Biotech Bytes: Conversations with Biotechnology / Pharmaceutical IT Leaders

How to Align People, Process & Technology for Real Impact with Irina Dymarsky

• Steve Swan • Episode 29

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How to Align People, Process & Technology for Real Impact #digitaltransformation #aiinbiotech #businessstrategy 

Too often, companies jump into new technology without addressing the real challenges holding them back. The key to successful transformation isn’t just about the latest AI tools—it’s about aligning people, processes, and technology to create real impact. Please visit our website to get more information: https://swangroup.net/ 

In this episode, I sit down with Irina Dymarsky, an experienced technology leader in biotech and pharma, to break down:

  •  Why defining your business “why” is critical before adopting AI
  •  The biggest mistakes companies make with digital transformation
  •  How to build a data-driven culture that supports long-term innovation

Irina shares her deep expertise in business and IT alignment, the importance of data governance, and why companies must be strategic about AI adoption. This conversation is a must-watch if you want to drive real digital transformation in biotech or any industry. What do you think is the biggest barrier to successful digital transformation? Let’s discuss this in the comments!

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🔎 Related Phrases:

Driving Real Impact, Aligning People, Process & Technology With Irina Dymarsky, Digital Transformation Strategy, AI in Biotech, Aligning People Process Technology, Data-Driven Innovation, Technology Adoption in Pharma, Operational Transformation, Biotech Digital Strategy, AI Implementation Challenges, Business & IT Alignment, The Future of Biotech AI


#digitaltransformation #aiinbiotech #businessstrategy #datadriven #pharmatech #innovation #technologyadoption #aiimplementation #biotechgrowth

Irina Dymarsky [00:00:00]:
And what AI can't do is draw upon experiences that it doesn't have loaded into its model. Right. So like going back to its people, its process, its technologies, industries, it's all of these different experiences that you as a human being can translate. The AI is going to be challenged with that, at least now. I mean, maybe in 20 years we're going to be having a different conversation. But right now, that's your winning ticket to being an expert, to being a leader, to driving something forward that's not going to be easily replicated.

Steve Swan [00:00:37]:
Welcome to Biotech Bytes, where we speak with IT leaders from biotech and pharmaceutical industry about their thoughts and feelings around technology. I'm your host, Steve Swan, and today I've got the pleasure of speaking with Irina Dymarsky. Irina, welcome. How are you?

Irina Dymarsky [00:00:53]:
I am great, Steve. So happy to be here with you and thanks for having me.

Steve Swan [00:00:57]:
Well, welcome. Welcome to Biotech Bites. I'm really excited to chat with you. Like we were just kind of talking about, excited to chat with you about your experiences and especially your experiences around the commercial space and commercial technologies. Right. Because I do see that a lot of chief commercial officers and a lot of companies that are getting closer to, you know, commercial really, really need that help. And it seems that it's getting tougher and tougher for them to find it. So I'm really excited to, to chat with you about all this.

Steve Swan [00:01:30]:
So, so what I like to do when I first get going with folks is to just ask for a brief, you know, rundown of, of how you got to where you are. You know, just give me a quick couple minutes on you.

Irina Dymarsky [00:01:41]:
Yeah. So, Irina demarski, I'm a executive technology leader. I love to sell, simplify all the operational complexity that exists in companies today. I've had the pleasure of driving transformation and enabling innovation in multiple industries, pharmaceutical services, technology. And I always center back to people, process and technology. The alignment of those three is what's going to drive the meaningful change and the sustainable business impact. So we can talk about all the different tools that I have, my toolkit, and how I collected them to be able to align that people process technology triad.

Steve Swan [00:02:25]:
Why don't we use that as our springboard, right. To, to get right into it? I mean, you know, I hear a lot of folks when I'm, when I'm interviewing them over the years, been doing this 26 years, right. A lot of folks mention on their resume or they say people processing technology, but you know, what, well, what does it mean to you and what, what have you seen work, right, as far as people processing technologies concerned over the years?

Irina Dymarsky [00:02:50]:
Yeah, absolutely. Well, I was, I was so lucky early in my career. I was part of Johnson and Johnson's leadership development program, which is such a broad, you have such a broad ability to learn across their different areas. And at that point, Johnson Johnson had the commercial segment, the medical device, the pharma. And everyone in the program was required to get PMP certified and Six Sigma certified. So everyone coming out of that program got a green belt, got their pmp. And so that foundation for me has really been what I think I can always rely back on. So everything to me is a project.

