Raiders of Every Industry: The Journey to Digital

Companies have a choice today. They can be the disrupted or the disruptor.

Every industry will be disrupted in the coming years. None are safe. The safer they seem, the more susceptible they probably are. In fact, only two things stand a chance of protecting incumbents:

But for those to matter, the company has to become truly digital. What do I mean by that?

Becoming digital is a journey with three distinct steps that a company would typically take in order, at least within a given business unit. The steps are: data transformation, data science transformation, and digital transformation.

Each step requires attention to strategy, technology, organization, and culture. Fortunately, the changes are gradual at first and then expand.

Data Transformation

The first stage, Data Transformation, might not feel particularly transformative:

So, what has really changed? This stage is about defining the core assets that create value for the enterprise, and it’s about discovering and governing that data without necessarily expecting — or forcing — upheaval. Data governance in particular is a greater lever than most of us realize. It means establishing policies that preserve privacy and protect data while making access to data frictionless for those who need it.

Strategy is important here. You’re focusing on understanding what data is available and how it can help existing stakeholders act more efficiently and with greater confidence.

At the same time, you’re setting up your data science team or giving your existing data science team more secure, self-service access to data and a wider mandate to gather and explore the company’s data.

Data Science Transformation

With the next stage, data science begins to lift off:

Here, the key changes come from letting the data science team discover — and openly discuss — ground truth for the business. What does the data actually have to say? How do you begin to get a 360° view of customers, products, talent, and the company at large? Where do those 360° views offer the company the chance to disrupt its own assumptions — before they’re disrupted by new competitors?

You’ll also need to ask whether the culture is ready to welcome the new ideas. If you’ve finessed the Data Transformation phase, the organization will already value and trust the data science teams and their processes. Force-feeding your insights to the organizing is a good way to jeopardize the entire transformation that you’re trying to enact.

Digital Transformation

The third and final stage is where the flywheel really begins to spin, but in the process, you’re likely to see fundamental changes to how you do business, including what you offer, how you offer it, and to whom:

Customers will tend to get more and more important as the transformation proceeds. You’ll know more about who they are and how to build connections with them that endure even through the change.

What’s Next

In follow-on posts, let’s look more closely at each stage and the details of what you’ll need to be successful. In the meantime, consider the table stakes necessary to get your transformation underway. For you to be successful, every tool you use must:

Start there and stay tuned for more detail about Data Transformation.



IBM Data Science in Practice is written by data scientists for data scientists to gain hands-on and in-depth learning and to read about inspirational applications and conceptual understanding for challenging topics in the field. Discuss and network:

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Seth E Dobrin, PhD

Vice President and Chief AI Officer || Leader of exponential change Using data and analytics to change how companies operate || Opinions are my own