Naji Gehchan: Hello, leaders of the world. Welcome to “Spread Love in Organizations”, a podcast for purpose-driven healthcare leaders, striving to make life better around the world by leading their teams with genuine care, servant leadership, and love.
I am Naji, your host, joined today by Moktar Diallo founder and CEO of Mangabey. Dedicated to transforming global pharma data interactions, Moktar brings over two decades of expertise in creating cutting-edge business intelligence systems, leading change management and transformative data architecture for multinational commercial operations. At Mangabey, Moktar leads a team of data and analytics experts, driving commercial data operations focusing on lean, open, and unified data ecosystems. Moktar’s impact extends beyond technology and operations; he is passionate about helping top-level business leaders navigate enterprise-wide change. Prior to Mangabey, Moktar’s successfully led Business Intelligence teams at Sanofi and Bristol Myers Squibb.
Moktar, It is such a pleasure to have you with me today!
Can you first share with us your personal story? What brought you to the pharma industry and being passionate about data in healthcare?
Moktar Diallo: Um, so first of all, thanks for inviting me to your podcast. And I’m very delighted to, you know, to discuss with you today and, uh, and share some of my experience.
Um, You know, starting with pharma, um, I’ve started in pharma 20 years ago, as you, as you mentioned, and it was pretty random. Um, originally I, um, before that I was working in data, uh, at some, um, after school, I had some interim jobs, um, You know, um, trying to, uh, basically earn my life. I, uh, I was kind of a dropout school.
Uh, I had the talent in, um, in computing that I’ve developed very early in my, uh, my life, very young. Um, I was good at school, but, um, when I left my home and, uh, and started to go to high school, um, I started to get prepared for, um, Uh, you know, engineering school, but, um, the level was too high for me in a way, uh, the pressure was really high.
I was far away from my family and, uh, and I had a kind of, um, kind of a dual, um, way of, of being. I could be very serious, really hardworking and very determined to, uh, to succeed in, uh, in getting good marks and, uh, and so on. But I was a kind of a rebel as well, um, and, uh, trying to, uh, to figure out what would be my, uh, my future, uh, in a different way.
And, um, so I left school and I started to, to earn my life working, uh, in different places and, uh, at some point in time, uh, I came back to, to data and IT, uh, working in different companies. Um, You know, I started to work at, uh, Shep, DHL and, uh, and different places, uh, that, uh, that would be, uh, you know, calling me for interim jobs.
And after a while, I, uh, finally started to work in, uh, in a pharma company called, uh, uh, Boots Healthcare. And, and Boots is a British based company, but they had an affiliate in France and we were selling, uh, uh, OTC products. And that’s where I started to, uh, to get accounted with, uh, with data, with analytics and, and so on.
Um, and after that, uh, the opportunity to work at BMS, as you mentioned, and go there, uh, in Paris, um, working with different affiliates, um, living to the UK for two years, um, and then back to France working for Sanofi. Uh, that’s where I’ve really, uh, uh, Um, you know, build my vision around what I was doing and the first thing that really struck me was The amount of waste of money that could happen in those companies to do something that was, uh, potentially, uh, you know, optimizable to an extent that was unseen.
Um, and, uh, I was seeing millions spent in project and so on where, you know, there would be opportunities to optimize and do a better job. And, um, And for me, we’re talking about, uh, the life of patients. We are talking about medicines. We are talking about health care. And the data was at the core of it. And, um, the, if you want, uh, the lack of, uh, of professionalism, the, the lack of, uh, of focus on making this data, uh, right and, uh, and optimize the cost managing it, um, coming from where I’m coming, you know, I’m, I’m coming from, uh, uh, very modest, uh, neighborhood.
Um, that was for me almost, uh, indecent to see this. And, um, and as I had a kind of a talent managing, uh, data, doing, uh, some IT work and, um, and building tools and algorithms and, uh, and, uh, and computing work. I dedicated my, uh, my time to, to improve that, generate savings and, and trying to do a better job than, than what I was seeing at the time.
