Episode Transcript
[00:00:00] Speaker A: Welcome everyone to a new episode of the FinOps weekly podcast. And today we are going to talk about one of the most difficult challenges that enterprises figure out today and is the hybrid cloud and the hybrid finop challenge. So when the cloud expertise and the cloud finops is not enough. And for helping us today with the challenge, we have Jeremy Chaplin from Rexera. Jeremy, how are you?
[00:00:24] Speaker B: Very good, Victor, thank you ever so much. And excited to be back on Finops Weekly podcast. So, yeah, very much looking forward to our conversation this afternoon.
[00:00:33] Speaker A: Yeah, you are, I think you are the first one that repeats in our podcast, which is, which is amazing.
[00:00:39] Speaker B: And you have that very much.
[00:00:41] Speaker A: Yeah, it's always there is only one first one. So this is, this is great. And we are going to talk about something that I think worries most of the companies, especially the big ones that have a hybrid cloud. So something part of premise, something on private cloud and on public cloud. So what do you think? To start with direct question is what do you think are the main challenges that arise from having hybrid cloud finops instead of cloud only finops where you only can have the CSPs that we all know. And now we have to interact between the on PREM or the private cloud and the public cloud for doing this optimization.
[00:01:24] Speaker B: It's a real challenge, isn't it? And you know, already, I think when I started getting involved in FinOps and the focus was on that collaboration with a broad range of straight stakeholders, public cloud was touching everything right all the way down to engineering.
And I came from a kind of ITAM background where we probably didn't end up speaking to engineers at the end of the day. And so that was a kind of paradigm shift a little bit in terms of the breadth there. But now as we see the framework, including other scopes of private cloud, Data center to SaaS management as well, I think that we're increasing even further the breadth of the engagement and collaboration that we're trying to achieve. And so doing that across the inform, optimize, operate life cycle ultimately becomes more challenging. And I'm sure we'll get into that. But the challenges in tooling and visibility and the different levers and things that ultimately we need to pull or at least bring together to have an aggregate understanding presents the, you know, real challenges mostly, I guess in organizational collaboration as much as anything else.
[00:02:37] Speaker A: Yeah, that's true. I think like whenever you change the paradigm from a cloud perspective to something that licensing, which is what we are going to talk about a bit, it's so different than the cloud and so different than the SaaS platform, which work in a totally different consumption way that you know, you need to put a different perspective of the whole phenos that is out of, of cloud. Right?
[00:03:04] Speaker B: Totally. Yeah. And you know, everybody kind of likes, likes to stay in their lane, don't they? To some degree.
[00:03:09] Speaker A: Right.
[00:03:09] Speaker B: I mean, you know, we spoke earlier, just before we started about people that have spent a lifetime doing license management and they understand all the nuances and terms and conditions and taxonomy and you know, all of the three letter acronyms in the Microsoft licensing space, for example, that you know, me as a finops practitioner and heavily focused on public cloud, would never have an opportunity even to scratch the Surface in terms of understanding. And so it's how do we leverage, I guess the expertise that those other folks have developed and be collaborative rather than trying to kind of reinvent the wheel or redevelop an understanding. Myself, I would never be successful unless I brought in the right people to work with to leverage their expertise in their domain as well.
[00:03:56] Speaker A: That's true. I think maybe we are seeing a specialization of finops since we are expanding what the practice is doing from cloud to all the different steps. Now we are integrating like with other roles that before weren't mentioned in the context of Phenox or where finally mentioned, such as you mentioned the ITAM or even the SaaS like SAS could be even different or the AI part. So you can do phenox for AI, very good, but not Phenos for cloud. So let's start with these domains and let's go step by step so that people understand what are the difference. So starting with the licensing, which is one of the topics that we have started, what do you think are the fundamental difference between cloud, finops and Item or this license management for, for controlling the cost?
[00:04:43] Speaker B: Yeah, no, great question. And you know, in the public cloud space, particularly as it's kind of, you know, been technically focused, we think about provisioning infrastructure, we think of this kind of mentality with a pay as you go mentality on.
[00:04:58] Speaker A: Right.
[00:04:58] Speaker B: I can put down a credit card and I can access all of the things that I need and I think the cloud vendors love that and of course we love the flexibility and the agility that that affords. I don' need to separately go and buy a Windows Server or a SQL license from Microsoft to get up and running if I don't need to. The same for Oracle and the same for the plethora of things that are in marketplaces across the cloud vendors.
