How we Avoided Paying $275K in a Microsoft EA Renewal

Hi, I'm Mike Austin, CEO and founder of Metrics Data 360. And I've got here with me today one of my consultants, Delano. Delano, you want to introduce yourself?

Absolutely. So I'm Delano Michael. I'm a delivery consultant here for matrix data360.

Excellent. And so Delano, I understand it you just finished a project with one of our clients where we got some pretty, pretty significant results. You want to maybe give us a little bit of background on who that client is and maybe talk about what we did for them?

Yes. So we were engaged by this hospitality Canadian company which manages, operates several restaurant chains here in Canada and one of their prime goals were to help them or assist them with their EA renewal. Right.

If I, if I remember correctly, when we first started talking to them, you know, they expressed that they were, you know, super confused by licensing. You know, they thought they were doing things correctly, they didn't have a lot of data in order to make decisions on. So those were some of the, the prime concerns that they had.

That's absolutely correct. So, so the corporate Office was basically using Google and they were probably aligned with their spent. It was the other entity which was running Office 365 where they had so much sprawl on their licensing, where they did not have adequate control put in into their licensing spend. So we were able to align their cost significantly by showing areas where they could improve on, pertaining to their spend. And this is not uncommon. We see that happen with many clients and through this itself we are able to help them to align their overall spend on the office 365.

And so how long were we engaged with them? I know they engaged us to help to do their Microsoft EA renewal.

Right.

But how long did that process take from start to finish? And actually maybe what was the end result? How did we end up, how did.

They end up doing so from a duration standpoint, the start to finish was about a month in end to end and in terms of the overall accomplishment, there's, there's a couple of areas. So one was on the Windows Server side of things. Again these were all derived through, I would call it utilizing data. So one of the things we saw through this was there was an overflux of host running, you know, Windows VMs and through, by reviewing that we were able to tell them or inform them that they could potentially reduce their host configuration by consolidating some of them to smaller numbers. And through that process there was a significant amount of savings on their Windows Server licensing by reducing around 90 plus cores on their windows data center licenses. And, and in terms of savings, dollar value wise, it was around 50 plus K. Right, that's, that's number one.

Right. And so I'm just going to peel that back a little bit.

Right.

Because I think this is a key thing. When you say data, you know, I'm assuming we went out and we inventoried their systems, found out what was out there, found out, you know, their host configuration. So in their VMware environment, you know, what VMs were on what host. And when you talk about consolidation, we were able to look at that and show them that they had clusters or hosts of servers that were consuming licenses inefficiently because there might have been a couple of Windows VMs on a host and if they were able to move those to another host, they could remove licenses and that's where those savings were able, were able to come from. Is that kind of. Am I close to what we did there or is that.

Absolutely, that's exactly what happened. There was a flux of host within a cluster which was inadequately utilizing some of the VMs. And through again the reviewing of data, that's a key piece here. That is through that we were able to determine and show them through the consolidation that they should, they could potentially, you know, reduce those host and maximize, maximize it by a smaller footprint on, in their Windows server environment.

Right. I'm guessing what we did with SQL is very similar. We don't really need to dive into the details of that, but similar sort of thing looked at how use their deployment data to look at where things sat and make some recommendations. Because I believe we suggested that they were able to reduce the number of vcores and things like that and were able to do that. So two questions around that was how do we know that the data we were using was, was good data? In other words, how do we know that we could trust it to make those sorts of decisions and make those recommendations to the client?

So one of the processes we go through is when we receive data is we run go through, I would say a coverage report and we make sure that we accomplish around a 95% coverage on their server footprint. And that's how we come to the conclusion that, okay, there's sufficient coverage for us to progress or proceed to the next stage in terms of our analysis and through that mechanism that we derive that the data is the best. We also validate to make sure that there is no missing additions or versions or you know, core counts. So some of the validation pieces are done prior to us analyzing the data.

So basically we run a report that looks at what we collected from inventory, compare that to their directory, figure out if we've got 90 to 95% or I think 95% coverage. And then not only do we look at from an inventory perspective, we also look at other key license metrics, like do we have all the processor counts, are they correct core counts, you know, do we have the guest, the host mappings, all those sorts of things. And then once we have that, we can say yes, you know, other decisions we're going to make we can make with a 95% certainty so that they can, they can move forward.

Right.

Would an LSP do this sort of work or is this unique to us?

It's, it's sort of unique in one way that they, in a way that we look at not just the data side, we also look at the business impact that, you know, it helps the client from optimizing the environment by reviewing the data. So that's a key differentiator, which I see compared to an lsp.

Right. So it's about not just looking at do we have deployment data and assigning licenses. It's taking it to the business contacts and coming back and be able to do that. Let's switch gears. So the one brand that we worked with that had O365, what did we end up doing around Office365 for just 300 years?

We were able to sort of advise them that it would be a better option for them to move or replace the EMSE 3s with the M365 F3 licenses. And that would, I would say yield, I would say some savings on that. And there's more services which through the M365 F3, which the client could benefit overall. That's Number one. Number two, was again looking at their O365, there was a bunch of licenses which they could re harvest as well. And that also was a, was a part of, you know, reduction of their overall monthly, you know, spend on their O365.

Right. And so if I understand it, it's about 40,000 a year or something that we're able to take out of 300 users.

That's correct. That, that's absolutely right.

And again, I want to just, I want to point out here that like we didn't go in and say like, hey, move from E3s to E1s or anything like that. We actually said move from O365 to EMS based on what they had so we were looking at their. Is it fair to say we looked at sort of their usage data to see what they were using. Alta understood their roadmap to understand where they were going, and then we use that to figure out what the best license scenario or option was for them. Does that summarize? Sort of, you know, what we did there?

That's exactly what it was. So there was a few buckets of information which we looked at from an optimization standpoint. One was looking at their inactive use accounts, number two was on their blocked users, and three were secondary accounts, and four was service accounts and unassigned licenses. So those were the five buckets we reviewed and came about in terms of the overall optimization strategy.

Right. So we found licenses that they were either ineffectively assigned, that they weren't aware of utilizing the data, and we won't get into the details of how we do that today, but that's awesome, Duano. I mean, at the end of this, I got to assume the customer was happy. What sort of things were they saying to you when we, you know, when we were finished the project, they were.

Pretty much happy with the overall service we provided to them, not only just from a data discovery standpoint, but we were there with them, you know, end to end in terms of having multiple meetings with their different groups of people in the infrastructure side of things, the online services. They also mentioned that they have not received this kind of service with their current lsp. And that was definitely something which they, you know, communicated that to us, saying that we were there with them for this entire renewal every step of the way in terms of giving them that, giving them the necessary guidance and to move forward with their renewal.

And I know because of other conversations I've had with you as well, that they said that this renewal was probably the smoothest renewal that they ever had with Microsoft and that the amount of time that they spent internally was significantly reduced due to, you know, working with the metrics data 360 team. Is that, is that that fair as well?

That's a fair assessment. Absolutely. Yes.

It was, yeah. Awesome. I mean, I look at this, I know, I know what we charge them. They got somewhere between a 15 and 20x ROI on the fees that we charge them in terms of savings and dollars that they put right back into, into their IT budget. You know, great work, Delano. I know that we have a happy client there and we've got other, you know, other work that we're going to continue to do, do with them. Is there anything else that you can think of that. You want to share on closing here?

I believe we covered everything we needed to cover with this client. It was a great experience working with them, and even they communicated that back to us as well.

Awesome. Thanks a lot.

Thank you.