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What do the following have in common – data, building organizational culture, and leveraging technology to augment that culture? Seemingly nothing, if you go by face value. However, these three seemingly disparate elements can help in building data cultures in an organization, and hence, collecting, analyzing, and inferring from this data becomes critical. How can organizations go about this? That is the crux of this recent conversation that Rajat Kohli, Partner at Zinnov, had with Ramshanker Krishnan, General Manager – EMEA Azure Cloud & AI – Microsoft Consulting Services, Microsoft, in this episode of the Zinnov Podcast – Business Resilience series.
Ram emphasizes on the nuances of building data cultures in an organization, and the importance of aggregating the right data. In light of how fast data changes, he speaks about how to build teams to prepare for change, the value of product management in today’s business and technology landscape, and the best strategies for managers to set achievable goals. He gives us a deep analysis into how Cloud has changed over the decade and what he predicts for the future of digital transformation, and AI/ML.
Rajat Kohli: Hello, and welcome to an all new episode of Zinnov podcast, Business Resilience series. I am Rajat Kohli, Partner at Zinnov and I’ll be your host for today. While the term Digital Transformation has become a staple of pretty much every conversation these days, there are still a few facets of digital transformation that are underexplored.
To get a better sense of what digital transformation means in today’s world and what kind of mindset is necessary to drive digital transformation, we have with us a very special guest Ramshanker Krishnan. Ram is currently the General Manager for EMEA Azure Cloud and AI at Microsoft. He has had a very momentous journey of 19 plus years in the field of technical consulting, product development, and IT management. He has been instrumental in leading organizations that deliver innovative and meaningful impact to customers through cutting edge data and AI technology. A very warm welcome to you, Ram, great to have you with us today.
Ram: Thank you, Rajat, thanks for having me on this podcast. And it’s a pleasure to be here and talk about a topic that I’m really passionate about.
Rajat Kohli: Great. Good to know that. Awesome. So without further ado, let’s jump right in and hear from the man himself. Ram you have had an exciting career spanning over two decades at Microsoft. Can you please walk us through your journey highlights?
Ram: Yeah, absolutely. I’ve always dreamt of being in Microsoft. I think it started the time that I started my coding career. I started writing my first line of code back when I was in the sixth or seventh grade on BASIC language. So that’s when I was introduced to Microsoft. And from that time, there’s always this love affair that I’ve had with Microsoft.
And after my college, I did my degree in computer technology. I was working in a couple of start-ups and product organizations, and then I moved to the US and I had my opportunity to get started working with Microsoft, initially as a consultant and then I got hired as a full-time employee there in the US, in Redmond.
I have had a number of different roles. Initially it was around engineering management, specifically focused on information security solutions. And then I moved to the professional services organization, which is where I have spent a bulk of my career. The reason for that is I love working with customers directly. I love working on challenging problems and opportunities and using technology to go address it. So the last, I would say 15 or so years, I’ve been in the professional services organization. In India, I’ve worked in EMEA specifically in the last decade or so, specifically leading transformation projects for our customers.
So that’s kind of been my journey so far. And right now I lead the professional services organization, as you mentioned, for Azure Cloud and AI, focusing on Europe, Middle East, and Africa customers.
Rajat Kohli: That’s great to know. And I’m sure that you have been in the field ever since the term digital transformation cropped up. In your career specifically, where did it begin? Very curious to know about that.
Ram: So it’s a good question. Because when I started with professional services, I think a big part of what we were trying to achieve at that time, and specifically in India, I was trying to build up our India team. Really looking at how we can help our customers through delivering the SMAC stack or, or trend. Mobile and applications and cloud were a big part of that really helping deliver differentiated experience through applications, through mobile technologies. And then I think it was back in 2015/2016 timeframe where the focus on data and AI started picking up again
I think there were a few breakthroughs that have happened in the field and I actually invested quite a bit of my time going through a number of courses and stuff on MOOC to really understand what’s going on, training myself a little bit on the data science aspects.
And then I also had a job I was fortunate enough to take, because my previous role where I was focused specifically on delivering data and AI solutions for our customers in India. That’s kind of where it started. When you think about digital transformation, the data revolution was kind of the driving force at the core, at the center of transformation, just the sheer availability of data and the sheer ability to process that data and some of the breakthroughs that happened with respect to machine learning and algorithms. All that coming together, in my opinion, kicked off this whole digital transformation, I would say, trend. And for me it was my previous job where I was leading the data and AI organization.