Irina Dymarsky [00:03:30]:
I mean, it doesn't matter whether it's process or it's technology. It's a project, it's an initiative. You break it down. So the first thing you learn early on is, is who is it for? Why are we doing the thing that we're doing? And I feel like a lot of times people don't have that good why and that right away puts them on the wrong path. And you know, you mentioned digital technology or digital transformation. You mentioned pharma. Now is the time where there's a lot of whys that are coming externally to the industry truly. You know, there's, there's new regulations, there's disruption.

Irina Dymarsky [00:04:10]:
A lot of those blockbuster drugs we saw in the nine, you know, in the 1990s and the early 2000s, they, they have impacted the large populations and pharma is increasingly targeting rare disease orphan indications. But that's not going to sustain for forever. So I really feel like we need to bring back the why. What are we trying to do? Is it that you're trying to simplify? Is it that you're trying to focus on a better customer journey? How are you engaging with who are your customers? Do you even know? Sometimes you have customer, you have companies. They haven't defined who is their customer. Is it a B2B is a direct to consumer. So I think that why your charter is really important. That's kind of core right from the project management kind of institute type, type of, type of deal.

Irina Dymarsky [00:05:01]:
So no matter what, you start with your why. And then I often find, and it's a little bit silly, but especially with the blow up of AI, everyone comes in and they say, I need the technology. I went to a conference, I met with a vendor, I talked to Steve, my buddy, and they just did that whatever at that other company. I made that. And so I've worked with a lot of business people who really understand their function. They did understand their why and they would see something and maybe not quite understand all of the technology implications, but come to their business partner and say, I picked this thing and I need it. Well, that's where I think now the IT people really need to have that strong foundational understanding of how they're supporting. So the business partner role, I think is really important in organizations.

Irina Dymarsky [00:05:53]:
So you have your core infrastructure, you have your core data. Who is the technologist talking to your business people? People and who's translating. So that's when I say process, do you understand the process? If you don't, that's okay. There's tools. So I reference Six Sigma. Let's map your process truly. Let's sit down and say, you know, Steve fills out a form or an Excel, and then that Excel goes into a folder and that folder gets picked up by a system, et cetera, right? You map the process and then you look at the best technology to either automate it or improve it, or what's steps can you cut out? Because in Six Sigma you call it waste. So you produce your.

Irina Dymarsky [00:06:35]:
If your process produces waste, that means it's not a good process. And my joke always is when you apply technology and when you automate a bad process, you produce waste faster, right? You, you're not really, you have, you haven't fixed the process. So that's what I'm saying. It's always the why that's focused on the people. Your process is how does the entire end to end flow work? And only then do I lean into technology and say, now that we have the people aligned, everyone understands where we're headed. We're following the same map. We have the goal. That's the people, right? You're aligning the people to what you're doing.

Irina Dymarsky [00:07:15]:
You've cleaned up your process. Then you say, what tool do you need? What system do you need? Or kind of automation, you know, whatever the latest is, then you apply it. And I think that that combination of rigor of using all of these different tools is what LED leads to success, especially on these big, big complex transformations.

Steve Swan [00:07:37]:
You know what's funny is that as I'm listening to you, all these examples are running through my head in my life. You know, I'm thinking about when I, when I talk to folks, when I interview them, I think about how does that apply to everything we do? You know, And I mean, I've got three examples that pop into my mind immediately as you're talking. You know, I get calls from folks talking about, you know, AI, right? And you know, I had one person call me and say, I need a leader in AI. And I said, I didn't say why, but I came. That's kind of where my question went to. Well, I just feel like we need it because other people are doing it. Fomo. I said, you know, I might not be your guy, you know, I, I, you know, because if you don't define it, right, why you need it and what's going on and what the drivers are, I always say the drivers, the motivations, right? If you don't really define the drivers around that and why you need that, then it's might not lead to success.

Steve Swan [00:08:36]:
And then that's going to be my fault somewhere down the road pretty soon. Down the road, Right. And I don't want to be involved with that. Right. So, you know, and it also another one of the examples, I think about my kids when they were young, when they were really young, I always asked why, you know, listen, if you need, I don't know, make it up a cell phone. Let's talk about why. If one of your reasons is because anybody else has it, you know, I saw it at a conference, AKA Right, let's, I'm done, I'm hanging up on you. It's over.

Steve Swan [00:09:05]:
Right, let's, let's talk about why you really need it. You know, so it goes through. I mean, it should be common sense, right? Don't do technology for technology's sake. Do it for business sake. Right?

Irina Dymarsky [00:09:17]:
Yeah, I love that. And you mentioned AI. I mean, that's everywhere. That's the tagline, that's the buzzword. Everyone's talking about AI. You know, I've been talking to peers across the industry. I've been going to webinars. And what it comes down to for me is again, it's not just we are doing AI, it is what is your digital strategy.

