In this exciting continuation of our series on digital transformation and innovation, we dive deeper into the crucial role of policies in driving successful change.
I’m joined once again by Chris Colangelo, who brings his extensive experience from working closely with IT and digital teams.
In this episode, we examine how companies often overlook strategic policies and the implications of build versus buy decisions. Chris shares his insights on aligning technology strategies with business objectives and navigating the complexities of organizational change.
Join us as we explore these essential aspects and provide actionable advice to help you lead effective digital transformation in your organization.
Here is Part 1 of this series.
Key Points:
- Policies: Importance of strategic policies in digital transformation.
- Build vs. Buy: Implications of building in-house solutions versus purchasing external ones.
- Technology Alignment: Aligning technology strategies with business objectives.
- Organizational Change: Navigating complexities in organizational change.
- Actionable Advice: Practical tips for leading effective digital transformation.
Understanding and implementing the right policies are crucial for successful digital transformation. Chris’ insights on build versus buy decisions, aligning technology strategies, and navigating organizational change provide a comprehensive guide for any statistician or professional looking to lead effective change.
Don’t miss out on the full conversation packed with actionable advice and real-world examples. Listen to the episode now and be sure to share it with your friends and colleagues who can benefit from these valuable insights. Together, we can drive successful digital transformation and innovation in our organizations!
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Chris Colangelo
Passionate Leader of Strategic Improvement
Chris invested 5+ years as the Director of AI Innovation & Design in Biometrics Statistical Data Sciences & Analytics at Pfizer; 18+ years in Global Statistical Sciences at Eli Lilly, departing as the Statistics Advisor of Clinical Computing & Automation; 2.5 years as a contract performance analyst for FBI/AFIS; and 5 years as biostatistician researching novel managed care models at multiple think tanks for the University of South Carolina. He has since left Pfizer for the opportunity for broader impact across life sciences & enabling industries via independent consulting.
His expertise & leadership journey started as a biostatistician, evolved to data science & analytics, advanced to devising AI/digital innovations, and then jumped to business ownership of cross-functional capital transformation initiatives.
He is a zealous fan of good pizza, Pittsburgh Steelers, the University of Kentucky sports, cooler-than-warmer climates, hilly terrain & coastlines, and Nina – his faithful Boston Terrier.
Transcript
Digital Transformation And Innovation (PART 2)
[00:36:06] Alexander: And now let’s get to the next bullet point. Policies. So I think this is a really, really interesting one, because we have I think there’s a lot of [00:36:20] companies or groups and companies that never really think about that. Yeah, they have some kind of default way to going about it. So what are the different policy aspects that we can, that we can think about?
[00:36:39] Chris: [00:36:40] Alexander, I have just listed a couple here. And so working so closely with I. T. Or or digital however we want to look at it has given me a perspective that not a lot of statisticians or data scientists experience [00:37:00] on a daily basis on DSO. It’s really been by and large last 15 years or so that I have Worked very closely with them, and there’s a lot of discussion from a let’s call it a tech strategy.
[00:37:19] Like [00:37:20] statisticians have their own strategy. Oh, we’re going busy. And are we not? Are we doing this? Are we doing that? Right? That becomes in in the analytics or the analysis aspect on really the big tech aspect. There’s a strategy as well for for the [00:37:40] enterprise. Statisticians tend to focus on business applications, not Hey, are we in the cloud?
[00:37:49] Or do we have 57 servers that were executing this on? Right? That is squarely more of of an I. T. Topic. And so, [00:38:00] like statistics, data science ClinFarm, Real World Evidence every other business line is forced to make economic decisions and, and operate in a more efficient, productive cost effective [00:38:20] way it’s the same with, with IT.
[00:38:23] And there are different approaches to, to doing that. And, and so there is a classic one of do, do we build something or do we buy something? And, and that has a lot of implications to it. [00:38:40] And a lot of the implications are contradictory. So, from an IT perspective, it is generally more economical to buy something than to, to build something, generally.
