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Introduction

Digital transformation efforts are well underway for the majority of enterprise organizations. However, it will be the operationalization of data-driven enterprise initiatives, rather than the simple digitization of existing processes, that provides transformative business potential.

Highlights

  • Operationalization is technology-agnostic and aims to optimize enterprise-wide processes so that maximum business value can be derived from data.
  • The competitive advantages of digital transformation efforts will be dependent on successful operationalization of data-driven initiatives.
  • Technology tools are necessary, but not sufficient, to achieve operationalization of data-driven initiatives. People, process, and technology must be orchestrated.

Features and Benefits

  • Identifies a working definition for the concept of "operationalization," and evaluates how this definition applies to data-driven initiatives in the enterprise.
  • Analyzes current data measuring the progress of digital transformation and enterprise-wide data leverage in businesses around the world.
  • Compares the concepts of digital transformation and operationalization, defining their relationship and identifying dependencies.
  • Identifies the three categories of a data-driven culture, and evaluates the role of each in achieving operationalization of data-driven initiatives.
  • Identifies practical steps that may be taken by the enterprise toward operationalization of a data science initiative.

Key questions answered

  • What is the definition of "operationalization," and what does it apply to?
  • How is operationalization instrumental in helping the enterprise achieve the objectives of digital transformation?
  • How advanced, statistically, are enterprise organizations in their efforts to exploit the value of data across the business?
  • What are the elements of a data-driven culture, and how must these elements contribute to operationalization?
  • What would be an example of an operationalized data-driven initiative, and what would be the steps taken to achieve it?

Table of contents

Summary

  • Catalyst
  • Ovum view
  • Key messages

Recommendations

  • Recommendations for enterprises
  • Recommendations for vendors

Operationalization maximizes the value of data

  • Creating a working definition for "operationalization"
  • Operationalization is a technology-agnostic concept
  • Enabling all workers to drive business value through data

Digital transformation relies on operationalization

  • Enterprise-wide data leverage is a goal of digital transformation
  • Most have not yet achieved enterprise-wide data leverage
  • Operationalization is critical to enterprise-wide data leverage
  • Enterprise-wide data leverage: A promise we have heard before?

Technology tools are necessary, but not sufficient

  • Data-driven culture is defined by people, process, technology
  • Operationalization scales infrastructure and processes
  • What operationalization looks like: A hypothetical case study

Appendix

  • Methodology
  • Further reading
  • Author