Meet the CI Fellows: Luis MADUREIRA

So, this is Eric Garland, with the first of our Council of Competitive Intelligence Fellows conversations, and I am very pleased to be here with Professor and expert Luis Madureira. Luis, how are you doing? >> Very well, thank you. >> And what country are you are you recording from today? >> So, I’m recording from Lisbon, actually sunny Lisbon today. Um >> Sunny Lisbon? >> from weather. >> Excellent. You and I are both um part of the Council of Competitive Intelligence. We are fellows. Um can you tell us how you got into intelligence at all? >> I’ve always had that kind of a a predisposition to um convert everything into numbers and metrics uh since university where I had a really really good teacher that taught me how to convert, you know, just text into assumptions and numbers, and then actually kind of a measure that.

Uh so, when I started working, for example, in in Diageo, and I was in sales, I was one of the one of the only guys who brought a computer, kind of, you know, to meetings with the with the with the customers. So, that uh you can call that customer intelligence, right? So, from there, I kind of I always kind of a develop >> [clears throat] >> kind of a information, or if you want an intelligence approach to business. And um a little bit kind of a down into my career, I got an invitation to set up the competitive intelligence function at uh Central de Cervejas, which is basically the biggest brewer in Portugal. And that was actually kind of acquired by Heineken, you know, >> uh the big two months brewer in Portugal.

So, you’re making beer. >> Yeah, beer, water, and soft drinks at the time. >> Ah. Now, uh are you aware that my my first book, Future Inc., was about the future of the beer industry? >> I did I was not. But, I should really know. I absolutely did. >> Um it’s it’s >> A major major major miss me. >> [laughter] >> No, it’s it’s it’s 20 it’s 20 I wrote it 20 years ago about >> Yeah, yeah, but I stopped working on on on on beer in 2007. So, it was you know, almost 20 20 years ago. So, it was pretty pretty on spot. I should I should have I should have not missed it. >> It was you know, um Well, now it’s a historical document. I think the forecasts in there were correct by and large. Um but in any event, so I’m I’m familiar with the brewing industry.

I also I I lived in St. Louis, Missouri, home of Anheuser-Busch for 15 years and it’s a it’s an industry close to my heart. So, you were doing also intelligence on the future of beer. >> Yeah. Yeah. Very much focused on So, the the the the Portuguese beer market is basically a duopoly. So, if you lose 1% market share, it actually means that you get kind of a 2% 2% points of difference to your competitors. So, it’s very very competitive. And kind of a my role was to actually to set up the CI function and kind of a guarantee that was that was my own, you know, my my only brief was guarantee that there are no surprises. That was my role. >> No surprises. That’s pretty good intelligence role. That’s That’s what we promise, right?

>> And pretty encompassing as well. >> [laughter] >> So, now before that, you know, when you were going to school, was there What did you study when when you were young? In your first university? >> Economics. I always followed economics and I then went to the Nova University of Lisbon, the School of Business and Economics, which is where I studied economics. I kind of I majored from economics and then I did all kind of the marketing. So, enterprise economics, which is basically management, and then I kind of choose and I did all the specific courses on marketing. So, this is when I found out that this is what I wanted to do. So, I focused on marketing. >> So, you came in from the marketing perspective.

>> But with a with an economics background, which is kind of a completely different and then if you just kind of go into the creative kind of a side of things. Yeah, so if you go, for example, and you study marketing on the on the creative on a creative university, you get more on, you know, design and this kind of stuff. If you go on the economic side, you get more on the macroeconomics, understanding a country, understanding kind of a industries, understanding the organizations, the firm’s performance, and then you go into the marketing. So, that gave me a rather specific background, which most people don’t have. Actually, I don’t remember anyone in my in my university actually doing all the all the marketing courses.

>> So, you did marketing, everything they had. You sucked it up. >> marketing. Yeah, advertising, econometric, research methods in marketing, you know, the whole the whole lot. >> The whole lot and with a with a focus on quant quantitative analysis. >> Not not really. So, not you know, marketing as a whole. At the time it was just marketing as a whole. But then I had this this trade marketing teacher, which was actually the CEO of Vileda. And kind of basically >> CEO of What What’s the company? >> Vileda. Vileda is a is a kind of a cleaning products company, very well known in Europe and international kind of a fast moving consumer goods company. >> Cool. >> V I L E D A. >> Vileda. >> got it.

>> Vileda. >> Vileda. All right. So, I have a linguistic question for you that that comes up amongst our our colleagues from time to time. Um, we’re speaking English, which is a very handy language. It’s not the only one probably either of us speak. Um, but here we are. Um, I grew up around people that spoke spoke English, so I I’m pretty attached to it. Um, we use the term competitive intelligence. Um, I have done I I’ve done speeches in Portugal and Brazil. I have done courses. I’ve taught courses in France, where I speak French. Um, what is the phrase that you use to describe what American English speakers call competitive intelligence? What do you say in Portuguese? >> You mean you want me to say the definition in Portuguese?

