Inside Insights: Data & Analytic Solutions in Complex Landscapes with Michael Kim
In this next series of Tech-Driven Business, Michael Kim, Data & Analytics Leader, joins Mustansir Saifuddin to discuss how to approach data and analytics in a complex landscape. They'll dive into how to simplify your implementation approach and what it takes to have a successful implementation.
Michael has 20 years of product management and consulting experience at Accenture, IBM, KPIT, DXC Technology. Michael is responsible for implementing over 15 Data and Analytics Solutions across multiple industries. He's a Product Strategist and Expert of the information delivery platforms: SAP, IBM, Snowflake, Salesforce, Workday.
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Episode Transcript
[00:00:00.000] - MustansirWelcome to Tech-Driven Business brought to you by Innovative Solution Partners. In this first episode of a multi-part series, I welcome Michael Kim, a data and analytics expert. Listen in as Michael shares his thoughts on how to address complex IT landscapes for a successful implementation. Hello, everyone. Joining me today is Michael Kim, a good friend and a seasoned leader in the field of data and analytics with a focus on SAP technology. Welcome, Michael.
[00:00:42.530] - Michael
Hey, Mustansir. Very nice to be here. It's a pleasure. It's always great to have a conversation and dialog with my good friend. What better topic than talking about data analytics, especially given time right now where things are going. It's an exciting time for the market and the industry, and I'm happy to be here. Thanks for having me.
[00:01:02.760] - Mustansir
All right. Now, great to have you, Michael. I think this is one of the hot topic as you go along across the board. Any organization, everybody is talking about challenges of implementing data and analytics in their environment, especially when you have a complex landscape. With that, I'd like to get into our discussion points. Are you ready?
[00:01:26.920] - Michael
Yes, absolutely. Let's get it going.
[00:01:29.020] - Mustansir
All right. Let's start with a high level. I wanted to get your take on how do you approach data analytics in a complex landscape? What are the things that you're seeing based on your experience? Can you explain, can you share some thoughts on that?
[00:01:44.100] - Michael
Absolutely. This is the big elephant in the room for all organization, is what is complex? And especially data analytics alone, topic itself is complex. So how do we tackle it? And it's been a conversation. It's been a question. It's been a challenge for all organizations globally for however long ,I've been doing this for a very long time. And it doesn't change. I think the way I see it and what I experienced for the past 20 years, serving multiple clients and multiple vendors, both from SAP and outside of SAP, and IT and business, I think it comes down to two things is what is a complex landscape and how do we approach it? And really nails down to, two, is process approach or is it a data-driven approach? And there's no right or wrong answer for that matter. It's really what sets the foundation of solving the complexity to provide business clarity on process and what role does data and analytics products and toolset comes into that picture as well. So I've seen an organization who prefer to have a data analytics landscape where they want to have it more centralized, meaning they don't want to have it decentralized from multiple regions.
[00:03:07.130] - Michael
They want to consolidate it from multiple regions to one centralized data platform, which will produce data products to the business and to the customers and to the vendors. And then I've seen organizations where they prefer decentralization of the data environment. And of course, I'm not going to say there's no right or wrong approach on this. I think it all comes down to the customer's desire and where they fit in the industry. And at the end of the day, it's understanding the environment of the landscape. And that's how you tackle it is a centralized approach of the data environment and how do you solve that complex landscape? And then what is that data product and process comes into place as to a data centralized data environment where you want to provide clarity and data insights in that decentralized, but how does that serve the purpose to the customers and the users in the business to provide data products around that area.
[00:04:05.550] - Mustansir
Got it. No, that makes sense. I think that's a good lead into my next question. When you talk about implementation approach, what criteria do you employ? And basically, what is the application to simplify the implementation approach is a better question, I guess.
[00:04:23.830] - Michael
I always go with this approach is I think it's taking a step back from applications or business, but how we come into this world from when we're infants to when we become an adult and as we age into more mature grownups. There's three stages. There's crawl, walk, and run approach. And of course, I think that's the most important thing for the organization to really realize where they are in the current state is are they in the infant stage? Or they are in the infant stage where they want to make that transition into walking and to running and then ultimately sprinting. And if I have to put that into an analytic perspective is, I think this is the most common term that's thrown out there is, where are you in the organization in your data products and analytics maturity? Is that really driven by descriptive analytics, or is it more predictive, or is it more prescriptive? And then it gets more complex with new embedded things like artificial intelligence and machine learning, which makes analytics going from prescriptive to a lot more advanced to do a lot more wonderful things on how to use the product.
