Inside HEINEKEN’s Digital Transformation: Why Change Management Comes First?

Digital transformation in B2B is no longer a strategic experiment or a “nice-to-have.” It has become a structural requirement for staying competitive. Customers expect digital-first experiences, supply chains demand resilience, and AI is rapidly redefining what operational excellence looks like. 

The market has already moved. B2B buyers now expect digital experiences that match (or exceed) B2C standards. According to BigCommerce, 90% of global B2B buyers expect a B2C-like digital experience, including self-service ordering, real-time availability, and personalization. This applies even to complex deals: Forrester predicted that more than 50% of B2B purchases over $1 million would be completed through digital self-service channels, with digital touchpoints shaping the entire buying journey.

Few enterprises illustrate this shift better than HEINEKEN, Virto Commerce’s client. Over the past decade, the company has built one of the largest B2B digital commerce ecosystems in the consumer goods industry. Today, more than €10 billion in revenue flows through HEINEKEN’s digital platforms, and in several European markets, up to 80% of fragmented trade, including pubs, clubs, and small hospitality businesses, place orders online. 

Yet this success story exposes a paradox. Despite massive investment in platforms, cloud infrastructure, composable architectures, and now AI, most digital transformations still fail. Bain’s research suggests that only 12% of business transformations achieve their original ambition. BCG similarly reports that about 70% of digital transformations fall short of their objectives. On the people side, Prosci’s benchmarking shows that initiatives with excellent change management are 7 times more likely to meet objectives than those with poor change management, highlighting adoption and change enablement as a key success lever. 

What’s striking is that technology is rarely the root cause. Platforms generally work. Infrastructure scales. The real breakdown happens inside the organization. 

As Denis Clifford, Chief Customer Officer at Virto Commerce, puts it: 

“Only about 30% of the overall effort in a digital transformation is actually on the technology side. The rest is about people, processes, budgeting, communication, and change.” 

This is where the perspective of Jim McGregor, Head of Change Enablement for Global E-business at HEINEKEN, becomes critical. In his conversation with Denis, the focus shifts away from tools and features to a harder question: why transformation succeeds or fails at the human and organizational level. 

The conclusion is uncomfortable, but empowering. Success in the age of AI and B2B ecommerce is not decided by technology alone. It is decided by how ready an organization is to change. 

Once organizations accept that digital transformation is unavoidable, a quieter, and often more damaging, mistake tends to follow. Transformation is framed as a delivery exercise, not as a redesign of how the business actually works. 

In large enterprises, transformation programs usually look familiar. They are organized around roadmaps, milestones, budgets, vendors, and timelines. Progress is tracked through implementation status: platforms deployed, integrations completed, features shipped. On paper, everything appears to be moving forward. 

But delivery is not the same as transformation. 

As Denis Clifford (Virto Commerce) notes, many initiatives can appear successful from a delivery standpoint, with technology live and programs completed, without meaning that the business has actually changed. 

What often goes missing is a more uncomfortable question: what exactly is supposed to change in how people make decisions, do their jobs, and run the business once the technology is in place? 

This gap is especially visible in large enterprises, where transformation responsibility is frequently delegated to IT, digital, or innovation teams. The broader organization continues to operate largely as before. 

The result is a familiar pattern: 

• Modern platforms sit on top of legacy processes 

• New tools coexist with old incentives 

• Digital channels grow, while decision-making stays unchanged 

Jim McGregor from HEINEKEN describes this disconnect plainly: 

“We’re very clear about technology budgets. We’re very clear about project management. But the conversation about how people actually need to work differently often doesn’t happen early enough, or deeply enough.” 

In these situations, transformation rarely fails dramatically. Instead, it quietly loses momentum. 

Research into transformation governance shows that many enterprises over-invest in execution and under-invest in operating model change. Studies from Forrester and RSM highlight a common assumption: that new tools will naturally produce new ways of working. Without explicit changes to roles, decision rights, incentives, and accountability, the opposite tends to occur: technology reinforces existing structures rather than disrupting them. 