Speaking language Portuguese? >> It Now, is there one term? Like for in French they’ll say la veille. It’s actually the >> Yes, veille veille veille is the is the monitoring. And but they also they also use intelligence économique, which is kind of a intelligence économique. Yeah, which is a kind of a slightly different approach. So, um, I’ve I’ve studied that in in all countries. I can give you a global perspective if you want. >> Please do. Hit us. >> So, for example, if you go to the Nordic Nordics, uh, they basically kind of they use market intelligence, okay? >> Okay. >> Uh, if you come to Portugal, you use competitive intelligence, mainly because we adopted kind of a the the the US kind of a approach to competitive intelligence.

>> you say inteligência competitiva? >> No, I tend not to do that because inteligência in Portuguese does not really mean intelligence, right? So, and that’s that So, in in in Portuguese, the the the word for intelligence, for the English word intelligence, is informações, which is like information plural. Yeah, it’s the plural of information. >> Right. >> Okay, so you say So, the national intelligence kind of a body, it’s called Sistema de Informações. So, information’s system. >> Mhm. >> So, intelligence system converts into Sistema de Informações. >> And Informações de Defesa. Right? >> Yeah. Yeah. >> For defense defense >> Defense. Yeah, yeah, yeah. Yeah, yeah. >> Right. Okay, so >> National I call it national intelligence, yeah.

So, for for all the all the national kind of intelligence services, I call it national intelligence. >> I was told that if you say Inteligência Competitiva, competitive intelligence in Portuguese, it sounds like you’re trying to compete at bar trivia night. That you’re trying to prove you’re the smartest guy. >> Yeah, yeah. Inteligência is like it’s like you you know, it’s like it would be the IQ kind of a thing. So, if you say Inteligência, you are referring to IQ. >> Got it. Now, now in in in Brazil, do they have a same similar thing? >> Got it. Okay, so you’re in the Informações. >> Informações. Yeah. >> Yeah. >> Yeah, exactly. >> All righty. See, I I think that’s, you know, it’s really important cuz cuz language frames up who we are, and you done academic work that’s in English, which is an incredible thing.

Um you know, to to work in something other than your mother tongue. And I know like we’ve lived through a certain period of time where the English language has been adopted as essentially kind of everybody’s second language for business purposes. That doesn’t make it less impressive. Um I started life as a translator and an interpreter. And getting things exactly right in a business context, my first job out of university was translating temperature and process control manuals from English into French. I managed the translations into Spanish and they all all the source language was Japanese. >> Woah. >> And these were devices that if they were set up incorrectly, if you if you got one number wrong in the software, you’re talking about making a um an industrial heater for plastics or pharmaceutical ingredients, >> Mhm.

>> that could be the difference between heating it to 400° and 4,000°. >> Yeah. >> So, precision is important in these things. >> It’s important. Yeah, yeah. >> So, you’ve been you have been doing landmark research and intelligence in your in your second language. >> Yeah. But I’ve I’ve lived in a in a in a English-speaking country, so I lived in London for 2 years, and I will always work in multinationals. So, my my kind of a my basically my working language is pretty much English now nowadays. So, I teach in English, I work in English most of the time, even when I’m in Portugal, because I work from Portugal, you know, globally. So, that’s uh >> And that’s the kind of you >> That makes it a little bit easier.

>> I I we we appreciate your humility. Nevertheless, wow. Um it’s it’s amazing to have you as part of our community. Um cuz I get to be lazy. Um I I I think I I’ve I’ve got Alvin Toffler’s books on >> Mhm. >> on Future Shock. >> Visualizations and and trends, yeah. >> As Mudanças do Poder, >> Mhm. >> the the the power wave or power shift or whatever the translation is in English. >> Shift, yeah. >> Yeah. So, anyways, I yeah, I’ve I’ve I’ve tried to read stuff in in our shared profession in Portuguese. I’ve been to conferences in in Portugal and and Brazil. It doesn’t mean I’m any good. >> [laughter] >> So So, thank you for the love. >> practice. You need to practice. I For example, I don’t teach in France in French.

I did I teach in France, but I don’t teach in French. And I I used to talk French like so from from the high school. You have like 3 years and we actually kind of we talked the basics in in in in French, but because I so for so long I didn’t practice it, I actually lose it. Same thing with Italian. I did a course on basic Italian, but I didn’t never practice. So, I understand it, but I cannot I cannot really speak it. So, it’s it’s we are lazy by default. So, that’s that’s that’s that’s us. >> And so, these are all countries that historically have had empires and have had reason to collect information from around the world. So, you know, these are There’s There is a great intelligence tradition, I think, in all of these countries and all of these languages.