And, um, and finally, after that, I’ve, I’ve made that my own business with Mongabay and, uh, the story.
Naji Gehchan: Well, thanks for sharing this. I’m intrigued. You said. Coming from mother’s neighborhood and you shared your upbringing and now leading data, a data company in healthcare, which that specifically it’s indecent to see how the waste of money and even practically the waste of data management and those large organizations.
Can you share a little bit more? Why what you saw and why you said it’s indecent and linking it to your background as you share it
Moktar Diallo: Yeah, I mean, it’s a strong word, but um, I wouldn’t say that now, uh, but back in time when I was 27 and uh, And I was trying to, to make my, my space. I was working really hard to, to build systems and, uh, and they were projects, um, similar projects around, uh, and people, they were almost building those projects to, um, to do the things, the way they were done, uh, and the things, the, if you want the way they, they had to be done, uh, in a, in a corporate environment.
So you set up a budget, you, you ask people, uh, to run a project and, uh, and distance to become very large. And, and basically doing data was a project, whereas people were working on data every day. And, uh, some of those people, they were building a real, uh, knowledge on how to do this in a way that was way.
cheaper and way more organized and those people, they were really undermined in the organizations. Um, so it was, uh, somehow it was me, uh, but, uh, the more I started to know about the organization, the more I was working with countries and different places. I was connecting with similar people. They were always the people in the middle of the organization, Um, you know, doing kind of 80 work data work, but that was crunching.
That was the way we were calling those people. The data crunchers 20 years ago. I mean, 15 years ago. And, um, and for me, that was, uh, it was difficult to see, uh, big companies coming and, uh, and running those projects for one year, two years. And at the end of those projects, people telling, okay, we, we tried, we learned a lot.
Yeah. We didn’t do anything with, uh, with those millions invested, uh, but at least we learned why those guys, uh, managing the everyday data and trying to do their best to automate and to serve their, their colleagues. They were very undermined. So this, you know, gap between we need data, that’s the shiny thing.
And, and the way people really working on it, we are treated on a daily basis. That gap was, uh, to me, um, a real, um, I mean, that was a real, uh, uh, issue.
Naji Gehchan: I love this. And it’s really what you shared since the very beginning, right? You’re a rebel and a smart, determined student. I feel within, within the work and what you, what you saw. there was this gap. So how did you deal with this gap? I imagine this is one of your leadership learning, working from corporations to now building a company where data is at the heart.
And certainly what you said is definitely true. Many times we talk about data, but at the end of the day, it’s, it’s, I love how you framed it. It’s a project. Um, well, our companies these days are more and more putting data at the heart of what we do and value it and really valuing it. But certainly for a while, it was more a project that someone would put and someone would stop.
So how did you deal with this to now building a company and what are your leadership learning along your journey?
Moktar Diallo: I mean, um, I had to be hands on. I had to go to the, uh, to the ground of, uh, of the needs. Um, to the ground of, um, of the data itself, I really had to go really to the level, uh, the most granular level.
Um, so I had to build very strong knowledge as to what is the data that exists? Um, what is the need that is out there? And what can I bring that is, uh, superior in terms of experience? Should it be faster access to the data, uh, best, uh, or better visualization? Um, fancy and, uh, an unseen, uh, indicator. Uh, I think that building that knowledge and that know how was really the base.
But the second is, uh, is to value the work you do the really, um, at that, at the time I started data was not, uh, the shiny thing that, uh, people are talking about today. Um, at that time, no CEO of a company would talk about data, no VP, no one would talk about data as such. And it’s very recently that this started, but at that time, no one was believing in this.
Uh, and, um, So I had to believe in that. I had to believe in the value of data as a piece of communication, as data, as a, as really, uh, uh, uh, basically the, um, the glue, uh, that connects people to each other in a modern organization. Um, really had to believe this and to see this very clearly to, to believe enough and suffer the way you suffer because you’re not valorized in the, on the work you do with data.
