RESEARCH REPORT

In brief

In brief

  • Data is everywhere today, growing constantly and enabling unprecedented insights. Becoming data-driven is the new table stakes for enterprise success.
  • What does it mean to be a data-driven enterprise? It means maximizing the value of your data and treating it as a differentiated asset. It means using data as the basis for critical decision-making through high-quality analytics.
  • In short, you must think of your data, and the analytics that rely on it, as a “product” that’s essential for driving desired outcomes.
  • Accenture Labs’ data maturity model charts the journey to data “industrialization,” an ideal state where enterprise leaders tap the best available data at any time for actionable insights and optimized decisions.


Our five-step model shifts clients away from a siloed, “single-use” approach, in which data is tightly coupled to certain schemes and formats, to an ultimate stage where data is treated like a “first-class citizen.”

1. Ad-hoc: Breaking down silos

Starting out, enterprises often lack a product mindset and treat data as a “second-class citizen.” Data is tightly coupled with applications, with limited capacity for internal sharing due to a lack of data strategy, architecture, delivery or risk management.

2. Organize: Sparking excitement

The enterprise recognizes the value of its data as an asset and it begins to decouple data from applications and develop a data-product mindset through a business vision and data strategy.

3. Tactical: Building momentum

The enterprise proves the value of its metrics and data-driven methods; it standardizes its tools, templates and methods to create an essential foothold as a data business.

4. Critical: Moving to production

The enterprise builds well-defined and automated methods for developing its data products, establishes a well-structured data product catalogue, and provides self-service capabilities across the organization. Data is transformed into an independent, digital asset for the business and expands its use out into the connected ecosystem.

5. Industrial: Data as differentiator

Data is treated as a first-class citizen and drives optimal outcomes. The competitive positioning of the enterprise is differentiated by the quality of its data products in the digital ecosystem.

As enterprise data volume explodes and the number of potential data use cases grows exponentially, an industrialized approach is quickly becoming a must-have capability.

Industrialization enablews an ever-greater degree of automation and rapid delivery to create the best data and the best models to enable the outcomes you want.

Read Accenture Labs’ full report to chart your journey to data industrialization on the data maturity model graphic.



An industrialized approach to data rests on a product mindset that makes data and models easy and appealing to use.

Teresa Tung, Ph.D.

Managing Director – Applied Intelligence Innovation Lead, Accenture Labs


Jean-Luc Chatelain

Managing Director – CTO Applied Intelligence

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