And I imagine there are are subtleties that that get lost or shaved off. >> Definitely. I would say so. Even even today, you know, the the what we were saying about intelligence economy, the way and technological inteligencia tecnologica. If you go to Spain, >> Sure. >> like, you know, all all of the all of the all of the kind of a definitions are slightly different and we we lose a lot in translation, as well. And And for example, in in Spain, they call it inteligencia competitiva. So, the the the same thing that we were discussing, but they actually mean intelligence. So, it’s a little bit different. >> And I know their their national intelligence services Centro Nacional de Inteli de Inteligencia.

Right? >> Inteligencia competitiva, yeah. >> So, anyways, we you know, we’ve all got we’ve all got ways of of of talking about this. You have done a this all this all matters because you have been focusing your um your academic work on getting everybody’s opinion. You have been you have been talking about um how how all of us do intelligence, how we think about it, the words we use, our feelings about quantitative and and qualitative. And this this went into your you know the the landmark paper that you you did that was published in 2023, correct? >> 2021 was the first one, so that’s the definition. And then on 2023, you’re right, I published about the empirical validation. >> Got it. Well, can you tell us about that?

>> Yeah. So, a little bit of context. So, all those papers were done in the context of my PhD. So, this is a PhD by publication. So, it’s not just a manuscript. You have actually have to publish the articles. And you have to publish them in top journals. So, you can actually get the the the amount of credits that will allow you to get the the the the doctoral chart. So, the the idea at the beginning was to do the PhD was to study the impact of social consumer data on the competitive intelligence model. But, as I actually kind of went to start to study and to find what the model was, I could not find the consensus definition. And because there was not a consensual definition, there was not a consensual model.

And then I had to go back and start studying the old that. So, when I started kind of doing my PhD, I was not even thinking about kind of a laying the foundations of the competitive intelligence science because I was assuming that somehow I would find those foundations already then. So, when I started studying and looking for the competitive intelligence model, I then kind of could not find you know definition that covered the whole all the dimensions. So, I had kind of to basically kind of search everything. So, I spent the next 3 years reading everything about competitive intelligence. To do that, I based myself on kind of a four really important articles from SCIP. So, at the point at the time the Society of Competitive Intelligence Professionals, which basically kind of listed all the kind of articles, books, everything that was published, all the you know scientific and also gray literature that existed on CI.

And then I collected all of that and then I collected from that I extracted all the definitions that I could find on in you know competitive intelligence. That means competitive marketing, competitor, business, artificial intelligence, you know marketing intelligence, customer intelligence, you know and so on. So, and all the related concepts. So, you know also market research, strategic planning and so on and so forth. Which come come come up to 816 definitions if I’m not mistaken. And because there was so many, I then kind of started using AI to actually kind of to find the patterns within those 820 definitions. So, that was used by that was done using a a clustering algorithm and using natural natural language processing.

So, basically kind of reading the reading the text and basically kind of grouping kind of the definitions and kind of finding what were the topics within those those those definitions. So, to cut a long story short, the the the algorithm found five groups. So, the the the the the number five was not random. So, that was that was I used another algorithm to find what is the [clears throat] optimal number of topics in that discussion. So, the discussion being the all the definitions. And then, I kind of I asked the algorithm to find me what were the keys what were the key Yeah. So, those are those are the only five attempts to define CI properly, I would say. And some of them are not even, you know, I just tries not really kind of a a really attempts to to to define this.

>> So, this is why, you know, I kick off our discussion with language because what you’ve been doing, among other things, is trying to understand how we describe competitive intelligence. What are we doing when we engage in intelligence practice um for private sector um economic means as in not not necessarily for our government or for a national security application, though there is that. You know, that let’s you know uh let let us remember or >> input it’s an input to that. >> It can be and it can be an output to it as well. >> Yeah. Yeah. >> But for the you know, um I think all of our colleagues would agree that um competitive intelligence design is This is where I think it it’s it it is separate from intelligence économique in the French sense cuz the French have no problem with intelligence économique being done by the government.

>> Or or the the lines between a government practitioner and a private are very blurred cuz France is a very unified government. Um that you know the the département versus the national l’état. In other words you’re you’re never that far from the the mothership with with the French. Which is why this needs this is I think why having these discussions matter because um particularly you know over the years competitive intelligence has great value to private business enterprise. Um something that I think was was very clear to the average executive in the 90s and even the 2000s and which may have gotten blurred so your work going first of all if we want to discuss what value is happening here and I remain a huge competitive intelligence partisan.

