Name: Enforce Governance, Compliance and Security Everywhere Data Goes (Europe & Middle East)
Uploaded: 2026-02-04T11:06:04.415Z
Duration: 50 min 8 s
Description: Enforce Governance, Compliance and Security Everywhere Data Goes (Europe & Middle East)

Transcript for "Enforce Governance, Compliance and Security Everywhere Data Goes (Europe & Middle East)": Hi everyone. My name is Nick Savides and thank you for joining us on our second installment today discussing data governance and compliance obligations in this rapidly changing regulatory and artificial intelligence driven world. I'm again joined by my colleague Michael Leach. And, today we're going into a level deeper from what we covered last time. So just to remind everyone, we discussed in our first session really what the regulatory landscape looks like that our customers and ourselves need to comply with and the major challenges that they face in building these new data governance programs that cut across silos in the business that touch technology, that touch the business, that touch the executive, all in different ways in order to understand what data they've got, understand the rules they need to comply with and, really deliver some meaningful risk reduction at the end of it. So we discussed the scope of the problem. If you, missed that session, please go back and watch the recording, because I think it's really worthwhile really get a basis on what the priorities are, that an organization needs to deal with when it comes to building an effective program to better comply with these new regulations, but also do that meaningful risk reduction at the end of it. Today, we are going to talk about how we actually go about doing that. And how we hear at Forcepoint not only build our products for the market and what they are capable of in assisting our customers with, but how we actually use those tools internally and how we develop them because we are governed by the same regulations that our customers are and we operate across all of those markets that our customers are in. So I'll start by talking a little bit about the history of sort of protection and data security. I've been in this industry for twenty odd years and a lot of people have thought of data security and data protection from the lens of DLP, data loss prevention. The ability to look at what a user is doing and, in the moment decide whether or not they should be allowed to send or copy or move some sort of corporate data over a channel out of the organization. Can Nick send this email? Can Nick copy this file to USB? Can Nick upload this document to a particular website? That has been sort of the thinking, around data protection for a long time. Now we know that that is not enough anymore. You know, in our last session we talked about the really sprawling obligations that organizations need to comply with. That now it's not just about, the movement of data, it's understanding what you've got. It's understanding what compliance needs that you have. A DLP is a protective control. Is one of the things a regulator or regulations will look at, but it's only one part of that. There is a much, much bigger set of obligations that need to do that. So what I'm going to do now is I'm going to ask, Michael who deals with all of this from a Forcepoint perspective, here at our company ensuring that we are compliant, how we actually go about doing these things and talk about some of the key capabilities that we've launched. Noting that Forcepoint has been a leader in the DLP market for twenty odd years. We have one of the world's most awarded products in this area, and yet today we have had to branch out into other data security adjacencies in order to deal with these problems. And we've launched things like data security posture management, data classification, data detection and response capabilities in order to do that. So Michael, over to you. Can you tell us a little bit about how we're actually doing this here at Forcepoint, as someone who has to live and breathe this every day as part of your job, making it real? Yeah, yeah, no, I would love to. That's a big reason why I've been with VoicePoint and I really enjoy what I do here. It's not coming in from just a legal and compliance overview. It's actually being able to work directly with our engineers and our product teams to basically go, how are we being compliant with what we put to market? How are we making our customers compliant with what they need to be for what we put to market? How do we leverage our own technology to ensure we're compliant? And having that insight and working with those teams and understanding and coming over, like you said, we have best in class DLP. That's where it kind of starts, right? Understanding what technologies you have, what are best in class. And I think that's the same thing as from a traditional data governance system, like we talked about in our first session, kind of broad, different misnomered understandings that are held across the spectrum from different people. What is data governance? How to attack data governance? A lot of times, it's like we talked about, oh, I need to go and have that conversation with this CISO about securing data and we're good. No, that's not where it stops. That's just one piece. So it's really about what is the toolset? Is there a cohesive platform? Hence, you've got to look at this holistic. When you do, a lot of them just becomes this unmanageable beast that you have to contend with. I just don't know where to start. Well, it's not about taking slices, about taking that holistic approach. But applying the right technologies and that's the second piece to that. Using desperate pieces of technologies may not play well together. I think we've all learned that from how we've applied our own technology stacks within our corporations, the incompatibilities that exist, the incohesiveness that