A different view by Jaime Porta

Why technology investments alone rarely deliver the transformation companies expect.

Over the years, I’ve been involved in several digital transformation initiatives, from implementing CRM solutions and developing digital sales channels to introducing new platforms designed to improve how organizations operate. Despite the differences in technology, industry, and business objectives, I’ve noticed a recurring pattern: companies are often much more comfortable investing in new technology than reconsidering how they actually work.

It’s understandable. Technology projects are relatively easy to define, at least on paper. They have budgets, timelines, deliverables, and implementation partners. Management can approve an investment, establish a steering committee, and monitor progress against milestones. A new CRM goes live, an eCommerce platform becomes available, or an automation solution starts processing transactions. From a project perspective, these are important achievements, and there’s certainly nothing wrong with celebrating them.

The problem starts when we confuse successful technology implementation with successful business transformation.

I’ve seen organizations invest considerable resources in modernizing their technology landscape while leaving their internal processes, responsibilities, and decision-making structures largely untouched. Sometimes the new systems even introduce additional complexity because they have to accommodate the same organizational limitations that existed before. The technology may be more modern, but the business continues operating in much the same way.

This raises a question that I believe deserves much more attention at the executive level: Are we transforming the way our business operates, or are we simply upgrading the technology that supports it?

The Comfort of Technology Projects

One reason companies approach digital transformation primarily through technology is that it’s easier to organize around something tangible. Replacing an ERP, implementing a CRM, or launching a new digital commerce platform can be translated into a project with clear boundaries. There will be difficult decisions along the way, of course, but at least everyone has a reasonable understanding of what is being delivered.

Changing an operating model is considerably less straightforward. It often means questioning responsibilities that have existed for years, redesigning processes that different departments have developed independently, or reconsidering who has the authority to make certain decisions. These discussions can become uncomfortable because they affect organizational boundaries, established habits, and sometimes the influence of individual teams.

Consider a company implementing a new CRM to improve sales performance. The project team might spend months defining customer data structures, integrating systems, migrating information, and developing dashboards. Once the platform is available, sales representatives receive training and management expects better visibility into the pipeline.

But what happens if sales teams continue managing opportunities in spreadsheets because the CRM doesn’t reflect how they actually sell? What if marketing and sales disagree about lead ownership, or different countries apply completely different qualification criteria? And what if management continues measuring performance using the same indicators that encouraged those behaviors in the first place?

The CRM may work perfectly from a technical perspective, yet the business benefits remain limited. Not because the technology was necessarily wrong, but because the organization never fully addressed the operating decisions required to make it valuable.

Technology Changes Faster Than Organizations

Modern technology gives businesses capabilities that would have been difficult to imagine only a few years ago. Companies can connect customer interactions across channels, automate complex workflows, provide real-time information to their sales teams, and increasingly use AI to support analysis and operational decisions.

However, organizational structures don’t evolve at the same speed. Departments still have their own objectives, budgets, priorities, and reporting lines. Processes often reflect historical decisions rather than current business needs. Data ownership remains fragmented, and responsibilities tend to be defined around functions rather than the customer journeys or business outcomes the organization wants to improve.

I’ve encountered this challenge particularly in initiatives involving multiple business functions and geographical markets. A digital platform may be intended to standardize how a company operates globally, but each region has developed its own practices, exceptions, and interpretations of what the business requires. Some differences are justified by local market conditions, regulatory requirements, or customer expectations. Others exist simply because nobody has challenged them for years.

The difficulty is not deciding whether standardization is desirable. Most executives would agree that unnecessary complexity should be reduced. The real challenge is determining which differences provide genuine business value, which ones can disappear, and who has the authority to make those decisions.

Too often, these questions reach the project team when implementation is already underway. At that stage, technology specialists are expected to resolve what are fundamentally organizational disagreements, usually under pressure to protect the timeline. The easiest compromise is frequently to configure the system to accommodate everyone, even when doing so perpetuates complexity.

This is how companies sometimes end up rebuilding their old operating model inside a new platform, at considerable expense.

The Operating Model Is Where Transformation Happens

When I talk about an operating model, I’m not referring only to an organizational chart or a collection of documented processes. I mean the practical way a company gets things done: how teams collaborate, how information moves, how decisions are made, who owns the outcome, and what behaviors the organization encourages.

