Building Trust in a Globalized World: Data, AI and Human Connection

In a world of increasing complexity, building trust across cultures has never been more challenging—or essential. Shahar Silbershatz and Axel Löber share insights on how global CCOs can navigate cultural nuances, leverage AI and data and foster authentic stakeholder connections. Listen to the conversation to hear how human connection remains at the heart of effective communication, to help build trust with stakeholders, in an AI-driven era.

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to help build trust with stakeholders

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Transcript

[00:00:00] Eliot: In today's globalized world, CCOs must navigate a landscape that is as complex as it is diverse, engaging stakeholders across regions with unique cultural, political, and social contexts. Think of it like a Venn diagram, where one circle represents what stakeholders care about, and the other what your organization wants to convey.

The challenge lies in finding that sometimes narrow but essential space where the two overlap. In essence, this is the shared belief that the Page Model argues is the starting point for building trust with stakeholders. In this episode, Shahar Silbershatz, the founder of stakeholder intelligence firm Caliber, and Axel Löber, the Chief Communication Officer at Merck KGaA, Darmstadt, Germany, share their strategies for how to keep humanity at the center of comms to build trust with stakeholders in this AI powered world. I'm Eliot Mizrachi and this is The New CCO.

Shahar, How would you introduce yourself to somebody at a cocktail party?

[00:01:11] Shahar: well, I'm ashamed to admit that I do sometimes start with my profession rather than myself outside of my profession. So I say that I, I run a stakeholder intelligence firm here in Copenhagen called Caliber, and I work with the companies worldwide to make them more trusted. But of course, I'm also an individual outside of work.

So I talk about being a husband and a dad, and probably mostly about being a curious person who have lived in many countries, likes to travel and be inspired by things. people from different cultures.

Eliot: Axel, let's turn to you. The drinks are flowing. You've met somebody new at the cocktail party. Introduce yourself.

[00:01:48] Axel: So having my gin and tonic, uh, in one of my hands already. I'm, I'm actually, I'm Chief Communications Officer at  Merck KGaA, Darmstadt, Germany, which is a science and tech company.

Based, in the middle of Germany, actually, but, active globally. Um, and yeah, privately I live in, Frankfurt, love good food, good books, and, I have traveled to seven continents already. And my big objective is now to fill the white space in between, all of that. So seeing a lot of the world in the next year.

So that's still my, it's my private assignment.

[00:02:24] Eliot: Shahar, You know, this conversation will be you. Around understanding and engaging stakeholders. you mentioned that your focus is on stakeholder intelligence. You recently published some research on the increasing importance of data driven communications in a world that's complex and rapidly changing.

Can you talk about, what you mean by, data driven communications and how that relates to our ability to understand stakeholders?

[00:02:49] Shahar: Sure. Thanks for the question. Um, you know, the complexity part, of course, we all know, right, the world is becoming more complex in so many ways, whether it's macro events, geopolitics, economy, polarization. There's a lot of things that are happening that that are making it more difficult for all of us as citizens to navigate our world, but also difficult for us as companies to navigate. And I think one of the main things that is changing is that, companies are part of this much more today than they were in the past. So people are expecting companies to have an opinion, they're expecting them to weigh in. employees expect it, external stakeholders expect it.

So companies have to do a lot more thinking about how to navigate some of today's, uh, complexity. What we're seeing in a lot of our research is that on one hand, trust is very, very low. We're definitely seeing that all over the world, in the U. S., in Europe, trust in institutions in general is very low, all institutions.

Trust is actually especially low when it comes to big corporations. people trust, uh, you know, mid sized businesses, small businesses, community businesses. But when it comes to global corporations, people don't trust them. So that's one of the things that we're seeing where companies are challenged.

We're also seeing in particular industries that there are a lot of issues that are affecting people's perceptions of companies. They expect certain problems to be addressed by companies, even if those problems are not necessarily related to the industry that the company is operating.

And what we're seeing also is that when companies do a better job at listening to their stakeholders, they're much more likely to be trusted. in our world, this means, um, stakeholder perceptions and analyzing it and using it as a fact base that informs our communications and our engagement as a company They're much more likely to basically come across as being credible, and therefore they might win . more support from their stakeholders in the form of loyalty, in the form of preference, in the form of advocacy, and many forms of support that businesses need in order to thrive.

[00:04:43] Eliot: So one of the things I hear from our member CCOs from time to time is, a decade ago, more than that, probably 20 years ago, there was just a dearth of information. And so listening was more straightforward. And today it's quite the opposite, that there's so much access to data that, that filtering out the noise and finding the signal is the real challenge.

