Transforming Enterprises into Next-Generation Data Businesses

By Team Acentrik

Published on

September 10, 2024

The future of enterprises isn’t just about products and services; it’s about developing data businesses to outpace their rivals and retain a competitive edge. Insights from McKinsey & Company suggest that approximately 36% of organizations are expected to develop data, analytics, and AI platforms within the next five years, underscoring the critical role of data in modern business strategies.

"Building a profitable data business hinges on having not just the right data but also a business model and enterprise capabilities to support it." – McKinsey & Company

Strategies for Building Successful Data Businesses

The strategic imperatives outlined by McKinsey for building successful data businesses align well with the capabilities of a cutting-edge data exchange platform. Here’s how these strategies can be implemented and extended:

1) Leveraging Massive Data to Create Market Innovations

Enterprises can unlock greater value from their vast data through computation and analysis – resulting in more market insights which can be monetized and leveraged by other businesses for improved decision-making. The process calls for a neutral platform with in-built privacy-preserving features, to enable computations on diverse data. The output can be shared with multiple participants, with connectors closer to data sources for secure data connection, transmission, and computation. For instance, different healthcare providers could integrate clinical and biometric data on this platform to generate predictive models that identify health risks effectively, while maintaining strict patient confidentiality.

2) Create Data Products from User Base

For organizations to achieve data-driven goals, it takes effective utilization of user data, while protecting its full privacy. Source data can be used for analytics purposes and also used to create further data products. These contribute to generating innovative revenue streams for the organization by monetizing these data products. The end goal of monetizing these data products requires a neutral platform that can facilitate the development of a community data marketplace, where participants can create, buy, and sell data products. Privacy-preserving features of this platform needs to be in place, including access controls at both platform and asset levels to maintain full control and ownership over one’s data and with flexible post-payment options to suit business needs.

3) Scale an Internal Platform for External Adoption

Organizations can build business models not just on their data, but on existing data management tools used internally. There is a huge opportunity to further scale such existing systems into an external product for markets, which enables organizations to pivot with their business offerings. This requires a turnkey solution which can be integrated with other global organizations – allowing them to flexibly customize and generate new value from their data on top of the platform. For example, a company’s internal data management system can evolve into a full-fledged service offering for other businesses to adopt, allowing external organizations to build their respective business models.

A Vision for Data Business Transformation

These strategies underscore the benefits for enterprises to not only unlock greater value out of their data, but transform organizations to data businesses. The adoption of privacy-preserving technologies like Acentrik that support these activities is pivotal for enterprises to kickstart this journey.

Reach out to discover how we can support you in building your successful data business. Read the full report from McKinsey & Company here.