Technology is an important part of that model, but it is only one component. Its value depends heavily on the surrounding business environment.

Take B2B eCommerce, a topic I’ve explored in The Hidden Complexity Behind B2B eCommerce. Launching an online channel may appear to be a relatively straightforward commercial initiative, but the implications extend well beyond the website. Product information needs to be reliable and maintained by someone. Pricing conditions must be consistent with commercial agreements. Customer-specific arrangements may require coordination between sales, finance, and operations. Order processing, logistics, and customer support need to work together to deliver the experience promised through the digital channel.

The platform brings all these dependencies into focus, but it doesn’t automatically resolve them.

A company can create an excellent online purchasing experience from a technical standpoint and still struggle because internal responsibilities are unclear or teams continue operating independently. In that situation, fixing the interface might improve usability, but it won’t solve the underlying business problem.

The same applies to broader omnichannel strategies, something I’ve discussed previously when exploring why omnichannel is no longer optional. Companies often invest in connecting physical sales, digital channels, customer service, and marketing, yet the teams responsible for those interactions continue being evaluated against separate targets. If a salesperson perceives online orders as lost revenue, or if marketing optimizes lead volumes without considering conversion quality, the technology is unlikely to produce the collaboration that management expects.

In my experience, some of the most valuable transformation discussions happen when we stop talking about system functionality and start discussing how the business should operate once the technology is available.

Those conversations are not always easy, but avoiding them usually makes the implementation more difficult and the long-term results less convincing.

The Missing Link Between IT and the Business

There is another recurring issue that deserves attention: the way organizations distribute responsibility for digital transformation.

In many companies, IT is expected to deliver the technology, while business departments provide requirements and eventually become users of the solution. This arrangement can work reasonably well for clearly defined technical projects, but it creates limitations when the objective is to change how the organization operates.

Business stakeholders sometimes approach transformation initiatives as customers of an internal technology provider. They explain what they need, approve proposed solutions, and expect IT or an external partner to deliver the desired functionality. When the project becomes difficult, discussions often focus on scope, resources, priorities, or implementation delays.

What is sometimes missing is a clear business owner who is accountable not only for delivering the solution, but also for achieving the intended operational and commercial improvements.

I’ve always considered this distinction particularly relevant in digital sales initiatives. Implementing a platform and improving sales performance are related objectives, but they are not interchangeable. The first can be measured through implementation milestones, system availability, and technical quality. The second depends on adoption, process effectiveness, customer behavior, commercial execution, and many other factors that extend beyond IT’s direct responsibility.

This doesn’t mean IT should have less influence. Quite the opposite. Technology teams need to participate in business decisions early enough to challenge assumptions, explain architectural implications, and identify opportunities that business functions may not recognize. At the same time, business leaders must remain accountable for the processes, people, and commercial outcomes their technology investments are supposed to improve.

The strongest transformation initiatives I’ve experienced are those where technology and business teams share a common understanding of the desired outcome, even when their responsibilities remain different.

AI Is Making This Even More Relevant

Artificial intelligence is bringing this discussion back with renewed urgency. As I explored in The AI Race Is Becoming an Execution Race, the competitive advantage increasingly comes from integrating technology into business operations rather than simply having access to the latest capabilities. Organizations are experimenting with AI assistants, automation tools, intelligent agents, and increasingly sophisticated ways of using data to support decisions. There is significant potential, and I believe many of these capabilities will fundamentally change how companies operate.

However, I’m also seeing a familiar risk: the temptation to introduce a new technology before deciding what needs to change in the business.

Giving employees access to an AI assistant can certainly improve individual productivity. Automating a repetitive activity may reduce processing time, and introducing AI into customer service or sales operations can create meaningful opportunities. But these improvements don’t necessarily translate into broader organizational transformation if the surrounding processes remain unchanged.

Imagine a company introducing AI to support sales forecasting. The system can analyze historical information, identify patterns, and produce predictions much faster than traditional methods. Yet if opportunity data is unreliable, regional teams use inconsistent definitions, and management continues making decisions based primarily on individual judgment, the impact of the technology will be constrained.