Rajat Kohli: Interesting. I think so you pointed out cloud computing and AI/ML as one of the key components of the digital transformation. But if we go back little, in the initial years of the adoption of AI/ML by enterprises, what were some of the challenges you faced more from a supply side point of view? And if you knew then, what do you know now, what you would have done differently regarding the change management?
Ram: There’s so many things that have changed and so many things that are changing right now. And every day there are new lessons that we’re learning. And of course, I don’t think we can necessarily go back five years and apply the same lessons that we’re learning right now as part of, I would say, being in an agile world right now. Because if you think about the maturity of the cloud of when it was back then to where we are right now, we’re far ahead right now.
So some of these lessons learned, I can put it in that context of where we are today from both the technologies and maturity of these technologies, whether it’s cloud or whether it’s the AI technology or even how the customers are as well. But a couple of things, which I still think are going to be relevant. You know, the first part, which we still struggle with today, as we struggled with that back then, is really having the right data, because at the end of the day, the core of any effective AI model is going to be the data that it’s going to be trained on. So if you really think about it, having a data strategy ahead of time that can support AI is going to be critical, because it’s going to help you set the right foundations to go faster.
People have spent a lot of time trying to sift through and find the right data to be able to create the insights that are required from the data. So in my opinion, having a very strong data strategy and investing in that readiness, so that you’re not just coming up with these cool AI models that people either are afraid to use or don’t know how to use, or don’t know how to maintain it and keep the effectiveness up.
So there is a lot of organization skills and readiness and the investment that are going to be required in that to really bring it up to speed to get the best of these AI models. So that’s the second piece which I will look at and say, when we start with, having the right data strategy and the data platform that as AI-ready and also having the organization readiness upfront and being core of any AI program. I think these are the two things that I would call out which are still relevant.
Rajat Kohli: So, Ram, you mentioned about the interesting aspect of the readiness, specifically in the AI, but on the other side, if you look at the agility, when it comes to agility, what are some must-haves for organizations in their technology, as well as, talent arsenals.
Ram: When you think about transformation, transformation cannot be treated like merely a technical implementation project. So that’s the first change in the mindset and approach.
When you think about transformation, this needs to be holistic where it covers the technical and cultural aspects. So in my opinion, investing in change management skills are going to be super important for anybody so that you’re are able to understand where you are, you are understanding where you want to go and make sure that you’re taking along everybody in the organization in that journey, you’re not leaving anybody behind in that journey. That’s the first part of it.
And when you think about other specific skills as well, I want to highlight one particular one, which is around product management, which is really about envisioning digital capabilities that you will have to build to deliver the outcomes that you would need as part of your transformation journey.
And I think product management is at the core of it. And when you look at any technology companies…successful technology companies have very, very strong product management skills. And when you now think about every organization in the world right now becoming a technology organization, this is one of those skills that they would have to continue to build so that they can really connect technical outcomes to business outcomes, that’s what product managers in product management skillsets would bring in.
And then when you think from core technology perspective, technologies that will help organizations be agile, in terms of, cloud being foundational to that, because your ability to move fast, to be flexible, your ability to scale, the ability to be secure, those are key aspects to being agile. And for me that’s foundational.
And then the other aspects of it is around, the whole notion of DevOps in short-circuiting your experimentation mindset where you can imagine an idea and be able to run a few experiments, learn from it and fail fast and recover fast as well. So that mindset and those skills are some things that every organization would have to build. And again, these are not something that you can outsource. And this is something that every organization, in Microsoft Satya calls it tech intensity… the tech intensity that every organization would have to build.
Rajat Kohli: That’s an interesting point. And I think so, in between you mentioned about the product managers, the product leaders. On those aspects, what are some common mistakes that technology leaders make that keep them from reaping the maximum benefits of the ongoing digital transformation wave according to you?
Ram: I think one of the core ones is trying to seek a silver bullet. Because when you think about transformation, there is no silver bullet. You can’t say this one thing is now we can claim, you know, we asked to be digitally transformed. I think it is that holistic approach. And in Microsoft, we call it ‘enabling that digital feedback loop’, which is again between your customers, between your employees, people and your products and services.
It’s really about enabling that consistent feedback loop. And these are very broad categories where, it’s not just one project or one initiative that is going to help enable that feedback loop. It is something that you’d have to invest in the long term. There needs to be a commitment for the long term. There needs to be sponsorship for the longer term in terms of enabling this for the organization.
So in my opinion, I think one of the core mistakes is to look at it as a one-off project or look at it as a one-off experiment, and not committing to the longer-term transformation. That’s one part of it. The second piece, which I think I mentioned earlier, from a leadership standpoint, committing to the cultural change that’s required to enable and reap the benefits of transformation project. I think that’s critical. At the end of the day, as leaders, you cannot leave anybody behind in your organization. The people would have to transform along with the organization, along with the culture. I think that’s when, so our best examples have been that… When we work with customers, when they deeply understand the intricate nature or the dependency between technology, people, and the business aspects.