I will defend it till I die. I think it’s a very valuable part of any enterprise. In many cases more so than just marketing where like well let’s let’s try and pass intel well let’s pass messages to the customer about how great we are which you know some marketing is trash. Whereas I think you know a lot of competitive intelligence is high high pressure and high importance and I think we deliver the goods. That I’m a partisan of I’m >> I would I’ll go further even Eric. I I would say that without competitive intelligence you cannot achieve sustainable performance in any any part of the value chain. So I’m talking about marketing and management as a whole sales you know everything. >> Hold on let me underline that.

You’re saying without competitive intelligence you can’t reliably develop deliver value in any of the other parts of the value chain. >> Yeah yeah. >> Heavy stuff man. >> That’s that’s my That’s my claim, yeah. That’s my claim and I I I would I would even like I would I would try to prove it. Well, or if you want I will I will prove it. That’s That’s another heavy claim as well. >> say I will fight you. So, why do you feel that way? Do you Why do you feel CI is so valuable? >> So, um >> [snorts] >> As I told you, I started in in in sales, then I moved into trade marketing, then I moved into marketing, and this was all, you know, started in you know, as a as a as a trainee, then I moved into kind of assistant and into manager, then into sales director, into marketing director, then I moved into marketing and, you know, head of marketing, head of business development, head of innovation, and then I ended up at board on competitive intelligence and innovation.

And I covered the whole lot, okay? And in in my in my in my role as head of intelligence and innovation in in Heineken, I’ve got to I cover the whole thing. So, I was basically supporting all the different functions. So, I was reporting to the CEO, I was kind of a supporting the CEO and all the members of the board. So, I can definitely tell you >> Just so we’re we’re we’re clear, so you the CEO of Heineken >> Of Heineken in Portugal. >> Of Heineken in Portugal. Okay. >> Heineken Portugal. And then I also helped other countries develop their own CI function. So, we were the top CI function within Heineken and also within the at the time 350-400 companies in the world by the GIAI survey. So, we were on the world-class level.

>> So, you were doing it better than anybody else. >> Well, not better than anyone else, but I was at the top level. So, in in by the by the by the world-class CI framework from John Prescott, which is another one. So, we we measure this by two different uh uh measuring instruments. One was the GIA survey, and the other one was the John Prescott uh world-class CI, so WCCI. We are also on the top 90% percentile, so we were always kind of uh on the top on the top companies doing this in the world. Not the best, but uh at the one of the best. >> So, for you, in your opinion, what defines the best intelligence function in the world? If I’ve got a group of guys going in doing intelligence for for some unit, some agency, some organization, what are they doing, according to you?

>> Yeah. So, John Prescott defined that very very well. In terms of the criteria to be very good intelligence, I would go for TAAR. So, it’s timely, actionable, relevant, and there’s another the another There are two A’s in there, so it’s TAAR. I’m missing the other A, but anyhow, timely, actionable, and relevant. So, in terms of criteria for good for for good intelligence. In terms of what is intelligence competitive intelligence itself, I’ll just refer to my to my definition. So, it’s basically the process and forward-looking practices that that produce knowledge on the competitive environment to improve organizational performance. So, this is critical this definition because it looks like very generic.

It is not really generic, and it’s kind of a modular, so you can go you have five models here, so which are the five dimensions of competitive intelligence. So, you have a process, so it’s like a series of steps that CI professionals need to to to endure. So, we need to kind of to plan, we need to First, we need to identify what what what are the key topics that we need to to to answer or that we need to investigate. >> You mean key intelligence topics and key intelligence >> Key intelligence topics and key intelligence questions, exactly. >> Kits. Kicks. Okay. >> Then we need to plan on how to answer those questions. Then we need to collect the data and information. Then we need to process that data and that information.

Then we need to analyze that information and convert that information into insights. And only when you have sufficient insights that allow you to make a decision or come up with a strategy, and again, a strategy is a set of decisions, okay? So, only when you have insights that allow you to make a decision, then only you only then you have intelligence, okay? And it’s on the competitive environment, meaning that these kind of insights are regarding the competitive environment. And the objective of that of that of that actionable insights is to make decisions that will allow the organization to improve its performance. Now, the perfor- I put performance on purpose because performance means a lot of things.

So, performance means that you are able to achieve your objectives, which is the most important thing. But, the objectives can be quite different. So, some companies’ objective is just, you know, increase sales because they just want to to to achieve economies of scale, for example. Some companies want profit, so they go straight into the bottom line. Some For example, Heineken. Heineken wanted to be the most international brewer in the world. So, that is an objective by itself, okay? So, you can sacrifice a little bit of the profit or a little bit of the sales to actually kind of to go into another country. Does that make sense? And be the most international. So, that was the vision of Mr. Heineken.

