate it then to their
head office in the US or notreally Asia, but I think it's
it's a lot driven in Europe forthese questions.
It's it's a really interestingtrend I'm I'm seeing.
SPEAKER_01 (15:26):
So I want to I kind of coming on the heels of that,
I'm wondering too.
So when we look at what ethicalstandards would be in our use of
AI and um integrating it intoour data practices, do you think
um are you seeing maybe by thequestions you're being asked, or
(15:47):
just a feeling in general, aconsensus across um, I'll say
the supply managementprofession?
Do you think these businessesare becoming more ethical with
their data practices?
And is is there differences inthat based on geography?
SPEAKER_02 (16:05):
Yeah, so I do see businesses becoming more
ethical, um, but there is stilla lot of a lot of work to do.
So companies are, I think,waking up um to the fact that uh
trust equals to value.
And if consumers don't trust abrand, then they won't share the
(16:26):
data.
SPEAKER_01 (16:26):
True.
SPEAKER_02 (16:27):
Um, and one exciting innovation is like the uh data
marketplaces where companies buyand sell data ethically, and
these platforms, um, forexample, they use uh blockchain
for transparency uh or to ensureum all these secure um traceable
(16:48):
transactions.
So that's just one example.
But um, but in terms of to makeit more ethical, and now you
asked about geography, I thinkjust because it's still kind of
at beginning stages wherecompanies are creating this
awareness, um, it is it is tooearly to determine.
SPEAKER_01 (17:07):
Okay.
SPEAKER_02 (17:08):
But I would predict, yes, it would differ from
geography, just because globallywe have different ethical
standards.
SPEAKER_01 (17:15):
Exactly.
Yeah, and that's always that'salways an interesting
conversation just to see how welook at things differently from
business perspectives, justbased on where you do business.
SPEAKER_02 (17:26):
Melanie, I would have the best podcast partner
for you in mind if you ever wantto do another one on that.
SPEAKER_01 (17:32):
Oh, yeah, I think it's uh a subject that none of
us get tired of just becauseit's always it's like it's a
topic that massages the brainconstantly.
Because just when you think youhave, you know, you're set with
the one perspective you have,someone will share something
else with you, and you'll justthen your mind will open up even
more.
(17:53):
And so, yes, we should talkabout that at some point.
Um so if if we can pivot thisconversation to um, let's say
the leaders, leaders in theprofession and other
professionals that arenavigating this AI-driven data
economy, and you know, that'sthat's here to stay, right?
(18:14):
So, Charlotte, what what's theadvice you would want to share
with them on how to get throughthis?
How to be more um not justaccepting of it, but um fully
embrace it and uh be comfortablewith the change that is going to
continue.
SPEAKER_02 (18:34):
Um well, I have I would say maybe a couple of tips
I could share to my fellowcolleagues.
SPEAKER_01 (18:42):
Okay.
SPEAKER_02 (18:42):
Um definitely staying adaptable because
technology is just evolving sorapidly, and leaders they need
to be open to change.
At this stage, we cannot even,it's not even a wish anymore, a
wish list.
It is really a must.
We need to be open and alsoinvest into digital literacy,
(19:04):
um, you know, with continuouslearning and um understanding
how we can somehow increase ourknowledge for digital literacy,
whether you're in procurement orsupply chain, but understanding
data is a must, you know, and wecannot just rely on finance how
(19:27):
we used to.
We are the owners of the newAI-driven data.
And we can, of course, benefitfrom automated dashboards, but I
think uh that's where ourprofession has evolved somehow,
um, being a lot more data-drivenas procurement professionals.
But also, I'd like to add uhthinking long term.
(19:51):
So data is is more than just arevenue stream, it's I think an
opportunity actually to createimpact.
And businesses that thenprioritize sustainability, as we
talked about, and ethics today,um, they will actually be the
industry leaders of tomorrow.
(20:12):
And then looking at it, youknow, from this different
international um cultural pointof view, especially in ethics,
there's still, of course, a lotto do in that way.
So thinking longs long-term,preparing uh for long-term
goals, but right now for theshort term, invest into digital
(20:36):
literacy.
SPEAKER_01 (20:38):
Interesting.
I I know I I feel like it wasn'ttoo long ago where there were
discussions um, you know, aboutyoung, you know, talking to
young professionals and wherethey want to kind of pivot their
skill sets to make themselvesmore marketable uh in the job
market.
And um it seemed as though likepeople could specialize in in
(21:03):
data and data analytics and umhow to maximize its use.
Where now it almost seems asthough everybody needs to kind
of get comfortable using this.
Are you finding that that thatshift?
SPEAKER_02 (21:19):
Absolutely.
It's um it's scary, you know.
It's scary how quickly we haveto be uh uh open-minded, and
it's really an eye-opener howhow data is evolving so quickly,
and how quickly we as leadersneed to evolve.
And I I see this I see thismassive shift, especially then
(21:44):
on the impact of our profession.
And that's why we shouldn'tunderestimate data.
SPEAKER_01 (21:50):
This is true.
This is true.
I I say that to myself everytime I get an email that
surprises me.
Um anyway, no, I This has beenreally interesting.
And every time we talk aboutyour data economy model, the AI
data economy model, I I get abetter understanding of what
(22:12):
you're sharing and just a betteridea of the magnitude of all of
this and how lucky are we thatwe are here and now watching it
all unfold and being part of itand able to make a our own
impression on it.
It's just, it's um, it's reallycool.
(22:34):
That's not there's no other wayfor me to say it.
I just think it's really cool.
Um, Charlotte, for anyone thatwants to kind of learn more and
you know, kind of pick yourbrain a little more, um, what
way should they contact you?
SPEAKER_02 (22:47):
Well, I'd be happy to answer any questions either
via my website, that'sCharlotteDebraban.com, or you
can also find me on LinkedIn.
And I think I'm quite good atreplying to the messages.
So don't hesitate, just reachout.
SPEAKER_01 (23:03):
Wonderful.
Thank you.
Thank you so much for beinghere.
Always a pleasure.
And and, you know, kind of uhtalking about uh getting more
knowledgeable on data and how touse it to your benefit.
You know, that's one skill thatwe all could, you know, get a
little bit more savvy on.
But just in general, it's agreat time to upskill yourself,
(23:25):
your teams, boost yourknowledge, and you can do it by
enrolling in any of ISMcertification courses.
They've got training programs,or check out their corporate
capability models andassessments.
They're um they're reallythought provoking and um very,
very beneficial.
(23:46):
You can find it all and so muchmore always at ismworld.org.
Thanks so much for being here.
Love having you with us always.
I'm Melanie Stern for ISM.
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