Irina Dymarsky [00:09:38]:
And so I've actually heard from a lot of people that they're starting to take a step back and actually think, what is the digital strategy? And what are we going to apply AI to? Because there's, you know, you may think I'm doing AI, so that must be good. And that, I mean, it could be, but there's applying AI to making your operations leaner so you can be applying to AI. So you had a person, you know, you had stickers. Steve. And Steve was spending three hours each week moving files from one folder to another. Okay, great. So maybe that's not exactly what we think of AI, but there's some automation, right? Some process automation. You put some tools in there and now these files are automatically moved based on some criteria.

Irina Dymarsky [00:10:26]:
Okay, so that, so you figured out why you want to apply it and in what specific use case you want to apply it. And then there's the use cases that are really forward thinking. Then you're starting to get into, I want to apply AI to my data. I want to train my own model, I want to create my own maybe internal kind of chat GPT like model which, with my proprietary data that I don't want to feed out into the Internet. You know, particularly in pharma and biotech, right? You might have, you might, you might have clinical information, you might have pii. Like you don't want to apply AI incorrectly. So just because it sounds cool and people say, yeah, like, you know, we're going to, I mean even, even something AI sounds very, very forward thinking, sounds very fancy. So let's take something even built in, right? A lot of the SaaS products now have AI built in.

Irina Dymarsky [00:11:20]:
So you're, you're, you know, you just, you get an update, it loads. And so now in Microsoft you have Copilot or now, you know, Salesforce is now advising you of the next best action. Your little Einstein guy, right, he's going to recommend something. Okay, but what data is it pulling? Are you appropriately using that data? You know, I've been on a couple calls with ethics people, legal people. So just because you have this data on your network doesn't necessarily mean that you can start running it in algorithms or loading it into, you know, into a system or if you, you know, for a company like Cineas, they've run clinical trials for a number of different sponsors. So if I, Irina, I'm working on a Pfizer clinical trial and a Johnson and Johnson and a Daiichi Sankyo. That doesn't mean that I can just run Copilot all across my notes because that data is really, truly proprietary to that sponsor. So there's a lot of additional things that go into than just saying, oh, I, you know, I chatgpt is the thing, I'm going to just do that.

Irina Dymarsky [00:12:28]:
What is your digital strategy? And this is where you really need people who have the functional expertise. And I'm going to go back to, you need to connect it to what is the result that you're trying to get?

Steve Swan [00:12:39]:
What are you really looking for? Because a lot of times what I'm hearing from the IT folks, you know, through throughout a bunch of my podcasts, they're not coming out and saying it, but what you're hearing, if you read between the lines, is that, you know, some of the leaders, the COOs, the CEOs, you know, whoever, boards of directors are coming to them and saying, hey, you know, I heard on the golf course a couple days ago that someone's making money or really using AI we need to do. That's what we need to do. And so they get pressured into doing it and they're building this cool new shiny object like you just said, but they don't know the why, you know, like you're talking about now. All of a sudden they got this Ferrari they built. But is the data ready? Right, the data is the fuel that goes into that Ferrari and they're not ready for that. Or, or from a governance perspective, can we use all that data? I got the cool thing now.

Irina Dymarsky [00:13:34]:
Yes. And sometimes it's not about having the best technology or the latest technology. It's just applying it to the best, most impactful problem that you're trying to solve. And that's why, you know, I really, I'm just going to keep going back. It's the people process technology. It's not the technology that is going to drive the change. It's, do you have the culture or is your workforce ready? Are your employees embracing the new technology? Are they trained? Are you training them to use it?

Steve Swan [00:14:08]:
What are your thoughts around that? How, how would you, how would Irene say the best way to get. Because there's many, many, many schools of thought on this. Let's get our, you know, we need to get our, we all agree, right? We got to get everybody ready for AI. How do we do that? Right? Because I've heard, I can tell you everything I've heard, I've heard from A to Z, right? And everybody's got different things. Some people even bring in outside firms that help to train and show people, you know, first they start with an external training partner that first and foremost gets everybody on the same program with terminology, right? Because if we're all speaking a different language, then not going to help us, you know, and then they start going into, you know, what do you know, what do we need to do? What are we going to do? What, you know, so, you know, how would you, would you say if you were an IT leader, right, inside an organization today, how would you start your team, your group, your crew, your organization on getting their feet wet with AI?