[00:38:56] The, the part that is the non general is [00:39:00] what are we asking it to do? And what are we asking it to do is building something that is fit for purpose Because something that already exists has been already built may not fit your purpose.
[00:39:18] Alexander: Yeah,
[00:39:18] Chris: And so [00:39:20] I have, I have worked at, at a, a company where there was a very well known software company that had created let’s call it somewhat of a, a, of a platform.
[00:39:34] And it, it was forcing the company that [00:39:40] was implemented, implementing it. And so my role was the business lead over implementing this globally, this thing. And so I was within the biometrics organization. And so what this forced was change how you operate so that you fit the technology.[00:40:00]
[00:40:00] Instead of determine how you’re going to operate in a way that is optimal for your department or, or your company or whatever the scale is, and then we’ll get technologies that fit how you want to operate, you can see they’re very, very, very different, and that is part of [00:40:20] build versus buy and.
[00:40:23] Somewhat related is there are there are times that someone up above in leadership sponsor, an executive sponsor, etcetera, might mandate. We just bought this, so we’re going to keep it [00:40:40] as a as a technology or. We’ve just spent a year and a half rolling out this new process optimization. So we’re, we don’t want to lose that money.
[00:40:52] We don’t want to frustrate people build around that. And those can be limitations. Usually it goes, it goes [00:41:00] back to the mindset. Of protect versus maximize, et cetera. So this is more of an application of that where someone has decided that we’re going to keep a technology and you can build around it.
[00:41:19] Or a [00:41:20] process and you can make sure that we enable this or our tech strategy is to build something. And oh, by the way, we have a strategic relationship with company XYZ and they might not have even the best product for what you’re doing, but that [00:41:40] helps us from a financial perspective. These are real pressures.
[00:41:46] I’m just pointing out that they can limit the value that comes from the actual production transformation.
[00:41:56] Alexander: Yeah. And yeah, there’s also, of course, a [00:42:00] big timing aspect always in these. And it definitely relates also to the mindset topic. I know definitely companies where if we haven’t built it ourselves.
[00:42:13] We don’t trust it. Right. And so any kind of software [00:42:20] training, whatsoever, every kind of things that you use, it needs to be built by us. Yeah. If it’s built by someone else, That’s crap. Yeah. And maybe they don’t say it, but they think it. They
[00:42:35] Chris: just say it with their friends in private, right? [00:42:40] They wouldn’t, they wouldn’t say it with someone that they fear saying it in front of, but given that this is the effective statistician, I I’m taking a lot of perspective of statistics, data science.
[00:42:56] And the the [00:43:00] group of typically very well educated with a niche expertise of statisticians and data scientists are very much the I need to make sure it’s done right, because there’s there’s a lot of things that a [00:43:20] statistician, a data scientist does, and I’m talking more on the statistical side of data science.
[00:43:25] That is not overt, maybe not obvious to someone that doesn’t have very similar training. And so really quickly, I, I, I spent three years leading good clinical practices [00:43:40] quality over bio, biometric, well, statistics. At a company. And part of my remit was to help infuse some subject matter expertise over system statistics, systems and processes and deliverables.
[00:43:56] And there is a general [00:44:00] hesitation when someone talks statistics because it’s really mathematics,
[00:44:06] Alexander: right?
[00:44:06] Chris: It’s, it’s not necessarily. Anyone can do something if they’re told, right? There’s an expertise. And so there is a bent that would [00:44:20] say, I need to do this myself. And there is generally some hesitation when something is going to be built for them.
[00:44:32] So to your point, it is very much alive and well In innovation transformation type [00:44:40] of topics, but it certainly goes beyond that.
[00:44:44] Alexander: And so yep, it’s it’s a very, very interesting point. Point to look into. Okay. Let’s look into the next bullet point. Which is communication and I’m repeating myself. Communication is the only tool you have [00:45:00] as a leader.
[00:45:01] And there’s lots of lots of different forms to communicate. And communication Yeah, is one thing that you really, really need to get right. Otherwise everything else will fall apart. And yes, there’s definitely overlap with all the other things that we talk about here.