You mentioned listening, um, To stakeholders and understanding them as a way to build trust. How do you do that? How do you figure out which data, what the data is telling you and how to decide how to apply that intelligence?

[00:05:15] Shahar: Yeah, and that's, that's, the million dollar question. I think the, the problem, of living in this world of, uh, infobesity, is, is really how to distill the information that you need and how to act on it.

Because we are all drowning in, in information and data. In our world, part of this was, of course, exacerbated By the advent of social media because you have so much access to so much information in real time and it can be very Um, bewildering. I mean, it can be very overwhelming to listen to all this amount of data.

Our listing is a bit different. We believe in actually conducting interviews with stakeholders so that we have a little bit more control on the representative nature of the audience that we're listening to. The problem with social media is quite often what you hear can be very, very noisy. And can seem very opinionated, but it actually isn't representative of your relevant stakeholder universe.

So sometimes you might be driven to make the wrong conclusions or take the wrong action based on very extreme voices, not necessarily the voices that are relevant.

This is part of our solution to the problem. The other part, of course, is as a, as a corporation is to have The means, the resources, the talents to be able to, um, connect a lot of data sources. and analyze them and draw conclusions. That's one of the challenges we're seeing on the, uh, on the corporate side that communication departments don't always have the data analysts internally.

But, but sometimes we're seeing that when they take them on board, um, they can actually do a better job at distilling all the information sources to actually connect the dots and make the right decisions. So this is not obviously giving the formula here, but this is some of what we're seeing is happening in the industry to be able to better, um, make decisions based on a lot of data points.

[00:06:57] Eliot: So, so kind of like public relations itself, it sounds like it's a blend of art and science.

[00:07:03] Shahar: I would definitely say it's a blend of art and science, and this is probably we're going to talk about AI today as well, and this is where it's interesting because AI helps a lot with the analysis of information, but it doesn't always help you know which which data sources are more reliable and what is the decision you need to take based on the data.

I think it is very much a mix of science in terms of having the skills to analyze data. and having the tools to collect data and the right data. But then it's also the skills of understanding what's important for you as an organization and what kind of decision you need to make. And that is a little bit more the art of it.

[00:07:34] Eliot: Axel. we're talking about the overwhelming amount of data and managing diverse sets of stakeholders. You're in a business with three lines of business operating in three major markets. So I would imagine there's a lot of customization of the engagement and message depending on where you're operating.

Well, it's, uh, it's kind of a dance of complexities, uh, I guess. So we have three businesses, 65 markets across the globe we serve, with very, very different stakeholder groups and cultural contexts. That's also a layer, which we must not, must not forget.

[00:08:07] Axel: The question for me always is what is relevant to our stakeholders? First of all, you need to be, of course, be clear who are your stakeholders, where do they sit and what are their wants and needs? It's a bit like in marketing and I have, have a. Past in, in, in marketing, served as a chief marketing officer before.

So you need to have that clarity beforehand. Who's the stakeholder? Where do they sit? How can you segment them? And then it's the question, what are they interested in?if you see there's two circles, one big circle is what are your stakeholders are interested in? The other circle is what do you want to say?

Both can be a lot. The question is how big is the overlap in reality? It's quite small because let's not forget. You mentioned it. Um, people outside are at the moment, facing a tsunami of information, a tsunami of messages. And, that leads in many, many cases to some mental overload. We all might have heard of people who say, well, I don't listen into the news any longer because it's a bit too overwhelming.

So, um, how do you find this, this little space of overlap then? in which relevance sits. I think that's the, that's the, that's the interesting question. And, Shahar, I agree. you need to drill down a bit deeper into your, target audiences, have conversations with them. And then also, To be honest, you have to be careful between what they say and what they do.

This can be two very, very different things. So to your question, I think stakeholder understanding in depth, stakeholder understanding is important in the first place.

And then it might be a bit of a, of a trial test and trial thing to find out what is working, what is not working, can be very different depending on country it's kind of a learning thing. an iterative process to come to that point where you come closer in finding that overlapping thing between what you want to say and what stakeholders want to want to hear.