Irina Dymarsky [00:15:14]:
Yeah, no, that's a really great question. A part of that answer has to do with how you originally hired all of the folks into your organization. So if you were Hiring for a very specific skill set. Let's say you hired C programmers because that's all they wanted to know and that's all they wanted to do. You're probably not going to have the best capability, you're not going to have the best interest perhaps in AI. And again, not to pick on C developers, but what I'm leading is continuous learning and a continuous upskilling. And then you really do want kind of a technically savvy workforce. So I'm going to say including, you know, including the companies that I dearly love, you know, pharma, I think is a little bit behind in having a truly digitally savvy workforce.

Irina Dymarsky [00:16:12]:
Obviously they're behind tech companies because in tech. So I worked for sas, that's a tech company. Your IT people at SAS are not the most technical people oftentimes in the room because you have your R and D folks that they're building software, you have your salespeople, they're speaking software to the customers all the time, right? So it's completely different in pharma and biotech. You have a lot of scientists, right? You have a lot of focus on different skills, different degrees, different education. And sometimes it's maybe some apprehension about the technology or not always understanding how it works. I'm actually going to make a, I'll make a case for regulatory compliance, which always is like, oh, that's the thing that's holding us back. I think a part of regulatory compliance can actually be the stabilizing force to get people more comfortable with AI. Because if you can figure out a way to both say, I built this new technology and we've got it certified, you know, it's CSV.

Irina Dymarsky [00:17:19]:
We did all the documentation, we checked it, and it's now compliant. I think that could help to build trust with people who kind of value, you know, value that stability, that regulation, that understanding of what it took to make sure that it works correctly. So again, let me, let me try to summarize what I'm saying here. Continue. Like interest in continually new, learning something new. I hope you've hired your people to be curious. So if that's one of the values in your company, you know, that curiosity you kind of want to try, you want to tinker. There's certainly change management applications to this.

Irina Dymarsky [00:17:57]:
You pick those, you know that you always have the laggards and then you have the people who are like, I'll wait to see when it's relevant to me. And then you have your early adopters, right? They're the ones coming and saying, oh, I want to try this, I want to put my data out here and I want to trial this, or I had downloaded something. So kind of leaning into that, finding those champions, making sure that you can bring back some values, like if you can get some hit some good results early on, right, Then that becomes your poster child. Hey, Steve really was curious. We worked with him, we implemented the same small thing. We did it quickly, we piloted, not too much money, some investment, made sure it was compliant or made sure it worked in the context of our process. Who else wants to try it? You can do a little bit of like a grassroots or you can crowdsource ideas. So at cs, we actually did some crowdsourcing of what processes to automate.

Irina Dymarsky [00:19:00]:
So we just put a form out on the intranet and people can volunteer. You know, here's, here's what I do day to day. Here are the systems that I interact with, and here's some opportunities that I see for applying some automation. Can you help me? And so you evaluate it and you pick the ones that are most valuable for the business. You get those champions. They're now walking around telling, wow, it's so great. You know, I saved this many hours. My people are now freed up to think about different things.

Irina Dymarsky [00:19:30]:
And you kind of build this, you know, your book of stories, your book of success, and then you just keep rolling. And I think even eventually the people who are skeptical if, if there's this overwhelming tide that's saying, well, it works, you know, it's regulated, it's past the audits, it's delivering customers, maybe success stories. You know, I think you, you, you put, you put effort into it. You don't just expect it to happen on its own.

Steve Swan [00:19:55]:
Sure, yeah. No, but there's, you know, and, and I think earlier, you know, you talked about some things before we were on camera, you talked about some things, you know, that can. That lead right into that, that were peripheral to what you were just saying. Right. You know, you had talked a lot about, you know, cultivating the diverse experience. Right. So, you know, doing a lot of that kind of work. And I think all this feeds into it.

Steve Swan [00:20:16]:
Right? Because like you said, different folks have a different threshold for different kinds of experiences. Right. And you were just saying that with the AI.

Irina Dymarsky [00:20:25]:
I think so. I think that's true. I mean, a big thing for me personally is in my career to have purposefully sought out different experiences across multiple industries. And what I'm starting to see, you know, the power of connecting the dots is really, is really something that's helping me grow in my career. So, you know, I ran the service desk for a couple years, many years ago at a company. Okay, I don't run the service desk anymore, but next time I'm talking to someone about their interaction with the service desk, an AI tool, maybe it's a chatbot that's now going to be answering, right, we want to shift. I mean, it doesn't matter what it is. That's the foundation of it.

