Unlocking value with data products
Five steps data executives can take to build high-value data products and increase competitive advantage.
A step-by-step approach to data product creation
From discovery to governance, learn the steps to building data products that drive business decisions and create value.
Companies spend billions on data ecosystems, assets, and services every year to shorten time to insights, increase productivity, and increase margins. Even when data investments underperform expectations, leaders remain convinced: The road to growth begins with data—and often, data products.
KPMG recently surveyed 250 executives across multiple industries to learn more about which sectors are using data products to gain competitive advantage, speed to market, and regulatory compliance. Key findings include:
Where do they see the most value?
Areas where respondents anticipate unlocking value
Building high-value, high-utility data products
The data product owner’s goal is to:
- Define and elevate the value of their data
- Ensure the usefulness of their data products
- Partner with others to help ensure easy availability for the good of the entire organization
Learn more about the key steps to success in this study:
Step 1: Inventory your data assets and inventory
Step 2: Quantify data value
Step 3: Confirm data usefulness and prune where needed
Step 4: Shape behavior, self-service, and a marketplace mindset
Step 5: Prioritize value measurement
Unlocking value with data products
Five steps data executives can take to build high-value data products and increase competitive advantage. Find out how by reading Unlocking Value with Data Products. Download and read the full report by completing the form below.
KPMG is here to help.
Build data products that rely on agile management systems, elevated data quality, and solid operational foundations. We’ll help you establish federated data ownership practices and data models optimized for specific domains and lines of business.
Anticipate and adapt to the wide-ranging impacts AI can have on your data and organization, including budgets and data controls, secure data practices, and cloud-native architectures.
Harness the power of data ethically and responsibly with trusted data principles and governance models for managing risk.
Create a consumer lifecycle approach that incorporates self-service models, AI assistants and agents, and builds a foundation for enterprise insights.
Operate and manage your data infrastructure with integrated frameworks that support access to a broad range of data sources and make analytics faster with less friction.
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