[00:10:03] Eliot: would imagine that Venn diagram that you're describing, it's not just two rings, right? Because you've got different countries with different cultures and different languages and different biases. And so that creates a lot more complexity and presumably makes the overlaps even smaller. the point that you're making as a marketer, I think it's fascinating that there's a personalization component to the way that you engage them. How are you thinking about how to meet people where they are in in terms of their different, um, cultures and biases

[00:10:32] Axel: So, you might come to a difference to marketing. Marketing usually has a much more clear data set and usually has a much, much clearer understanding on what's going on. On what is the outcome of what you do because you will see it in sales You will see it in click through rates and all of that comes is a bit further away Um If you work in in a large matrix organization, like I do, I rely heavily on my colleagueson the experts on the ground.

So something that is working in Germany might not work at all in the U S and definitely will not work in China. So you have to find to create an understanding of what is it, what you want to achieve and balance it. Constantly with the local view and it starts with very technical, seemingly boring stuff like which channel to use.

Yes, you can have a wonderful campaign that works on, let's say LinkedIn in the U S try that with China. So LinkedIn doesn't work there. So you have to, to find, to, and to adapt to the different, different channel, also different tonalities. So you need a lot of, a lot of flexibility. It is one size fits all just doesn't work.

Um, And that is a bit of the problem because if you work in a large international organization and maybe have a central role, You try to make things simple, but that doesn't work out. So, and you need this kind of, this balance of giving a clear direction, have a clear understanding of what you want to achieve, but at the same time, be flexible in how do you do it then on the ground in the country with a specific stakeholder segment and so on and so forth.

[00:12:10] Eliot: So Shahar, I would venture to guess that the challenge that Axel just described is one that you hear frequently from clients and data driven communication is the way that you address that. how might you leverage the tools and approaches that you apply, to engage stakeholders in the way that he's describing?

[00:12:32] Shahar: I think this challenge, you're right. We hear it, across the board, especially for multinational companies, because I think what the challenge that they face is this balancing act between having a corporate narrative that is consistent across countries, across stakeholders, and supports their business strategy, of course, on the one hand, and then on the other hand, they need to balance that with being .

Local localized in their communication based on, as you said, the actual the channels, the messages, the expectations, that the data really helps with that, because the data helps you. First of all, understand what are the issues across the geographies and stakeholders. Just as an example, if we're talking about the life science pharma world, in a recent report we did on the pharma world, we talked, we asked a lot of questions about the weight loss drugs that are now being a very big influence on the pharma industry.

Okay. And the perceptions that people have in different countries are very, very different. in China, people, for example, see, weight loss drugs as a way for the industry to help solve a global health crisis. They actually do believe that there is a chance here to use the power of pharma and a new medication to solve a global health crisis.

In the U. S., people will be more likely to think that this is a way for the pharma industry to take advantage of a global health crisis. That's a very, very different approach, and that would require you to tailor your communication in different countries according to that.

what we think is that data helps you, narrow down what are the key issues and key expectations across the regions, and then helps you make decisions on how to tailor your corporate narrative, which should stay consistent, global, and supportive of your strategy, to those global concerns, to those local concerns and local needs, and sometimes even local channels.

[00:14:13] Eliot: Is AI one of the ways that you help achieve that kind of customization?

[00:14:19] Shahar: I think AI, um, the problem with AI is that AI can be a friend and AI can be a foe.

But I think what A. I can help you do is it can sometimes help you accelerate the pace at which you respond to things. It can help you sometimes, especially with content generation, of course, but not just that.

In many, many ways, A. I can help you as a small team. And we know that corporate comms usually is a smaller team than the marketing team. They don't always have all the resources and all the talents that they need to operate effectively. And now they need to be much more agile than they were before. They don't always have the capacity for that.

AI is a great help. it allows you to create variations of communications very, very quickly, for example, so that you can tailor it for different needs, different audiences, different geographies sometimes, much faster than you would otherwise.

And in that sense, I think it helps companies and helps help them be quicker. The danger of AI is sometimes and we see that, by the way, when we speak to CCOs on our own podcast, we also speak to CCOs around the world, and we see that one of the major issues that they deal with today is is actually how to weigh in on public debates when there are discussions regarding macro events and typically, you know, political issues, social issues, sometimes very sensitive issues.

And, AI is not going to be helpful in that context. And using AI can actually backfire. So in many cases, it's very important to understand when do you have to rely on the people in your organization to give you a diversity of opinions that can help inform your decisions. A decision by a CEO, whether to speak out on something or not, that is a very, very sensitive human based decision.

that's a decision where AI is probably not going to help you so much versus something that is a little bit maybe more technical where you can actually act quicker by multiplying a certain message in different variations, where technology can help you do that.