Irina Dymarsky [00:21:11]:
It's always going to be prevalent across the company. So you have that experience. You have an experience implementing an erp, you have some data experience, you worked on a budget, you reached out to a customer, you did some marketing. You know, the more experiences you can layer in and the more diverse city you have in your toolkit, I'm going to say, I think that's going to be the winning formula. I just finished a book, it's called Range by David Epstein. And he talks about the difference between, you know, in. In music, I think in particular, there's this concept of 10,000 hours of doing something makes you an expert. The book, this book in particular, argues that AI is going to be the best at taking over those very siloed specific expertise in one field because you can train it to, you know, play just the violin or play chess.

Irina Dymarsky [00:22:11]:
Like that was another example. That's throughout the book. You saw that early on when Gary Kasparov was beat by the first. It wasn't even AI at that point, but it was a computer, because you load every possible permutation of the chessboard, and the computer can process that faster. But what a computer can do and what AI can't do is draw upon experiences that it doesn't have loaded into its model, right? So, like going back to its people, its process, its technologies, industries, it's all of these different experiences that you as a human being can translate. The AI is going to be challenged with that. At least now. I mean, maybe in 20 years, we're going to be having a different conversation.

Irina Dymarsky [00:22:56]:
But right now, that's your winning ticket to being, you know, to being an expert, to being a leader, to driving something forward that's not going to be easily replicated.

Steve Swan [00:23:07]:
Yeah, it can't reason. I mean, I have a nephew that's involved with AI and. And, you know, his example is, you know, you have three glasses on the table, right? One's a margarita glass, one's a, I don't know, plastic sippy cup, whatever. You push them all onto the ground, right? So it recognizes all three as glasses, right? As they're on the table, push them onto the ground. Two of the three, break the two that break. It doesn't recognize, it doesn't know if that ever held water or not. The sippy cup that didn't break, that's still a cup to it. Right.

Steve Swan [00:23:36]:
So it can't reason, it can't figure that out. It also, what you were just saying reminds me of, I've paid a lot of attention to Warren Buffett and Charlie Munger over the years. Right. And Charlie Munger. I used to go to the shareholder meetings and Charlie was great. Charlie just bottom lined everything. But Charlie felt that the school system, university system was doing us all a disservice. It was teaching us this, it wasn't teaching us this.

Steve Swan [00:24:01]:
He's like, the schools need to give you an overview. Let's connect, you know, the sciences, the humanities, the Eng, you know, whatever. Connect them all and then we'll be able to, like you just said, get a full view of everything and really be able to. That's what makes us human. Really be able to figure things out.

Irina Dymarsky [00:24:17]:
Yeah, I've, I've been connecting with some students from my alma mater at Drexel University. And you know, most of them are graduating and they're saying, you know, Irina, what, you know, what do you think? Like, should I just go into this area or this area? And you know, you can never say for a person, they really have to find the right opportunity that that makes them tick. But I have been cautioning in this book, mentioned it, don't specialize too early in your career because back to my C plus plus example, because that thing that you have specialized in is going to change. It just is. It's just year after year things were going to change and there's going to be something new. So you don't want to go too deep on one thing. Now if that one thing is kind of emotional intelligence or it's people or it's change management, okay, that's applicable. Right.

Irina Dymarsky [00:25:07]:
That's broad, but that's a broad discipline. But when I'm talking about technology or kind of a certain area specifically in it, it's changing too rapidly. Don't get locked in to just that one thing. Really think broadly and I think that will open up new opportunities.

Steve Swan [00:25:25]:
Well, to, again, I'm going to, I'm going back to Charlie, sorry about that. And he may have stolen this from Ben Franklin. To the person that only owns a hammer, every problem looks like a nail. Right? So that's what we're talking about. Let's let's, let's get diversity, right? Diversity of experience and diversity of background. Right. Not only for the individual, but for the group too. Right.

Steve Swan [00:25:44]:
That are helping decision making processes. Now another thing that you, we talked about early on when we were off camera was digital, right? Digital transformations and such. You, you touched on that a little bit ago. You know, and, and I know that being on the commercial side and working who you work for, you've probably been involved at different levels with many different, you know, digital transformations. I guess first define what you mean or have seen as digital transformation. Right. And then explain, you know, why that's so big and why that's so important for all of us in pharma.

Irina Dymarsky [00:26:20]:
Yeah, and I, I'm, that's a great question, Steve. And I'm sure that everyone is going to have their own definition and maybe people will watch this podcast and say, oh, that Irena doesn't, you know, doesn't know what it is. But to me, in my experience, digital transformation isn't just about adding new software. Like, let me just say that again, it's not adding new software. It is fundamentally rethinking your workflows, your processes, your interactions. It's leveraging data in a smarter way, in a completely different way. It's making sure your decisions are data driven. Now based off of, you know, is it the right report? You know, and I'll give you an example with ChatGPT and how you have to be careful about making decisions off data if you don't trust it.

