Thriving In The Digital Age: Imran MacMillian and Digital Technologies

In this episode of Thriving in the Digital Age, Joe Crist interviews Imran MacMillan, Senior Director at Launch by NTT Data, about the challenges and trends in the digital world. Imran highlights the importance of managing the separation between expectation and reality when it comes to implementing digital technologies. He also discusses the impact of AI ecosystems on digital transformation and the evolution of employee toolkits. Imran emphasizes the significance of data in AI maturity and advises companies to focus on a data-first approach. He also explores the concepts of process mining and platform convergence as key trends in digital transformation.

https://www.linkedin.com/in/imran-macmillan/

Transcript

Joe Crist (00:02.361)
Hello everyone and welcome to another episode of Thriving in the Digital Age. I'm your host Joe Chris. Joining me today is Imran McMillan. He's a senior director from NTT Data. Imran, thank you so much for joining us today. Could you please tell the audience a little bit about yourself?

Imran MacMillan (00:21.704)
Absolutely, Joe. First of all, thanks for having me. It's a pleasure to be here and talk a little bit about some of the digital trends that a lot of businesses are navigating today. Personally, I've been in the professional services industry for a little over 15 years at this point. I've seen a lot of change. At this point, I'm really focused on go -to -market innovation for NTT data. So a lot of what that involves is making sure that we're incorporating leading practices into things like software delivery and application development.

making sure that we're strategizing with our clients to make sure they can address some of the trends around digital disruption today. Things like AI based delivery of services, things like platform convergence, things like managing and navigating the trends around sustainability and ERGs. So I'm really excited to talk to you about some of these themes and personally represent a very large company, but I've been around the block.

and I've worked just about every angle of software delivery lifecycle across my career. So really excited to jump in

Joe Crist (01:25.017)
Hey, I love to hear that and I'm very excited too. So obviously you've been doing this for a while, right? 15 years is a long time. And based on the work you're doing nowadays, like what challenges are you seeing out there for a lot of your clients?

Imran MacMillan (01:38.888)
If I could boil down the challenges into one consistent theme, it's really the separation of expectation versus reality. And I think that divide has never been larger than with the advent of artificial intelligence in our day -to -day life. All of a sudden, our clients have the expectation that we might be able to deliver software services for 50 % less cost with 50 % more speed than we have a year ago.

And quite frankly, the reality is not there. So when we talk to clients about matching up their expectations to the outcomes they're trying to deliver from a business value perspective, that's one of the first conversations we have is grounding ourselves in reality and understanding that they might not necessarily be ready to adopt the level of maturity that they think they are. And getting and crossing that Rubicon with, you know, a fairly obstinate client.

can be quite challenging as I'm sure you've experienced as well. So that's definitely one of the major threads that I would pull in terms of trying to understand some of the challenges that businesses are facing today with the advent of digital technologies and software everywhere.

Joe Crist (02:54.307)
You know, that's absolutely something I see a lot. It's, you know, the expectation of what technology can do. And I think that has to really do a lot of glamorization of these new technologies coming out. Right. When people think of AI, they imagine AI is this, you know, one fix can solve every single problem. But what they really don't understand is there's a lot of work that has to done beforehand to really adopt things like AI. Right. And even to adopt things like

A lot of these technologies, it's not a you just plug it in and lights are switched on and then you're good and you're rolling. There's a lot of infrastructure on these to be created first, but also the education of how it works and what it can and can't do. And also is it their actual right technology? Just because someone heard something may change their entire business doesn't mean necessarily will.