But the reality is, for Most enterprises, at least that have been in business for many years, they own those licenses. They've had a whole procurement process and probably a team of people that are managing license compliant from an audit perspective, you know, cost saving perspective, are we using these efficiently? Have we got licenses that kind of overlap with each other? Have we bought things that, you know, we could reconcile, you know, down to single licenses and so on? So there's a lot of different lenses that we can look at that problem through. But historically at least, my experience says those in the public cloud space typically haven't thought about it too much.
But the reality then is, you know, that actually we did some research internally. We saw of this cloud spend that Flexera had Under management, over 5% of it was on two products which was Microsoft Windows Server, Microsoft SQL Server, of all of the cloud spend, 5% pay as you go on those operating systems and databases, and another 20% of our customers spend is in Marketplace. And so if we're not working with our software asset management counterparts. Right. The people that do manage that procurement cycle, the people that, that do know the nuances of what they own and how I might use it in public cloud, there's basically a quarter of your cloud bill you're ruling out from an optimization perspective.
So, yeah, that's really kind of where I see the challenges are in terms of gaining that understanding, bringing those teams together.
I, as a public cloud practitioner, won't know the nuances of Windows licensing, to know whether I can use it in public cloud or whether I can't, and how many CPUs I need to count for a SQL license and so on.
[00:07:19] Speaker A: Right.
[00:07:20] Speaker B: It's pretty complicated stuff.
[00:07:21] Speaker A: Yeah, yeah, indeed. And also something that brought up in a conversation that I had with another practitioner is that talking with these people that have a different role may help you even improve as a finops in your cloud role. And I can put on a specific example, which is negotiating contracts with cloud providers because they are very used like ITAM people or licensing people, procurement people, people are way more used to license management and license negotiation that when you are in this contract management, like the Microsoft program or the AWS program, the gcp, they will be so much, probably they will be much better than you doing this negotiation that you can leverage them to lend your hand on this.
[00:08:07] Speaker B: Right, absolutely. Yeah. No, it's a great point. And that whole contract negotiation, particularly with, we use a term mega vendor. Right. But someone like Microsoft, where they're doing public cloud, they're doing SaaS, they're doing on premise Licensing. In order to have a successful negotiation, you need to know the holistic view. Right. What am I spending on all of those domains? Because ultimately it's the aggregate of that cost that is going to that vendor and you should leverage that for negotiation.
There was a really interesting example that came up recently. Obviously anonymity for the customer that this was about, but they had negotiated an all you could eat kind of license agreement for certain key products from, from Microsoft. And yet we saw a significant amount of pay as you go spend in the public cloud space. So they've spent a lot of time in the procurement cycles and negotiating to get this all we can eat licensing. But then they're not leveraging it right, they're paying again, which is not untypical for us to see.
It's still relatively early days, I guess. Right. So procurement getting involved in the kind of public cloud conversation, EDP negotiation also becoming that we're seeing partners provide a role for their customers for as well.
[00:09:27] Speaker A: Yeah, definitely. And I think it's getting there.
The expansion I think for FreeNups is very early. So till, as I know, till enterprises are able to integrate something like a practice or a technology like happen with cloud, it takes time. So it will take 10 years or more to have everything matured and figured out. And then from there we are starting the maturity level and then evolve. So moving on to a second cost driver that is very different from cloud, which is SaaS. SaaS. It's probably one of the highest or the hottest topics from past year, I think in FinOps, especially on the FinOps Barcelona and on San Diego. That is driving out of course especially certain observability tools, data analysis tools, et cetera that ingest a lot of information and they drive a lot of cost. So for SAS tools, what are your perspective which are like, what are the challenges to analyze and to do phenos for SAS tools?
[00:10:37] Speaker B: Yeah, again, it's an interesting domain, isn't it? And there's a lot of confusion, I think often when we talk about SaaS, particularly in the FinOp space. So the number of people that I've spoken to and said how do you manage SaaS? And they immediately think about Marketplace.
[00:10:54] Speaker A: Right.
[00:10:55] Speaker B: That would be the initial, you know, that's the SaaS side of things for a, for a public cloud, you know, or finops practitioner and then you know, historically here at Flexera. Well, what was SaaS? Well, it was your Office 365S, your Salesforce, your ServiceNow. Right. All of those typical SaaS platforms. But you know I think the, well certainly obviously the, you know, the AI aspect has blurred the lines between what is SaaS and what is public cloud.
