The COVID-19 pandemic taught us a crucial lesson: To survive and thrive in today’s volatile, uncertain, complex, and ambiguous world, organizations must manage change and make decisions more quickly than ever.
To adapt to this reality, Chief Data and Analytics Officers must help their organizations reimagine themselves around customer journeys, product development, and other value-creation processes. This often means moving away from multilayered, command-and-control functional structures into simpler forms.
Enterprise agility involves redistributing authority and decision-making to autonomous teams, each with a clear purpose and the skills and resources required to achieve business objectives.
For example:
To achieve business agility, organizations must not only change their structure but also who is responsible and accountable for managing data. Chief Data and Analytics officers are reevaluating traditional centralized data management approaches that are slow and cumbersome, as they make quickly adapting to new business situations difficult.
Increasingly, they are finding the new architectural approach of data mesh a compelling option to empower business agility by enabling domain teams to take charge of data curation and use.
Data mesh is an approach to data and data interfaces for efficient and business-aligned consumption and value delivery. It serves business domains with relevant, timely, high-quality data views and perspectives packaged as business-relevant data products or services. These data products encapsulate all the functionality required for a specific business need, such as product demand forecasting. We will cover data products in more detail in an upcoming blog.
Data mesh shifts the paradigm of designing data architecture to be oriented around business domains, which are functional activities and processes required for a business outcome. For example, delivering consistent and personalized customer experiences across channels and touchpoints. It deconstructs traditional monolithic data architecture into decentralized components designed to support specific business domain needs.
It changes the operating model for data governance to a federated approach that requires chief data and analytics officers to carefully balance the need for domain team autonomy with the need for cross-domain interoperability.
CDOs and CDAOs who have moved to data mesh say the characteristics that enable business agility include:
The whole premise of data mesh is to help organizations make business decisions faster by shifting responsibility and accountability for data and analytics to the domain teams that best understand the business situation and context. This paradigm shift promotes a culture of innovation and adaptability, enabling organizations to respond rapidly to changing market conditions and stay ahead of their competitors. Five compelling business reasons chief data and analytics officers report for moving to data mesh are:
To successfully implement data mesh, keep the following best practices in mind:
Decision-making speed and agility are critical to success in today’s fast-changing world. Data mesh is an architectural design pattern that distributes responsibility for data to small autonomous teams focused on specific business domains. By taking a business-centered, technology-enabled approach, data mesh helps organizations generate more business value from their data.