In the age of AI, any organization serious about innovation will tell you that they are data-driven. However 80% of enterprise data is never utilized.

Being data-driven isn't just about data collection and analysis—it's about exploiting the full potential of the available data within and outside the organization, for which data sharing is essential. While data sharing is relatively common within academia and the scientific community, it’s often not the case in industry.

Data sharing as a strategic asset

Data sharing for efficiency

Even though data sharing might seem counterintuitive to foster commercial interests, the Gartner survey of Chief Data Officers or CDOs proves otherwise. CDOs who have adeptly implemented data-sharing projects within their companies are 1.7 times more proficient in demonstrating business worth and ROI from their data analytics approach. And the cherry on top: organizations championing data sharing will continue surpassing their competitors in most business value metrics.

Data sharing for collaboration

In today's dynamic business world, effective data sharing is more than just a technical process—it's a strategic asset. By breaking down information silos, businesses can foster a culture of collaboration, paving the way for partnerships and potential diversification into new sectors. A comprehensive understanding of market dynamics derived from shared data, enables informed decision-making.

Data sharing for insights

Furthermore, the wealth of insights from diverse datasets propels innovation, giving businesses a competitive advantage. Open innovation, facilitated by this data sharing, allows enterprises to harness external ideas and paths to market, fostering a collaborative growth ecosystem. The depth of customer understanding offered by shared data allows for a more personalized consumer experience, while access to shared industry insights provides an edge in identifying market trends. Moreover, transparency in data sharing strengthens stakeholder engagement, building trust and collaborative growth.

Data sharing for society

In addition to direct benefits to companies, data sharing has an immense societal and environmental impact. It plays a pivotal role in the green transition, aiding in carbon reduction by alleviating traffic and enhancing energy efficiency in buildings and vehicles. It also optimizes industrial and agricultural processes while assisting in disaster management like floods or wildfires. Data sharing increases data availability that helps promote new product development and competitive services. For individuals and consumers, this translates to more service choices, smarter urban environments, and improved public health responses.

The challenges of data sharing

Even though the benefits of data sharing are well known, since it’s not the current norm in industry, companies encounter multiple challenges while sharing data. Foremost among these are safeguarding data privacy and intellectual property. They also face interoperability issues in terms of IT and data formats. Concerns about data accuracy, integrity, and misuse of confidential data are other main challenges.

Promoting a data-sharing culture requires collaboration and overhauling outdated data management strategies. It's essential to foster a sharing mindset, even when the objectives might differ or seem at odds, by addressing the culture of status-quo and biases against data sharing.

While overhauling the existing practices may seem daunting, enterprises can begin with operational strategies like building data governance frameworks that detail specific guidelines, responsibilities, and roles related to data sharing. Combining this with essential security measures include data encryption, data anonymization, and enforcing access limitations will promote the buy-in. Educating stakeholders about the importance and procedures of robust data sharing is vital, and fostering an environment of transparency and trust is fundamental for successful data-sharing efforts.

Synthetic data for data sharing

Technical solutions such as using synthetic data could provide a win-win solution to overcome data sharing challenges. Synthetic data's introduction to the data-sharing paradigm can be transformative for enterprises since it offers a viable solution to data privacy and security by providing rich datasets devoid of personal identifiers. This allows organizations to share and analyze data without compromising user privacy or commercially sensitive data.

Moreover, synthetic data helps businesses model various scenarios, which can be invaluable for training machine learning models or simulating complex systems without relying on actual user data. Thus, as enterprises recognize the significance of data sharing, synthetic data emerges as a critical tool, ensuring that sharing is ethical, secure, and efficient.

Conclusions

Irrespective of the technical or organizational strategy on how it’s implemented , data sharing acts as a catalyst for business growth, efficiency, and innovation, and is becoming an integral aspect of modern enterprise strategy. To fully harness the potential of data sharing, organizations must navigate a complex landscape that involves not only technology but also cultural, ethical, regulatory, and economic considerations. As organizations continue to adapt and evolve, data sharing will remain a pivotal element of their strategy, propelling them forward into a future where data is the lifeblood of success.