Quite interested actually to see the FinOps foundation come up with data clouds as a domain or a taxonomy because I would have called those snowflake and Databricks actually SaaS applications and I think that they do themselves but there becomes then a difference. Right. So what was historically in the typical business sash domain was possibly per unit pricing on a per user basis, consumption based pricing possibly or outcome based pricing as well.
But that's shifted. Right. The public cloud was always a price times quantity thing and so I think we're now seeing the data clouds if you treat them as SaaS ultimately then becoming completely different. Right. How much data are I indexing, how many API calls am I making? How many queries are you running against these services? And then not just the data clouds but then the, the SaaS based AI services Meta and others. Well how do you start to measure and understand both the price and the quantity of those kind of things given all of the different dimensions that are being introduced.
What about you Vix? I'm interested in your view on the whole data cloud piece as well. I didn't see that one coming.
[00:12:40] Speaker A: Yeah, so the data cloud, yeah it's a different thing. I think it's super important. There are like companies built upon data especially now that you know everyone. I think now everyone can get like a lot of data from, from the Internet with all the AI scraping all the, the information. So there is a lot of information especially with IoT devices, all these things and the, the thing I think there is a paradox here is that there are data tools that work like SaaS that are embedded within the cloud providers which is like bigqueries quicksight if you can do it that way. And on Microsoft I don't remember what is but I think there is one and I don't remember one but there are all the providers have this tool because they use it because BigQuery is probably the backbone of most of what Google does. And you know, aws of course with, with quicksight that's a lot of things. So they are probably bigquery especially it's the biggest, if I think one of the biggest cost drivers for this type of data clouds. I think it's probably the biggest one. So you have the interaction between SaaS and Cloud here which is a very different and difficult thing to manage because you can have like the SaaS tools working on like on prem or similar things or custom. Let's say deployments and then you have it on cloud, which is databricks on each of the cloud providers. So that's like quite a challenge. I don't know how you are thinking about it, but for me it's like quite a challenge to figure out.
[00:14:27] Speaker B: Yeah, so a lot of those vendors are making their services available via the public clouds as well and then in some degrees it makes it easier. So if I've already got tooling that gives me visibility of all the cloud services then I can start to see some of those AI based or what we would call SaaS based or data cloud based services in my own cloud bill.
But often that's not the case. And it's then it's a whole new build to ingest, it's a whole new domain to understand how is it billed, how is it priced, what are the levers I can pull, can I normalize it into a common taxonomy, is it Focus compliant and all of that good stuff. So those are the challenges that we're trying to solve here. Ultimately is it almost looks like the process we went through with Kubernetes. Right. So it was just another abstraction of spend that we already had and I needed to get another layer of granularity kind of to the namespace or even to the container level to start to understand and break down that bill. And we're just repeating the process here but with a whole load of different kind of metrics and measures, you know, behind the data consumption. So it's certainly interesting times as we look to solve that problem.
[00:15:44] Speaker A: Yeah, definitely. And I think maybe in these type of tools, probably freenops like analysts or whatever you you want to call that role have an advantage because they are used to deal with similar things for analyzing the billing data.
Well, BigQuery was basically, I'm not sure if it is still but for gcp bigquery was the export. You need to do it to do it on focus. So you need to deal with these type of people I recall like Anderson Oliveira's work on Databricks for Azure with focus. So everyone in FinOps is kind of related to these tools. So there is probably like an easier development here from FinOps and they could probably handle better than for example compute optimization or as you said, kubernetes. I think Kubernetes you need to have domain expertise because it's very difficult to do the optimizations to do the cost allocation. For example, if you have like shared workloads in Kubernetes you need to know what you're doing So I think maybe here finops like analysts could have an advantage. What do you think?
[00:16:56] Speaker B: Yeah, definitely. I was watching actually a recording of one of the sessions I think that had been done on ar, which is of course one of the areas that really spans all of these domains from Mike Fuller and others at the foundation.
And they started out saying, look, you probably know more than you think you do.
That's the starting position here is having done this for public cloud. You're in a really good space. You understand the complexity, you understand the nuances and you understand the terminology.
I think it just for me just means that you have to be open to a new wave of learning almost right. And just kind of again understanding the levers of how is it licensed?