[00:05:41.950] - Mustansir
Yeah. I think you hit it right on. That's one of the things that a lot of organizations do have to analyze where they are in this journey. And that can be challenging, depending on the maturity of the data analytics approach that the organization is using. And to your point, when you talk about these three phases of descriptive, prescriptive, and predictive, it is a balance of what you currently have and where you want to end up. That's the key, what I'm hearing from you.
[00:06:23.260] - Michael
Absolutely, Mustansir. I mean, you and I work with a lot of colleagues going back to many of us, we serve a lot of customers in the past. And I think it's the same story, even for you. You've been into a lot of big high profile, large cap companies, large different, I guess, corporations, different business global wide and SIs. And when you walk in, first thing I believe you always look for is even for yourself is where are we? What am I walking into? And then where are we as a project, program, also as a client? And minute you, I think, harness that realization, we're in the program, then you also define what you need to do and how you can add value to simplify that implementation approach. It's the same thing for every consultant, every data analytics professional is really understanding your surroundings, your current state, not only for yourself, for the program and the client, and also where does the Si role come into picture? Where does the application or software vendor come into picture? It's really understanding your current state and where you want to get to, which is the future state.
[00:07:28.730] - Mustansir
Yeah, for sure. I think that using that as a driver into our next conversation is based on your experience working with system integrators, as you mentioned, customers, SAP itself, what constitutes a successful data analytics project?
[00:07:47.520] - Michael
That's really interesting question. I guess it's coming from IT then. I guess it all depends on who you're serving as a data analytics professional or as industry wide consultant or expert. But it really comes down to, in my opinion, is who are we here to serve? Is it IT or is it business or is it organization? What makes the company click? And in my personal philosophy is it's always prioritized business first, mainly because going back to the whole fundamental three pillars is people, process, and technology is when you start a business, even for a small startup, it's selling a small hamburger for mom and pop stores to turning that into a multibillion dollar global hamburger chain. It's all about selling the product and serving the public. Who's going to help you get there? It's the people. It's the people you hire and people who share the same vision. And then after that, after those people are defined to collaborate in that vision, what is the set of process that we need to put in place not only for the company, but also within the division, within the people and the culture? And then once you set that good process and strategy, then that's when the technology comes in and make sure that we execute.
[00:09:15.520] - Michael
I think with that said, what I'm looking for as a cost is successful is the business objective is met. And if that business constitutes a C-level executives, or it constitutes a middle management, or also even for the customers and vendor is can they make data analytics about providing insights and providing data and providing intelligence so they can make informed decisions? And to me, that's the prioritization that constitutes successful is that are business able to make better decision for the company than they were able to do it in the past than as to today and also for the future? And also there's no right or wrong answer. It also depends on where you are in the program. And at the end of the day, it's always going back to the core fundamental is making the business and organization successful.
[00:10:09.520] - Mustansir
Yeah, I think I like the way you summed it all up. And it seems like first you need to know your end-customer, especially when you're dealing with analytics. And at the end of the day, the business needs to benefit. And if the business is benefiting, then that will allow an organization to grow, which is the whole idea behind Analytics is to help businesses, organizations as a whole, to make sure that they are on the right path, they are making progress. And your approach makes a lot of sense, especially when you talk about success factors, like what are the things that makes an organization click? Thank you for clarifying that. I think this is really important. Then when you're talking on this topic, let's look at it from a different angle. Why is it important to have all these projects? We look at different projects and why is it so important to have a good senior analytics architect who can see things from a holistic perspective on these projects? Why is it that so critical?
[00:11:15.180] - Michael
Well, I can share my personal experience working with you when you join the program, one of our clients is they want you join the program. Mustansir here comes in and say, Hey, Michael, Mustansir, very nice to meet you. And we click. And then the first question you asked is, What am I walking into? And who are my customers, and you wanted to get the whole picture all together. And my questions is like, Okay, there's a lot of good questions you're asking. And one of the things you're saying is that everything is connected, Michael. As a senior architect, not only have to see it from technical perspective, but you have to see it from business perspective, and you have to see it from process perspective. That's what the senior analytic architect brings to the successful program is having that right combination of technology and business and also process in place to really see the holistic picture where the whole fundamental principles that you add here that you always preach to me and also we preach to our team is, Analytics and data are all connected within the organization. We just need to help the business and the technology, IT and the customers be able to see the holistic picture of how everything is connected.