Irina Dymarsky [00:27:11]:
And you know, again, for pharma, most importantly, it's staying compliant and patient centric. So digital transformation could be all of those things on the basis of data and technology, but it's fundamentally impacting your workflows. And my funny story about ChatGPT, I asked it to, you know, write me, I was researching some things and it said a recent study found that 20% X, Y and Z. And I wrote back immediately and I said, cite the source of the 20%, you would not believe it. So ChatGPT replied to me on further research, I was not able to find a citation for this number, you know, and then like, you know, whatever, you know, but, but it's like commonly known something, something. So it basically immediately, immediately backed away and was like, oh, there's actually no 20 study that found this. It just made it up.

Steve Swan [00:28:10]:
Total hallucination, right?

Irina Dymarsky [00:28:13]:
And so I was like, okay, well then rewrite this paragraph without citing this, this percent. So I mean, you're going to see this with AI and But you actually may be seeing this already without AI, right? How many times have you got in an Excel file and you look at a number, you know, maybe it's a financial calculation, maybe it's a sales number. Just the number looks off, right? So don't forget about. You are a human being with a brain again, going back to that range, if the number looks off, like just doesn't feel right. And you have been working with this data for even a month, a year, 10 years, how many times have I asked, what is this number? Like it doesn't make sense. Oh, that's a typo. Oh, that, you know, it's missing a zero. Oh, you know, this one was multiplied to be in millions and this is in thousands.

Irina Dymarsky [00:29:08]:
Like all of those reasons are true and they exist in, in organizations, big or small. So digital transformation to me is having trust in your data again, building those workflows, developing the questions in your workforce like, don't be afraid, build that culture of questioning the chat GPT. Don't assume that if it says 20%. A recent study. What study? Oh, I can't find one. I made it up. Basically that was like Chad GPT saying, I think I just made that up. So that.

Steve Swan [00:29:46]:
I don't know, I don't know.

Irina Dymarsky [00:29:47]:
What do you think is, does that resonate with you about what digital transformation is?

Steve Swan [00:29:51]:
Oh, sure, yeah. And I mean, I think like you just said, at the core of it, right, is trusting your data. And at the core of it, if you have bogus data, right? I mean, it doesn't matter what else you're doing, it's not going to work. You know, it's not going to work.

Irina Dymarsky [00:30:07]:
It's a catalyst. Your technology can be a catalyst for sure. But to really have this long term vision, your long term value, you need all of that support around it. And I've been seeing a lot of, you know, I mean, you're in the recruiting field. Are you hearing about a lot of people kind of going back to the basics? You know, I think people are now talking about, you know, I don't have a good erp, or maybe I have an old erp, I really need to update it. You know, I don't have a good handle on my financials. I don't have a CRM, I've been kind of doing it. We grew so fast, we didn't have a chance.

Irina Dymarsky [00:30:43]:
So again, it doesn't have to be any of these big names that I'm sure we can all rattle off, you know, but it, but you do need to get those processes right. Like, how are you doing your financials? How are you measuring your customer relationships? Are you serving your customers from like a NPS perspective, like a Net promoter score? Are they happy with the service you're providing? Would they recommend you to a friend, you know, or a colleague, you know, kind of get back to the basics. And if you don't have an MDM again, or mdm, like program Program, where you trust and you can trace through that, like etl, that extract, transform and load on your data. I mean, again, maybe it's outdated that terminology because now we're in, like data lakes and it's not a data ware, but whatever. Do you trust your data? Can you trace it? Can you prove your decisions to be accurate? That, to me, is digital transformation. I think we've kind of have like a 50, 50 going on. There's some companies that need to go back and kind of clean up their foundations before they're able to go. And there's others who have certainly made that investment and now it's paying off because they're able to now leapfrog to the new.

Steve Swan [00:31:53]:
And to your point, going back to the basics is about getting that data right so that you can use it going forward. Right. You know, so I do have companies and some of them, some of the folks have been on my podcast who have, and they've talked about it. Right. You know, from. I'm just going to make this up. From 2015 forward, all their data is great. Love it.

Steve Swan [00:32:13]:
Before that, we got 20 years worth of data we're trying to get through. We're never going to get through it. You know, so, you know, were the systems right? Were the processes right? Was the tracking of the data right? Have we changed the way we track her? I don't know. You know, they don't know. So now we've got different kinds of data or different. Maybe it's measuring something. Who knows, right? It's. So is it useless? No, but they still got to get through it.