At that time, uh, that’s second and third, um, to work with early adopters. So I had the chance to, um, to work with people who were believing in this. So, um, uh, some, uh, some of my managers, uh, uh, uh, Delphine Aguilera Caron. Uh, Ron Cooper, uh, Daniel Kinney, uh, those people from different horizons, uh, some of them, uh, uh, French, but, uh, working in the UK, some of them US people because US guys are, are way more advanced.
In the way they see data than people in Europe as well. There is a cultural difference. Um, at that time, the U. S. was already quite advanced as well. Uh, versus Europe talking about data and leveraging data for for superior results. And I think those are the three elements really building the knowledge.
Don’t know how believing in, uh, in the in the vision, setting the vision and really be, uh, be loyal to that. Yeah. Vision and, uh, and, and third, uh, working with people who believe in you, uh, because you cannot, um, I wouldn’t be where I am today without the support of, of those key people I’ve mentioned and others, uh, a lot of others who share the vision and who love the know how.
Naji Gehchan: That’s a great framing, uh, Moctar. When you look back, really starting your company now, would you do anything differently?
Moktar Diallo: Plenty. Um, yeah, I mean, uh,
I think it’s important when you, when you start a company to really strongly believe in the value you bring on the table. Um, because when you strongly believe, uh, in that value, If you want to, um, you don’t, you don’t sell it in a way that would be detrimental to yourself in the future. Um, because you know, when you start a company, you’re not necessarily sure of the value of what you’re doing and you get a customer and, uh, and when you start to have a customer, everything the customer is telling you is, uh, is, is incredible.
And you don’t necessarily protect yourself of the consequences of some of the lines in some contracts and, uh, some, um, if you want, um, behaviors that you undermine and so on, um, and the return to reality can be very, very difficult to manage. So I think it’s important to really strongly believe in the value to be proud of it.
Uh, and protect yourself as much as possible. It’s not easy. It’s easier to say that after you started and, and, and seen the issues, but at least it’s important to be conscious of the weaknesses that are there, uh, in the relationship with, with clients, uh, as opposed to discover them, uh, down the road and, uh, and be a little bit naive.
Naji Gehchan: So let’s talk now about data. Your company focuses on lean, open, unified data ecosystems. Can you help us understand what do you mean by this? And what is your personal vision and beliefs around data?
Moktar Diallo: So, you know, the data we’re working with is, uh, the data is like a fluid. It’s like, uh, it’s like water. Uh, it’s like a liquid and something that needs to be consumed. It, it, it comes from different sources and, and gets together, uh, at some point in time for basically feeding, uh, you know, business insights and, uh, and actions.
Um, and to correctly pilot an organization, which is supposed to be one body. You need to assemble all this knowledge. That’s the basic thing. You need to assemble all this knowledge at some point in time. And an organization has this magical effect of, of moving different parts together. Um, but, uh, but you know, the brain is centralized somehow in an organization.
So the brain at some point in time needs to receive all the information. You can have the arm, the legs, the everything moving around. It’s important as much as possible to be able to concentrate that information. So I, I’m a strong believer in, uh, in data unification, um, as opposed to, uh, uh, data silos. And one thing that, uh, that happens when you have silos is that, um, instead of, Of having, uh, data being a tool of performance, which it is when it is, uh, transparently shared and, and, uh, and, uh, you know, assembled, it becomes a, an instrument of self power when it’s remained, uh, in silo and so on.
So people tend to keep the data for themselves. Because they, they believe that, uh, this piece of intelligence is what makes their work more efficient. And I think it’s not a modern idea. Uh, we are, we are, uh, more and more, uh, changing that. And technology as well is, is pushing for a different, uh, path. We see, uh, generative AI.