Imran MacMillan (03:46.44)
That's a great point. And you know, that's why I love to think about AI from the context of an ecosystem and less as a point solution. Right. And so frankly, I'd love to pull on the thread of what is the impact of AI ecosystems on the process of digital transformation? You know, so in my experience, as you said, you know, I've been around the block and considering that I used to be heavily involved in building and implementing software and IT solutions at scale for

massive public and private enterprises. One things I'd really love to focus on is the evolution of employee toolkits. And I think it's important to sort of start with a brief history. So, you know, in the advent of software implementation, it was primarily focused around command line interfaces and really programming in those. And ultimately there were packages developed to pretty them

Right? Because no one likes to look at a black and white terminal for eight hours a day for, you know, 300 days a year. Nobody wants to do that. So things like VIM, Nano, Nice, really prettified command line interfaces. But then there was the next era where development interfaces became even more prevalent as software frameworks and languages expanded. And so what that led to was this era of competing integrated developer environments.

otherwise known as IDEs, right? So there were both software specific and non -software specific editors, things like Eclipse, Atom, Visual Studio, PyCharm, things that many, many people are listening today will be very familiar with. Now, these IDEs could be augmented with packages and tools as well, enhancing graphical usability, improving workflow functionality.

implementing shortcuts for format editing or even basic auto completion. And then there was even third party tools. So eventually an ecosystem around IDEs started to develop things like Git really enhanced and ease developer work streams. But one thing that was sort of noticeably absent from this evolution of work stream for software engineers was what about the rest of the ecosystem? You know, what about

Imran MacMillan (06:01.99)
business analysts who are still writing user stories and requirements in Word or Jira or God forbid, Excel, or designers who could do wireframes and mockups and a bunch of different tools, but didn't really have that customization enhancements to their own individual workflows. You know, there's product managers who are still relying on manual efforts to reconcile work streams, determine story points, burn down, and a whole bunch of other agile software delivery metrics.

And then we go to the data side where you're still completing complex schemas and unintuitive tools like sparks. God, that's almost giving me tremors just thinking about that. And then of course, the final end of the SDLC is like QA and testing, right? They did benefit from early adoption of automation frameworks. It's actually where artificial intelligence was really focused three years ago in the service industry was really all around

test automation and QA automation. But still many teams relied on point and click techniques for things like feature validation and end user testing. Well, you know, where I see AI playing a role is it took this fragmented approach to augmenting the life cycle of software delivery. And it was really destined for disruption. And AI has become that agent for change. So nowadays there's a lot of talk about things like

platform engineering and to boil it into like really simple terms, it's the ability to create a productive ecosystem of accelerators for developers that can help them in a range of activities from things like creating new application templates, recommending new function additions, auto creating APIs and backend functionality based on natural language and an understanding of the front end code. And of course there's many, many more.

use cases. However, in my opinion, this is a very limited way to look at what the AI revolution can deliver. And at NTT, we're not just solely focused on IDPs, which are integrated developer platforms, but more broadly at something I'm coining IXPs, which is integrated experience platforms. And the difference is it can span multiple functional roles. So we're essentially talking

Imran MacMillan (08:28.55)
role -specific work benches and AI augmented ecosystems that can provide expanded functionality and amplify the efforts of any single individual across a cross -functional team. And so this could be creating automated functions and unit tests as a developer, as coding and access management portal, or it could just be AI -driven syntax enhancements for a product manager that's trying to determine requirements or an analyst.

that's working on user stories. So ultimately, the broader scale of what AI is delivering to the service industry is these comprehensive workbenches that can span roles and create ways to accelerate work in all of these different domains and ultimately tie it together under a single schema or under a single accelerator that's really fueled by AI.

So for us, IXPs are the wedge that allows us to deliver better, faster, stronger to our clients. And also I quite frankly see it as a bit of an arms race, especially in the service industry where everyone is trying to level up their workforce, right? Upskilling has always been big, but now it's not just upskilling, it's up tooling.

what kind of proprietary platforms can we deliver as a services organization to our employees, to our workforce that enables us to be cost effective in the market, that enables us to drive industry specific solutions, that enables us to be more competitive than an internal business team might be. So that's sort of how I see the timeline of interference and how AI is playing a role in the evolution of digital disruption in software.

