General

The Data Clean Room Dilemma: Why Building In-House Beats Renting

Sadegh Riazi
July 25, 2023

Data is power, and companies today rely on it more than ever. But as data fuels opportunity, it also fuels risk without proper privacy and security.

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Data clean rooms emerged as a solution - virtual spaces for private data sharing and analysis. However, while clean rooms promise control, companies may be ceding more control than they realize by renting from vendors versus building in-house.

The appeal of renting is clear: it requires little initial investment and outsourcing the complexity. But this comes at a cost. Renting means relying on vendors’ tools, skills and timelines, limiting how data can be analyzed or what new technologies like AI are used. By the time companies receive insights, questions may have changed. And vendors, seeking maximum profit, have incentive to box companies into generic one-size-fits-all solutions.

In contrast, proprietary clean rooms can be tailored to companies’ unique needs and integrated with cutting-edge tools as desired. While building in-house requires substantial initial investment, over time it allows far greater flexibility, oversight and cost savings. And developing specialized data/AI expertise creates a durable competitive advantage.

Still, there are counterarguments for renting. Building clean rooms is resource-intensive, and few companies have expertise to do so securely. Renting provides access to third-party experience and “best practices” for data control and compliance. Partnerships with vendors also spread the risk of managing sensitive data. However, compliance and security ultimately depend more on a company’s internal oversight than on outsourcing. And risk is best mitigated through selective, transparent vendor partnerships where companies maintain control of their data, not by ceding it entirely.

The answer may lie in a hybrid model. For some companies, renting makes sense for initial capability or specific applications, if control and oversight stay internal. But proprietary ownership of core elements - data storage and I.P., for example - preserves flexibility and savings for the long run. Strategic investment in specialized talent will be essential. And companies should demand vendors share expertise to build in-house skills over time.

While clean rooms promise privacy-preserving data analysis, only those companies that govern data internally stand to gain a real competitive advantage from it. Renting clean rooms for short-term gain risks long-term dependence and loss of control. The question is not whether to build or buy, but how deeply a company’s data capability and expertise should be outsourced versus owned and developed internally. With balance and oversight, data need not be a risk to manage but a power to build, prosper and lead. And a power that belongs not to vendors but companies themselves.

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