Is it true SaaS? Is it per seat, is it per user, is it per query? Are we going into AI? And it's about data and model optimization. And so it's just a willingness to jump in again and kind of learn all of these new terms, terminology. But actually the framework itself for good reason is well positioned to help you through that process. So it still becomes an inform, optimize operate conversation and the domains and capabilities are no different really. It's just a different abstraction or a different domain or the KPIs and course of other things that we need to start to learn become different. So it's really embracing change as always.
[00:18:26] Speaker A: Yeah, I think it's going to be like especially with AI you need to embrace change because.
And you need to be prepared for because otherwise you are going to be disrupted every, every few months. So moving on to AI but, but before on that I want to remind the people that are listening that we have a webinar on the November 13th at 6pm Spain time or 5pm UK time. About that we are going to dive deep into all these cost challenges for hybrid finops that you are going to be here and we are going to have Gerhardt which is an expert in one of the topics that we have discussed which is licensing and all this hybrid cloud thing. So we'll leave the link in the description below so you can join and we'll do a deep dive on SaaS on licensing and of course what we are going to talk about about which is AI.
So everyone can join in the, in the link below and you know moving on to the hot topic everyone talks about now and which is AI.
So in your perspective, you know it's been a very talked about topic but in your perspective like AI cause how, how they are differing from traditional cloud cost that you have seen and what are the complexities you have seen either from customers or from your personal experience on this topic?
[00:19:54] Speaker B: Yeah, it's an interesting one and I think this has been the real catalyst for the convergence of all of these domains. Right. So just looking at the numbers from the FinOps foundation in that webinar, as I say, that recording that I watched, right, so gartner projecting gen AI spot spend to get to 644 billion this year. Right. It's massive growth here. And ultimately, you know, the audience, the practitioners in the foundation have also articulated that it's not just a public cloud problem.
So they are using sas, they are using Data center, they are using private cloud, they are using the data clouds to do this. And so the first one is just recognition that it is a driver behind how do we solve this hybrid cloud problem. Right. And it may be the thing that forces organizations to say, yes, I need to bring a SaaS Persona in. Yes, I need my SAM or ITAM person in the room. Because the only way we're going to solve this AI problem, which we've been challenged to do, ultimately from realizing value, is if we get together. And whilst we've tried to kind of do that For ITAM and SaaS separately, the momentum maybe hasn't been there for all organizations. So I think it's a real catalyst to change and to better bring these things together.
But it also then becomes an interesting problem that starts, and you made this point really at the start here about how do we go and buy this stuff? How do we negotiate with a vendor and in many cases that nobody knows how to even estimate what they're consuming. You go and ask, how many queries are we going to make for Copilot or chatgpt or whatever? Nobody knows how to start to even make a guess at these. And so we're often reliant on the vendor to give us some sort of indication, oh, you need this tier of consumption or queries or whatever it might be. So the problem actually starts in buying it. How do we even go around procuring licensing ourselves when all of these different metrics become. Become part of the conversation? It's no LONGER I need 20 licenses because I've got 20 people that are going to use.
Could be actually that you've got AI that is using its own license for these things, when you're starting to automate stuff. So a ton of complexity that we're seeing there as we start to think about the breadth. But again, I would encourage people to think about that from a SaaS management perspective. Perspective, right. If you're not managing the SaaS environment that you have today for business SaaS, when we start thinking about the AI element of all of those platforms you're already using and data clouds and other things, the complexity of what we now would typically say SaaS management is I think is going to balloon ultimately.
[00:22:49] Speaker A: Definitely. And I think that you know, I think AI changed the paradigm especially for SaaS consumption in like from as you mentioned per user perspective to a consumption base like you are now moving on. Which I think it. What happened to procurement when you know, moving to, on prem to the cloud. That is something that is way more difficult to estimate especially for the future. Like if you tell, I don't know, 100,000 company employees tell me like estimate how much AI will be spent in next year, which is probably what they are going to be asked about for procurement. They will know like how, how are you going to to know about that? If the models are changing, the pricing of the, the models are changing every time the consumption is changing so the context is longer so all these cost drivers are going to change. Right? And it's, it's super different and super difficult to, to know what's going to happen happen for companies that they need to know this like they need to do their estimates. They, and they, you know, we are, you know, and we are in the middle of Q4 so that's going to happen, right? What, what, you know, what you can say to these people.