[00:45:18] Chris: Yeah, [00:45:20] I agree. Right. That that is our our tool.
[00:45:24] Andi. So from my from my perspective I have been part of two very large transformation efforts at two different companies. I have been the business leader over to cross functional programs. [00:45:40] Capital campaigns. They they all had over 100 folks in them. And I’ve had an innovation team that was within biometrics.
[00:45:50] The common thread that I have used in my leadership style is to be as transparent, as [00:46:00] absolutely ethical and, and responsible to, to do. I do not keep information close to the, the vest. I believe in being transparent, and I think that there sometimes can be a tap into the [00:46:20] emotion by not being transparent.
[00:46:23] I think that there are times that certain people can fear or have concern. Over what is unknown more than what is known, but disliked. So there there is a complexity of emotions [00:46:40] that that people have, and I think we need to respect them and understand that as part of of learning our craft to be effective.
[00:46:52] And that part of that starts with transparency and what the objective is. [00:47:00] And I was being transparent before when I was saying if someone lives in fear, they may not be part of of your future, right? You try to break someone out of the fear. You try to create a different mindset by communicating [00:47:20] genuinely and clearly, transparently the facts and opportunities.
[00:47:25] But ultimately you’re not responsible for that. You can’t be responsible for that, but we can only do what we can do. And that involves being transparent as communicators, especially in a [00:47:40] role where we’re trying to influence someone to, to move from point A to point B.
[00:47:46] Alexander: And now that is an interesting aspect.
[00:47:49] You say transparent, and that is kind of, is a very, very. positively associated word. Yet, [00:48:00] very, very often when change comes, yeah, and change is implemented, people are, or leaders are, everything but transparent. And I think that’s the It has a lot to do with mindset, you know, [00:48:20] because when they, when they are not transparent, they are very often not transparent because of, they think if I tell everything here, Yeah, that will, people will not be able to handle that.
[00:48:37] Yeah. And the mindset [00:48:40] behind that is this kind of, I think it’s a little bit like adult to child communication, yeah. Rather than adult to adult. Communication. And honestly, I’m a big fan of adult to adult communication. Although I need to say I’ve done that in the past. [00:49:00] And sometimes people really like to be treated like a child.
[00:49:06] And I had, and I had real challenges with these people. Although I need to say coming out of that, I still want to communicate at all to adult level. Yeah, [00:49:20] and it’s not my problem if there is childlike behavior or childlike kind of mindset in there. So this kind of mindset behind that is really, really important.
[00:49:33] Yeah. So it’s not being transparent versus being, you know Irresponsible. Yeah. So [00:49:40] it is very often transparent versus being protective or overprotective.
[00:49:47] Chris: Yeah, yes. And and so for for me, I think being transparent is part of being genuine that [00:50:00] there are times that 100 percent of the situation can cannot be shared in any organization.
[00:50:07] And so that’s beyond necessarily our control. But I take transparency as part of trust and rapport. And being genuine. And [00:50:20] so, as I have influenced, regardless of position, have influenced IT, have influenced cross functionally, have influenced team, have influenced upwards, and, and gotten capital funding at, at multiple companies.
[00:50:37] I have been transparent, [00:50:40] not always fully appreciated. But we have to live with ourselves, right? We have to be genuine. And so, for me personally, I am going to be trusted and want to be respected [00:51:00] and appreciated for being honest and responsibly honest. But I am not trying to win a popularity contest.
[00:51:11] I’m trying to do my job as ethically and morally effective as I can and [00:51:20] be as genuine a person as I can and and forge genuine relationships. And they don’t always go you know, happy duty. You don’t, you don’t always have rose colored glasses and in every relationship, but what we each can control is, are we going to be genuine and authentic and, and [00:51:40] transparent?
[00:51:40] And I think a lot of it has to do with respect for the audience. So if we were to get this back to innovation transformation, if, if we are not really comfortable with where we’re going. And, and asking people to take that journey of transition to [00:52:00] where we’re going. What I think we’re more likely to not be transparent and I’ll put a different word on it, manipulate.