[00:16:06] Eliot: Axel Axel, I can almost tell that you've got thoughts on this topic. What are you thinking?

[00:16:12] Axel: So, um, a big fan of AI, especially as I work in a company that's very close to the semiconductor industry. And so we are at the, at the source of it from the material side, from the hardware side, if you will. Um, for me, what I've been reflecting as a chief complications officer, um, that is AI for me in our daily work is a, is a three fold, Turbo, if you will, for creativity, for efficiency, and also for quality.

Having said that. It is an enlargement of our brains and not a replacement for our brains. So I would, I'd see it like that. It's a tool, like every tool. The question is, how do you apply the tool? If your expectation is that you can sit back and relax and enjoy the ride. Um, good luck. It's not there yet. If you see it as something that.

Expands your wingspan, makes you more agile, more quickly in what you do, enhances your quality. I think, it's, it's a very good thing to do. Um, the big watch out I would have at least by two, the one is the ethics of it. So when to apply, when to also, disclose that you are applying and don't find this easy to answer because do you disclose, well, we have used AI here in, in comms.

Well, you don't. You don't disclose that you have used a search engine when crafting, uh, uh, crafting a text. So where's the fine line here? Not sure yet. The second one, and I discussed it literally yesterday with our chief AI officer in the company is the data quality and how we are here in the question of, of data again, is data clean?

Is data usable? Is it comparable? Is it, is it, Is it able and able, does it enable you to compare apples with apples and not differently, because that is a bit of a challenge, whatever you have with a kind of commodity, I mean, that's easy to have, but the input, the data input you have that needs to be. That needs to be really, really considered.

And I sometimes think we as a profession might learn a bit more to raise the bar here, uh, on how do we look at data? How do we use data? How do we model things? Um, are we always sure that things are correlations or causations? For example, that's a very fine distinction between the two, but a very big one, actually.

So these kinds of things that is, I think super, super important. And that would speak for having, data experts. On the team also in, in comms as an enrichment of our profession, uh, and enrichment of our teams

[00:18:54] Eliot: so this conversation, you know, we're talking about data and message testing and AI. I want to bring us back actually to the first thing that Shahar said at the beginning of the conversation. It's about building trust with a diverse set of stakeholders, engaging them as individuals to the degree that it's possible.

And Axel, you started out talking about just the diverse range of your stakeholders. How do you think about Building trust in that context.

I think comes remains to be, um, people's business. So, um, how do you create trust between human beings? It's about creating a human connection. And I think that's the sweet spot, which AI will not take away. Um, there might be some conversations in our profession at the moment about well, will AI take over?

[00:19:43] Axel: Will it replace people in comms? Not so sure about that. Uh, maybe it might replace people who can use, can't use it, but the creating a human connection that comes, that comes first. And then it might be the old truth of just explaining, be transparent and, and, Give a reason for what you do. So for example, taking, taking my own company.

we are still active in Russia. There's a very simple reason for that because we are also a healthcare company. So we serve patients, human beings with our, with our medicine, there would be a problem for human beings. And this is a responsibility we have. If we pull out, that has an immediate effect.

on people's lives.

And I think, that can also help creating this trust when companies live up to that, to that responsibility where they have it and the important pieces. And we just talked about it, explaining it, making transparent what we are doing, why we are doing it.

Um, and give a reasoning. I think, we all We all might agree that it's important to treat our stakeholders as grown ups and adults, people who can have an educated conversation. I know sometimes it doesn't feel like that if you look into the news these days, but, that's my, that's my strong belief.

And this is the starting point for, for, for building, for building trust. And not everyone might agree with every decision. That's also okay. Um, as long as you can have an explanation and, create reasoning. behind what you, what you have decided.

[00:21:23] Shahar: I would just follow up on that if I may, because that point that you made, we, we definitely found that to be true, that, um, one of the things that we measure, using data analytics is not just, where to build trust and what to focus on, but also what drives trust primarily, across different stakeholders and regions.

And, almost without fail, we find that authenticity is one of the things, drive trust the most across geographies and across stakeholders. So people want to perceive the company is being authentic in order for them to trust it. And authenticity is very hard to achieve by using solutions like algorithms and A.

I. So actually, I think With the rise of AI, the importance of the human voice and the authentic voice of an organization grows.

[00:22:08] Eliot: I love that you made that comment because as Axel was talking a moment ago about the choice of doing business in Russia. You know, you said we're a health care company and it's about caring for human beings. And as you said that I was thinking, this is a decision that's based on the organization's values and purpose.

and while you might have done someanalysis on how will this play out? this was a choice that was made for those reasons. caring for human beings.And how much did an analysis of what the implications of that decision would be, play into it?