So, you need also to understand what is the, you know, the motto, the mojo of the companies to to actually to perform, going back to your question, really good intelligence. Because good good intelligence means different things into different organizations, although the criteria is always the same. >> But that in itself would become a key intelligence theme or question for someone else because if I’m competing in the in the brewing business and I want to sell beer and I go, “Wait a minute. I I have 23% market share in Mongolia.” I you know, and it’s very hard. We it took us a long time to get in there and we make 20% profit, but that took years to get to. >> Yep. >> There’s no way Heineken is going to come into our market cuz they’re they’re going to have weak supplier relationship, blah blah blah.

Actually, I don’t know what Heineken’s deal is in Mongolia, but if you don’t understand that what Heineken wants >> Yeah, exactly. >> It’s like, “No, no, no. We want another flag on the wall.” >> Exactly. >> And when we’re done with that, we’re going to go to Papua New Guinea. And we don’t care if it’s 3% profit or or maybe even 0.2% [clears throat] profit, we want that flag. If you don’t understand that then you didn’t understand >> Understand the arts. Yeah, exactly. >> strategic >> of that playing. Exactly. I got it. >> That’s right. You you you you you you >> the timely, actionable, and relevant. So, you need it needs to be relevant. So, you know, if if I if I imagine that I was the the the the CI director of of Heineken and I need to develop intelligence on Mongolia, you know, even if it’s just for us to kind of to go and kind of fulfill the vision of the founder, which is kind of a be the most international company in the world.

Which other CI director might not actually kind of even think about because it was just saying, “Okay, we need performance is profit, for example.” Or performance is sales, whatever. >> Got it. So, timely, actionable, relevant for you if if a an intelligence function achieves those things, it’s world-class. Now, let me ask you, where where does foresight uh come in here? Predictive um in you know scenarios of the future, stuff like that. Is that something that it belong, you know, where do where does that fit in the intelligence model, according to you? >> You have hindsight, insight, and foresight. Yeah. So, hindsight kind of looks at the past, so you need to understand the past to understand where you are.

If you don’t understand where you are, there’s no, you know, you cannot even predict the future. You cannot anticipate the future because you don’t know actually where you are. It’s the same thing that if I make kind of if I put a blind on you, I take you to any, you know, uh whatever city, but like if I take you blinded all the way and if I just put you on on a on a alley in a kind of a random city, that would be really hard for you to know where you are, correct? >> Absolutely. >> So, you know, it’s the same thing. So, if you are in a company, you need to look back, you need to understand how did we get here? And only by doing that, you actually understand where you are because you need to understand your market positioning.

And then, this will actually kind of you’ll will be the the you know the the the I I kind of say the the the point of the cone of possibilities into the future because you need to know where you are, and then the cone starts kind of opening, and you start to see what are the options that open to you. But, the options that that are open to you also depend on your capabilities as well as on the environment that you are facing. So, the foresight for me, it’s one of the critical things that not that many people talk in competitive intelligence, but for me that’s the critical in like that’s the that’s the the what you want to achieve. So, you want to produce knowledge as I said in in the definition, right?

The when I say knowledge, I mean insights that are so good that are going to reveal themselves true in the future. Okay? So, if I have an insight, it’s like an hypothesis, right? So, if I say competitor one and competitor two are going to do a strategic partnership, okay? So, that in itself is an hypothesis, but I cannot wait for that hypothesis to actually to come true because if I act after they merge, you know, I’m I’m losing my strategic acumen, correct? So, I need to actually I need to develop that insight, which is an hypothesis, and that insight needs to be so good that I know that if I let it go, it will actually kind of a come true in the future, but I need to act now. So, I act on the intelligence, but what I want is the knowledge.

So, I want intelligence that’s going to be true in the future. Does it make sense? >> Absolutely. So, this is Foresight is not This is not a dress rehearsal. This is the real show. So, I I remember when one of our colleagues from the the the the fellows started a new job in strategic intelligence. And this person suggested, “Hey, we should look at STEEP trends, society, technology, economics, ecology, politics.” And or PESTLE, the British version of that, which includes legal. Um He This person was told um “If if you want to study things that don’t matter, you should go back to grad school. And >> I cannot agree with that. >> I agree. Like um but you know, and then they were It turned out that the creation of this strategic intelligence unit was a fraud in a sense.

They were actually told to go back through spreadsheets of past product performance and tell the the board of directors where they used to make their most money. >> Yeah. That’s like driving the car looking at the rear-view mirror. >> It’s trying It’s like driving the car from the trunk. >> [laughter] >> Or even >> And it was like and they were they were kidnapped, taken away from the actual intelligence function of the organization and um essentially gagged. But it made it look like there was intelligence going on. But then they were told they weren’t allowed to look at the future like at all. Like not even like 2 weeks in >> does not make any sense. Because you you cannot make decisions on the past.