[00:52:08] So and, and management, right. We, as managers different than leader as we try to manage something, we want to have is as little disruption [00:52:20] as possible for the group that we’re managing. And so sometimes we may not tell them the whole story, or we may not put as fine an edge on it because we don’t want the, the disruption.
[00:52:37] And I believe that that [00:52:40] cut, cuts people short. I believe that that is not respecting what you have planned and people’s ability to see it and their respect for someone that is genuine and transparent. And I think that disliking [00:53:00] something is, is different than a fear of the unknown. They’re different emotions and you’re going to get a different response.
[00:53:08] So if there’s something that’s going to be. Negative, I’d rather be ethical, transparent, genuine, and, and trust in their [00:53:20] response and trust in my plans.
[00:53:21] Alexander: Yeah. And. Honestly, very often people are smarter than you think. And so when you hide something, even for reasons that you tell yourselves are good, [00:53:40] yeah, it probably comes through because some people will think like.
[00:53:46] There is an aspect, there’s a kind of, there’s a hole in the argumentation here, or this stands on shaky ground. And I think this will going to happen, but they don’t speak about it. [00:54:00] Are they not smart enough to not speak about it, or are they hiding something. And those consequences. I’m not increasing trust and trust is absolutely important here to drive change.
[00:54:17] Chris: Absolutely. Without [00:54:20] trust, you cannot have influence. Eso. Absolutely. That that is that is important. So for me, If, if there are rare occasions where I absolutely cannot say something, I’ll say, I just, I just can’t get, get into that [00:54:40] responsibly I’ll do something that says, I know this is awkward. There is more.
[00:54:45] I can’t reveal more. Yeah. Yeah. Yes. And so under communication risks versus opportunity is again, The manifestation, making, making real of messaging that reflects a [00:55:00] mindset. So there, there is a way to, to communicate something that I’ll make up a, a, a scenario here. Specifications for all of the analysis and reporting for, for a study that up to today has been predominantly [00:55:20] manual, and that that has been really painful and, and iterative and cumbersome.
[00:55:27] And there has been a lot of perceived. Direct control over that because of a small platoon of people that get involved [00:55:40] in that and starting with some of the capabilities that I was part of rolling out in my previous job. That is being done in more of a digital way, and we have the foundation for [00:56:00] creating an A.
[00:56:01] I. Way of drafting that. So A. I. Is coming to do what was heavily manual before. Now that could be communicated as a risk, right? We don’t need the 57 people that were doing this for for each [00:56:20] study. You can communicate that. Or you could communicate that as in reality, we need your brain power. We don’t need as much of your physical.
[00:56:32] to do that as much as your coordination of putting, you know, version one on the screen and version two on the screen [00:56:40] and making sure that you didn’t screw something up because we can do that with technology now. So it becomes an opportunity instead of taking two hours to do this yesterday. Tomorrow you could take 40 minutes.
[00:56:54] Right. And so that gives you 80 minutes to do something else and be more productive [00:57:00] and so forth and so on. Right. So there’s different ways of communicating that that show the mindset towards the change. And I believe can be very, very influential on someone’s therefore emotion of whether there’s a fear or an opportunity.[00:57:20]
[00:57:20] I have more. I have more time to get into something that would be higher value. Versus wow, I’m not doing what I have known to do for the last four years. That kind of concerns me. And so that touches communication, emotion and mindset all together. [00:57:40] But to your point, communication is the actual tool that that we use to share what our mindset is.
[00:57:49] Alexander: Yeah, the communication term for that is framing. Yeah. So how you frame something is really, really important. [00:58:00] And as it’s 2024 and there’s you know, elections in lots of you know, important areas around the world, you will see that politicians use this framing all the time. Yeah. Because within their given frame, all the [00:58:20] logic makes sense.
[00:58:21] And you will see that again and again and again.
[00:58:25] Chris: That, that is absolutely true. That, that’s a whole other discussion that would be. Fun as well.
[00:58:31] Alexander: Yeah, so let’s go to the fifth topic now.
