Part 3: Data Protection and the Future of Data
This brings up a really good point though about data and really offering it up like the London tube example. Did they have any worries or concerns about protecting that data? I mean they just gave all the data to the citizens. How do we and how do companies think about protection and managing data now?
That's a brilliant question. I mean the whole data privacy thing and the data sovereignty piece and the data security piece, plus data rights. Such a tough, tough topic right now. You know, what if I break it down and look at a couple of perspectives, again, from a consumer standpoint and an enterprise standpoint.
As a consumer, I don't necessarily want all my data used. So I don't like turning cookies on where they can track me on everything. And what if I'm looking at barbecue grills and I'm reading the Wall Street Journal and, all of a sudden, I get a barbecue grill ad in the Wall Street Journal? I don't like that experience. Right? It doesn't work me. So, I like turning those cookies off. But I get how valuable that is.
I think the key thing for consumers is trust. I think if companies and enterprises tell people how they're using the data and you have a relationship that goes beyond just a customer relationship – one where I'm giving value and getting value back from it. I think we're open to it. I think organizations and companies are going to have to look at it. At least from a consumer perspective, that would be my first thought.
So, I'll take the other extreme. The consumers’ experience is quite often driven by personalization. In our own business and research, there is data about a provider or about a client that is extremely confidential. But in aggregate and in an anonymized manner can be hugely insightful. Just knowing that and having the controls to make sure you're never exposing the confidentiality is key.
So, you can still use the data in a way that is insightful to different stakeholders. So, understanding the attributes of data and what's okay what's not okay. Kind of an almost plain speak is an important aspect of decision making whenever you're thinking about data.
You bring up a really good point, because my role as the Chief Data Officer, I lay awake at night thinking about, “What if we expose data that we're not supposed to expose?” And we have rigorous processes around the ability to anonymize that data. Because you're right; there's value in building groups of data together that are anonymized that can drive really good insights. And this is versus exposing single points of data.
So, there's different types of data that you may want to expose, or with the transparency just making everyone aware of how you're going to use their data. Okay. That's great. But you also have to protect that data, not only from a proprietary perspective, but you also need to think about how your users are using the data and make sure that they're using it appropriately that they understand the data. I worry about that as well. Do people really understand what they're looking at? Because using data incorrectly can be dangerous.
I think we're going to get further and further away from a human or an individual being able to understand how that data is being used. Especially if you think about the millions of APIs and microservices that are out there and all the different ways that data is being used. Right? Like Amadeus airline: passenger reservations. All they're doing is saying, “is a seat available or is a seat not available,” right? How many people in seat apps do we see, though, where people use it differently. And you go in and see, you know, do you want this amount of leg room, that amount of leg room, do you want this type of seat, do you want that?
There's all sorts of aspects of that that change that experience, similar to that TFL example we talked through. I don't think we can control that downstream. Just like the deals that we do with companies today. If I'm getting ESG data from somebody, they can't dictate how I use that data; they don't necessarily interpret the data for me. It's got to be developed in a way that is consumable across the supply chain that we no longer control. And that's going to be a different level of thinking for all of us as we think through, “how do we expose data.” Which will also drive through our strategy of what data needs to be and should be exposed.
That's right. And I would even go to the extreme. If data can be misused, assume it will be misused. So just protecting it through contracts is probably not good enough. It means you have to design to protect that exposure and prevent that misuse.
But at some point, what you're saying, is that at some point in the value stream, you have to just let go. You just have to let go.
That’s right: you just have to let go. I think when you design your API strategy and your microservices strategy and your overall data monetization strategy, you have to assume it's going to be used in ways that we can't even fathom now, and you just have to let go. So you provide things – I know it's hard for is right, like: “God, you know, I'm the only one that knows about this price point, what do you mean that somebody can use in a way I don't understand?”
But I think we've got to design to let go quite frankly, and once you do that, I think that's when you get the exponential growth in data strategies, which is why I'm such a huge proponent of data APIS versus just data services. I can't imagine what a Wall Street analyst is going to do with my data. You know, I could put a screen together for him, I could try to compete with Bloomberg and put a terminal together or something else. But I'd much rather say here's some great insights. You go, combine it with other insights in ways that you may figure out and tell me what's going on in it. And I think that's how we have to think going forward.
Right, well, that's why we're good together, Steve, because I'm a little more “control.” You're a little more “let go.”