The interesting question is not simply whether AI can generate a better forecast. It’s whether the organization is prepared to change how forecasting information is produced, validated, interpreted, and used in commercial decisions.

The same logic applies to AI agents. Their potential becomes much more interesting when they are designed around complete business workflows rather than isolated tasks. But that also requires organizations to define decision rights, establish appropriate controls, clarify accountability, and reconsider how people and systems collaborate.

In other words, AI may accelerate the need to rethink operating models rather than eliminate it.

Transformation Requires Decisions That Technology Cannot Make

This brings us to leadership.

As I discussed in Sustainable Digital Transformation: Building Change That Lasts, organizational change requires strong foundations and sustained leadership commitment. If digital transformation requires changes to processes, responsibilities, incentives, and organizational behavior, it cannot be treated as a technology program delegated entirely to IT. These are management decisions, and many of them require coordination across functions that have different objectives and competing priorities.

Senior leadership needs to define what the organization is trying to achieve beyond the implementation itself. Are we trying to improve customer experience, reduce operational complexity, accelerate commercial growth, or create a more scalable business? These objectives are often connected, but they can lead to different choices when trade-offs become necessary.

For example, a global company may want to standardize its commercial processes to reduce complexity. At the same time, regional sales teams may argue that their markets require considerable flexibility. Both perspectives can be reasonable. The leadership challenge is deciding where standardization creates value, where flexibility is justified, and which principles should guide exceptions.

No implementation partner or software platform can make that decision on behalf of the business.

Leadership also needs to create the conditions for departments to work toward shared outcomes. If a transformation initiative requires sales, marketing, finance, operations, and IT to collaborate, but each function continues being rewarded exclusively for its own performance, expecting a common platform to overcome those divisions is optimistic.

This is why I believe digital transformation needs stronger executive ownership, not necessarily more steering committees or governance layers. What matters is whether someone has the authority and willingness to resolve cross-functional conflicts, challenge established practices, and keep the organization focused on business outcomes rather than simply completing the project.

Success Should Be Measured After Go-Live

One of the most revealing moments in any transformation initiative comes after the implementation team has completed its work. The system is live, the project is formally closed, and responsibility moves into daily operations.

At that point, a different set of questions becomes relevant. Are employees actually using the new capabilities? Have processes become more efficient, or have we simply added another layer of work? Are customers experiencing an improvement? Has the investment contributed to better sales performance, lower operational costs, or greater scalability?

These questions should not appear for the first time after go-live. They should influence the business case, project design, and governance model from the beginning.

Of course, not every benefit can be measured immediately. Organizational change takes time, adoption can be uneven, and some investments provide capabilities whose value emerges gradually. But companies should still distinguish between delivering technology and realizing business benefits, with clear accountability for both.

I would also argue that transformation is rarely finished when a platform goes live. Once people begin working with new capabilities, they discover additional opportunities, identify limitations, and develop a better understanding of what needs to change. Organizations that treat implementation as the beginning of continuous improvement are more likely to capture long-term value than those that consider the project completed once the system becomes operational.

A Different Starting Point for Digital Transformation

Looking back at the transformation initiatives I’ve participated in, I believe one of the most useful changes in perspective is also one of the simplest: start by discussing how the business should operate, rather than which technology should be implemented.

That doesn’t mean technology selection is unimportant or that organizations need to redesign everything before investing. In practice, technology and operating model decisions influence each other, and transformation is an iterative process. New capabilities can reveal opportunities that were not obvious initially, while operational constraints can determine which technological solutions are realistic.

But the direction matters.

If the starting point is exclusively the technology, the organization risks adapting a new platform to old ways of working. If the starting point is the desired business outcome, technology becomes a means of enabling a broader change.

For executives, this distinction has significant implications. Digital transformation should not be evaluated only as a portfolio of investments, platforms, or implementation programs. It should be understood as an ongoing management responsibility involving strategic choices about how the organization creates value, coordinates its resources, and responds to changing market conditions.

And perhaps that’s the most important lesson I’ve taken from working on digital transformation projects: the difficult part is rarely getting technology to do something new. It’s getting the organization to work differently because of it.

Ultimately, digital transformation is not just a technology decision. It’s an operating model decision, and leadership needs to treat it that way.