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Accelerating Data-Driven Transformation

To gain competitive advantage, companies are rushing to digitalize their businesses—but their efforts often fail. Many organizations start with sweeping IT programs that take years—and don’t deliver. BCG has developed a faster, better, and less risky way.

Moving a big company in a new direction is a huge challenge for management. The best-conceived and most urgent transformation programs—digital or otherwise—are sometimes no match for organizational inertia. This may explain why 70% of publicly announced transformation programs fail to meet the company’s ambition, its timeline for the transformation, or both.

But large organizations can overcome resistance and build the enthusiasm needed for change to succeed if they approach transformation in the right way.

What Data-Driven Transformations Require to Succeed

Through our work with clients, BCG has determined exactly what data-driven transformations require to succeed: These undertakings must be cost effective, incremental, and sustainable. Drawing on our experiences, BCG has developed a three-phase approach to data-driven transformation.

  • Use quick wins to learn and fund the digital journey.
  • Design the companywide transformation.
  • Organize for sustained performance.

The approach starts with small-scale, rapid digitalization efforts that lay the foundation for the broader transformation and generate returns to help fund later phases of the effort. In the second and third phases, companies draw on knowledge from their early wins to create a roadmap for companywide transformation, “industrialize” data and analytics, and build systems and capabilities to execute new data-driven strategies and processes. You can read about the approach in greater detail in BCG's Data-Driven Transformation: Accelerate at Scale Now.

This three-step approach is faster, less costly, and more likely to succeed than a systemwide overhaul. Using existing data systematically and combining it with external data (from social networks, for example) for marketing or resolving customers' issues can deliver fast results. BCG has seen companies achieve 15% to 20% of the potential of a full data-driven transformation in six to nine months.

Use Quick Wins to Learn and Fund the Digital Journey

By starting a transformation journey with a small number of quick initiatives that demonstrate what can be achieved by using new approaches, companies greatly increase their chances of eventual success.

Leaders should choose quick-win initiatives carefully, on the basis of several critical criteria: they must have a high chance of success, a significant and rapid payback, and visibility across the company. A major industrial company, for example, started by digitalizing high-profile processes, including inventory management.

Companies should use agile methodologies to build any new analytics models, with short sprints and tight timelines for developing a minimum viable product that can be tested and used to define additional requirements and refinements.

Quick-win projects should require no more than four to six months to complete, and their value should be demonstrable within weeks.

Design the Companywide Transformation

As soon as it is clear that the early digital transformation projects are off to a solid start, the company can start preparing the roadmap for extending digital transformation across the enterprise. This starts with a thorough understanding of where it stands in terms of data, digitalization, and current capabilities.

The company should quickly and objectively assess its situation and gauge how its capabilities stack up against best practices in its industry. One option in this area is a diagnostic developed by BCG that weighs 21 factors in assessing a company’s starting point in data and analytics capabilities and assets, backing up the assessment with extensive, continually updated benchmarks.

With this information, the company can formulate a high-level vision, which company leaders translate into a portfolio of initiatives (or use cases) to be rolled out in a logical order, on the basis of factors such as size of impact and competitive needs or opportunities. Then the company must agree upon some underpinnings of digital operations—analytics, data governance, and data infrastructure.

Creating a roadmap that outlines applications and projects to build data infrastructure and other resources needed for data-driven operations can not only make the transformation run more smoothly but also ensure that these investments pay.

Organize for Sustained Performance

As is the case with any change program, the success of a data transformation is measured by sustained results—and those will not materialize without making the company and its culture data centric. To prepare its organization for a digitalized future, the company needs to move on five fronts:

Define new roles and governance rules. A company must make clear who has responsibility for building and running new systems and maintaining specific types of data—and how to manage those people.

Build a data-first culture. To move quickly and to continually find new ways to apply data, companies should behave a bit like software development operations, embracing a test-and-learn culture that encourages experimentation, accepts—even celebrates—failure, and is always learning.

Adopt agile ways of working. The company can adopt many of the tactics of the agile method and use them in everyday operations to increase the organization’s responsiveness and adaptability. It can establish scrum teams with squads and tribes to tackle specific problems—and accelerate the pace with weekly sprints, rather than months-long efforts.

Cultivate the necessary talent and skills. The company should create an inventory of the talents and skills that its employees will need, and it should identify where the gaps are in the current workforce. Companies will need to retrain current employees, hire new talent, or use a partnership to get the right capabilities.

Consider the build-operate-transfer model. Adapted from the construction industry, this model involves creating a stand-alone organization in partnership with an outside vendor that has the expertise to run transformation initiatives.

Looking Ahead to the Finish Line

The companies that succeed in achieving data-driven transformation will be agile, pragmatic, and disciplined. They will move fast and capture quick wins, but they will also carefully plan a transformation roadmap to optimize performance in the functions and operations that create the most value, while building the technical capabilities and resources to sustain the transformation.

Transformation
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