☎️ Interview: Stijn Christiaens, CEO of Collibra on the State of Privacy-Enhancing Technologies #004
On competing against non-consumption; why Data Asset Systems of Records are like CRM systems 20 years ago and; the changing role of the Chief Data Officer
Collaborative computing is the next trillion-dollar market. We are at the beginning of fundamentally reshaping how data is used in the economy. When data can be shared internally and externally without barriers, the value of all data assets can be maximized for private and public value.
I spoke with Stijn Christians, CTO of Collibra, the market-leading data governance platform to explore this vision more deeply. Highlights include:
How competing against non-consumption changes how you sell;
Why Data Asset Systems of Records are like CRM systems 20 years ago and;
Why the Chief Data Officer is becoming one of the most important C-suite Roles
"Even if the technology is 5x better, the risk is much higher too. In some cases, even if performance and therefore revenue increase by X amount, the decision might still be not to do the thing because the risk and costs are too high. When it comes to data sharing those risks are huge."
Let’s start with selling. When you pitch customers on making better use of their data, what benefits do you lead with?
There aren’t any general rules, as you would expect when we are selling into businesses across different markets and different sectors. Each customer has a different internal data landscape and a set of external constraints like regulation, etc. But the reality is that we are almost always selling again non-consumption. Customers either buy us or they don’t solve the problem. So it’s inaction and inertia. GDPR has helped generate budgets and answer the “why now” question for many firms. We expect this to continue to drive business as we see ever more privacy regulation around the world as well as AI regulation which will require robust data governance processes. So we can easily say you need to be compliant; other propositions that land are making analysts more efficient by giving them access to data quickly. That’s not to mention the great migration to the Cloud generating demand for our products.
What is the most common barrier when selling your products and/or services?
We are selling a new product. Organisations haven’t bought it before, so there isn’t a process or buyer in some cases. A system of record for data assets also touches almost every department in the organisation, so there is a lot of market education to be done with many stakeholders. The value proposition is so strong, so once you get everyone coordinated, it’s a no-brainer, but the coordination is the challenge. It’s getting easier with Chief Data Officers now, though. We had like 1 CDO in 2002, maybe 400 in 2004, and maybe 10,000 now, with Gartner saying every large organisation will have a data office by this year, so, by extension, they will have a CDO. CDOs are responsible for managing data assets, so it’s the CDO’s job to coordinate internally so we don’t have to do it. The sales process is much simpler. That said, not all CDOs are the same and have the same mandate. CDO version 1 was defensive and about managing risk. CDO version 2 is offensive, and thinking about how to get data flowing internally to maximise value. The new CDOs and there aren’t many of them, and thinking about data as products. How to package up data assets and monetise them. That’s the future for leading organisations.
What do you think about the opportunities between internal and external data sharing?
You need to think about this through the lens of risk. Even if the technology is 5x better, the risk is much higher. In some cases, even if performance and therefore revenue increase by X amount, the decision might still be not to do the thing because the risk and costs are too high. When it comes to data sharing those risks are huge. Not just the risk of being fined, but just the risks of not understanding what you can and can’t do with data assets. The data creator might be giving away value in a dataset and not even know it. It’s complicated. Maybe what you can do in one country you can’t do in another. You don’t want the analysts to have to go to legal all the time. Most of the time it’s not worth the bother. I suppose with this in mind, internal data sharing has a lower risk profile and is more manageable. You can have a highly defined PoC and have strong measures to protect data. So I expect internal data sharing to grow first and only once that process is pretty embedded for external data sharing to be considered.
When thinking about helping companies utilise their data, a sensible framework is: governance, sharing, and monetisation. It feels like 95% of companies investing in their data infrastructure are still on data governance, maybe 5% are finding ways to share internally, and <1% are even thinking about monetisation yet. Does this sound right to you?
We need to put a dollar amount on data. We need something like accounting principles for data. This is a huge piece of work that would need global buy-in, but it is starting to happen. It’s being led by the big tech firms as they are already eschewing traditional accounting principles as they feel they aren’t quite fit for purpose. Different firms don’t like different bits of it. Investors already rely on pro forma results instead of GAAP accounting because GAAP just can’t handle intangible assets. And tech firms are mainly intangible assets and no-one wants that as cost instead of investment. So we are in the space where our accounting principles aren’t accurately reflecting what they are supposed to reflect.
What about data markets as a way to price data?
Yes, this is one route. If we get to a place where we can price data then I think the shift from governance to sharing and monetisation will happen rapidly. There are some price discovery engines in AWS, Databricks, Snowflake, etc that are trying to do this. Also some experiments on pricing in the crypto industry. This is the other route into pricing. Instead of new GAAP with data, let markets price data and then find some way to get that on the balance sheet. Data markets are a very interesting space.
Finally, what cultural, technical or social change would be required for demand in data collaboration to increase 10/100x?
Antitrust. It seems like Governments around the world are looking to find ways to address the monopolisation that has occurred in the data space. These firms might not be exerting monopoly control by raising prices, but their ubiquity and size has forced data into a few large silos. Breaking up these silos somehow seems to be the target. There are lots of different ways that might happen, some sort of standard interconnect would be one way to do it, or once we have decent internal data sharing based on a system of record for data assets, then you might want to legislate that companies must expose those systems to external developers like PSD-2 forced banks to open up. The EU’s GAIA-X is an interesting attempt to drive standards in Europe. They are already getting customers saying they have to run on GAIA-X . Solid is also gaining traction in the EU, so we might see this unblocking silos happen faster than expected.
There are technical changes like fully homomorphic encryption with mathematical guarantees that no-one can read the data being processed would be a technological enabler. It’s hard to see a pathway technically for fully homomorphic encryption to get to cost parity so it is competitive with plaintext processing, but if it does and there is a strong software ecosystem around it, you can imagine use cases around sharing data internally and then opening that up to partners. It’s like the compliance tick box is completed at source, so you can speed up deployment and access. But these sorts of visions are decades away. Practically, it’s going to be regulation that is the catalyst for change.