Navigating the Evolution: The Rise of Data-Driven Enterprises
Macro Trends and Economic Potential
The future of business depends on data and technology, but there are three things to keep in mind.
First, the market favors companies that use data and technology well, because they have maturing technologies and a more accessible talent pool.
Second, lessons from recent recessions and economic disruption shows that companies that continually invested in innovation during these periods had much higher returns than their competitors.
Third, the new wave of technology—generative AI—could contribute $2.6 trillion to $4.4 trillion annually across various use cases McKinsey recently analyzed.
These factors underscore the pivotal role of data as the driving force behind this growth. Business leaders need to know what to change and how to drive that change to create a data-driven enterprise.
The what: Seven data shifts
There are seven key shifts that companies need to make on their journey to becoming a data-driven organization.
1. Cultivate a data-first organization
Instead of applying data-driven approaches in a piecemeal fashion, the organization can unlock the full potential of data and foster a culture of innovation. By providing self-service tools, learning opportunities, and leadership support, the organization can empower all employees to use data effectively and creatively to solve problems. This is how the organization can embed a data-first mindset in every level and function.
2. Power up data and analytics technology
The business can leverage ubiquitous technologies to transform data into insights faster and more effectively. Data is not only generated and processed, but also analyzed and visualized in real time. This enables the use of advanced analytics such as generative AI, self-serve data, and low-code/no-code platforms for all users.
3. Create dynamic and reusable data products
Instead of organizing data with relational database tools for each use case, data is transformed into rich, multipurpose, dynamic data products. This reduces data engineering efforts and enables high-value use cases, accelerating time to market and ROI.
4. Treat data like a product
Instead of having data scattered and duplicated across multiple and expensive systems, data products have their own squads that take care of data security, engineering, and analytics. Data product owners guide the teams to keep improving the products according to user needs.
5. Expand the chief data officer’s role to generate value
CDOs and their teams are not just policy enforcers, but also value creators. They leverage data to generate insights, design an enterprise data vision, and create new revenue streams by offering data solutions and data sharing opportunities.
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6. Make data-ecosystem integration the norm
Data-sharing platforms enable large, complex organizations to work together on data-driven projects, both internally and externally. They join a data economy where they exchange data and insights with other members, creating more value for everyone.
7. Prioritize and automate data management
Instead of relying on manual processes and regulatory compliance, companies are adopting AI-powered solutions and best practices to manage, protect, and recover their data. These solutions use metadata and lineage to describe the data, enhance data quality, and generate predefined scripts to to provide safe and secure data access to users in near real time.
The How: Rewiring the Organization
While these shifts are intuitive, translating them into action requires a broad and deep approach. It's not about isolated change programs but a transformational journey. The key lies in developing a roadmap that prioritizes value domains, identifies data sources, and highlights critical capabilities. A crucial aspect is building in-house technology expertise and integrating agile pods for efficient solution development. The backbone of this transformation is a cloud-first architecture centered around reusable data products.
This level of rewiring is non-negotiable—it's the engine for building a data-driven enterprise that continually creates value.
We hope this edition will provide you with a comprehensive understanding of the evolving landscape of data-driven enterprises and the profound impact of AI on our economic future. The strategies outlined will serve as a practical guide for organizations aspiring to lead in the data-driven era.
Stay tuned for more insights on the evolving landscape of data-driven enterprises.
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