[00:58:35] Chris: Let’s let’s go to two decisions. [00:58:40] Okay, so I view, I view policies as a pre specified guide rails. Yeah. Okay. If we come into.
[00:58:53] A situation going. Look, we know we’re gonna buy something. We know we’re gonna [00:59:00] buy something from just making us up a W s or sass or whatever. If if if someone says that to us first of all, we can be concerned that we already know how we’re going to solution that and with that small sample of [00:59:20] companies out there, but we haven’t made a decision about which one.
[00:59:27] So we just have the guide rails. We know we’re gonna buy. We’re not gonna build. That’s a guide rail. Now we need to make decisions about who do we buy from, what product do we buy, et cetera, in that, in that scenario. [00:59:40] So, you brought up a point earlier that I have absolutely been waiting to, to make. And I put it here as the second bullet just to fit the space.
[00:59:53] Okay, it’s really, there are a lot of domain [01:00:00] experts in management. And upper management that are not change or technology experts. And so we have in the statistical world, we have a lot of very smart, well meaning, [01:00:20] even can be trusted senior leaders that are making decisions well outside of applied mathematics.
[01:00:30] Well, outside of analytics well outside of providing evidence for drug hunting and that’s more their sweet spot. [01:00:40] It is not. Where would I invest today for a technology solution that’s going to come in three years. That’s going to change how we operate. And so there is a a bit of an epidemic. Okay.
[01:00:56] I think it’s starting to be [01:01:00] recognized that the decision makers need to be a little closer to the transformation, the operations, the technologies that are part of a digital transformation. Instead of just the consumers of it [01:01:20] now, consumers of it need to have a voice at the table and absolutely have have part of the information picture in which to make decisions.
[01:01:29] But the consumers of it, in my opinion, should not be the ones making the final decisions. About, about a transformation.
[01:01:39] Alexander: Okay. So [01:01:40] that is an interesting point because I want to come back to your earlier Henry Ford example. Yeah. See consumers would always go for faster horses. Yeah. Because they can’t imagine the curve.
[01:01:56] Yeah. So and what’s up even possible there. [01:02:00] Yeah. So if you want to do innovation and instead of optimization, yeah, they are absolutely necessary is to, to move the decision making more to the subject matter experts.
[01:02:15] Chris: To the change subject matter experts, the digital [01:02:20] or, or, or operations. Yes. Agreed with you completely.
[01:02:23] Alexander: Yeah. No, there’s, when we talk about decisions I think a really interesting aspect is say a kind of who takes decisions. Yeah. So I very often see that. It just basically [01:02:40] depends on your title, whether you’re empowered to make a decision. Yeah. So, and I’m not talking about the, in many pharma companies, we have, you know, the title in terms of your, let’s say technical track.
[01:02:55] Yeah. But it’s really about your how far [01:03:00] you are up in the hierarchy of the organization. Yeah, so for these kind of decisions, you need to be a senior director for that decision. You need to be a vice president for that decision. You need to be, don’t know, the father of the universe, don’t know. Yeah, but very often, yeah, decisions is [01:03:20] just thought about in that direction.
[01:03:24] What, what’s your experience on, on that and related to change.
[01:03:31] Chris: So I align completely with with what you’re saying. I have been fortunate [01:03:40] in that the the two predominant companies that I’ve worked with. I have had Really good trusted relationships with the organizational heads and above about transforming and bringing and bringing [01:04:00] change.
[01:04:00] And so I am going to call out someone, someone here. And so at Eli Lilly, I had a very strong relationship with Pandu
[01:04:13] Alexander: Kulkarni.
[01:04:13] Chris: And Pandu for certain types of things. We were we [01:04:20] were taking out an old platform and putting in a new one would actually defer people to me.
[01:04:26] So he is a, a, a rockstar at statistics and is great as an organizational leader but un understanding what decisions we need to make now to [01:04:40] create change, right? How, how would we architect a, a digital future? Was was yielding. And I, I always thought that that was humble and I, I appreciate that when I went to Pfizer I worked with a woman named Patty Compton.