happens, it's not highly efficient, it's not highly manageable. So coming out and being able to provide a platform that basically provides a very cohesive system, that provides an easy, manageable, per current resources and teams for what they're doing today, and providing that oversight and capability to manage it, is key to having that holistic approach, being able to set up a good data governance program. And you're coming to some of those basic tunes in what we do, and our technologies. Best in class data loss prevention. But it's not just blocking the data. It's not about just having a policy, I recognize this, I'm going prevent this from being transferred. We want to increase it. We want to make it smart. We want smart policies, okay? And that's just one piece of it. But it's got to work with the whole ecosystem of tools that you have around it that address all of your requirements for compliance and all of the different data types you have. So it really starts with that basic understanding, coming to a platform that can deliver the understanding of, can you identify the data that I have? Can you tell me where it's sitting? Do I have the ability to actually control what happens with that data? Okay? That's for what's existing. Your employees are creating that data dynamically, as we see. Exactly. Okay? How do you capture it from an in motion aspect? It's got to get a lot smarter from where we started. And that's exactly what I work with and talk with our product teams about. AI, as we mentioned in our first session. It is the concern that is pretty much on everybody's mind, corporate or not, even individuals, in their smartphones and in their day to day, right? In their personal computing industry. Everybody's got the concerns around AI. Well, you use that same technology to increase and make what you have smarter. That's exactly the approach we took, is basically looking at what do we have and what we don't have that we need to be doing, how do we make what we do have smarter and work with these new technologies. We've brought in new constructs and basically have developed and further designed a new platform, our DSP, the Data Security Posture Management, along with DLP, you start complementing. DSPM is an AI Mesh driven technology, you're already making it smarter. It can go out into a customer's network, look and see what data you have and begin categorizing and classifying that data for you. Let you know, you have PII sitting here, you have government controlled information sitting there. Discovering where that is, classifying that, then allows you to begin prioritizing what you need to be addressing per the laws that you need to be following. All these regulations that are across the landscape from a global jurisdiction perspective. How do I begin aligning to that? Much less than, once you begin prioritizing, how do I actually begin to take action? Well, you need smart policies. I don't need you to block you, I need to recognize you're not just PII, I need to know your EU national PII and I need to ring fink you to the EU unless I already have what I need from a lawful mechanism to transfer that. A smart policy can recognize these, but a lot of that needs to be driven dynamically. AI can facilitate that. That's very much where our aim and our focus is currently. Okay? Once you have that ability, you begin remediating your landscape, bringing it and aligning it with your compliance and legal obligation that you have around each of the data types. It is not the slice piecemeal, it is that holistic approach. You don't need huge resources. You have AI going out and being your foot soldiers, going to discover where that data is, understanding what that, reviewing that data and understanding what it is, classifying it, and serving it up to where you and individuals like me within corporations begin to understand, okay, here's my landscape. I understand this is my biggest concern and my highest risk. I can begin prioritizing. I can begin working with our technical teams to go, hey, this is the type of smart policy we need to have. It's not just about PI and blocking it. It's about allowing the business to conduct business. That's the second piece. We are not here to secure you and ring fence you and limit your operations. It needs to facilitate your productivity and your operations. Okay? And so that's very much what this would allow us to do, is basically have a smarter policy and real time automation. It's not like you have people there in a SOC behind management going, okay, I'll help him permit this, I'll allow that. Basically making these decisions, you are building that into your AI mesh construct, you are making it smarter by saying, hey, this is how I want you to handle this, this is PI, it's EU national PI, I want to read things there, but go and look at my repository for my other source, do I have the transfer mechanism to lawfully transfer this to where they want to send it, from what you are seeing in real time? If so, allow. If not, block it until we can get that addressed and alert my DPO, hey, we need a lawful mechanism here so we can facilitate this and continue with business. That's the way and how it needs to think and it needs to be at a platform level to where I'm not managing these tools. I'm not working in these isolated scenarios. I need something cohesive. That's very much what we're working on and bringing to lighten when I've been working with our teams to do. Yeah, it's exciting. You know, I really enjoy working here and working with the product and engineering teams on delivering what I, what I really think is the future of data, data security. And, and I've been here five years and the engagement, being able to take an idea and deal with a problem that a customer sees and directly feed that into our product teams workshop that idea and then see it manifest in product, you know, in a matter