This explains another recurring pattern: the late arrival of change enablement. 

McGregor is explicit about the cost of this timing: 

“When change enablement comes in after resistance starts, you’re already reacting. What you really want is to understand readiness and risk before you commit to the transformation path.” 

The lesson here is not that delivery discipline is unimportant. It is that delivery without organizational redesign produces activity, not transformation. 

Once transformation is understood as a business challenge rather than a delivery exercise, the next question becomes practical: what does effective change management actually look like in large enterprises? 

From HEINEKEN’s experience, success does not come from more communication plans or additional training sessions. It comes from how early, how clearly, and how structurally change is designed into the transformation itself. 

One of the most consistent patterns in successful transformations is timing. Change enablement is most effective before solutions are locked in, not during rollout. 

Early readiness and impact assessments help organizations answer questions that technology roadmaps alone cannot: 

• How prepared is the organization to change the way it works? 

• Where is resistance most likely to emerge, and why? 

• Which parts of the business can move faster, and which need more support? 

• How much change can the organization realistically absorb at once? 

This perspective aligns with Forrester’s view that digital transformation is not a linear journey with a clear endpoint, but a state of continuous adaptation. “No tunnel, no light at the end.” 

Another defining characteristic of effective enterprise change is clear ownership. 

In large organizations, transformation often becomes everyone’s responsibility, and therefore no one’s. Strategic decisions are spread across steering committees, delivery teams, and functional leaders, while accountability for adoption remains vague. 

McGregor has seen a different model work: 

“The companies that do this well assign a senior person whose only job is transformation. A transformation director, accountable for adoption, not delivery.” 

This role sits across strategy, execution, and enablement, ensuring that success is measured not by go-live milestones, but by whether the business actually operates differently afterward. 

Many enterprises invest heavily in executive alignment and frontline training, yet still struggle with adoption. The missing link is often middle management. 

“We engage the top and the bottom, but we miss the middle management piece. And they are absolutely critical to adoption,” McGregor explains. 

Research supports this view. A peer-reviewed study published via ScienceDirect identifies middle-management resistance as one of the strongest predictors of transformation failure, largely because this layer translates strategy into day-to-day behavior. 

Without explicit engagement, middle managers are left to reconcile new digital expectations with old performance metrics, legacy processes, and unchanged incentives, which is an impossible balancing act. 

Structural separation is another quiet barrier to change. Digital initiatives are often organized as parallel units: “e-business,” “digital,” or “innovation”, while the core organization continues to operate as before. 

At HEINEKEN, this mindset is actively being dismantled. 

“We’re actually moving away from talking about e-business. It’s just the business. Digital flows through everything.” 

Practically, this means breaking down silos between IT, sales, marketing, and operations, and replacing them with hybrid operating models. One example is the creation of product teams that bridge Data & Technology (D&T) and commercial functions, ensuring that technology decisions remain anchored in real business outcomes. 

This approach aligns with governance best practices increasingly recommended by firms such as Celonis, which emphasizes embedded digital capabilities over isolated digital teams. 

Finally, successful transformations recognize that adoption cannot be driven from the top alone. 

Beyond formal leadership roles, HEINEKEN relies on change champions, trusted individuals within teams who support peers in adopting new ways of working alongside their day-to-day responsibilities. 

“You appoint people lower down the ranks as champions. They’re approachable, trusted, and help others adopt new ways of working.” 

This distributed model scales change without excessive cost and enables more meaningful tracking of adoption outcomes, such as time-to-proficiency, process compliance, and reduction in workarounds, the metrics that are often missing from executive dashboards but are critical to long-term transformation success. 

While digital transformation ultimately succeeds or fails at the organizational level, technology still plays a critical enabling role, especially for global enterprises. The question is not whether technology matters, but how it is designed and introduced into the business. 