[00:24:08] Speaker B: I mean let's face it, right? Budget and forecast in public cloud has been hard enough I think, right. If I see, you know, most of my customers and their level maturity there, it's been really difficult to get, you know, the organization to get their head around P times Q and that's when the price and the quantity are relatively, you know, relatively well understood, you know, items themselves. So yeah, I think we're going to see again organizations going back to the coral walk run, right. And so the initial stages is just defining well what, what makes up the price and what makes up the quantity. Quantity for the, you know, the services that we're consuming there.
And a real kind of back to back to basics start as they kind of iterate over that.
I think ultimately it's part of the problem in terms of the whole value proposition of AI is well how do we define that value but also how do we measure all of these different things that go to make up you know, ultimately the cost element as well as the complexity in measuring the business Outcomes because they, they're often very non tangible things that you're looking to measure.
[00:25:15] Speaker A: Yeah, that's true. And I think you brought a very interesting topic which is the complexity, the complexity that we are getting now, especially on the cost level for freedoms. How do you control this?
And we can talk about the paradox that it brings which is like now you have to control more things so you may need more tools for the different providers especially know big companies with multi cloud cost, with hybrid cloud cost like on prem cost, the SaaS code. So what can you explain us like why having all these tools providing you visibility and trying to, you know, figure out things, it could probably lead to less clarity to a finops to be able to see. Okay, this is my picture. So why do you think it's going on?
[00:26:05] Speaker B: Again, it's really, it's been an interesting space and I've spent a lot of time, you know, in the domain and obviously seeing native tools from the crowd vendors grow up and become, you know, really quite capable tools. But we always kind of defend from a Flexera perspective against that because typically they don't do multi cloud very well and you know, they don't interface with other business systems and they're not necessarily, you know, as configurable as third party tools might be. But when you then start to think well all of those other domains, right, what is it that you use for visibility into your data center or private cloud? Right. How do you know what the costs are? Where does the usage data come from? How is it exposed? Right. This is definitely an area where Excel typically is the tool of choice, right? The most popular finops tool on the planet and then we get the SAS element and there's going to be another set of tools. Right? There's of course market leaders in the space of doing SaaS management as well because they have their own sets of different criteria. We're looking at licensing, we're looking at compliance, we're looking at whether there are unauthorized users where they've left the organization and they're still using my office license or whatever it might be. And we're looking at it from a perspective of in a year's time I need to renegotiate and understand what my true consumption is and if I'm using the right type of licenses. Whereas what we're trying to do now is bring together that kind of typically license based discipline and then the you know, the P times Q the public cloud discipline and provide visibility of that. And it's a massive tooling challenge. We're fortunate enough to have a consistent data layer across the tools that we have in all of those spaces. But it's still difficult, of course, to start to normalize these things and report on them in a meaningful way.
I have discussions with our product managers from SaaS Manager, and I'm saying, well, my FinOps tool is probably the right place to put data, cloud data like Snowflake and Databricks, because it's a P times Q thing and that's not going to make a lot of sense when you compare it against Office licenses and Salesforce.
It's really difficult. How do we bring this together, which ultimately we need to when we start to say, well, what's the unit cost? Or how do I budget and forecast based on a particular service that I'm delivering when its costs are spread across all of those different hosting domains?
So exciting problem to solve, but I think it's definitely a challenge, you know, to bring those tools together.
[00:28:36] Speaker A: Yeah, that's cool. And I think that, you know, what you mentioned about the visibility and the different, you know, the different context, I think what, what each information should be put, I think makes a lot of a difference between having, you know, something that is just pure data and something that is, you know, knowledge and an insight. So I'm going to, to dive into this because it's, it's a topic that, you know, I've been seeing a lot lately. It's like, you know, what do you think, think makes the difference between having visibility on information and having an actual insight or an actual, you know, action item that you can do? What do you think makes that difference for. Especially in finos for, for hybrid.
[00:29:26] Speaker B: Yeah, that's a great question. So the visibility piece is, you know, arguably. Well, it's hard for a start, but visibility for me is not just ingestion of the cloud build, but it's actually contextualization of the build or that, or data center or data cloud, whatever it might be. So how do I get to a showback perspective? That would be visibility solved for me. And of course all of the metadata challenges and everything else become a problem there. But until you can get to that point, just ingesting it, whilst you might say, okay, well the bill is visible, do you have any insight?
[00:30:04] Speaker A: Right.
[00:30:04] Speaker B: The insight comes from the business context that we try and lay over the top of that and, you know, we're challenged, of course, of doing that in public. Cloud tagging is probably the hardest part of the job for a lot of people to get right.