of months is just absolutely fantastic. And I think the pace of innovation here has never been faster at force point and at least in the five years that I've been here. And in that process that you've just described, I think this defines our fundamental approach. Because we recognize that DLP wasn't enough, that protection piece wasn't enough. And now we have that sort of, we've out a guiding set of principles, not just for our products, but for our customers to follow, you know, Discover what you've got, no matter where it is. Tell me what I've got, classify it, tell me what it is and what risk it presents to the organisation and what rules it's governed by, So then I can prioritize what I need to deal with first. Cause that's, that's often the biggest challenge. Talked to a lot of CISOs, a lot of CIOs and they just don't know where to start. Their operational teams don't know where to start because this problem has become so big. They kind of go, I just don't know where to start because no matter where I start, I feel like I can't get to the end. To prioritize where I need to go, then remediate my risk in either near real time or close to, or even retrospectively remediate that risk by applying some automation and this is the key thing automation. Because we cannot scale the people in the same way that our data is scaling. You cannot hire your way out of this problem. You can't make people work. 20 fourseven know, three sixty five days a year. People do need to stop. Simplification of resourcing that, right? Exactly. And we need to apply those protections at the end. So we have to have those pieces and to your point, it's very hard when you're doing this across a set of different products. Now the industry defines these things as categories, as product categories, data loss prevention, data security posture management, data detection response, but really they're all trying to solve part of the same problem. Exactly. And this is why I think a unified approach and the approach we are taking at Forcepoint makes the most sense, which says yes, yes, these are discrete categories of product, but they should all be part of a platform that allows us to share the intelligence across them, that allows these products to operate as one, that allows them to deliver the outcome as a unified outcome, not as I'm going to do a little bit here and a little bit there and then have to spend all this time trying to plumb these things together. Yeah, I know my DSPM works with my DLP. I know that when my DSPM can go out and use this cutting edge AI mesh, this AI classification technology that we have here at Forcepoint to go and see a piece of data for the first time, pick up a document for the first time, read it, understand it and then come out the other side of it and say, yes, this is sensitive information. It is financial information or it is health information and it's never seen that before and I haven't had to describe it to it. And the DLP on the other side goes I am now going to go, now that I know that this piece is of a sensitive classification and it contains health information for a person in Australia, because that's what the AI has told me. I can now apply my adaptive and protective policies that say this set of rules apply to that. Instead of the old paradigm where I'd have an analyst sit there and go, I need to describe to the DLP exactly the type of document I'm looking for. It has to match on it. And then I have to craft a policy for that exact scenario. And if you end up in what I call the policy spiral, the escalation spiral, where you lay a policy and policy and policy and you end up with hundreds of policies and no one knows how you ended up in that scenario. AI allows us to do the great thing about AI is it allows us to to do this massive generalization and the AI can in real time, the AI that's in our DSPM and in our DDR, the data detection response piece, look at a piece of data as it's being created or as it's stored and identify what it is, what risk it presents and what rules apply to it and then inform the DLP to go and protect it. That to me is magic. That was impossible three years ago. It's now magic. Absolutely. And it's real. You know, I'm going come back and touch on, you know, a key phrase you said there, you know, that policy spiral. Okay. Why historically do we, you know, pre advent of AI, have companies and corporations keep stacking these policies, right? Because you're kind of trying to keep up with that regulatory landscape, that operational landscape. And that's one thing we're here. We're talking about security, data security, we're talking about getting you compliant, and that's the other approach I also took. It was not just looking at the technology, but it was like, how does that technology and that's what think everybody's view of AI how can it help me be productive? That's the underlying message Then that goes to your policy spiral, okay? We're increasing efficiency and productivity in what we're doing. It's no longer a spiral of, okay, I've got this, contain this, send this here, my DPO needs to make a decision, you've got slow process touch points, you're removing that, you're removing these layers, you're removing those operational steps to create a much more productive operational workflow that's purely automated to drive your business, much less your compliance and security here. So why don't we talk through then how we actually apply that in each one of those steps, right? So how do we do that automation in the discovery and classification piece? We know how we do it. We have this, we have the tools that go out and do that. We have the AI mesh, but what are the outcomes But are estimated is it serving up, right? I mean, let's break it down. I mean, we talked about governance, we talked about the pillars, let's you begin understanding what does it actually instantaneously serve as