For companies like HEINEKEN, scale and diversity fundamentally shape technology decisions. Operating across 74 countries, the business must support different regulatory environments, routes to market, and customer behaviors, without fragmenting the core platform. 

In this context, rigid, one-size-fits-all systems quickly become constraints rather than accelerators. 

As Jim McGregor explains: 

“We used to have to customize the technology to fit the business. Now it’s about having a small core, platforms around it, and apps on top — much more flexible.” 

This “small core with platforms and apps” model, often described as a Digital Backbone, reflects a broader shift in enterprise architecture. Instead of forcing the business to conform to monolithic systems, leading organizations build composable stacks that balance global consistency with local adaptability. 

This is precisely why composable ecommerce platforms, like Virto Commerce, resonate with complex B2B enterprises. Rather than prescribing a fixed operating model, composable platforms allow the business to define its own structure and evolve it over time, integrating with existing systems and adapting to market-specific needs without replatforming. 

Architectural flexibility becomes even more critical with the rise of artificial intelligence. 

AI is often positioned as the next major inflection point in enterprise transformation. Yet McGregor consistently urges realism over hype: 

“Right now, what we’re seeing are pockets of real value, not full business model transformation yet.” 

In practice, most B2B AI initiatives today are incremental rather than disruptive, focused on areas such as: 

• improving data completeness and quality, 

• automating order capture from unstructured inputs, 

• enhancing forecasting and operational efficiency. 

These use cases deliver real benefits, but they rarely redefine how the business fundamentally operates. 

The limiting factor is not AI technology itself, it is organizational and data readiness. 

McGregor is blunt about what must come first: 

“You need to get the boring stuff right first. Data hygiene. Data sets. Process mapping.” 

Without clean data, clearly defined processes, and strong governance, AI simply accelerates existing inefficiencies. This is where composable architectures again matter: they make it easier to improve data flows, swap components, and evolve processes without locking the organization into brittle dependencies. 

This context also explains McGregor’s skepticism toward overly confident AI consultants: 

“When a consultant shows up and says they have all the answers, I don’t believe they do. Nobody really knows yet.” 

Rather than chasing definitive AI roadmaps, the most effective organizations adopt a test-and-learn mindset: experimenting with targeted use cases while steadily strengthening their foundations. 

In one of the most revealing moments of the conversation, Denis Clifford reframes the AI discussion through a historical lens: 

“A hundred years ago, the shopkeeper knew you, gave you credit, suggested products. AI just allows us to do that at scale.” 

Seen this way, digital transformation, including AI, is not a rupture from the past. It is an evolution of long-standing commercial principles: growing revenue, operating efficiently, and delivering better customer experiences. 

Technology accelerates these goals. It does not replace them. 

The patterns visible in HEINEKEN’s digital journey mirror what we see across Fortune 500 transformations. These are not isolated successes or failures, but recurring structural choices that determine whether large-scale transformation delivers lasting impact or stalls after early progress.

High-performing enterprises treat digital transformation as an enterprise mandate, not an IT initiative. Despite global spending reaching $2.5 trillion in 2024 and projected to hit $3.9 trillion by 2027, only 30–35% of transformations meet their objectives. Weak governance and fragmented leadership are consistently cited as primary causes of failure. 

Organizations that succeed establish cross-functional governance with shared accountability across business, technology, and operations, ensuring scale becomes an advantage, not a liability. 

Another consistent pattern is the move away from “big bang” platform replacements toward modular, composable architectures. High-profile failures, such as Target’s Canadian expansion, which resulted in over $2.1 billion in losses, illustrate the cost of inflexible systems at scale. 

By contrast, enterprises like HEINEKEN adopt a “small core with platforms and apps on top” model, supporting flexibility across the operating countries without fragmenting the business. Composable platforms, including Virto Commerce, enable this incremental approach by allowing systems and operating models to evolve without repeated replatforming. 

