Richard Knott.
"Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.” — Tom Goodwin
For a few years, no digital transformation deck was complete without Tom Goodwin’s famous observation, made back in 2015, which perfectly captured the shift from ownership to access in a post-digital world. Many of the most disruptive and successful companies of the last decade haven’t focused on owning assets. Instead, they’ve focused on connecting them.
And now, this shift is coming to the data economy.
Just as the music industry moved from physical ownership of records and CDs to the peer-to-peer sharing model of Napster and ultimately to the on-demand, personalised experience of Spotify, the advertising industry is undergoing a parallel transformation in data collaboration and management.
But this shift is happening faster, driven by growing pressure from data privacy regulations and the need for more effective data-driven marketing in a post-cookie world.
Data as an Asset — or a Liability?
Another phrase that was impossible to avoid a decade ago was the concept of ‘big data’ and the notion that "data is the new oil."
In the world of advertising and marketing, that idea held true as data became integral to every part of marketing, from targeting to insights and performance. Brands and their agencies have been in a data arms race to ensure they have the ‘best’ and most up-to-date data to maximise client outcomes.
Up until recently, this race was centred around two strategic approaches: buy or build. Either you acquired large-scale data assets or you built your own proprietary data infrastructure. This strategy has created a wave of high-profile acquisitions with some agencies betting on data ownership as the foundation for competitive advantage.
Whilst potentially powerful, this approach comes with considerable challenges. When you acquire data, you inherit not only the strategic benefits but also the legal and reputational risks associated with managing consumer data.
Regulatory frameworks like GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act), and the expected updates to the Australian Privacy Act place stringent demands on how data is collected, shared, and processed, with clear responsibilities defined under Controller or Processor obligations. Mishandling data can lead to massive fines, reputational damage, and loss of consumer trust.
Consequently, we’ve seen the rapid emergence of technology that facilitates data connectivity and collaboration. This is giving brands and agencies the ability to access and leverage insights from multiple datasets without ever needing to centralise or take ownership of the data. It’s a shift from the ‘big data’ mentality toward one of data minimisation.
Rather than data being a commodity to be owned, traded, and hoarded, it becomes an asset to be connected and activated. This produces all the reward whilst minimising regulatory risk.
Why Data Connectivity Trumps Data Ownership
Decentralised data connectivity enables companies to work together without ever needing to share raw data. Using privacy-enhancing technologies (PETs) and AI techniques like federated learning, companies can connect their datasets, generate insights, and activate campaigns without the data ever leaving the controller's environment.
This means that any business can collaborate securely, confident that their data remains protected. For example:
- A brand holds data about customer purchase history.
- A media owner holds data about customer engagement with content.
- Through decentralized data collaboration, these datasets can be connected to generate insights about which customers are most likely to engage with specific media — without the brand or media owner ever sharing raw data.
The key is that the raw data never leaves the control of either party. This allows both parties to collaborate without taking on each other’s data controller liabilities, reducing risk while increasing the quality of insights.
This model is particularly powerful in environments like retail media networks, where multiple parties (brands, retailers, media owners) want to collaborate to better understand the customer journey. The ability to pool insights without sharing data enables more effective audience segmentation, improved targeting, and greater measurement accuracy — all while preserving consumer privacy.
Performance Without Sacrificing Privacy
A decentralised approach to data collaboration offers a significant advantage in a privacy-first world, and it’s gaining adoption fast.
While the music industry actively resisted the move to peer-to-peer models, there’s more of an incentive for the media and marketing industry to embrace it as it ultimately helps the data collector manage their data controller liabilities and the data user avoid taking on those liabilities
The future of data collaboration is not about building bigger data warehouses — it’s about building better data connections.
In a decentralised world, success will depend not on how much data you own but on how effectively you can connect and leverage it in a privacy-safe way.
By Richard Knott, SVP APAC at InfoSum