The invisible but potentially incredibly powerful asset of every organization - data. What is the true value of that elusive substance?
In this episode of #WeeklyTaival we discuss new data-enabled business models and how data can fuel your circular economy and business successes.
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Transcript of the episode:
Keywords: data, regulation, monetisation, monetization, service, circular economy
Welcome to weekly Taival. This is a podcast where we share our weekly insights and have an improvised discussion around them. Welcome to weekly Taival. All right, go on Michael.
So this week guys, I wanted to introduce one of my favourite topics to our discussion. And while saying that I realised that I seem to be having many favourite topics, but I guess that's not a problem.
This week, I thought we could discuss the theme of data as an asset, not just the sort of pink and fluffy expression of data as an asset, but really dive into the details of how does data become a real business asset that businesses can actually transact with. And if, as an introduction, we could think about, for example, some social media players who are in the business of marketing, where they've been able to get themselves into a position where they get quite a rich set of consumer data, in exchange for their services that they can actually use in creating hyper targeted marketing capability that they can then sell to their sort of marketing customers. And they really get insightful data about their consumers, and hence, they can really drive out high conversion rates on their marketing campaigns. So I wanted to ask, have a critical look at this and think about whether we could actually make data in such business contexts. A value generating asset also for the sources of the data here in this example, the consumer. So what if we had a model where us all as consumers were providing our data for, let's say, Facebook, in exchange for a stake in the profits, they could actually make in the use of that data in their marketing engine. So that would be a slightly different model, compared to today's model. So that's my introduction for today. And with this opening, I wanted to ask your perspectives on how you view data as a business assets. And if you have any good examples of applications of that.
I want to start as this happens to be one of my favourite topics as well, among as many as you bettering. I think the first thing is the the my data movement. And that needs to be mentioned immediately when when we're talking about the the ownership of data and especially people's personal data, I think the model that you describe where people would get the returns for in exchange for providing their personal preferences and personal data is something that is that is being explored as we speak, I think, when the social media giants, Facebook's Google's and these guys were born, the data, monetization was a wild west, there was really no regulation, and there still is a limited amount, I think GDPR is seen as the kind of gold standard of what needs to be done in order to control things. And I think EU has done a phenomenal job in that. And I think what we're going to see in the future is exactly what you described that there, there is an added amount of control over personal data and the use of it. And that's going to hit Google's and Facebook's business models, how hard they're going to be hit. We don't know yet because they they at the moment have quite a considerable control have also the political sphere and they can they can somewhat address topics to their liking. But I think EU has done done a good job. But I think we'll will then investigate a little bit more about the the other monetization methods of data because they're there are various, various areas, but I'll maybe pass on to Michael to pitch your ideas first.
Thanks Reko yeah, I mean, it's a really interesting topic, and we've been discussing it in very many different projects of ours. Some time ago, we did a strategy for one of our clients around office space in real estate, and we looked at the fact that in the future office space might actually Before free, you might actually be paying with your data as a company for the office space so that the company can monetize the data. Very similar vision has actually been discussed in private housing so that you will actually not pay for your flat anymore. But that the rental company can actually use your data. I think what's very interesting in the office space context is who owns the data of an employee? So if the employee is in the office or not, or if the employee walks around the office? Who owns the data? Who can use the data? Who can monetize that data? Is it the individual employees data? Who needs to agree to it? Is it the company's data? Who actually employs the employee? Or is it the data that the company that owns the building or owns the office space, basically owns and can monetize? So there's, there's various different layers in in these models, or if you step into a tram. And basically, the tram provider, sees how many people are in the tram, how many people go from A to B, who owns the data in those cases. So I think privacy is extremely important in this space, I think there's a huge opportunity for monetization, but also for improvement of services, and definition of completely new services. So for example, imagine you sit in the office, and your food, your favourite food is basically ordered before you even know that you're hungry and delivered to your table. So there's just a multitude of new services that could emerge out of that. But I think there is on the other hand, also. And I think, Michael, you, you play to that question a little bit, the question of what is data ownership? And who owns the data who controls the data, as legally there is most likely not even a an ownership in their context.