You you only make decisions on the future. So that’s what’s connect when you ask what is the importance of foresight. That’s the whole thing because you cannot make decisions on the past. So if you cannot as I said definition, the idea is for you to increase or to improve the organizational performance. And the only way that you can do that is by making decisions. And the decisions are only made from the present into the future not not in the past. So there’s no point of You need to study the past to understand present and to actually kind of anticipate the future. But you can only make decisions on the future. So foresight is what you really need. So that’s the timely and the relevant just checking there.

And then [clears throat] they need to be actionable. So you know, it needs to be You need to be able to put that into a decision. >> But it’s easier said than done. You know, it’s it’s one thing to suggest that we want it to you know, we want timely actionable intelligence about the future and we want to put it in through a competitive intelligence framework, but not um you were telling me about um the Heineken meeting the standards for, you know, for best-in-class intelligence, world-class. Um you know, people ask me sometimes who has the best organizational foresight. I said, “Not just who, when.” Because Nokia used to. >> Yeah, yeah. >> Exactly. You can lose that. >> Yeah. >> You can lose it.

Coca-Cola used to have a nine-person um futures program at its corporate headquarters 25 years ago. >> Yeah. Not sure they have it now. >> And maybe they don’t need one anymore. >> I would I would challenge that. I would say they need it more than ever. >> I you know, I have there I’m a person as well. So, but speaking of >> How would that If If I can, Eric, maybe it’s a good idea to introduce this here. So, my my my approach is kind of a it’s twofold. So, you need to have really really good foresight, but you also need to have really really good real-time intelligence, which is something that I don’t hear anyone talked as well. Now a little bit more, but when I started kind of my or when I launched my SMINT approach, that was back in 2000, >> SMINT, would that be S M I N T?

>> Yes. So, social media intelligence, not social media. So, sorry, social market intelligence. So, the idea was it was the idea was to be social competitive intelligence, but the thint is not very good in terms of like, you know, pronunciation. So, the marketing gimmick, I put it I I it mark So, social market intelligence and mint because it was a fresh approach to competitive intelligence. So mint you know the the mint the small mint things. >> Yeah, sure. >> So mint the fresh for for people to connect to connect this and this was presented in in a skip conference in Dublin so 2010 something like this. >> Speaking speaking of how we we come together here as as a profession here where do you see the where is the the competitive intelligence profession right now is it doing well could it be doing better and where are we headed where do you think this whole thing is is going?

>> So we are worse than we were in the 90s mainly because in the 90s you had much more awareness to the to the to the discipline and to the profession. Because in the 90s you didn’t have the access to the data that you have now. So with the democratization of data uh kind of the the the the competitive intelligence I think lost a little bit of of not didn’t lose the value but it lose the awareness okay because like with with the internet basically everyone now has access to information so you know I didn’t need anyone to actually go and collect information. So the you mint actually kind of a lost a little bit of the of the of the not of the value again but of the of of the of the awareness or the perception.

>> I as a you know I started as a collector operative in the in the 1990s and I can give you a very specific example. >> Yeah. >> We used to get paid to go order through the United States Postal Service a mailed copy of the annual report of a manager. >> Yeah, yeah. >> And and to read it once it came in because getting a 10K report from the Securities and Exchange Commission >> Yeah, exactly. >> of a company took >> That was a thing. >> That was a thing and >> Exactly. >> So, I got I got paid to read stuff in the mail and go, “Oh, we have a We have a dossier. We have a client. All right. So, we got four companies that have been identified as our competitors. First thing, call or mail the investor relations.

>> Yeah. >> And then we would get We would get the paper documents. We would read them, summarize them, and we got paid for this. >> For that. Yeah, yeah. >> And that is something that can happen in 0.17 seconds now. So, >> Yeah. >> uh [snorts] It doesn’t mean you’re reading it correctly. You’ll still need guys like like me. >> You still need to make sense out of it, but now you have all the information in like, you know, in the time that you actually got that in the the the mail, now you like, you know, the information is outdated. >> That’s right. >> crazy. >> You’re expected to have the project should be over by the time the the the mail would have turned up. >> With the right, yeah. >> And there And there’s still the skill set I I still believe in, which is just because you have the document, who’s going to sit there and read the document go, “I think they’re lying.

I’m going to go ask somebody who knows.” >> [laughter] >> Yeah. >> Which is, you know, >> Who is going to read between the lines? Even AI cannot do that at the at this point in time. Yeah. >> AI can’t do it at all. They can I mean, it can >> Yeah, yeah, cannot cannot read between the lines. That’s what That exactly what I was saying. They cannot read between the lines. The AI can read the lines, but they cannot read between the lines or read the the tea leaves as like Ben would would call it. >> I mean, I I would say that um as I did not in a keynote speech very recently I said AI is very useful as a search engine and and as a pattern recognition engine but in terms of the information it gives you as a conclusory statement it has the confidence of a psychopathic serial killer.