Joe Crist (10:21.049)
Yeah. You know, and not only are you focusing a lot on hyper automation, it's really comes out the hyper scaling, right? You're giving employees the ability and organizations the ability to really have a really customized experience on how they're doing their jobs, whether it's bringing on new tools that give them a competitive advantage or just designing a process where it really does work for them, right? Where you can turn, and correct me if I'm wrong, but you could turn one person into many.

Imran MacMillan (10:29.007)
Absolutely.

Joe Crist (10:50.817)
at this point, right? Because you have AI since you're augmenting them and then on new process design and everything connecting. So you have essentially a person piloting the ship, you know, and being able to do their job far more effectively.

Imran MacMillan (11:06.92)
I love what you just said there, right? The personalization of experience. I think that's a huge, huge focus area for AI because you have general LLMs, right? You have the chat GPTs of the world. You have the bards of the world that can handle natural language querying that can give you very generalized, non -specific answers, non -legally binding answers to just about any question that you can come up with.

Now the focus is shifting to domain centricity in the application of AI and LLMs. So one great example of what we're doing with clients today is in the healthcare health plan space. So we want to create situations and tools that can actually lead to the advent of personalization of healthcare. You want to be able to have proactive healthcare solutions based on your patient records,

based on the EMR EHR data that already exists around your profile, but has never been used aggregated together, cross referenced against multiple different external libraries and turned into a proactive approach to prevent something like type two diabetes, right? So for us, this advent of personalization in different domains is playing out very, very live. And the way that we're sort of enhancing

our service capabilities with AI is really topical, especially in the healthcare space.

Joe Crist (12:41.987)
You you brought up a really interesting point earlier. Well, I guess the phrase arms race, right? So the way technology has been moving, it's everything's happening so quickly. There's a lot of capital being invested. A lot of people are now innovating things, leveraging AI and other technologies and obviously integrating. So what practices can companies really start doing today to start working towards these solutions?

Imran MacMillan (13:08.412)
That's a great question. So if you talk to any AI expert or any service delivery specialist, they're going to say that the crux of AI maturity is in the data, the underlying data, right? If you still have large pools of unstructured or semi -structured data that hasn't been properly indexed, that lives across different sources,

that might be spanning hybrid cloud environments, you might not have a good way to articulate or have schemas that bring that data into a usable format, right? So data first approaches to AI are where a lot of times we recommend to our clients. So, you know, that's quality, that's governance, that's really understanding the business principles behind the data generation.

Sometimes there's just random data being generated in the course of a business process because you might have batch processes that you didn't realize were navigating through certain repositories in certain way or interfacing with certain applications in certain ways and creating data fragments that are utterly unusable and actually even influencing the usable data that you have. So it takes us back to a point that me and you have talked about quite a

where digital digitization is really the advent and the interface between people, process and technology. And data is really the bits behind the process. Right. And so if you can understand the process, understand how that's driving the generation of data, and then use that to find new business rules that can clean up your data for long -term consumption into AI models, that's really

ground zero in terms of how you can sort of prepare your business to take advantage of things like multimodal LLMs or natural language querying and processing, or spanning out new AI interfaces for enhanced customer acquisition. All of that starts with a fundamental understanding of business process and how that's generating data for your organization.

Joe Crist (15:26.423)
You you brought us something interesting too that I think we should really elaborate on. So you mentioned unstructured and semi -structured data. Could you elaborate like between like semi -structured, structured and unstructured data? Like what that really is and what that means for companies?

Imran MacMillan (15:41.64)
Sure, and I think it's probably important to take an industry lens because it could mean very different things for very different businesses. So just going back to the health metaphor that we were working on, right? So structured data, very easy, right? If you're looking at an EMR, electronic medical record or an EHR, it could be things like, you your blood pressure, your temperature readings, your weight, you know, some of your lab results.