you move through each of these phases, right? As soon as you discover all the data, you begin classifying that, I now, like I've mentioned earlier, oh, I know I have data by the nature of the category discovery, I was classified, I have a data residency requirement here. It cannot move out of bounds. Can instantly have a policy reinfence that. I'm compliant, I'm secure, I've provided data residency just at the discovery classification phase. That's step one. I'm already achieving I'm already seeing and monitoring data in motion, data transfers. Where is data moving? I've sourced it, I've known where it's located. Where is now that data moving me? Hence that plays into what is my business activity? What do I need to be compliant with? Should I be transferring and allowing the transfer of that data? What type of data? Once you have that discovery classification, you've got that paradigm right off the bat, too. Then we get into the overall, where we started with data governance in the old days. It was about business record retention, how long do I need to keep what records, for what business purpose, for what laws, SEC, etc. You now have a scope of that and you have the ability to go, I've got this type of record, I should have this long of a retention period. As soon as that retention period is up, and as we know in our legal world, you don't hold on anything longer than you need to, delete it. You're not waiting on teams to act on this from IT or from your infosec, you know, it's happening dynamically, automatically, in real time. And that's just in the first step. Data subject access requests, everybody's got them, regardless of the organization you're under. You got that personal data. You can automate those types of business functions and routines. You're instantly able to see the portability, financial, healthcare, where is that data, that control data being moved not just from a transfer but portability of the data itself from the systems and tools that are ingesting and processing, things of that nature. That's just the discovery and classification. That's just the first pillar. Then you start beginning to begin: How do I begin prioritizing, remediating? Now that I know what I have, how do I begin aligning? I start beginning to maybe understand things I may never know. I may not have even known I had this data, holding this data. It begins bringing new insight to you from your business operation, which you may not have even understood you need to be on top of. So that begins to help begin providing that view, that landscape in a very manageable way to go, how do I, in a manageable way of prioritizing, you can take that categorized data, okay, you can take policies and create policies, you begin joining that for your highest risk data scenarios and start moving down that from your risk categorization, begin remediating and instantly coming into compliance. Because as soon as you know what you have and you're applying that policy and it's automating on that, you're compliant. You're not going to hire consultants and teams to bring you in compliance. Once you have all of that wrapped around, you've got remediation happening, you're compliant, you're also protecting your data because it's doing only what it needs to do and is being enforced from an automation, not somebody's decision and a one off on a different function in a different team. Fantastic. Think these are, as you were talking. In my mind, all of these examples, are coming real and manifest in my mind with the customers that I talk to every day. I talk to, mostly the C suite, and executives within our customer, set, as part of my role and they are all. Every one of these problems I have had a real world example of this. It's funny when you talked about deleting stuff that you, you know, retaining things for, only as long as you need to. I've got two really interesting examples of this that I was discussing recently. The first one is, of a customer who, they sell a product with a twenty five year warranty and they were retaining all of these records for customers who had purchased this stuff. 1999 just so that in case they came back for a warranty claim and they knew it was this person, they actually did the numbers on it and said the number of warranty claims that we get at year twenty onwards is so small. We may as well delete all of this data so that we don't retain it because the risk of retaining all of that PII, even though we might have to replace this item, the risk of retaining that data was higher than them keeping the than taking the risk of having to replace one of these items under warranty because the claims were so low above twenty years. And I just thought that was fascinating when they did those numbers. But the second one is a more serious one and that is, you know, we had a here in Australia financial services institution was compromised and under the notification laws here, they complied and they said we have to go and contact everyone who was affected by the data breach and it took them months to determine everyone who was affected and they said, it's everyone in this database. They didn't know. They didn't know what data they had or where it was. Once they got a scope of that, it was like everything. They were sending letters to people who had died fifteen years ago. Who hadn't had any dealings with them since 1996. And yet they had retained all of these records. And the media here was interviewing people. Know, every country has its own tabloid journalism and they're interviewing people. How do you feel that your dead mother received a letter from, from them asking, you know, notifying them that their data was in breach and they might be in danger, and to contact them for identity protection services. This is just an X. I thought of this as an excellent example of an organization and of a category of problem that a lot of companies