Generative AI doesn’t work with, uh, um, with big data. It works with diverse data. The more diversity you have, the, the, the better the intelligence can be. And that’s, and that’s, uh, diversity comes from assembling data from different pieces of the organization, as opposed to keep them in silos and, and, uh, where they basically, uh, uh, stay a little bit poor, uh, we can say the same for human being and all those things you need to, you know, mix, um, uh, informations for, uh, getting the, uh, through, uh, richness.
Naji Gehchan: I certainly agree with this. It’s fascinating how much data is actually siloed, you know, within our organization. And when we think about healthcare, the non connectivity of the different data, you know, I’m thinking back when I was chief marketing officer and we’re starting to do some pool databases and the complexity of making data connect.
And more recently, in France, I’m sure you’re aware, all the work the government is doing to connect data and have some medical shared platform and databases and the complexity of doing this, even though We would argue the assurance maladie, so the healthcare system in France has all the data for us, but still nothing is talking to nothing for us to be able to predict and do better healthcare.
Any thoughts about those? And probably Pivoting from this to what’s exciting about the future if we get to a unified, uh, data system.
Moktar Diallo: Yeah, it’s, um, it’s incredible how, um, artisanal, um, how, um, uh, how much crafting is behind data. I mean, people don’t imagine how much it is of manual work, of, uh, uh, human interaction to make, uh, to make sense of even raw data and build those assets.
I think that’s, uh, that’s something that people don’t necessarily realize that it is a tedious work to, to do. To create a database, to, to work on it and so on. Uh, we tend to see the really, the the last piece, which is the, the insights and the, the, the moment the data is, is refined. Um, and that’s what is, uh, is incredibly important, is the fact that it is a real effort.
A real conscious effort to make this happen. It won’t happen. Um, automatically, um, we, we work at Mongabay. We work on a lot of strategies to make that happen, to facilitate that transformation so that, um, it’s, it’s effortless if you want, but, but the reality of the work of data management is a really tedious work.
Um, especially when the data doesn’t have. Uh, the same format, uh, especially when the data hasn’t been built in a way that it would connect automatically with the, all the other pieces, all this work of unification or stitching together different sources of information is something that needs to be done.
Even that work needs to be done in a certain way. There are sciences to transform organizations and drive them towards the unification of their information systems. It’s not only an IT work that says, okay, we’re going to take a database, uh, you know, like, and structure it and make it happen. Um, if it was only this, the organization would be completely aligned for decades.
Naji Gehchan: Yeah, no, for sure. And I, and as you said, like, this is the, the heavy work that needs to get done. All executives, we get excited with like, Oh, we clicked on something and we saw it right. Like data visualization is obviously what excites us. And you know, you get. Whatever you need as an info, but really realizing the value that companies like yours or internal teams that work on those data to make sure that this data is relevant.
Well done. You have categorization. Well, all the things that you guys do is many times, as you said, in the very beginning of this episode. Many times not valued or not even seen. And it’s all the people actually working to make sure that those are relevant, clean, correct, in the right categories, well transcripted, etc.
is a key part for you to be able to visualize fast and most importantly to get the right vision to make the decisions.
Moktar Diallo: At the moment, just to rebound on that, at the moment, we, we start to see the masses as this is a subject that starts to be interesting for organization, we start to see the masses around what’s the cost of data.
Um, how can we maintain. Especially in the post pandemic where, you know, costs needs to be reduced and data is exploited because of digitalization and so on. We have an explosion of the amount of data to be managed by the organizations. And at the same time, there is a need to reduce the cost of this data.
Data represent 5 percent of the revenue of companies. So that’s a huge amount of, uh, of, uh, of, uh, Of basically financial transactions around data acquisition around data management around data consumption, and that needs to be kept at the level that that allows, you know, to basically maintain and contain the explosion of this data, and that becomes a problem for organizations to make sure that they can still.
Uh, you know grabs the the the value of data because if data goes in silos We discussed that before you cannot really grasp the benefit of it But the cost of putting that together is so high that you need to work on Optimizing that cost so this is becoming a very strategic issue for Not only for pharma, I would say pharma perhaps a little bit more than other industries, um, but this is a real general problem for, uh, for any organizations.