Like those are all highly quantified, highly specified data points. And then if you go into the flip side of that and into the semi -structured or the unstructured data, then that could be, know, scanned PDFs of doctor's notes on the patient as he came in. patient appears to have a bucolic appearance as he came into the room, or the patient seems to have gained more, you know, let's say fat

let's say an unhealthy physicality since his last visit or anything that the doctor notices, maybe his eyes are red, maybe he's building up more mucus, maybe there's things that aren't traditionally captured in an EMR but are still annotated by a doctor and then scanned into a patient record later, that's highly unstructured data. So then you have to have enhanced mechanisms for even retrieving

and acknowledging and understanding that data within the context of some kind of tool that will use it for prescriptive diagnosis, right? Then you have to have a PDF digester, scanner that can parse out the relevant pieces, associate that to the existing data elements and use that to create a complete picture of the patient health. So that's just one specific industry example of the differences between like highly structured

highly ordered data versus some of the most errant types of data that can come about in a patient provider experience.

Joe Crist (17:46.521)
Absolutely. it's really like the way I'm seeing this, it's so structured data. There's typically a very standard definition of what that data looks like, right? Whether it's, you know, obviously your blood pressure, like if it's BP, BP should look like this, right? And then it doesn't look for, right? And then unstructured is like, here's a doctor's signature, which I'm sure everyone's seeing the doctor's signature as well anyway. it's like, well, that's the signature right there.

Imran MacMillan (18:09.852)
Hahaha

Joe Crist (18:16.437)
So obviously the data part is a big deal, You can't really, AI can't read data if it doesn't know what it's looking for. when I see like implementing these types of systems, right? And these types of solutions for companies, obviously you have that data first approach. What happens after?

Imran MacMillan (18:27.72)
certainly.

Imran MacMillan (18:38.704)
Yeah, so that really varies. It depends on what the ultimate business objective is. Right. And so for a lot of companies these days, I mean, let's be real, we're living in a hyperinflationary moment in the economy. so businesses are somewhat focused on expansion, but a lot of times focused on cost mitigation and consolidation. Right. We're seeing it in the service industry with a lot of vendor consolidation.

We're seeing it in the healthcare domain where a lot of companies are merging and acquiring other similar organizations to create economies of scale that can benefit them in the way that they approach the marketplace. And so for a lot of businesses, they're really focused on cost reduction, especially when it comes to digital implementation and digital delivery. And so for us, what does that mean? It means reconciling EMR, EHR systems,

It means reconciling license provisioning and software consumption. means reconciling cloud spend. It really means streamlining experiences, like taking it back to healthcare vertical, right? So for one thing that we noticed, there's a lot of inefficiencies intrinsic to especially the United States healthcare experience. Even the way that you go into a doctor's office and you're waiting and

you see a nurse and then maybe you see a GP and then maybe you get referred out to a specialist and maybe your MRI is scheduled three weeks later and maybe you get misdiagnosed along the way. Like there's so many opportunities for inefficiency throughout the process of discovery to diagnosis. And so that is one area where AI can be a massive accelerator for not just accuracy of diagnosis, but also prevention of disease.

because if you can sort of identify early indicators of going back to diabetes or going back to things like insulin resistance, if you can identify early indicators, because now all of a sudden you're interfacing all your patient health data through an AI tool and not just one general practitioner's hearsay or whether or not he may or may not be up to date with all the latest research in the field, then all of a sudden you have a trough of data

Imran MacMillan (20:57.552)
person and relative data available to you to actually make those quantum leaps ahead of time before you're in, you know, sort of the deluge of dealing with the diagnosis. so predictive health is, I think, one of the most exciting areas of AI applicability that we're working with today. And so I love that example. I think it's a great one. And I think it's something that impacts all of us. I mean, personally, on a

personal level, I've already been told by my doctor to start avoiding things like red meat, to start doing things like daily exercise. And, you I always tried to consider myself a healthy person, but sometimes we don't find the hours in the day to get all of those things done. And so it's one thing to have that hair save from a doctor once a year, maybe if you're doing your annual physical and you're actually keeping up with that, because I know a lot of people don't. But if you had

a quarterly email digest that's coming out to you based on your data points, based on your family profile, based on your diagnosis data, based on your latest lab results that could actually tell you, hey, have you done this lately? Hey, have you tried doing this? Hey, have you scheduled your annual physical? Those kinds of things really have the ability to shift the needle in the way that we deal with healthcare in the States today.