Rajat Kohli: So these are the interesting aspects. Shifting gears a bit and I’m sure, me and others would be interested to know, looking at the coming new year 2022, what are some upcoming trends in the AI/ML space according to you?
Ram: Two things that we are seeing in terms of…one is how do we bring large scale models? How do we leverage large scale models that, you know, for example, Microsoft is working on a few of it right now with…it’s only possible for some of these hyper scalers to go to train those models, but then, applying that and leveraging those models in everyday scenarios? I think that’s going to be critical. So leveraging these large scale models is going to be critical.
The second piece of it is, in my opinion, is inferencing at the edge. Really making sure that we can have intelligence move closer to where decisions have to be made. So we’re seeing much more of that happen.
And the third trend is in terms of the low code/no code and ability to leverage AI more holistically, not just with specialists, developers, or data science or data engineers, but much more broadly in our low code/no code approach as well. So I think those are some of the trends that we are seeing in this space.
Rajat Kohli: Interesting. Yeah, I think so the low code is a vital one. We are also looking at that aspect. We are looking at the combination of AI with the low code/no code is what we are seeing. But if I look at more from a business outcomes from an enterprise, how do you think these advancements, like use of the large-scale models in a daily life and the implementation of these advanced technologies… How do you think these advancements and the trends can be leveraged to improve business outcomes? It could be on the revenue side, the cost optimization, the productivity, etc.
Ram: I go back to the digital feedback loop I referred to. Data and AI and cloud is at the centre of enabling this digital feedback loop. So when you think about delivering new experiences for our customers, these are models that we see this…How chatbots are being used in innovative ways and whether it’s in the banking sector or the telco sector, or the healthcare sector, especially with this pandemic there’s been a huge amount of transformation that it has triggered. So these chatbots and the ability for using natural language processing is dependent on these large scale models for example. Then you look at operations, in manufacturing, in digital manufacturing, quality control, using vision in quality control, massive amount of data is being processed as part of these large scale models to be able to make this possible. And also in terms of autonomous systems right now, that’s coming up more and more, where you can make decisions in an automatic fashion. In terms of the people and employee and providing a differentiated experience for your employees. Knowledge mining is a massive area where AI and ML are being used to make sure that people have the right information and access to the right information in the fastest amount of time that will help them make decisions faster. Whether it’s your sales force or whether it’s your research teams or whether it’s your engineering teams, even when you think about how AI and ML is being used right now.
Recently Microsoft announced as part of GitHub, the ability to have AI-generated code. So as software engineers, we’re looking at making life easier for software developers as well, being able to come up with code. Similar situations are happening across various areas as well. For example, you could have next best actions being much more prescriptive depending on the scenario. If you are a sales person, if you are a marketing person, having feedback in terms of how effective your campaigns have been, where do you see the biggest benefits and how you can target much more in terms of those specific areas?
Really on the employee experience perspective as well, AI is being used and infused in a number of different ways and then if you really think about all the AI-infused products and services that you could create as well. So in my opinion, the opportunity is to really start thinking about infusing AI more broadly across the business, across all business processes and across all customer experiences and employee experiences.
Rajat Kohli: Wow. I think these will help big time to improve the business outcomes across industries, not any specific industry. I think so these are important ones and before I let you go, I want to ask you a few rapid fire questions that will help our audience get to know you better. A favorite gadget or app that you can’t live without?
Ram: Right now, it’s a Flipboard, which basically does news aggregation.
Rajat Kohli: Which technology according to you will revolutionize the world in the next five years?
Ram: I wish I had the foresight on that one, but my bet is going to be on IoT.
Rajat Kohli: Interesting. Great. Thank you so much. This has been a wonderful conversation, Ram. Thank you for sharing your perspectives with us. They’ve given me a lot of food for thought, as I’m sure our listeners will also agree to that. Thank you once again for taking the time to be here with us.
Ram: Well, thank you, Rajat, thanks for having me, and this is again, a really exciting conversation, so much opportunities ahead of us, and I really want to wish you and all the audience a fantastic start to 2022.
Rajat Kohli: Likewise, happy new year to you and the Microsoft team and family. Thank you everyone for tuning into this episode of the Zinnov podcast Business Resilience series. We’ll be back soon with another episode, with another trailblazing leader. Till then, take care, stay safe. Wish you all a happy new year. Thank you.