have. They hoard data. They keep it. They don't know what they've got. They don't know where it is. They retain Which is its own liability itself. I retain did a webinar the other day and I actually leaned over and I pointed to my cupboard over here. And if you have a look, if you ever visit me here in Australia, Michael, I'll show you my, I think most technologists have a drawer like this. I call it my junk cable drawer. Where I have every bridge of mine. Right? Don't know ever if I'm going to need to use a SCSI cable ever again in my life considering I haven't had a SCSI drive in twenty years, but I have one in there just in case and, you know, that doesn't present much of a risk to me, but if I'm keeping data in the same way, that risk goes up. So understanding what you've got where it is getting a handle on it is like that first step. And then to your point, what is the next thing that happens? Well, if I deploy that Forcepoint DSPM technology, I can go across all of my repositories, whether they are on premises, in the cloud, or in structured data, right? So in databases, or in file repositories, it doesn't matter where it is. I can tell you using that technology, what you've got, what it is and, who's got access to it. So immediately, I have an awareness that I didn't have before with that technology that we've got. And then we move into that. You said prioritization remediation. Once I've got that, I can automate a lot of those rules. Again, within the platform. In the old days, absolutely impossible. I'd go and discover those old records and then I don't know, it would go into a report. So I'd have a consultant come in and they're, Oh, you've got financial records from 1999. Most of these customers have passed away. You probably need to do something about this data. It go into report takes six months. I'd pay hundreds of thousands of dollars to this consultancy. I then go and have some decision making process that would take forever. And then someone would copy that off anyway and just archive it because they want to go, Oh, well, I'm not sure if I should delete it anyway. I'm going to store it somewhere else. And maybe that makes the problem go away. It doesn't, right? I can see you shaking your head. Doesn't actually make the problem go away. You've liability for that. There's not only liability from a legal perspective that can play into that, but you also you've got the cost associated with that. You're not storing it for free, right? So you're paying for that. And paying for what? You can't qualify, you need to put the business certification for why I'm holding that data. That's the worst case scenario. It's kind like you said, the consultants coming in. Corporate auditors coming in and telling you what you don't even know. What data you have that you didn't even realize, right? Then basically having to qualify why you didn't need it. They're telling you the story that you should have already been ahead of, already been operationalized. Imagine getting behind our platform, having your auditors come in and go, let me show you and let me tell you. Exactly. Let me show you what we've got, where it is and what risk it presents. And then, you know, maybe they can give you some advice, tick that box, move on to the next one because you're actually ahead of the problem. So now I can automate a lot of that remediation. Okay. I'm not, I'm going to move this data. I'm going to delete this data. I'm going to notify the inferred data owner, which is a really powerful capability to say, alright, this data is once the tool discovers it and says, okay, I have found PII. I have found PII for Thai citizens. Because we do business in Thailand. I have found PII of Thai citizens stored in this location. That is based on the location it's stored in, the type of data and who that data is from, that is, that's Mod's problem. That's this specific person's problem. And I actually use an example of an employee in Thailand. So Mod's a real person, I work with. That's his specific problem. I'm going to tell him he has to go do something about it automatically. That was basically impossible before. That was a person having to troll through that and then go, right who in the business? I've got to look at all this data, go inspect it. Okay. Okay. I think it's this type of data. Oh yeah. It looks like, it looks like, health information. It looks like information. It looks like toilet. Okay. That might be who do I have to go find? Now I just go tell that person automatically, Hey, you've got a problem. You need to go come into the tool or go and do some other remediation. We have an issue here that you need to go and deal with. Absolutely amazing capability. Yep. Like I said, it comes back to driving that productivity. That's where all of this is coming from. Having that good data governance programme keeps you compliant, keeps you secure, drives productivity, as we mentioned as well, that it's really coming to the base of understanding, and all these regulations that are coming and being put forth by governments globally. It's around basically making corporates and owners of that data, the collectors of the data, the processors of the data, good data stewards. Good data stewardship, whether it's the old paradigm of life cycle of retrofitting or contending with AI Straw in today's landscape. It's the same thing. Be a good data steward. How do you do that? Have a good, cohesive, compliant data governance programme. You know, I often give presentations and I have a slide that I try to generalise across the entire region I work in. As we said in our last session, there's regulations basically in every country now and they're all slightly different. But if I had to boil them down, say what is the essence of all of the regulations? It's what you just said about good stewardship of data. And I have a slide and I just say all regulation basically it