[00:22:43] Axel: actually it was not. with the company at the time the decision was made. But, if you think about it and that, that is true, I guess, for every company who has a healthcare business,like we have all is pure play healthcare. your decision has an immediate effect. We are not talking in this case about consumables, where it's nice to have it or not in this case, that's a matter of, uh, So it's very, very personal.

Making this transparent, um explaining, um, the, the gray zones. we sometimes might find ourselves in. That is important. And I know it's hard. We live in times where many people are looking and seeking actively for easy answers, in a very complex world.

Um, I'm afraid, I'm not sure if these times ever existed, but we are definitely not living in the time, in times of easy answers. so we need to find ways to have that educated conversation. Listening is an important part of that. And here we again, back with data, but also human listening, really trying to understand the person, not only the algorithm, but also the person on the other end, what is the interest, what is the starting point and, and then start to have a conversation, very old school values, if you will, but, maybe even more important, in these days,

[00:23:59] Eliot: So we're a membership of chief communication officers and other senior communication leaders. what is your word of advice based on the conversation today? for how CCOs and other leaders should be thinking about data and AI And trust and authenticity. So let's start with you.

[00:24:20] Axel: One piece of advice would be break out your own bubble and try to avoid or at least to overcome your own biases. I had the wonderful opportunity a couple of months ago to, to visit my, my team in, uh, in Shanghai, in, China, and it connected to a couple of colleagues from the Page Society.

So we actually connected their, colleagues in China from other companies I never had met before. Um, that was. incredibly helpful because it gave me a different perspective on the world, deeper insights on what's going on in a different part of the world, which enriches, hopefully, my own decision making in all aspects.

And which also challenged my own biases I have in my thinking. All of us, we all have, our biases and they sometimes are the biggest, the biggest roadblocks we also carry around with ourselves and overcoming them, breaking them, avoiding them, at least reflecting that I have the biases and try to manage them for me would be the, the, biggest advice.

As we have this broad role, as we have these international roles, as we have to think beyond the horizons and connect the dots in our organizations, you need to have that broad view. And so you need to remove everything that is blocking your broad view.

[00:25:45] Eliot: Yeah, and be open minded. You know, the insidious thing about a bias is, you know, you often don't know that you have one.

[00:25:52] Axel: That's

[00:25:52] Eliot: Uh,

[00:25:53] Axel: That's exactly true. And it's a normal psychological, phenomenon. So it's, it's built in, it comes as a standard, so to speak. so, that is, uh, I believe the At least one secret recipe here.

[00:26:06] Eliot: yeah. Shahar and you?

[00:26:09] Shahar: I think that one thing that distinguishes communication leaders from other leaders in the company is that they have a dual, almost contradictory role. Because I think on one hand, CCOs, they represent the company to the world. But on the other hand, they represent the world to the company. That's a very peculiar, contradictory nature that no other executive has in the organization.

And I think in order to be successful you have to be both curious, All the time. You have to remain curious. curious about other people. Curious about other opinions. Curious about, where the world is going and what's happening that might affect you. And curious to understand new skills and talents that you might not have and your department might not have in order to keep evolving.

Curious But at the same time, be confident. Be confident that you are the only one in the organization that can explain the world to the organization. Nobody else can do that. They're all focused on their niche. You are the one who can do that explanation. That's why you deserve a seat at the table.

That's why you, you need to be an advisor to the CEO So I think this nice duality of curiosity and confidence, is the trick.

[00:27:13] Eliot: Well, I think that's a great place to leave it. Thank you both so much for your time and sharing all this wonderful insight. It's been a pleasure.

[00:27:19] Axel: Thank you very much. Really a pleasure to have that conversation. My most favorite meeting of the week. Thank you.

[00:27:26] Shahar: Same here. Thanks a lot, Eliot. It was great to be here.

[00:27:34] Eliot: As this great conversation highlighted, effective global communication is about finding that small, but crucial overlap in the Venn diagram, the shared belief on which trust can be built. Shahar and Axel reminded us that while data and AI offer incredibly powerful tools, The heart of communication remains human connection and cultural understanding.

Thank you for joining us on this journey across regions, industries, and ideas. Don't forget to subscribe to The New CCO for more stories that explore the evolution of the CCO.

 I'm Eliot Mizrachi, and this is The New CCO.