Joe Crist (22:21.645)
Yeah, it's really interesting bringing up, as obviously going to the doctor, right? It's no small feat, right? You have to schedule a appointment, you take it off from work, do all these things, but actually having like those emails, those notifications, and I'm sure at one point too, could probably integrate with their technology, right? So what does the future look like here then, right? Is obviously we're developing so rapidly, right? And there's going to probably be a lot of integration here. Like how do you see the future in this space?

Imran MacMillan (22:52.23)
That's exactly it. think you hit the nail on the head, right? Integration is key. You need interoperability and bidirectionality between systems of interface and systems of record and systems of action. It's not enough to have them siloed. It's not enough to have different teams managing each one separately and reporting up to some kind of a business layer representation. You need multimodal interface between all these different departments.

to actually get to outcomes that can shift patient outcomes. And so one thing that I've seen, a technology that's maybe on the cusp of commercial, not commercialization, but sort of massive influence across our economy is process mining. So this is one of those AI tools that has the ability to unpack the people and process element of technology adoption. It's really difficult.

as a single practitioner or even as a team of practitioners to unpack all the business rules, all the business process that can go into something like hospital operations. It might take years for you to understand all the edge cases, understand the whole dichotomy of the services landscape, the way that nurses interface with volunteers, the way that nurses interface with doctors and practitioners, the way that doctors and practitioners interface with patients.

all of the process that lives in those little nooks and crannies, it's a beast of burden, right? And so now all of a sudden you got tools like Solonis where you can sort of just wheel it in and it can crawl through your enterprise, crawl through all the systems of record, crawl through all the interface points and really come up with a web of how the end -to -end business process looks. And once you have that view, then you have the ability to effectively deep

strategically place accelerators, strategically modernize certain systems or applications. So you're not looking at multi -billion dollar efforts. You might be able to look at a $10 million effort that can create multi -billion dollar impact. So that is one of those next gen technologies that we're seeing really move the needle in a lot of the companies we work with. And a lot of times when you thought about process mining, it was an ITSM game, right? Like how can we mine IT service management data

Imran MacMillan (25:14.866)
to better operationalize IT departments. But now it's moving beyond that. It's like, how can we get into the business layer of what the enterprise is actually doing and really start from that and then modernize upwards? So that is one of the exciting aspects of digital transformation that I'm seeing impact us today. And I'm sure that that's something that you've probably seen start to impact some of the clients you work with as well.

Joe Crist (25:44.601)
Absolutely. I love that this is growing too. It's one of the most challenging parts of the deal or any sort of client. It's when you're asking them for documentation or a map of a process. typically what I see with lot of companies, at one point they didn't map out the process because it made sense. But as the company begins to scale and they're obviously

Imran MacMillan (26:00.21)
Ha

Joe Crist (26:13.593)
growing and adding more to the process and more connections to that process, they focus less on documentation and more on just the throughput of the process, which is, it's a double -edged sword, right? Obviously they're making more money, they're helping more customers, but this becomes a really big challenge for integrating new technologies because technology is not a solution that fixes a process, it's a solution that makes the process faster, right? So if you don't have a well -documented process that's not well mapped out, it's not our mind,

then it becomes really hard to actually bring in new technologies and scale more effectively. since process mining is still fairly new, could you explain a little more? It's very interesting topic.

Imran MacMillan (26:49.327)
Absolutely.

