Why Digital Transformations Keep Failing and What 25 Years Taught Me About Getting It Right

Worldwide spending on digital transformation is expected to reach $4 trillion by 2027. 

Yet studies from McKinsey, Bain, and Forbes consistently put the failure rate of these projects somewhere between 70 and 88 percent. In the US alone, more than $30 billion is wasted on software annually. Depending on which report you read, the number shifts slightly. The reason behind it does not.

I have been leading digital transformations for 25 years, across industries, geographies, and organizational sizes. While the tools have changed beyond recognition in that time, the failure pattern has remained consistent. Time and again, what derails a transformation comes down to the same factors: people, culture, and a leadership approach that treats the human side of change as an afterthought.

That is the problem this piece talks about, and what needs to change to put people at the center of transformation.

The project from my early career that changed how I think

Early in my career as a Managing Director at a consulting firm, I took on an assignment that I would carry with me for the next two decades.

The client was a large retail company in the United States, operating both online and in stores. The task was to convert a suite of core business applications from a mainframe environment written in COBOL to a modern client-server architecture written in C++. 

We approached the project as a pure technology exercise. Our focus was on the code: re-engineering it, rewriting it, and modernizing the architecture. Treating it as a business transformation never entered our thinking. We did not bring in the people who understood why the COBOL code had been written the way it had. We did not map the legacy workflows or interrogate the business logic embedded in decades of institutional knowledge. We assumed that the engineers who understood the technology also understood the organization. This assumption proved incorrect, and in hindsight, reflected blind spots on both sides. 

The consequences were predictable, though they did not feel that way at the time. The re-engineered applications failed user acceptance testing. The business users, who had never been meaningfully involved in the process, reacted with frustration and resistance. The project ran over budget and missed its delivery timelines, and because we had structured the engagement on a fixed-bid basis, the financial loss landed squarely on my business line, impacting the P&L of a publicly traded firm.

We knew the technology, but we failed because we refused to see the project as something that involved people, and our inability to recognize the knowledge and buy-in we needed from the humans at the center of it.

That experience has stayed with me ever since, and it is precisely why I no longer approach transformation as a primarily technical discipline.

Why tech keeps failing: three patterns I keep seeing

Over the years, I have watched different organizations, different industries, and different technologies produce the same outcome for the same underlying reasons. There are three I encounter more than any others:

1. Cultural resistance

When new technology does not feel safe, understood, or valuable to the people expected to use it, they do not use it. Employees gravitate toward established methods they trust, and when training and support are insufficient, that instinct only deepens. 

For example, a 2025 Workplace Tech Resistance report by Yooz found that 14 percent of employees outright refuse to use new workplace tools, while 39 percent identify as reluctant users. Organizations that do not invest in bringing their people along through the transition will consistently find that even well-selected technology fails to take root.

2. Digitizing dysfunction

I define digitizing dysfunction as the practice of implementing new technology onto legacy, inefficient, or poorly designed processes without first addressing their underlying flaws. When an organization’s processes are fragmented, poorly designed, or built around outdated assumptions, new technology will only amplify those problems at greater speed and scale. 

Research shows that employees face at least two IT-related issues per week, collectively wasting nearly 50 hours per year in environments that were never properly prepared to receive the technology in the first place.

3. Shiny Object Syndrome

We are surrounded by technology, and it has accelerated the need for immediate gratification and solutions. Boards want to see innovation. Leadership teams feel pressure to adopt the latest platforms. The result is that organizations acquire new tools before they have built the foundations to support them. The training, data strategy, and process redesign that determine whether those tools will be used are overlooked entirely.

What compounds this further is the absence of a people-centric narrative, a clear explanation of the why behind the change. Without it, stakeholders disengage early and adoption rates remain low. 

The pivot - a human-centered framework that actually works

Identifying what goes wrong is necessary, but it is not sufficient. I believe that the organizations that get this right share four common characteristics. These traits are behaviors and choices that leaders make consistently before and during a transformation. 

1. Culture first, tools second

In most organizations, the transformation conversation begins with the technology decision: which platform, which vendor, which architecture. The culture conversation, if it happens at all, follows as a secondary-stage concern.

A culture that does not support agility, collaboration, and psychological safety will struggle to absorb any technology placed on top of it, regardless of how well that technology has been configured. Shared values, cross-functional trust, and a genuine appetite for learning are the structural conditions that determine whether the tools will be adopted and sustained over time.

2. Empathy in design

Most organizations will tell you they are customer-first. Fewer can tell you what it feels like to be the end user of the systems they are implementing. What is the cognitive load? What are the friction points in the daily workflow? What does the person sitting at that screen need the technology to do for them?

These questions matter more than any feature list. Technology that is designed around the user's real experience is technology that gets used. Empathy in design is a strategic discipline that requires leaders to spend time with the people closest to the work before any implementation decision is made.

3. Leadership as enablers

There is a version of leadership in transformation that measures success almost entirely on system go-lives, project milestones, and delivery timelines. While these indicators have their place, they represent only part of what effective transformation leadership requires.

Leaders who drive successful transformation understand that their primary job is to enable human capability. That means removing blockers, creating psychological safety, ensuring teams have the context they need to make good decisions, and staying close enough to the work to recognize when people are struggling. Shifting focus from output toward outcomes is one of the most underestimated changes a leader can make.

4. Purpose-driven change

When a transformation is connected to a clear, compelling narrative that explains what is changing and why it matters, employees have something to orient around beyond the disruption of the transition itself.

A colleague of mine, Giles Lindsay, a technology executive and an award-winning author of The Adaptive Leader, arrives at the same conclusion from a different angle. In his most recent piece, he draws on MIT research showing that 70 percent of AI implementation challenges are rooted in people and process issues. The presence of a great, purpose-driven change is what closes the gap between a transformation that is announced and one that is embraced.

The cost of ignoring the human element

In my opinion, when technology is deployed without cultural alignment, employees frequently experience increased workloads, heightened anxiety, and a sense of being inadequately supported through the transition. These conditions ultimately lead them to quietly ignore or abandon the very tools the organization has invested in.

A Gartner survey found that 56 percent of organizations experience a high degree of regret over their largest technology purchases within the last two years, most linked to difficulties encountered during implementation when teams had not been adequately prepared for the change. These costs are a predictable outcome of underinvesting in the human side of transformation.

The strategy has always been the people

The tools available to organizations today are more powerful, more accessible, and more sophisticated than anything I worked with when I started leading transformations decades ago. However, the failure rate has remained roughly the same throughout. 

Transformation succeeds when leaders make a deliberate choice to treat the human element as the foundation on which everything else is built. This means establishing culture before selecting tools, understanding the user experience deeply, and empowering people throughout the process.

This work is among the most disciplined and consequential a leader can undertake precisely because it cannot be automated, procured, or delegated to a project plan. It requires presence, judgment, and a genuine understanding that the people inside an organization are the mechanism through which transformation takes hold.

I remain convinced that this is solvable by leaders who are willing to ask the harder questions at the beginning of the process rather than searching for explanations at the end. The human factor is the strategy, and it always has been.