But if we're not Looking in at those costs in the context of my business and what I'm using those resources to deliver as business outcomes.
The insight is purely maybe useful from a procurement perspective, I. E. This is the aggregate of my spend. But actually to take any meaningful decisions and you know, lead that into business drivers and other things is very difficult. And then of course the problem then becomes compounded because metadata, business context, units of consumption, they all start to differ as we then go into SaaS and data center and everything else. Right. So now we've got four sources of metadata that we need to normalize and I'm hopeful that things like the Focus standard are really going to help us deal with that. Right. If we can get that common taxonomy across sources of data, that's at least going to get you started because normalization is again a really big problem there. Alongside the metadata, we do have some customers that are using Focus for their on premises infrastructure, for example, which I think is fantastic. Right, that's exactly the way to go.
[00:31:26] Speaker A: So yeah, I think, yeah, yeah, I think that that was the goal of Focus. Right. Or that's when I understood, you know, the focus.
When I studied it, that was the idea and I saw it like, I first saw it like, you know, open API for big cloud building data, which is like I come from a developer perspective perspective. So I was easily for me to. Okay, why does, why didn't this appear before? It's like it's something that is normalized and you know how to do APIs, which is probably one of the most widely done things in development and you have a standard on how to do them. Why don't you have it for, for billing? Right. And what is for me is like it really is a challenge. It's like you have so many now out of the cloud, you have different cost drivers that we've been discussing today that are super different in a way that they are counted. The only thing that they have in common is that they, you know, they apply to your budget. So at the end of the month they will probably remove some, some money from, from your budget apart from the value that they generate. Right, but you know that having come on like, but the way that they generate these, you know, this quantity is super different different from one to the other. So if Focus is doing that like for SaaS, for on prem the moment that it can be done easily that way we have a very powerful tool for, for finops in hybrid cloud, which is like probably hybrid cloud, including like we discussed, AI and SaaS is the definitive till the Moment, situation, right? So it's the final, let's say situation with. You cannot get probably more, you know, more complex than that right now. Maybe in the future we'll have like another cost driver that will appear and we need to count on like, I don't know, image generation or video generation or whatever that is different and goes to a different way. So I think that's, that's, that would be the key, right? Like, we have an easy way which is difficult. Like, simplify. This process is super difficult where everyone can, like, like, okay, let's deploy this, let's have this, let's count everything, let's have a situation. And then, okay, from this data, tell me what an insight is, how I can do this, how I can, you know, analyze that data. And I think, well, AI helps on there. I have to say that I use it for a lot of data analysis. And, you know, having the insight is like, okay, thank you. This is what I was asking for. Like, like, yeah, I hope that you are accurate, but I think that this would be ideal if you are, you know, you can give me the number, right?
[00:34:06] Speaker B: Yeah, no, it's an interesting challenge.
And, yeah, well, AI, as you say, may be part of the problem.
We had a conversation with some of our product teams recently just about taxonomy for AI services, and they surprised me because we're actually using AI to classify AI.
[00:34:26] Speaker A: Right.
[00:34:28] Speaker B: We've got a model that looks at it and says that's an AI service or whatever. Right. So a bit of a circular reference there, but interesting space.
I'm excited. I think, you know, the go forward really, you know, now we've got the focus standard, now we've got the framework that is applicable to all of the scopes. These are really good building blocks to build on top of and, you know, continue to remember the principles. Principles of collaborating, of course, with other members is really the kind of key to solving these problems.
[00:34:57] Speaker A: That's true. And we've been talking a lot about AI, all different tools or technical things. But one of the things that I think it's one of the core drivers and the core drivers of success for a finance practice is the people are the ones that are doing this implementation, developing all this stuff, you know, learning the new things, adapting to the new model. So, you know, for companies, what is your, you know, your perspective on how they should, you know, structure themselves for solving the hybrid phenot challenge? On your perspective?
[00:35:36] Speaker B: Yeah, that's great. A great question. And again, I think the collaboration is the key. But, you know, how do you how you achieve that in an organization can be very difficult.
[00:35:47] Speaker A: Different.
[00:35:47] Speaker B: Right. So small organizations, agile, nimble, whatever you want to call it, you know, small, relatively number of people, then it's easy to kind of break down barriers and, you know, collaborate and sit around a chair or a room, you know, to have these kind of conversations.