Steve Swan [00:32:38]:
And then I, then one of the folks I made a comment to, why can't you go out and buy the data, you know, for this? You know, whatever you need here. They said, we still can't trust. We still got to go through it. I said, okay, all right. So, you know, it's, it's, it is. It's about getting all that data together. And like you said, you know, having master data management and so on and so forth. I see a lot of that lately.

Steve Swan [00:33:00]:
You know, data is, is, is king right now. And and, and everybody's trying to figure out how to harness their data, keep their data, you know, secure. Right. And then utilize it to their advantage, you know, and there's a lot of it. We got a lot of data in, in all those systems, the CRM system, the ERP system, the, I mean, you know, your procurement, I mean everything, you know, and it all feeds together and, and they're all good at doing this. But like you said, we gotta go across now and what does this mean when this happens? What's it gonna do to this over here? And so on and so forth. Right. So got a lot of moving parts in pharma.

Steve Swan [00:33:35]:
Yeah, so. Well, good. Well, I appreciate that. Anything else you think we should be thinking about as far as technologies? People process data before I, because I always ask one last question to folks and it's always off topic. So before we get to that, I want to ask you if there's anything else we want to cover.

Irina Dymarsky [00:33:54]:
Well, I think I'll just wrap it up. You know, we talk about implementations, big technology implementations and again, maybe this is me being a little chatgpt, but you do hear these double digit percents of failure like these ERP implementations go off the rails. We overspend, we don't deliver to scope. I truly believe that it fails not because the solution is flawed, it's because we didn't address some of the additional elements. So they could be human or process elements. If you forgot it, you kind of missed it in your due diligence and you just tried to layer the technology on. I think that's that, that's where a lot of the failure happens. So the real magic, you know, and I'm all about like, you know, let's make magic together.

Irina Dymarsky [00:34:38]:
But the real magic happens when you align those, the people process technology in a single strategic vision. That starts with. You talked about, you know, we talked about the why, that's the building of the roadmap. Right. You know, what is your roadmap? It's your digital in it. If you want to lean in digital, it's your digital roadmap. So you can have a business strategy, you can have a digital roadmap. You're prioritizing the high impact areas first and you're going to sequence it so that you get these early wins and they're going to fuel that excitement.

Irina Dymarsky [00:35:09]:
They might actually may fund some of the investment and then you're moving on to the more ambitious efforts after you've gotten your feet wet. You're communicating and you're training because without it, your people are not going to be able to support this new thing. You're going to create these champions. You're going to use multiple channels of communication. You know, you have to say something seven times for people to remember it. Now, I can find you that citation and you're celebrating the early wins, right? You're going to share these success stories. You're going to speak on podcasts, you're going to maybe publish something. You're going to work with your vendors, right? You're going to promote each other.

Irina Dymarsky [00:35:47]:
And then that, I think, is the transformation that we're going to see in pharma and even other industries. You're going to see, see the human factors coming together. You're going to see the transparency, the communication, and we're going to be celebrating this progress over time.

Steve Swan [00:36:03]:
Again, I'm going to reiterate, I'm almost saying exactly what you just said. I think, I think any process, whether we're, whether we're switching jobs, right? Whether you're talking to Steve Swan about a career opportunity, whether you're putting in a new ERP system, whether you're changing your data or your data source or curating your data in one way or another. Understanding the why, the foundation of the dry. I always call them drivers, motivation. What's the why behind this? You know, when I, When I talk to somebody about a position, I need to understand their why, what's driving them. And then I'm always talking to companies to understand what their why is, what their drivers are. If I'm not matching those up, it's not the right, it's not the right way to go. Right.

Steve Swan [00:36:40]:
It's the same thing as being in, in, in, in a company. You know, what's the why behind this? If it's, if we don't understand where we're trying to go and how we're going to get there, it's. It's game, game over, you know, So I agree. That's where I am on that. So, and, and I, I spend a lot of time talking to folks and individuals and companies about their drivers and the why. Because if I don't have that why on the foundation, again, just like you're talking about, the rest of the house that we're building is on a shaky foundation, you know, for lack of a better term. So. Well, thank you.

Steve Swan [00:37:11]:
So I do have one final question I ask, folks. Okay. And, and, and I, I like music. Right. So just today, I bought some tickets to a concert I'm going to in a few months. But so I. I go. My.