[01:04:57] Patty is a very intuitive [01:05:00] and very sharp on. We worked very well together. Patty put me in a role that wasn’t based on level or position so much that gave me a big seat at the table and a lot of input very much. A lot of [01:05:20] input into what we were doing. So it became relational based and gaining trust. To have someone defer to the right the right role.
[01:05:35] But to your point, it is default back to [01:05:40] generally a position a level or a position. And honestly, whoever is is great at mathematics and as as a scientist, May not be great for creating disruption and and innovation and and and transformation there. They’re [01:06:00] different. They’re different skill sets.
[01:06:02] So as a as a data scientist, as as a statistician, there’s a lot of analysis, a lot of breaking thing that things down into parts, whereas in in creating a [01:06:20] future state that that has multiple pieces. Is, how do I put the parts together in a new way to make it better? So it’s almost the opposite type of skill.
[01:06:32] Alexander: Mm-Hmm. .
[01:06:32] Chris: And if we, if we think back to something that was pretty horrifying to me and we go back to chemistry, I was not [01:06:40] a chemist. There, there was analytical chemistry there, there was the ability to break down into parts and then to synthesize. And and create something, something new.
[01:06:52] Those are opposite skill sets, right? Analysis is opposite of strategic or architecture type of [01:07:00] thing. People have bits and parts of, of both, but different times call for different ones. And to your point, when it’s merely a position or a level or a rank. There might be the wrong skillset and the wrong domain expertise to really make an informed decision.
[01:07:18] Alexander: Thanks so much for [01:07:20] going through these five different aspects of change mindset, emotions, policies, communications, and decisions. And before we started the podcast episode, we talked a little bit about this and. We said, well, for each of these, we could [01:07:40] easily record, you know, at least one episode, probably more than that.
[01:07:45] So don’t be frustrated if you think like, well, that is all great. But now if I want to drive change Yeah, it would be great to get some help. And there, of course as we [01:08:00] talked at the beginning, Chris vision is to help people and leverage things that he has learned from his two previous jobs.
[01:08:10] Now, Chris, where can people reach you so that they can work together with you?
[01:08:17] Chris: So I appreciate that. So up on the screen, [01:08:20] I, I put the the way to contact me and, and look up the, the company. I can provide additional information and, and follow up that breaks out the LinkedIn link and provides a link to, to my, to my page.
[01:08:35] I, I do want to say something else. So. [01:08:40] I, I have worked for 25 years with Lily and, and Pfizer before that might have been the most impactful education that I’ve gotten was roughly two and a half years as a contractor under the United States FBI, and I was part of a [01:09:00] 640 million computer system that exists today that a lot of people have seen on the TV shows, NCI and CIS.
[01:09:09] It is an A. I. Powered fingerprint identification system, and it created a lifetime transformation [01:09:20] of real time crime fighting. So the ability to take a fingerprint and understand in minutes. Who it was for. And so working alongside Lockheed Martin and other groups helped me understand what is possible from the computer science [01:09:40] perspective.
[01:09:40] I never would have got that strictly within either pharmaceutical company. Because the core business is drug hunting and, and marketing of the drugs. And so it was really a great experience to have my mind stretched and, and opened by [01:10:00] these other perspectives that are outside of pharma and we’re very technology focused.
[01:10:06] Alexander: Thanks so much. And yeah, that’s a, that’s a great case study. How new digital tools. Can completely change the way we work. And so for everybody that listens [01:10:20] to this episode you can find all the details on the homepage of the effective statistician. And there, we will also have a link to the slides and an overview of that.
[01:10:30] Chris: I’m sorry, Alexander. I just remembered that there will be a podcast and not necessarily a visual. So I will say that an email [01:10:40] address to get me is Chris, C H R I S at talk to the CAG T A L K T O T H E C A G. The CAG is the Collegial Advisory Group. So that is my email, my direct email address.
[01:11:04] Alexander: Awesome. Great.
[01:11:05] Chris: Thank you so much for the opportunity, Alexander. I appreciate it.
[01:11:09] Alexander: Yeah, me too.
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