Imran MacMillan (26:58.916)
Yeah. So the way we love to describe it to our clients is it's the MRI machine that can scan your enterprise and understand, identify and map out deficiencies across what you're doing as a business. Right. So you sort of wheel in this tool and I'm not going to sit here and lie to you and say that it takes zero upfront configuration, zero expertise with implementation, zero context of the actual business that you're working with.

It requires all of those things to be successful. But ultimately what it does is it comes in and it crawls across your enterprise almost like an agent based tool in an IT operational framework where it's going into all the different data pockets. It's going into all the different logging mechanisms. It's going into all the systems that you're using.

whether that's your ServiceNow, whether that's your Salesforce, whether that's your SAPs, it can go into each of those sort of enterprise resource planning tools, ERMs, HRPs, all of those different verticals. can go into the tools that the business is using, understand the configurations that those tools have, understand the outputs that those tools are creating, and understand the processes that they're using to get from the input to the output. And by creating a map,

a weave, a web, whatever you want to call it, literally, if you can imagine a massive tentacle diagram that has steps along the way, that's what it's creating. So you have a way to visualize, actually articulate the different processes that are happening between each system that is being used across your enterprise. And, you know, that's just step one. That's discovery phase, right? Once you can see the entire end -to -end scope of business operations, you can start to plan.

you can start to optimize, you can start to deep bottleneck. But that's really the promise of process mining is the ability to visualize and understand end -to -end business process between all the different apartments, all the different systems, all the different applications, all the different databases, all the different cloud providers, all the different SaaS consumption that you're using and get that full picture top to bottom. And then you can bring

Imran MacMillan (29:16.028)
really smart systems analysts, really smart business analysts, really smart architects to maybe redesign parts of it, re -engineer part of it, maybe, this was an unnecessary approval phase, or, this was an undocumented regulatory risk, or all of those kinds of concerns can be visualized and understood with really effective process mining. And so that's the goal, that's the promise, that's really the burden that process mining is trying to alleviate.

Joe Crist (29:45.923)
extraordinary.

Joe Crist (29:50.711)
in all right now, right? It's like, I've had to map these things out myself and like, just find things and ask a ton of questions. And a lot of people just don't know. And that's a big challenge I've seen for pretty much every company I've ever worked with. honestly, it's just impossible for one person or even a team to really do this effectively because as organizations grow, their complexity grows exponentially, right? New software, new processes, things that are still being done that no one knows

Imran MacMillan (29:52.166)
Hahaha

Joe Crist (30:20.791)
Right. Because there's just lack of communication and that's a very normal thing. And for a large company or even a small company, really, but yeah, the ability to actually be able to map and see the entire enterprise architecture. It's extraordinary. That is that they're like, wow. Right. That is you have, you have the ability to really digitally transform yourself now because it's

Imran MacMillan (30:38.01)
Yeah, it really

Imran MacMillan (30:43.772)
Hahaha

Joe Crist (30:52.51)
The people part, right, when it comes as a transformation, you're gonna be able to create that digital literacy as you know what tools you have, right? And you're gonna understand with that, you have where it's going, you're gonna be able to see your processes, because it'll be very clearly mapped out for you, here's what goes where. And then obviously now you can start integrating the right technology, because you say, here's where we're, here's where we are today, here's where we need to be.

we can do a gap analysis because we have a much better understanding of our own organization.

Imran MacMillan (31:24.208)
Yeah. And honestly, it's leading to one other technology trend, which is we can loosely call it platform convergence, right? Where all of a sudden, if you have that end to end map of systems of records, interface and execution, if you know where you're consuming data, if you know where the business process lies across your entire ecosystem of tools, software, applications, systems, once you have that, all of a sudden,

they can start collaborating in new ways, right? Now you can tune your SaaS applications to work together. And so that's this whole concept of platform convergence. And I'm sure everyone understands what ServiceNow is, especially in the world of ITSM. It's been the workflow orchestration engine of choice for IT departments for many years now. But what you see them doing now is stepping a bit outside of IT operations.