But recognizing, of course, as you scale that out and you get to, you know, large multinational or government organizations, then often there isn't the process or the ability to, necessary to break down those barriers. It becomes a lot more challenging. And so I think we have to recognize as part of that kind of framework some of the complexities of the political landscape ultimately that you might be operating in and how you break down those silos.
[00:36:29] Speaker A: Right.
[00:36:30] Speaker B: It's a big part of, I guess, building a new FinOps practice, it's the stakeholder management and mapping and other things and it becomes ultimately more, more important here. So it's about change at the end of the day. And I think it's really looking at your organization and saying, well, how do we deliver change and how do we manage change across what may be a very large organization with multiple stakeholders and lots of politics and other things in play.
So seek the collaboration, but recognize that the challenges that your specific organization may have in helping you achieve that.
We see organizations where SAS or ITAM and FinOps all report into the same leader and they're very, very successful. But we see organizations where that's true and they're still struggling.
And we see conversely organizations where they've got separate ITAM and FinOps teams reporting into different parts of the business, but they've been very able to collaborate and work together.
So executive sponsorship always going to be the key here.
Understand the mandate and maybe AI and the value of AI is one of those drivers to helping your exec help get alignment across the organization and pull people into a room so that they can ultimately work on the problem together.
[00:37:56] Speaker A: Yeah, that's, that's true. And I think you, what you mentioned is very specific that, you know, each organization need to have, you know, the, the system and the context and the structure that works for them. And it doesn't have to be, you know, a generic thing. You have guidance that you can, you know, take a look and check, especially if you're doing the new practice because of course, you need to adapt to your own infrastructure or your own structure the way that you think so that you can develop the best practice for your company. Right. And, you know, talking more of a, in a practitioner level is that, you know, for people that are maybe a company of them, their company is expanding to on prem and to hybrid cloud. Or maybe There are new SaaS because of an expansion of an MIA incorporation which is something that normally drives a problem to integrate different providers. What is your advice if you have one for these people that may now encounter a transition between cloud to hybrid cloud?
[00:39:03] Speaker B: Yeah, I mean again, it's kind of share and communicate what you have. Right. So there'll be silos within that organization that don't know anything about the public cloud and the licenses that you're running in public cloud and the marketplace costs and AI costs that you have running in cloud. Right. So they're as kind of blind or blinkered as you are in terms of visibility of the overall picture and they're going to be just as pleased to see you pop up and say, hey, I can help. I've got some visibility of the data clouds that we're consuming. Right. Does that sit within SAS or FinOps? Well, maybe it doesn't really matter right now, but we'll get together and solve the problem. So, so recognize that there's a lot of value there and find the team members in other areas that are trying to solve that same problem. You can do that collaboration at the bottom levels as much as you can have it as a top down mandate from the exec.
But it's again about bringing the value that you have and sharing the data.
I also think as a finops practitioner that you're arguably better placed than anybody else understanding the concepts of cloud and the complexities of cloud. But understanding the framework. Right, because we're recognizing that that is actually a pretty good playbook for us to work through these things. And so sharing your experiences there with colleagues in other areas of the business is super valuable too.
[00:40:27] Speaker A: Yeah, that's true. I think the collaboration and the communication and being able to, to present the information properly. I think it's probably one of the soft skills that you value the most in finops because you are going to be talking about and you know, sharing with a lot of different Personas and being able to adapt the context and the pitch and the information that you share to the specific audience that you have. Talk their language, which is one of the most, you know, sharing finops. I think it's, it's crucial and, and I think that's, that's super valuable base.
So yeah, Jeremy, it's been a pleasure. I think it's going to be, you're going to share a lot of value with, with us on the, on the 13th of November, right?
[00:41:08] Speaker B: Yep. Very much looking forward to that and appreciate the opportunity to come on for the second time to today, Victor, a fabulous conversation as always. So very excited to continue that on the 13th, you know, with you and Gerhard as well.
[00:41:23] Speaker A: Yeah, it's going to be a wonderful conversation. So if you don't want to miss it, please check the link below so you can register.
Jeremy, it's a pleasure and an order that you are the the first repeater of finish Weekly Podcast. It's been a wonderful conversation and I hope we have helped a lot of people with with your insights on how to do this challenge and more information on that will be the 13th of of November. So thanks a lot for coming and see you in the next episode. Episode.
[00:41:52] Speaker B: Thanks, Victor. Pleasure. Take care. Pleasure.
[00:41:54] Speaker A: Bye Bye.