comes down to three questions. Are you a good custodian of the data that you hold? What data do you have and where is it? And are you doing enough to protect it? And they're all variations on that. Some are more detailed, some are more punitive, some are less detailed, and more high level, but they all kind of address those three things and this is what our tooling is built to give you. It allows you to demonstrate that you are a good custodian of the data that you hold because you know what you've got, you know where it is, you know who's got access to it, you know what risk it presents to the organization and then are you doing enough to protect it? Well, I know that I'm automatically remediating risks as they appear. I know that I am protecting the movement of data, outside of the organization and more importantly, often in these regulations in monitoring the movement of it inside my organization. And I can demonstrate that with continuous reporting that shows I started off at a risk level up here and I'm progressively lowering my risk over time, and I can demonstrate that not just to my board, but when or if an incident does occur or I need to perform an audit or a regulator comes and inspects me, I can say I have been doing this, I have shown meaningful risk reduction, I understand what my obligations are, and compared to my peer group, I am ahead of my peer group in what is expected of me. If something does happen, you will be in a much much better position, not just from a regulatory perspective, but in the scope of your incident. If you do this well, if an incident does occur, instead of the incident being this big, it's going to be this big, right? So, not only are we preventing incidents from happen, if they do happen, they're much, much significantly reduced. That's exactly right. I mean, that's where, you know, basically remediate and then mitigate, right? From an incident scenario in any cybersecurity situation, it's kind of the same concept, you know, It's basically allowing you to basically remediate and continuous mitigation based on the remediation. Exactly. My policies, remediation, I've figured out what I need to do to solve the problem. The mitigation is continuing automated at this point because I've just made that policy. And then for the CoVisa platform, smarter policies, the automation. Now, not only are they compliant today, I know those new regulations are coming on the horizon. They're being formulated, the major changes to the Australian Privacy Act of 2025, they're evolving. New ones are coming up. You are now set and prepared. I have a full view, full management, and full automation. Now, it's not a matter of bringing in consultants, setting up a whole new program for this whole new legislation that's coming into play that I now need to comply to. It's a matter of breaking that down, get a clear understanding of what I'm required to do, and put that into my smart policies and begin automating. And now I'm ahead of it. And I'm keeping it. You're ahead of it and you can demonstrate that you are, you can show that you're compliant with those regulations and you've got a vendor behind you that is updating all of the fundamental technology to stay up to date with those regulations. And it's not, you know, it's not falling on the customer's shoulder to go and do that because the vendor who has the experts in this space is doing that for you. And that's what I find You're not so having consultant that needs serving it up for you. Yeah, exactly. It's so exciting, right? And when I actually show customers what's possible here, at Forcepoint, when I go out with our teams and I, you know, I've got some of the best systems engineers I've ever worked with, go out and show some of this technology to our customers. A lot of them just walk away and go. I had no idea that first of all, that you guys did this. Secondly, I had no idea that any of this was actually possible, to the extent that you're showing me. Because as I said in the last session, a lot of their thinking has been because of what they've done previously and it's been a linear progression. Wish they're focused a bit, right? And in that slice, not that holistic understanding of all the interconnections that actually are there outside of just their focused area and how they can compliment each other and create much more efficiencies if you do it in that holistic approach, that's highly cohesive. You're not just taking care of that one focused area. You're taking care of all of it. Alright, so, Michael, you do this here at Forcepoint. You use our technologies here at Forcepoint to ensure our compliance. I had my thoughts on where a customer should start. If you were on the other side of the fence, and you were at a customer, where would you start if you were embarking on a journey down like this and someone from Forcepoint was talking to you? Where do you think would make sense for you? Well, I think to make this, you know, basically, it's hard to accept what you don't understand. Hence, some of the concerns around AI, right? That we've mentioned. It's really about demonstrating you have a good, crisp understanding of the compliance needs out there, those regulations, what's actually required underneath that. And that's exactly like I said, when I work with my product teams, I'm coming in from that perspective. I'm not coming in from the new technology, new product perspective. I've got these real world problems I've got to continue with every day, which means every one of my customers have these problems too. How do I fix this for me? Okay, is where I start. I look at that individual process, like I mentioned earlier. I get that individual data subject request. What team, what resources, what does the process flow around that, what systems and tools do I need to put around that for that one requirement that I need to address? Rather than panning