into other domains like CRM with Salesforce or even software delivery with Jira. And really the outcomes that that kind of orchestration across SaaS platforms, it's really tremendous. So, you know, on the simple side of things, it could just be maybe you're reclaiming unused licenses that you didn't realize you were paying for, or maybe you have more tight tracking of software subscriptions because you now have a basic integration of Salesforce marketing cloud

your ServiceNow instance. But if you're really thinking about workflows and tracking workflows end to end, then you're thinking about from the point of customer inquiry to the point of implementation or resolution into ITSM vertical, that's where the value lives, right? There are a lot of companies that are trying to be that connective tissue, but quite frankly, I've seen ServiceNow and Salesforce work together to develop joint go -to -markets.

with the help of service integrators like us at NTT data. And it's really the convergence and integration of these platforms that allow a single system of action that spans customer engagement all the way through to service management. And then you really have the ability to adhere to deadlines. you say, customer says, hey, Mr. Service provider, we need this feature because our customers are demanding

Imran MacMillan (33:47.228)
then you don't have to go crawl against three different tools to figure out how long it's going to take for you to deliver one IT upgrade or one software delivery upgrade or one feature functionality upgrade. All of a sudden you can cross -functionally sort of understand what the workflow is for you to get from the point of customer inquiry to the point of software delivery and testing and quality assurance and get it back to the customer faster, have

towers involved in the process of decision making along the way and actually get to the value faster. And so that's the whole beauty of platform convergence. I think we're going to see a lot more of that. mean, everyone loves to say SaaS is eating the world. It is, but not as fast as people thought. And it's because the more SaaS you consume, the more complex your business operations become. And now that we have this way, this methodology that's sort of gluing and anchoring these different systems together,

I think the whole SaaS eating the world mantra is actually going to accelerate now because now it's not just separate SaaS platforms that are doing their own business modality, but it's actually systems that can work together to create higher level business value and actually appease customer objectives at a greater rate. And so I think that's the value of platform convergence. And that's one thing that process mining is really leading

So it's sort of cool to see these separate threads come together in a way that's actually going to enhance the experience of end users like you or me or businesses that are trying to reach customers faster, better and provide more effective platforms for

Joe Crist (35:26.649)
That is so exciting to just think about how the world's really changing because that's the direction we need to go in. The world is getting fast and in order to compete, you have to be faster. And by really mixing your technology, converging your technologies together, and then obviously you're having, whether you're using AWS or Google Cloud, having things talk and be not just efficient, but effective.

Imran MacMillan (35:37.541)
Absolutely.

Imran MacMillan (35:49.864)
you.

Joe Crist (35:55.619)
That's the difference maker.

Imran MacMillan (35:58.062)
Absolutely. And, you know, there's, there's a lot of other things, areas of focus for, you know, businesses trying to get ahead into digital world. You know, I just love to touch on just a couple. You know, one of them is a lot of people are talking about the influence of AI on customer experience and user interface design. You know, this used to be sort of this designer focused activity that required a lot of expertise, a lot of understanding of the end user functionality, a lot of understanding

who the end user is and how they prefer to interface with a tool. But now a lot of those things can be driven by AI decision -making. And so it goes back to your trend of around personalization. It's not just personalization of healthcare. It's not just personalization of experience, but it's also individualization of software and how that will ultimately be the pinnacle of what AI can provide for software engineering. If you could design one application,

that let's just say helps you aggregate and track your investment and spend across all the different bank accounts and investment platforms and brokerages that you have accounts in. So let's just say there's a single application like Mint, which unfortunately went under or got bought out. But the point is people can't use Mint anymore. And so they were trying to tackle that customer problem of how do you manage spend across all these different platforms that you have accounts in. But now if you just had one application,

but let's say you are on Fidelity and Charles Schwab and I'm on Truist, Capone and three other banks. And so it's all about the personalization of experience and tweaking that application for your, to best optimize your experience within it. So if there's only one application, but you have an AI module that can tweak the experience based on the types of banks that you tend to go to because it can determine

preference for the ways that you like to interface with the banking institution based on the ones that you use all through one module that sits on top of an application that's baselined. Now that's personalization of a whole nother degree, right? So to me, that's the kind of thing that I get excited about. A lot of people talk about how AI is cannibalizing services and how AI is cannibalizing humans and intuition and all kinds of other terrible things.