It will lie to you. It will lie to you like a serial killer would like >> Exactly. Yeah, yeah. >> totally cold >> convince you that it’s talking the the truth exactly. Yeah, yeah. >> So >> That’s exactly [snorts] that that’s a really good definition. >> And when you go if you if you say back to this thing not and people don’t assume because it’s coming in paragraph form it doesn’t look dissimilar from when our friends are typing to us because that’s where the language tokenization and the the the ability to guess what the next word would be so it seems like language to us. We would never get angry at a spreadsheet being wrong. We would never get angry at Excel if we put together a formula and that formula comes with a certain output.

We wouldn’t take it that seriously. We would go oh the computer came up with this number because of the formula. It’s not telling me the truth. It’s giving me a number. But with AI people because of the language output people are measuring this against truth which is not what it does. >> Mhm. Yeah. There’s also another thing here you ask me about the state of of CI currently but you know the some so-called CI professionals basically do that. So they basically copy paste and they also do not provide an opinion. So and we need to also to make that distinction because one of the reasons of before you know the collection was very very valuable and only a few people had the skills to do it. So the good ones would bring the information in, they would know where to find the information and then they would be able to analyze the information.

So if you want if you go through the process of competitive intelligence you see that the value is kind of always moving into the next step. So you started with you know knowing exactly what the the the executives need or the decision makers need. Then you went into the into the planning, then you went into the collection and then you know human collection was a big big big thing. Now it’s a little bit more on the on the secondary but also you know primary is always it’s the cherry on the cake and it’s actually kind of you know probably also the the the the source that will actually kind of make the things really really valuable. And then now now you are going to into the stage of analysis. So now everything is focusing on the analysis and everyone is focusing on the intelligence.

But intelligence, artificial intelligence I mean, it’s just you know it just reads the line. It does not read between the lines. So the point that we were just making. >> I would even argue that it’s not reading the lines and if we’re going to continue the metaphor, it doesn’t know what it’s saying. It doesn’t care. It’s just an extremely good parrot, mimic, copycat. >> Yeah. >> Just it it’s like hey this sounds like this is what somebody who knows what they’re talking about would sound like. >> Yeah. >> And it doesn’t know what it’s saying. >> reason the only the only the only thing is that we as humans do not do not know as also as we think. So you you cannot say that the machine is not thinking because we cannot really we do not really know how we think.

Make sense? So >> Yeah that’s right. We don’t don’t know how we think. >> how we think. So we don’t like, you know, basically what what the machine does is that basically compares the text with other text and say, oh, they basically is talking about this, so probably the answer is that. And it’s all it’s all all about probabilities. But we don’t know actually how we think. So, I don’t know if the machine thinks or not. So, I’m I I I I keep myself neutral on that on that on that on that on that on that topic. >> They they keep saying that we are approaching something like sentience here, but >> Yeah, but you don’t know what sentience is, you know, it’s not well defined. >> sentience is in ourselves.

Why do we sleep? >> Exactly. >> The neurologists don’t really know. We know what happens when we sleep. >> When you sleep, you have to rest your mind. >> But why? No one knows. >> It’s it’s it’s like a cloud when it’s like compressing kind of a the the the context window. So, we are basically compressing what we’ve kind of a went through the day and then basically it stores in our mind. But that’s what it does, not really why >> Not why it does that. I did intelligence in the psychiatric medication field for some years and particularly schizophrenia medications. And every one of those drugs had in the label that the United States government put on the drug. Nobody knows why this works. >> It’s a black box as well.

So, you see, it’s very close to the to the algorithms that that we use every single day. >> Schizophrenia is associated with a high a high amount of serum dopamine. So, your neurotransmitter of dopamine as opposed to serotonin norepinephrine, your dopamine is higher in people who have schizophrenia and people who are hallucinating. If we reduce the dopamine, then we tend to reduce the reports of hallucination. >> yeah, yeah. >> We don’t know why any of this is though. And you know, and also so society is is a hallucination bad? Is this function of of the brain is it bad? We associate people that are diagnosed with paranoid schizophrenia as people that are kind of hard to work with and would be hard, you know, to have in charge of um a navy base or to be you know, a kindergarten teacher.

They might not show up the same time. Every They might not say things that are uniquely helpful or remember what they said yesterday. Um but is it bad? And anyways, the when when we’re talking about um cognition here, there’s many of these very financially interested parties who want to talk about their large language models as if they are a direct competitor to people who who sleep, eat, fall in love, um who dream, who think crazy thoughts and who, you know, have a thought in the shower and then come out to their meeting with a little different insight about >> But you know what we’re talking about. >> Yeah, we’re comparing this large language model to human beings. And sure, the people that have a financial interest in doing so say we’re this close to cognition.