[00:12:29.030] - Michael
So it's not just the analytic architect who's specializing on tools like SAP or Oracle, or not just the business architect who comes from consulting company like McKinsey, just focusing on such much business process, but being able to connect both process, business, technology all into one, and then package that into one holistic picture and drive that whole success of the program. I think that's what sets the importance of senior architect. And what I'm trying to... I think the lack of a better word is the total package, who sees everything and who are able to connect everything and then able to drive to that success. That was an impressive experience. We always adhere to and we always preach it to our colleagues. So far, it worked out well, right?
[00:13:14.650] - Mustansir
Yeah, for sure. That's the key, that holistic view like you explained it. Especially when you're trying to do a robust data environment, how do you define your goals? What is short term versus long term? And like a strategy approach versus more operational approach. So seems like having that person, that view of the whole landscape really allows you to get into the details. And the only way you can do it is having that experience in the past, right? Having been there, experienced it, seen it, and now you're applying all those learnings into this project, right? So I think that's what I'm hearing from you.
[00:14:02.620] - Michael
Absolutely. I'm going to quote you on this. There was a moment in the program when we're working together, you said, Hey, I'm here for two things. I'm here to either add value, I'm here to fix the problem, I'm here to do both. I think if that mindset comes in, and that's mindset and the principle that senior architect holds, I think that program is due for good success. I'm sorry to steal your quote on this, but that was the very impressive that the principles that I still go by is I'm always learning from my colleagues like yourself. I think that's the core founding principles as a senior analytic architect is to not only add value but also fix problems, but at the same time do both, not only for short term but long term as well.
[00:14:45.640] - Mustansir
For sure. Thank you for the kind words. I think that takes us towards the end of our conversation. I'd like to always ask this question from our guests. Based on what we covered so far, what is the one key take away that you would want to leave with the listeners today?
[00:15:02.200] - Michael
Analytics, data, this technology, there's no right or wrong answer. It's changing every day. And one thing that has, I think we're in 2023, year 2023, but the year 2002 pandemic has taught us, if anything, is that we still don't know. Even with the week, we're never well prepared. It's always evolving. And there was one way to counter that is always preparing ourselves to, technology wise, people wise, and process wise. But in order to get there is understanding your organization, either organization as an executive or organization as a middle management, or organization as a customer and vendor we work with. It's understanding your current state and where you are. And then from there, using that self realization to really drive the strategy, the short term strategy and the long term roadmap to really have a good, clear picture of where you want to get from point A to B to X, Y, Z. I think that is the key take away for I want to share with the listeners today is that I think analytics and data technology, what we're doing in this industry is always going to be a journey. We just need to know that where we are in the journey and how we want to get there.
[00:16:18.240] - Michael
I think that is the critical component of our success, not only to ourselves, but to our customers and vendors and our partners.
[00:16:25.860] - Mustansir
I think you said it very well. My two takeaways from this is change is the only constant in this industry as well as self realization. Self realization is the key for an organization to move forward on where you want to end up as a data analytics landscape. And then, of course, the long term strategy that becomes part of the goals that you want to put together. This was a great conversation, Michael. Looking forward to having more sessions with you where we do some more in depth conversations on this topic. I'd like to get some real life examples from you. Thank you very much for joining the session with us today.
[00:17:07.090] - Michael
Thank you Mustansir. It's been a good first session and thanks for having me. To our listeners, definitely it's exciting times for the field of data analytics. This is an incredible journey we're going to embark on. I'm looking forward to more conversation and more dialogs and experiences we're going to discuss going forward.
[00:17:28.700] - Mustansir
Thanks for listening to Tech-Driven Business brought to you by Innovative Solution Partners. Michael shared valuable insights on what it takes to handle complex landscapes. His main takeaway, there is no right answer when working with analytics, data, and technology. It is constantly evolving and it's a journey. We would love to hear from you. Continue the conversations by connecting with me on LinkedIn or Twitter. Learn more about Innovative Solution Partners and schedule a free consultation by visiting isolutionpartners.com. Never miss a podcast by subscribing to our YouTube channel. Information is in the show notes.
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