As businesses embrace accelerated digital transformation, new ways to share data between organizations without compromising privacy have emerged.

As companies continue to embrace accelerated technology transformation in response to the disruption presented by COVID-19, some have emerged as digital frontrunners, finding new and creative ways to put emerging technologies to work. Central to their pioneering success are innovative ways to share data across and between organizations without compromising privacy.

As COVID-19 turns to the endemic phase, the lingering challenges reverberate throughout the global economy. Persistent labor and resource shortages, hybrid work models, the explosion of new devices, and supply chain disruptions, to name a few, require new solutions.

Deloitte’s 13th Annual Technology Trends Report, Simplified data sharing, shows that pioneering organizations are navigating this volatility by automating, extracting and outsourcing many of their historically in-house capabilities to the cloud. Nowhere is this shift more pronounced than in the rise of cloud-based data platforms.

Effective data management is at the heart of success in this disrupted market. One of the trends in Deloitte’s Technology Trends report explains how new technologies are enabling advanced business models by simplifying the mechanisms for sharing data between organizations, without compromising privacy.

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Unleash the possibilities of shared data

Making innovative use of shared data is not a chimera. For advanced organizations, this is the reality.

For example, when COVID-19 vaccines became widely available in the spring of 2021, SVC Health (CVSH) leveraged external data from vaccine suppliers and the Centers for Disease Control and Prevention (CDC) to forecast supply and demand.

The team immediately implemented governance to prioritize data protection and compliance with privacy and data security laws, then fed that information into internal systems that enabled patients to plan appointments, partners to set up clinics and analysts to measure the effectiveness of the campaign.

The team also shared data externally with research agencies and universities to help assess vaccination rates in the population. As vaccine rollout continued, CVSH used demographic and demand data to identify underserved areas to facilitate access to vaccines where they were needed most.

Connecting more easily with existing partners is only part of the story. Cloud-native data platforms also encourage organizations to seek out and leverage external data that was traditionally out of reach or otherwise prohibited to open up a new arena of data-driven opportunities.

For example, industry data marketplaces can enable otherwise fierce competitors to solve common challenges through collaboration. Consider banks in developing regions: together they could pool anonymized credit data to create an interbank credit risk model, opening up new insights and opportunities for the benefit of all.

Along the same lines, many manufacturers and retailers already purchase consumer data from third-party data brokers, but that data is often of poor quality or too limited to have any meaningful business impact. Sharing high-quality data between consenting parties can allow every partner in the value chain, from suppliers to manufacturers to marketers, to pool customer data and create a demand picture. at higher resolution.

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Acquiring external data can be simple and valuable

The recent proliferation of cloud-based data sharing platforms makes it easier for organizations to buy and sell data than in the past. The data-sharing-as-a-service model allows subscribers to manage, curate, and adapt data and to aggregate and sell access to that data to other subscribers.

These models have already been successful in music streaming and social media, where providers provide easy-to-use platforms and customers provide content to share. Similar systems are within reach for enterprises, and the data market sector is in the midst of a “gold rush” as startups join incumbents in asserting their market rights.

This model is promising and has led to a surge in demand for high quality data from external sources. Data is no longer just a tool to inform high-level decision-making, it is increasingly seen as a critical business asset that can be explicitly valued and monetized. This sea change underscores the need for savvy companies to explore what data markets could do to their bottom line.

Yet despite the frenetic acceleration in this space, it still remains early. Governance, security, and pricing models continue to evolve as the business and technology community evolves in response to supply and demand. That said, as new participants continue to join the fray, the volume, variety, and value of these emerging data markets are only growing.

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Keep privacy issues under control

Positive projections aside, every emerging tech trend carries the potential for risk. Privacy policies; competitive secrecy; and a myriad of safety, security and governance issues have historically hampered companies’ ability to openly share their data.

Enter a new class of computational approaches known as privacy-preserving computingwhich can help reap the benefits of data sharing without compromising discretion.

Emerging privacy preservation techniques are complex and multifaceted:

  • Fully homomorphic encryption makes it possible to share and analyze encrypted data, without first decrypting it.
  • Evidence without knowledge allow users to prove their knowledge of a value without having to reveal the value itself.
  • The federated analysis technique allows companies to share insights from their analysis without sharing the data itself.
  • Differential Privacy adds noise to data sets, making it impossible to reverse engineer the original inputs.

At their core, each of these techniques, and others like them, enable rich collaboration without compromising competitive secrecy or data confidentiality. This “best of both worlds” approach can help mitigate data security risks and gain buy-in from customers, partners, and other stakeholders.

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How to take the next step

What does this mean for businesses moving forward? First, business leaders need to stay focused on today’s data management initiatives, even those that cannot be solved by data sharing. Strong data governance, quality, and metadata initiatives, for example, are still essential for success in the modern marketplace.

Second, technology and business leaders must recognize that these new tools and approaches, while potentially disruptive, will not change their organizational culture overnight. Businesses of all sizes have deeply rooted processes and standards for managing and accessing data.

Established companies may have strict, fixed practices, while startups and digital natives may assume a more relaxed approach. Some companies may be less willing to share data or be inherently suspicious, even with anonymized data. Others may need to take a long look in the mirror and adapt accordingly to overcome these cultural challenges.

Still, these are no reasons to avoid exploring and, once ready, embracing the trend. Organizations at the forefront are already reaping the benefits and leaving their less aware and/or less prepared competitors in the dust. Companies in all sectors have increasingly liquid assets. Now might be the time to make the most of it.

About the authors:

Mike Bechtel, Chief Futurist, and Nitin Mittal, Head of AI, at Deloitte Consulting LLP