And you know, I’m I I one of the themes I’m I gather that we’re that the fellows are going to do a a webinar that I’m going I’m going to be the moderator on next month about I think it’s human intelligence, human >> Human AI. >> Yeah. >> Personally, I don’t want to I I don’t want to bias this, but I don’t think AI is what people say it is so far. Like I don’t think um that you know, not only do I not think we are close to sentience with it, I don’t even think we know what sentience is. >> Yep. >> So, >> [snorts] >> uh so what are some of the what are the some of the things that you would like to get done in the intelligence profession? >> Mhm. >> Whether with the fellows or in your life or whatever.

What what do you hope to see? >> [snorts] >> So, basically I hope to see kind of a CI gain the recognition it deserves. That’s basically my I would say my my objective. Um that is like why I’m so proud to actually kind of being able to to to do the competitive intelligence science doctoral thesis. Which actually kind of a puts all of this stuff together. So, what I did was I defined CI and I defined CI on the shoulders of giants. So, basically on all the literature that existed before me. So, there’s that’s not my definition. That’s the definition of everyone that come before me. Then I developed I did an empirical validation meaning uh how good is the definition in terms of traction to the real world and I interviewed 61 experts from all different cohorts meaning you know, from consultants to CI software developers to educators to researchers to executives and to CI professionals.

Uh then I developed the the implementation frameworks meaning you know, how do I actually kind of implement this into into a a function, into a company, into a working function. I also kind of did a exploratory paper on the mindset. So, what should be your approach when you’re doing competitive intelligence, which I kind of recommended using design thinking as the mindset to to to do competitive intelligence. Um and that’s it. So, this is basically kind of the foundations. So, now there are a lot of other things that you can do. For example, developing an anthology that would allow us to actually kind of, you know, to even use AI in a much more efficient way when we are doing CI. Um that would also another project that we are doing on the CI fellows is actually kind of developing a curriculum builder, okay, or developer.

So, how do you develop the curricula that you need students to learn and professionals to to know so they can actually do proper CI when they go into companies or, you know, when they are in companies, how they can actually kind of improve that. Uh and, you know, there are a lot of other kind of a foundational initiatives that I’m kind of pursuing. And at the same time, this is basically the foundation and at the same time I’m pursuing the, you know, the the I’d say the cutting edge. And the cutting edge is the inter like the the the integration of AI with with CI. So, going to your to your to your future webinar and debate, my view on that is actually that there’s like for for you to do good CI in the future, you need to integrate AI.

Uh but you need to integrate that with the with the human which is called the natural intelligence. Okay, so natural intelligence is our capability of actually kind of a uh uh, reason and, you know, to to to come up with the with the insights. And that is my line of work on the cutting edge and you know, on on at the same level I’m working on the on the foundations so I can actually kind of a develop the cutting edge because without that it’s impossible. If I don’t know what CI is, I cannot kind of put the two things together, right? So if I don’t know what CI is, if I don’t know what AI is, I’m not able to kind of to explain what is the intersection of both and you know, what’s in what’s out of the scope and how the these two things actually kind of interact.

>> So it sounds like competitive intelligence professionals need to be the ones at the front of the line with CEOs and boards of directors to say, “Here is how to use AI for decision making because we are the experts in decision making.” We are the expert we are the experts in in in in furnishing information >> Exactly. >> on which you will make decisions. >> Yeah, yeah, yeah, yeah, exactly. So the the I call the the competitive intelligence professional the trusted advisor and there’s actually a book on that. Uh, so you need to be the person which is completely unbiased, okay, and that can support the the top decision makers. So if you go to the top decision maker, the CEO, the CEO is like the responsibility of the CEO is to make decisions, okay?

So he’s the he’s the ultimate manager of the corporation, of the organization. So his role is to make decisions. The role of the CI professional is to support that decisions with the proper actionable insights, with the knowledge so the insights that are going to be true so that he can makes the the best decisions possible given what is known and what is foreseeable. >> Got it. So thus CI has a future. >> Definitely. >> to be We’re still going to be serving the decision makers in years to come. And we need to both deal with artificial intelligence, but also help perhaps guide how it is incorporated. >> Yeah. >> And in your work academically and professionally, we understand how to discuss these things with with each other.

So, that’s why getting the terminology down is so so important. >> So critical. Yeah. >> Well, thank you. >> Otherwise, we cannot communicate. Yeah. >> Well, thank you for everything you do. And I appreciate your work and have for years and I appreciate being able to talk to you today. And I I’m looking forward to this and other discussions with our close colleagues in the Council of Competitive Intelligence fellows. And we’re going to have a lot of fun. So, we’re >> Thank you. >> Peter, thank you so much. >> forward also for your next next endeavors with the with all the other colleagues at the at the CI fellows. >> It’s It’s going to be a lot of fun. >> Thanks, Luis. >> Thank you.