Imran MacMillan (38:23.186)
but really I think it's gonna lead to the advent of personalization on a greater scale. And I know Black Mirror has toyed with some of those concepts in their shows and I love it. But for me, that's one of the things I get excited

Joe Crist (38:39.769)
It's such an incredible thing to think about. So I actually do have one last question for you. So obviously, you've been in the game for a while, right? 15 plus years. What piece of advice could you give to the audience that you think would really help them? Whether it be a data first process or just how to implement AI or run a company better, or even that advice is always welcome. What would you tell them?

Imran MacMillan (38:45.778)
Please.

Imran MacMillan (39:08.36)
Great question. So I'm going to take it in a slightly different angle than you might have been expecting. And let me frame it by saying we live in the era of the conscious consumer, right? Someone who is buying services and products, not just for their functionality, but also for the values, the mission and the ethos of the company that's driving them. Right. And so sustainability is coming to the forefront of the services industry. It's coming to the forefront.

of the software industry and it's really changing the way that consumer behavior works, right? We don't want to just buy a product because the product suits our basic needs. We want to buy a product because we believe in what that company is doing on a greater scale. So if I could give one piece of advice is don't just plan your business operations around evolving footprint, around customer acquisition.

around demand generation and marketing, but really try to pivot your business towards an ethos or mission driven approach to business operations. Right. And so for different companies, I could mean very, very different things. You know, for a software company, that means, okay, now you're using AI tools, but does that mean your cloud spend increased 50 %? Does that mean your carbon intensity increased 500 %? Does that mean your sustainability dropped by 20 %?

So even if you're a US based company and we don't have a lot of those regulatory standards that exist in the EU, that doesn't mean that you shouldn't be focused there. Eventually those standards are going to come to the States. Eventually sustainability is going to come into the focus and eventually your mission and your ethos and your values are going to come to the forefront of whatever you're selling. And so for me, it would be that if you're not already thinking in that direction, start thinking in that direction because it's the way that services

and products are going to be consumed and bought in the future.

Joe Crist (41:08.771)
That's, man, I love that so, so much. Yeah, it's, it's, it's, man, so

Imran MacMillan (41:13.008)
Yeah.

Joe Crist (41:20.605)
We live in such a connected world now where everybody knows what every company is doing and it's very easy to the news. And to your point, doing the right thing. Don't just do things because it's the right thing, do it because it's needed, right? Because the world is changing and people care about this stuff. know, it's we're all on the same planet together. We're all sharing the same resources, right? We all, it's globalization.

Imran MacMillan (41:39.24)
All right.

Joe Crist (41:49.963)
Right? Where it's things we do here impact things that happen in other countries and things in other countries happen here. So it's really just trying to be, you know, not just ethical, but good. I love it, man. So beautiful.

Imran MacMillan (42:06.139)
Absolutely.

thanks. Yeah, we're in a global village, right? And, you know, it's naive to think that the actions that one business takes is not going to impact the lives of many others. So yeah, if there's one thing that I would leave it at, it's

Joe Crist (42:23.961)
That's awesome. Well hey, everyone, thank you so, much for joining us today. I'm sure the audience appreciates it. Everyone again, that's Aaron McMillan. I hope everyone enjoyed the show as much as I did. I had a great time. Definitely came back a little, definitely a little smarter now already.

And everyone, thank you so much for joining us again. And I hope to see you again next week on another exciting episode of Thriving in the Digital Age. Thank

Imran MacMillan (42:52.05)
Yeah, thank you so much, Joe.