back and going, okay, we have technology that can automate some of this. And start working from that paradigm up and start, like we said earlier, working from what looks to be an impossibility, looking at what is there, what new technology is there, what new capability is there, technology facility and most of that capability for us today, to go, we'll make this possible, design it, develop it, this is how it should work. It's not just going to serve us, it's going to serve an entire market. Yeah. And look, I think that's a really good way to look at the problem start that sort of engagement. It's very outcomes focused, not technology focused. It's what is the outcome you are trying to achieve? And then we work from there. The advice that I give my teams and if anyone's on this, listening to this webinar, I would encourage you to engage, with your local force point, representative or partner to do an engagement with us, specifically around the discovery piece. And the reason I say that is a lot of organizations simply don't know what they've got or where it is. And that, you know, and we've said that that's been a fundamental piece of how to do this program. And the reason I say talk to Forcepoint about doing something like this, like a data risk assessment, to understand what, it's to go through and understand what you've got, in your environment is that what it does, it's not just about the technology. It gets the organization to go through a process to understand what their maturity is and. You know, sort of start to define what are the outcomes we want to achieve at the end of this? It'll be nice to know what we've got and where it is, but what are the outcomes we want to get to? Do we want to do these things first? And often just going through that risk assessment process with Forcepoint can help a customer start to define some of those outcome priorities. And then from there, as a team, jointly with the customer, we can build what I like to call an adoption model. And that says here is the broad platform that Forcepoint has. We do end to end now. Do that. The DLP protection in real time at the point of transaction or event all the way to the discovery, classification, labeling and tagging of all of your data, historical data where it is, and in real time or near real time of the data as it's being created. We now cover the whole spectrum. Now I love it if we go into a customer and they go, yeah, I want everything. I want to do everything. Oh, please Forcepoint come in. I want to buy everything that you've got. Let's make it happen. That's great. But that doesn't often happen because customers are constrained by budgets, time and resourcing. Don't have infinite budgets. They don't have infinite people and they've got other competing priorities that they have to deal with. So my recommendation is to work with Forcepoint. We do one engagement, very brief one to understand some of that risk and that helps us set some priorities. And then we can build an adoption model that says, you know what, for your organization, starting over here You should three have maybe for for nice prioritization, right? Exactly. Let's start over here and we'll do the data discovery first and then we'll go through and label all of your files and we'll do all that could be your biggest risk. Another organization might go at the end of that risk assessment piece might go, you know what? We have an actual massive problem with people sending PII over email. That could be the number one thing and they've got to, they literally have to stop that on day one. Great. Let's start there and we'll put DLP in for email. Look at the PII, do that. Now that I've put that fire out, I can start dealing. Let's build an adoption model and go now understand your risks. What are the next pieces that come into place? So we can do that here at Forcepoint. We've got an excellent team on the ground. In basically every region of the world. And we can help customers with our partners go through that process and I invite you all listening to have a chat to your Forcepoint group so that we can show you first of all what is possible, but also perhaps do an engagement with you to understand those risks and then build an adoption model to help you really level up your data security and your data governance to bring us into this new world, so that you can be more compliant and importantly, ready for the future and be productive while being compliant, while being protected. Empowering your employees to use the latest technologies, to be able to harness the power of artificial intelligence, and really deliver business results for your organisation. Yeah. And then like we mentioned too, it's not just about the compliance and security. It's a productivity multiplier. It's productivity. Right? No one's adopting AI just for the fun of it. You go. There you go. And what we're trying to do is this kind of looking at it in the same instance of what it was developed for productivity. Boom. That's what we're trying to deliver. And just from a different angle. If you're compliant, you don't have these legal concerns and risk, you have security around everything, I can focus on operating, I can focus on being productive, can automate the rest where I can to know I'm in safe hands and I don't have heavy resourcing needs to stand up programs as new regulations are stood up and to stay on top of any of it. Wonderful. Well, thank you very much for your time today, Michael. Thank you very much for everyone listening. It was a wonderful conversation. Let me thank you again, Michael, for all the work that you do here at Forcepoint to keep us compliant with our obligations, and keeping our customers data safe and our organization productive being able to use these tools, enabled by our own technologies, which is fantastic. So thank you again, sir, and thanks for everyone, who joined us today.