Across Fortune 500 case studies, transformation success correlates more strongly with change enablement than with technology choice. Failure rates of 70–90% are most often linked to cultural resistance, misaligned incentives, and insufficient support for middle management. Gallup data reinforces this gap: only 27% of employees strongly believe in the value of major organizational changes. 

Organizations that invest early in leadership alignment, middle-management engagement, and adoption metrics consistently outperform those that rely on late-stage training and communication. 

Across industries and geographies, Fortune 500 leaders converge on the same conclusion echoed by Jim McGregor and Denis Clifford: enterprise digital transformation succeeds when governance, architecture, and change enablement are designed together. Technology enables scale, but only organizations built to absorb change can turn it into lasting advantage. 

To summarize, based on HEINEKEN’s & Virto’s experience and consistent patterns across large enterprises, the path forward is not about doing more, it’s about doing a few critical things differently.  

1. Redefine What “Success” Means After Go-Live  

Stop treating launch dates as success markers. Instead, track: 

• sustained usage and adoption, 

• time-to-proficiency for teams, 

• retirement of legacy processes. 

If the business operates the same way 6 months after launch, transformation hasn’t happened. 

2. Lock the Operating Model Before You Scale 

Before expanding platforms or AI initiatives, make 3 things explicit: 

• who owns outcomes (not delivery), 

• how decisions are made post-implementation, 

• which incentives and KPIs will change. 

Without this clarity, new technology only accelerates old behaviors. 

3. Make Change Enablement a Leadership Responsibility 

Treat change as a leadership capability, not a support function: 

• sponsor change visibly and consistently, 

• make trade-offs explicit when priorities conflict, 

• engage middle management as owners, not messengers. 

Fund change early, not as a rescue effort once resistance appears. 

4. Enforce Readiness Gates for AI 

Move fast on AI only where foundations are ready: 

• clear data ownership and quality standards, 

• consistent processes across teams or regions, 

• governance that separates experimentation from scale. 

AI will amplify what already exists, strong or fragile. 

5. Institutionalize Learning, Not Certainty 

Avoid searching for perfect transformation playbooks. 
Instead: 

• test in controlled environments, 

• measure real impact, 

• adapt continuously. 

The strongest organizations build learning into how they operate, while maintaining discipline around governance and outcomes. 

The Shift That Matters Most 

Digital transformation is no longer a program to complete or a technology wave to catch. It is a permanent capability, the ability to adapt how the business operates, decides, and evolves. 

Leaders who treat it that way move beyond transformation theater toward durable advantage.

HEINEKEN’s experience, viewed through the lens of Fortune 500 transformation patterns, reinforces a critical insight: technology enables transformation, but organizations determine its outcome. Success depends on governance that aligns business and technology, operating models designed for continuous change, and leadership that treats change enablement as a core capability rather than a support function. 

AI will only accelerate this dynamic. It will reward organizations that have invested in data quality, process clarity, and decision ownership — and expose those that have not. In this environment, transformation is no longer something enterprises “do.” It is something they become capable of doing repeatedly. 

For enterprise leaders, the imperative is clear: move beyond transformation programs and toward transformation readiness. 

Virto Commerce goes beyond standard PaaS. Its composable and decomposable architecture gives B2B companies the power to shape, scale, and govern their digital commerce infrastructure without compromise, whether you're operating in a highly regulated industry, managing multi-vendor ecosystems, or supporting multiple business models across regions. 

• Watch the full Thought Leader Session with Denis Clifford (Virto Commerce) and Jim McGregor (HEINEKEN) to hear these insights in their original context. 

• Explore our analysis of enterprise transformation patterns across Fortune 500 organizations in Enterprise Digital Transformation: Lessons from Fortune 500. 

• Learn how composable, business-led commerce platforms support organizational change, not just technical delivery, with Virto Commerce.