Naji Gehchan: So I’m going to give you now a word. And I would love your reaction to it. The first one is leadership.
Moktar Diallo: Loneliness. Oh, say more. For me, leadership is a lot of loneliness, um, thinking, thinking, thinking, um, and, um, and that’s, yeah, that’s the first reaction that I felt, um, about leadership. Um, you listen a lot, uh, you think a lot, um, you, you suffer a lot.
But meanwhile, it’s extremely rewarding.
What about change?
For me, change is bringing joy. I think there is nothing more important than change. Change is what makes people go further. You know, the routine of things is what is slowing down. So sometimes we need to slow down and enjoy the routine. Uh, but change is really for me an accelerator,
health equity, um, you know, have my roots in, uh, in Africa. Um, so, uh, I think that, uh, there is a duty, uh, human duty to bring health everywhere on earth. Um, and I believe this is, uh, one of the missions, uh, we would love, uh, uh, pharma, perhaps being a little bit more, uh, Um, vocal about, uh, and that’s, uh, that’s something that is still, uh, you know, a coming issue.
Um,
Naji Gehchan: do you think data and all that we’re saying generative AI, all the access to, to, to those preventive and also predictive? Models to better health care will help from this or do you see it as actually the data that we have is not representative of all the communities and the word and thus is biased by itself.
How do you think about those?
Moktar Diallo: We talked before about the fact that data should be raw data or intelligent data because at the end You know, it’s recycles. So, you know, what we, what we get from GPT is new data that can be used to feed another system. So data at the end, as we said, uh, if it’s in silo, uh, it will be an instrument, if it’s transparently shared, it will be a tool of performance.
And, um, and as the same for, uh, for, uh, you know, the, the most, uh, advanced way to, uh, to produce data. Um, if it is shared, um, it will become a good thing to spread more equity, more, let’s say, um, really to bring more power to empower people who have not necessarily the capacity to, uh, to get access to data.
So I think it. It goes in the right direction anyway, uh, there are dangers to it. But, uh, at the end of the day, we talk about sharing knowledge and, uh, knowledge is, uh, the most powerful, uh, um, let’s say asset of, uh, of any human being.
Naji Gehchan: The last one is spread love and organizations.
Moktar Diallo: I mean, transparency is extremely important. That’s the way I see it, uh, to have the courage of, uh, of being transparent and honest. Um, I believe is the base for, uh, for, uh, healthy and sane relationship. Not always easy, not always easy. You don’t do this. You don’t do everything day one. You know, uh, even love needs to be built, uh, as well, uh, because, uh, we, no one is, uh, they won’t, they will never be perfect love.
They will be always people learning to, to live with each other. So, um,
but I think transparency is a, is a good way to, uh, to accelerate this
Naji Gehchan: and your final word of wisdom, uh, Mokhtar for healthcare leaders around the world.
Moktar Diallo: I mean, for me, uh, I strongly believe about, uh, the fact that, uh, the models organization will be clear about their data, the more they will be doing, uh, best decisions, good decisions, um, healthy decisions, uh, as opposed to, uh, To, you know, fill the gaps with, uh, with, uh, guess second guess and, and biased, uh, point of view.
Uh, so, you know, understanding the data, sharing the information, the analysis, and, uh, and, uh, having an unbiased view on everything, um, is the, the, the best way to, uh, I believe, uh, be a good leader.
Naji Gehchan: Well, Moktar, thank you so much for being with me today and for this great chat.
Moktar Diallo: Thanks, Naji. Thank you so much for the discussion.
Naji Gehchan: Thank you all for listening to SpreadLove in Organizations podcast. Drop us a review on your preferred podcast platform
Follow us on LinkedIn and connect with us on spreadloveio.com. We’re eager to hear your thoughts and feedback. Most importantly, spread love in your organizations and spread the word around you to inspire others and amplify this movement, our world so desperately needs