Yes, thank you very much. So I try to keep my time. So without further ado, I just start the, the, my talk is entitled convergence integrating cm into enterprise architectures, and that is aiming at giving a, a bigger perspective for cm, for IAM, for marketing automation, and even bigger. That is the idea for today. And maybe that, that also gives us a good perspective for the start of the day. But before we do that, I have been asked again, to reiterate on the, on the platform that we are using for this, and as an incentive to download the app or to use the app within the web browser, there is a free download available in this section for just this opening keynote that we're just watching. So if you use the KC live event platform, you can download the leadership compass on fraud reduction intelligence platforms by my colleague, John Tolbert, who will be on later today as well for free.
And this is really a, a good opportunity, and it's really valuable information on that interesting topic. So go to the room for this, for this keynote and find this download there for free. So that was the short interruption that I wanted to do and have been asked to do. And I think it's really an opportunity to get that document, but now let's get to my agenda for today. So very quickly I will have a look at the cm promise. I will kind of do a reality check, how things look like in many, not all organizations. And I will talk about convergence instead of yet another integration, but converging IAM and cm, and look beyond the identity fabric, our concept for integrating all the things I I am and the challenge of managing enterprise data. So that's the, the root for today. So let's start with the consumer identities and the challenge.
So I think many of our speakers do today focus on identities as the key for the digital transformation. And this is really true. I don't read this out because, because this is something that many of us really are here for, I assume so C I M extending identity and access management towards new types of identities, including cons, consumers, partners, customers, and B2B B2C scenarios. That is really something that, especially in this crisis situation, but before as well is something that is of important for all organizations to enable you kinds of business models. So the idea is to en enable access to customers and consumers to welcome them. And maybe to go back a bit, this is a slide that we used years ago for explaining what this is all about and what is changing. And it has this, this chilling headline, everything, and everyone becomes connected or become connected.
So it's really not only me as a customer working and interacting with a website or an app on my smartphone. It's really understanding the, the inter the dependencies between individual types of identities. It's me using advice, me using a smart thing in IOT device, me belonging to an organization, and all this, to understand that, and to understand these complexities behind that, that is also something that is really one of the challenges that cm has to take to understand who I am and what I actually represent within a certain situation. Am I a customer? Am I an employee? Or am, am I the same? Am I both at the same time? So this is really an important thing. And to use this identity relationship management, how is also called, this is really an important aspect. So now we come to the promise of C I M.
The, the promise is that you understand your customer from the registration on and throughout the complete relationship that hopefully never ends at least never for. And with regards to the, to the business relationship that you have with them. And this really covers all the aspects that are in these four boxes, a bit grouped, just to make sure that you handle consumer identities as appropriate as possible, including their onboarding, including their consent management, including their hopefully improving user experience and individualized customer experience. So this is really something that is very close to the, to the business, very close to the new modern digital business processes, business models. And this is something where CIM really needs to deliver and where it can then also contribute over to marketing automation. And more, a large question that we have to look at is who drives CIM. And I have, I have taken another quote from John from the leadership compass CIM platforms in 2018.
And he said something very similar to what I mentioned earlier, that it departments should welcome C I M initiatives if they provide an opportunity for it, which is usually just the cost center to closely team with marketing a revenue producing center. So really getting a bigger picture, combining existing IAM initiatives with cm, and really move closer to the business, to the business people, to the business processes, where the money comes from. But if we do a short reality check, this is often not the case. Often CIM systems are still frequently operated and purchased decentral. They are just another module within a marketing campaign, or are required for creating a app, a website. There is no enterprisewide strategic role behind that. It's really just a checkbook approach to make sure that there is something for managing customers and consumers in place to solve immediate issues for creating yet another digital process, yet another digital solution for customers.
And this, this is often, also much closer to CRM than to IM. So it's really a closer connection to the customer relationship management. And sometimes, and that is most, probably the worst case. There is even more than one CRM, one cm for one solution that had to be built so deployed for different purposes and different lines of businesses, whether that not talk to each other either. So in many organizations, there is unfortunately the view that we have missed strategic opportunities. And that of course is the cause for many problems downstream. And if you do CIM in that manner, not well integrated, not, not well converged where I'm aiming at, then you end up with yet another silo, and this is a silo containing on the one hand consumer or customer data. And on the other hand, being the data source for many other solutions that want to benefit from consumer data.