Thanks, Michael. And Thanks, Reko, I think you brought up really good points here, I wanted to first tackle called the two mechanisms that you kind of brought up that in setting up the stage for data to become a real business asset to your product two, sort of major mechanisms. One of them is regulation, data privacy. And, Michael, you also alluded to that. So I think regulation is important when the owners of the data or the providers of the data are in a weaker position than the exploiters of the data if you like. And then you need some regulation to govern and control and protect those individuals. I wouldn't go down that route in this discussion further, because I think the other one is more interesting from a business application point of view. And that is the market mechanism. That is kind of guiding a win, win and win applications of data. And those could be exactly the situations where the provider of the data can actually provide valuable data that the other party can create value with, and also provide something in return in market terms. So whether it's a monetary compensation or some other beneficial condition, business term or other compensation to us that data, I think that is the important thing. And that is the area where we need more innovation, because this is not an evident thing. We haven't been using data as a market mechanism or transaction mechanism. And that's, I guess, why we are still like critical. You mentioned we are exploring how to use it. And then the rule set is not really strictly set out. Yeah, I recall, you had a reflection to that.
Yes. And and wholeheartedly agreed. I think the the question of utilising data, I mean that the question that I faced multiple times, is, so how do I sell my data? Who buys it? And that question is not really easy to answer. I think the easier way of thinking about utilising data is is kind of binding it to your own products and services if you're able to monetize your data in a way that that your product becomes cheaper, or has a feature that he didn't have before because of data that's already data monetization. And that's a way of primarily creating value for date. And one of the interesting things about data as you said, Patrick, it's not really clearly regulate it also, that there is a very positive side to that, because also the, the financial side of companies does not necessarily recognise the value of data. So what you can actually do, if you utilise your data correctly, is to have an asset in the organisation that is recognised recognised in the books. So, if you're able to create a really a date the business, then it is not necessarily something that is recognised in your books. And it's also not something that is being taxed. So in effect, you're able to get tax free benefits out of utilising our data as part of your products and services.
Very good point. And one of the very practical problems with recognising the value of your data asset in your books is the fact that data, as such doesn't really have any value, the value is in the context, you use it for value creation, therefore, it's really difficult to define the standards for evaluating your data asset. So that's obviously one challenge. Michael, did you have any other reflections on these topics?
Yeah, I mean, I think one, one thing that comes to mind as a key example, and we've been discussing that a lot with our clients is for me, circular economy, which is one of the key areas where data will be a key enabler of whatever new services you will be having. Because in order to cater for circularity, between companies, you need to make sure that the data streams are understood the resource streams are understood. And that to a large extent, is defined by exchanging the right data between companies so that the whole concept can actually work at the end of the day. So I think from from that point of view, we will see areas where data is a nice to have, where you will basically see it as an add on or to provide new services. But then we will see areas emerging where data is basically a key ingredient. So without thinking about exchanging data, and without building on a on an active data exchange, you will not even be able to tackle these areas. And I think that that will be something where we will see more and more new services or potentially even completely new industries emerging on top of the data. At the same time, I fully agree with what was said what you were saying about the data privacy, I think this is something in the regulation. I think this is something where we're only seeing the beginning of this. And I think specifically, regional regulations will only go that far as data can be transferred and moved around the world very quickly, legally or illegally. So So on the regulation side on understanding what what needs to be put in place, I think we will we still have a long way to go.
Excellent point, Michael, an excellent points, I should say.
To wrap up, I think we had really, really good aspects to how to get data to become a real business asset. We we reckon you mentioned the balance between the need for regulation, as this is a new fee, not phenomenon. But also that regulation should be balanced with the market mechanism that is allowing for new business innovations and providing a structure for this kind of a business.
Then we talked about Michael, you mentioned, paying for your services through your data. And then you raise the ownership question of data and also highlighted the need for privacy and the related complications that there may be between employers and employees, for example, then, Michael, you mentioned the very important point of data being an enabler of the circular economy. And you've also product this very important topic of data being used as a value creation booster for your physical assets, not only your material flows, but also, for example, higher utilisation of your capacity, beat office space or anything like that. Data is very powerful there and I think we can see many applications in that area.
So to sum up, I wanted to basically inspired by this discussion, I've wanted to offer a business Tip of the Week for anybody who's listening and interested in challenging themselves with this kind of a thing. Given the example we talked about, in the start, the Facebook kind of a thing where These giants get their most important raw material for free the data, the consumer data, and use that in their production engine, the hyper targeted marketing engine. in generating revenues for themselves. There could be somebody who's setting up an alternative model where you kind of get that data. But in exchange, you provide a token a stake in the returns, you are being able to generate with the help of that data back to the providers of that data. That could be like America, you mentioned the my data movement. So that could be a direction we can see some of these data enabled businesses going forward. Taking so really interesting discussion.
I know we could talk about this all day, but it's time to thank you thank the listeners. And looking forward to our next chat. Thank you, Michael. Thankyou, Reko.
Thanks, Petri. It would be really good to talk more about this