Digital Transformation: Beyond Technology

In 2016, I was fortunate to launch the Digital Hub, an organization with which Ferrovial aimed to drive the Digital Transformation of its businesses. I came from leading IT departments, and the first thing I had to do was break many biases from my previous life and open my mind.

Soon, the term Digital Transformation began to discomfort me due to its confusing nature and the number of consultants trying to exploit it with limited value contributions. Also, because of its project-centric approach rather than seeking a holistic approach.

There are some frameworks that help understand and analyze the complexity of a transformation (digital or not). One well-known model is McKinsey’s 7S model, which aligns seven interdependent elements of an organization — strategy, structure, systems, values, style, staff, and skills — to achieve a comprehensive and successful digital transformation. Without wanting to focus on this model, it is interesting to see the holistic vision in which systems (or technology) is just one piece.

Now, after almost a decade dedicated to this, I would like to reflect on it.

The Myth of Digitalization

Digitalizing, digitally transforming, and digitally reinventing are not the same.

• Digitalization is converting analog to digital by transforming documents, processes, or physical products into digital formats.
• Digital transformation is integrating technology into the organization to improve efficiency and customer experience by redesigning processes, adopting new tools, and changing the work culture.
• Digital reinvention is creating new business models or ways to generate value through technology and involves questioning the existing model and leveraging technologies to innovate radically.

In summary: the first refers to operational efficiency, the second to organizational change, and the third to strategic innovation supported by technology. If you want more detail on this reflection, you can read my post What is Digital Transformation?

In the past, we mixed and confused these concepts. We perverted the ideas, and when executives hear “digital transformation,” the mind goes to the cloud, ERP, CRM, or an APP. Fortunately, I believe that by 2025, we will have moved past that stage. The concept is clearer now, especially because the concepts of Artificial Intelligence and Agents have absorbed everyone’s attention and are now at the center of confusion.

In 2016, it was common to hire transformation projects from leading consulting firms that implemented tools often with little impact. Our approach was different; we focused on equipping the organization with new capabilities and generating impact through them. We didn’t reach that approach on the first day and made mistakes. We pivoted to achieve greater impact by leveraging those areas and businesses that were “early adopters,” generating interest from those who were not.

But as humans, we do not learn. Now, with Artificial Intelligence, the same thing is happening. I see companies investing in AI, incorporating agents that do not transform but achieve apparent efficiency. Through them, I can draft a report or write this post faster, more attractively, and longer. Thus, whoever reads it has to spend more time, or not. Can’t the reader use an agent and read a summary? That is apparent efficiency.

One says: “How many agents do you have?” Another responds: “2 (one that writes and another that reads).”

This example illustrates the difference between metrics that matter and vanity metrics, which I will discuss later.

The Four Pillars of Real Transformation

But, let’s return to the topic of the post: Digital Transformation and the pillars on which it rests.

Purpose: The Reason for Being

A transformation without a purpose makes no sense, and that purpose must be part of the business strategy: what do we want to achieve with this transformation?

That purpose may be related to improving operations, generating revenue, achieving better market positioning, or enhancing our customers’ valuation. It may also stem from the business model itself: Is it still relevant at this moment? Are our competitors the same as a few years ago? Many companies are no longer competing with companies in their sector but with startups or corporations that have reinvented their market positioning through the opportunities opened by the digital world.

Transforming the business model involves exploring how technology can create new sources of revenue, not just optimize existing ones. This could mean shifting from selling products to offering services, creating platforms that connect multiple actors in an ecosystem, or monetizing the data and insights that the organization generates in its daily operations. But this does not apply to all organizations; the purpose should not always be reinvention but must align with the reality of the company and the market in which it operates.

Digital business models have distinctive characteristics. They tend to have marginal costs close to zero, benefit from network effects (where value increases exponentially with each new user), and can scale in ways that would be unthinkable in traditional models.

Culture: The Key

Organizational culture is the second pillar, and it is no less important. It is the most difficult to transform because it is also the most human: it cannot be bought and is not included in any software package. However, without a culture that embraces experimentation, continuous learning, and tolerance for failure, any digital transformation effort will be impossible.

Any transformation requires organizations to shift from a mindset of “we do things this way because we have always done them this way” to one of “how could we do it better?”

In the case of Digital Transformation, it involves developing fundamental capabilities:

• Cognitive agility: the ability to quickly take opinions from data and change one’s mind when the data suggests a different path.
• Cross-functional collaboration: breaking down the departmental silos that characterize traditional organizations.
• Customer orientation: where every decision is evaluated from the perspective of the value it brings to the end user.
• Decision-making: decisions do not flow exclusively from top to bottom. In addition to “top-down,” team autonomy is encouraged, controlled experimentation is valued, and the failure of a project is accepted as a means to achieve the necessary learning.

This is a particularly difficult transition for organizations with traditional hierarchical structures, where seniority and position have historically been valued more than the ability to innovate.