Steve Swan [00:37:24]:
We go to different concerts and different shows and things like that, my wife and I. And so what I always like asking folks, is there any one particular live music show or act or band that you've ever. That's the reaction I get from almost everybody. They start laughing, they giggle, and they're like, okay, what should I. What should, what should I be saying? Don't think about what you should be saying. Think about what you really, truly. And if you're not a live music person, that's fine too. I totally get that.

Steve Swan [00:37:50]:
You know, some people are scared of crowds, right? Or what have you. So. But I like, I like asking folks that it shows a more personal side of the individuals as we're speaking to them. So any. Anything that comes to mind throughout your entire life that you would say, that was the best show or act or whatever that I ever seen.

Irina Dymarsky [00:38:09]:
Yeah, yeah. I have, I have a perfect story for you. So two years ago, is it? Two. Yeah. Two years ago for the holidays, my husband says, I got you a gift. I got us a gift. And I'm like, okay, what is the gift? So he goes, I got us two tickets to see Scooter. Okay.

Irina Dymarsky [00:38:30]:
So I'm like, okay, this is really cool. Like, I like Scooter. It's kind of like electronic. I think it's called, like, Happy Hardcore is like the type of music that he created. A lot of electronic music, you know, a couple words, a lot of effects, you know, fire and then, you know.

Steve Swan [00:38:50]:
Kind of stuff, Right?

Irina Dymarsky [00:38:51]:
It is, it is, yeah. So Happy Hardcore is literally the music that Scooter is like the father of. So I'm like, okay, this is great because we listened to this when we were in college. We, you know, there's lots of, lots of that we love about it. So I'm like, okay, great. Where is the concert? He goes, it's in Germany. Okay. Yeah.

Irina Dymarsky [00:39:12]:
So I'm glad that. That was basically my reaction too. So on the holidays, he's like, I got us these tickets. I'm like, okay. So right away, you know, I told you, I'm like this PMP kind of brain. So I'm like, did you plan, did you buy tickets? And goes, oh, no, no, no, no. You can do all that.

Steve Swan [00:39:30]:
You do that.

Irina Dymarsky [00:39:30]:
Because I love, I love to do this. I do that for my family. I'm always planning the vacations. I'm always, you know, like, you know, doing all the research and doing, like, on this day we have this agenda. So anyway. But I loved it. We went it was a trip that my husband and I took. We don't take too many of them because we have young kids, but it was a trip that we took.

Irina Dymarsky [00:39:48]:
It was April, you know, April of last year, we went to Germany. We saw this concert. It was unbelievable. Unreal. So good. Like, just. Just amazing. And yeah, we loved that.

Irina Dymarsky [00:40:02]:
We had a great time. But, yes, he was like, I got you the tickets, you do the rest.

Steve Swan [00:40:07]:
I'm the idea guy. I'm done now. Right? Yeah, yeah.

Irina Dymarsky [00:40:10]:
You know, and, you know, and to translate that, you need those people in company. So, sorry, I'm just going to kind of wrap it all up. You need those idea guys or gals who are going to say, oh, we're going there. Like, we are going to Germany, you know, or whatever. We're going, you know, we're going to that customer. We're going to go to that product, or we're going to, you know, we're going to do that. And then you also need the rest of the folks who are going to make that real. So, truly, when we talked about getting your workforce ready, recognize the strengths.

Irina Dymarsky [00:40:41]:
And so, yeah, in our family, it's definitely. My husband's the idea guy, and I'm more like, how do we operationally and compliance regulated, make this work and make it real?

Steve Swan [00:40:51]:
And think about it. You. You being the boss at home, right? I mean, he. If he put it together. Because I know I would have done that. Probably the exact same thing if I put it together. Be like, well, why'd you pick that hotel? Or why are we flying in and out of here? We could fly earlier that day. We don't have to fly that.

Steve Swan [00:41:07]:
You know, whatever. Okay, I got it. You know, so anyway, yeah, I would.

Irina Dymarsky [00:41:11]:
Have done so if you don't know, Scooter, you should check it out.

Steve Swan [00:41:14]:
I will. Yeah. No, I've. My two daughters are in big time into EDM and such, and they go and see those shows all the time. One of them is in the city, New York City, and she goes to see a lot of that stuff. And I think my girls went to. They did. They went to something in Spain a couple of years ago.

Steve Swan [00:41:32]:
They took it. They took two weeks and they traveled to Spain. And I remember seeing pictures from some EDM show they went to, and I think they're off to Tokyo this year. They're going. So, anyway. Well, cool. Well, thank you very much. That was great. I'm glad you joined me on this. Thank you.

Irina Dymarsky [00:41:50]:
Yeah, thanks for having me. I'm really excited to see it all come together and let's continue the conversation.