So there is only limited benefit. So no full return on investment. There is hope most probably there will be compliance issues because if there is one more system processing personally, identifiable information, then that is an issue when we think of regulations and we think of cybersecurity. And are we really sure where this solution actually stores its data, if it's GDP or compliant, if it's just has been acquired as part of an overall solution to just create another app. And of course, there's also governance issues is this customer that we are dealing with probably also an employee, which could be a segregations of duty issue. And of course there will be user issues. So if you have more than one account for customers and different solutions, they won't be happy with that. And you just don't get the benefit that you wanted to have. You just don't get what you wanted to achieve this full insight into your customer in all the information that they are willing to give to you.
So what I'm claiming for here is an integration and convergence of technologies, and that is not only IAM and cm. It's not only cm and marketing automation that we are talking of today, but to also think of a bigger picture. And that is just a quick overview of the solutions where I think that cm needs to be well integrated, where you need convergence, where you need to have cm as one important player on important part of an overall enterprise architecture. Of course, we need to talk about IAM and I will do that in a, in a further slide, but very quickly, because these are very close technologies, although they have variations, but they are closely related and integrating IAM and cm, having a single view of all types of identities that is really of importance, but cm is important in many other aspects. If we think of security, integrating cm data, for example, failed lock in attempts possible attacks into a system that looks at the overall cybersecurity of an organization that is of course of high importance.
So the security orchestration automation and response area is of importance. We're dealing with customers. We are dealing with money. We are dealing with purchases. So threat and fraud intelligence, both are of importance. Yes. So need to be well integrated. Well converged, not point to point. It's really having cm as part of an overall architecture framework, of course, business intelligence and marketing automation. That's what we're here for. And of course, customer relationship management, because they had customer data before and they need to be aligned with us, but also more modern technologies need to be looked at. So machine learning that can help in, for example, business intelligence and marketing automation, wherever they make sense, we might want to use them that might want to use cm data there as well, integrating it into enterprise GRC is of importance. And we will have a look at data access governments later as well.
So really looking at understanding how we govern our data, how we maintain data, keep it secure and keep it aligned to our security requirements, to our governance requirements, to our compliance requirements. So we need to govern PII, where do we have CIM as a central solution? And then we need to make sure that we trace and track customer data wherever it goes. Because for as one example, we need to fulfill all the requirements and laws and regulations and policies and the will of the user needs to be taken care of. So if we have that single view of the customer and the consumer in one place, and we want to reuse that in other places, for example, for analytics, then we need to understand where it is stored and where it's processed. And we need to govern it when it comes to all the consent that has been provided to us for using this data. And to make sure that we take care of the required privacy of this data.
This is the slide that I mentioned, and Martin presented that in the very first Casey life event as well. So this is just a short reminder, how we consider how IAM and cm could converge into one, what we call I identity fabric. So something that is really dealing with all types of identities with the consumer, only being one part of it. The one part that we see to the upper left, but all of these identities to the left want to have access to all the services and all the infrastructures and applications to the right and consumers are one part of that. They need to be handled adequately as part of CIM, but we want to see that in a single pane of glass into, within one identity fabric, something that really makes sure that we have one single view of all our identities. So that's one convergence, but that is really of importance here when we think of identities.
And although this also makes sure that we then can combine all types of identities and get to this identity relationship management that we've seen before. But convergence goes beyond that data is shared and used, as I mentioned. So we look at machine learning at analytics, at data lakes, at data warehouses, at business intelligence platforms and all of those come with this huge promise of better understanding your business processes, your customer of improving supply chains, improving all that you're doing in your business. And you need to make sure that you have a well defined set of data quality. You have consolidation verification, you combine this information. And again, you need to make sure that this data is well governed when it comes to data protection, access control. In every context, especially when we are talking about business intelligence and compliance with the content given. And in the end, we need to make sure that we prevent uncontrolled dissemination, just putting all the cm data into a data lake and applying machine learning might not be the way to go forward here.
Final ideas from my side, we need to understand CIM data as enterprise data. So we need one concept to rule them all one concept to find them. So we need to identify cm data as one data asset, we need to manage the meta data. And that includes also constant access management, et cetera, to have them handled adequately wherever they go. We have to think in end to end data flows so that we really make sure that we know where data is, where it's in transit and where it's stored. We need to do this enterprise wide. So really not only in that ugly silo that we've seen before, we need to apply access control, wherever we use that also in these new shiny business intelligence tools like Tablo, we need to make sure that this is well maintained. And by final thought, we need to plan for the D in C R U D. So create, read, update, delete of personalized data. We need to make sure that the D for deletion is taken care of as well. So you need to make sure that you completely remove PII, and there is no good reason to store it anymore within any of your systems. So the right to be forgotten is something that can only be managed when you have converged infrastructure for maintaining your enterprise data, including your CIA M data. That's it from my side for that presentation, if you have any questions, I'm happy to answer them.