The Customer: The Extraordinary is the New Norm

The third pillar recognizes an uncomfortable truth: today’s customers compare your service not with your direct competitors but with the best digital experience they have had, regardless of the sector. If they can order a taxi with a “click” on their mobile or receive their purchase at home in 2 hours, what can they expect from an onboarding process?

This expectation that the extraordinary is the new norm applies to customers but also to employees. When competing for talent, these “little things” can make a difference.

Our customers and employees expect:

• Immediacy: they expect answers and solutions now, not tomorrow.
• Personalization: each interaction should recognize the individual customer’s history and preferences.
• Consistent omnichannel: an interaction on mobile can continue on a computer and finish in the physical world without friction or repetition.
• Excellence: it is not enough with the above; for it to be extraordinary, the experience must be excellent. Seamless.

Technology and Data: The Means

Finally, we arrive at where many times the journey begins, although, as you can see, technology and data should not be the purpose but the means to achieve it.

Technologies have some common characteristics and others that differentiate them, but I have always found the concept of their cumulative effect interesting. Technologies cannot be viewed in isolation; their impact is greater when combined appropriately. For example, with IoT devices (“Internet of Things”), we are capturing information from reality, but if we do not have AI models capable of interpreting it or suggesting actions, its value is limited. This has the positive effect that the impact of technologies increases with their combination but the pernicious effect that once a technology is incorporated, removing it is often costly because it has created dependencies with others and with the users themselves.

Data is the new oil, but raw, unrefined oil has little value. Organizations need to develop analytical capabilities that turn data into actionable insights. This involves building modern data infrastructures, “data lakes,” or “data meshes,” probably in the cloud. Again, we should not confuse the necessary data culture with the culture of the “data lake.” Having data that is not used is nothing more than a digital (and costly) version of Diogenes’ Syndrome.

Artificial Intelligence is the most advanced way to refine that oil, which is structured and unstructured data. But let us not forget that the value lies in the action taken based on the data and models. It is also crucial to understand that AI is not magic. It requires clean and abundant data, clearly defined objectives, and a continuous process of training and refinement.

Without intending to provide an exhaustive review of technologies, I will mention cloud technology, which has democratized access to computational capabilities that were previously available only to a few, and cybersecurity, as organizations become more digital, they also become more sensitive to potential attacks as their attack surface expands.

Metrics that Matter

Measuring seems simple, but it is not. One of the common mistakes in digital transformation is measuring the wrong metrics. These metrics are often referred to as vanity metrics. It is easy to fall into the temptation of measuring the “number of applications migrated” or the “percentage of digitized processes.” These activity metrics provide information on progress but say nothing about the advancement towards the established purpose.

The metrics that truly matter are those that connect with strategic objectives. Sometimes they are not measured out of ignorance, and other times because it is not possible. In the latter case, metrics are established that are the best proxy for those we would like to achieve, even if they may seem vanity metrics.

Digital maturity indicators provide a useful framework for assessing progress. They evaluate dimensions such as the organization’s digital strategy (Is there a clear vision?), culture and capabilities (Do we have the right people and mindset?), organization (Are our structures aligned with digital objectives?), and technology (Do we have the necessary infrastructure?). Each dimension can be evaluated at levels ranging from initial or ad-hoc, through defined and managed, to optimized.

If our work is the creation of digital products, the most revealing metrics are probably iteration speed and delivered value. In my days at JCL, this took months or even years. Now these cycles last weeks or days. These metrics implicitly capture whether we have the right processes, culture, and technology.

The Balance: Quick Wins vs. Deep Transformation

Earlier, I spoke of transformation, but that requires gaining the trust and support necessary for that transformation. I also mentioned “early adopters,” as those who embrace transformation before their peers. Thanks to them, transformation shows value and gains credibility. This demonstration of value requires “Quick Wins” that visualize the long-term impact through short-term results.

This creates one of the most interesting tensions in the process: the need to show results while building the capabilities that will take longer to materialize their value. This tension is real and must be managed.

On one hand, if we only pursue “quick wins,” low-risk projects that show results in a few weeks, we run the risk of staying on the surface. On the other hand, if we only focus on the long-term vision, building the perfect platform, or waiting to have all the data integrated before doing anything, we risk losing credibility and the organization’s patience.

The answer is not to choose one or the other but to balance between both. Each feeds back into the other.

Final Reflection

Digital transformation represents a profound change in how organizations operate. It is not about adopting technology for the sake of keeping up but about rethinking how we create value and how technology helps us do so.

The most successful organizations are not necessarily the largest or those that invest the most in technology. They are those that understand that Digital Transformation is a cultural and strategic change enabled by technology. They are the ones that intelligently balance short-term results with long-term capability building. And they are the ones that accept that digitally transforming is not a destination but a continuous way of evolving and adapting.

There is no one-size-fits-all recipe, but there is also no alternative.

Best of You

Foo Fighters is that band that should never have existed because it was formed by the supposedly least qualified member of Nirvana. Years later, they have continued to create small gems like this Best of You from 2005.