Over the past decade, “digital transformation” has become a catch-all label for almost any organisational change involving technology. New systems. Automation. Analytics platforms. Collaboration tools. If it plugs in or logs on, it gets called a digital transformation.

The term has outlived its usefulness.

Introducing or upgrading technology is not the problem. Organisations must continue investing to remain competitive, productive, and secure. The rise of documented technology-driven change started early 2010s, as cloud computing, mobile platforms, data analytics, and collaboration tools reshaped work across industries (Westerman et al., MIT Sloan, 2014).

Technology is embedded in daily life. Embedding it effectively in organisations remains inconsistent.

Large-scale studies show that 60 to 70 per cent of technology-led initiatives fail to deliver their intended value (McKinsey, 2018; BCG, 2020). These failures are rarely attributed to technical defects. Research instead points to leadership alignment, organisational culture, capability, and ways of working as the primary drivers of underperformance (MIT Sloan & Capgemini, 2017).

The problem is not the technology. The problem is how we frame to start with. 

When we label complex organisational redesign as “digital transformation”, we centre the technology and marginalise everything else.

When the Language Shapes the Work

Language shapes behaviour. The way organisations describe change influences how it is scoped, funded, governed, and experienced.

When change is framed primarily as a technology initiative, ownership typically defaults to IT. Delivery milestones become proof of progress. Timelines follow implementation schedules rather than organisational readiness. Success becomes a go-live date rather than a shift in how work is actually done.

Leadership disengages. Culture becomes secondary. When results disappoint, we blame “resistance”.

But these initiative involve far more than technology. Processes shift. Roles evolve. Decision making moves. Performance expectations change. Ways of working are renegotiated. Outcomes depend on the interaction between people, organisational structures, and technology, not technology alone (Vial, 2019). When these elements are misaligned, new systems can be introduced, but meaningful change does not follow.

When Tech Takes Over

When technology dominates the stage, critical questions are pushed aside.

Are people ready to work differently? Do they understand what is expected after implementation? Do existing structures support the new way of working? Most importantly, how will the day-to-day work actually change?

When it is not addressed upfront, the consequences surface later and we’ve all seen it before. Processes are unclear. Workarounds emerge. Temporary fixes become permanent. Roles blur. Uncertainty increases. Time to competency extends far beyond the plan. Post-implementation outcomes shows that these issues, not technical defects, are the primary drivers of delayed benefits and change fatigue (Markus & Benjamin, 1997; Prosci, 2020).

Technology is implemented on schedule. The organisation is not ready to operate differently.

Technology Is an Enabler, Not the Transformation

Most so-called digital transformations are simply changing how the organisation functions. The aim is to change how work flows, how decisions are made, and how information moves and is stored using new or improved system or platforms. The mistake is assuming a new system will automatically produce a new way of working.

Technology enables change. It does not create it.

Culture and ways of working are stronger predictors of success than technical capability alone (MIT Sloan & Capgemini, 2017). When expectations about behaviour and decision making are unclear, new technology amplifies existing problems rather than solving them.

In practice, this pattern is familiar. The system works exactly as designed, yet teams struggle to adapt around it. Processes are disrupted. People are left to interpret new expectations after implementation.

It is not a technology failure. It is a failure in the framing and messaging that leaves people and processes behind.

People are more likely to support change when they understand its purpose and relevance to their role (Kotter, 2012). Psychological safety and clarity of expectations further influence whether people experiment, adapt, and adopt new ways of working (Edmondson, 2018; Schein, 2010).

When the narrative shifts away from the technology and toward capability, clarity, and opportunity, it creates space for a coherent change story. One that makes sense and that people can connect with.

Slowing the Framing to Speed the Outcome

Speed of technology implementation often exceeds speed of organisational understanding.

Many rush to implement new technology without stepping back to consider how the change fits within the broader system they are trying to improve.

Change, technology or other, does not sit in isolation. It connects with strategy, structure, leadership, capability, and culture. When these connections are not made explicit, change efforts compete, priorities fragment, and mixed signals spread.

Organisations that examine the whole system early, including people, processes, structures, and context, reduce rework and disappointment later (Beer & Nohria, 2000).

Taking a step back is not about slowing progress. It is about ensuring the technology supports a clearly defined organisational shift and that leaders reinforce the same story. When alignment is present, implementation accelerates and outcomes are more likely to stick.

Beyond “Digital” Transformation

Technology can be a catalyst. It is often the most visible element of change and the trigger for investment. For most organisations, it is also now a business-critical capability, shaping customer experience, workforce productivity, and the ability to adapt in a fast-moving environment.

However, a tool is only useful when people know how, when, and why to use it.

The real value comes when people understand what is changing in their roles, why it matters, and how work will be done differently, supported by clear messaging and reinforcement that helps new ways of working stick.

If the only thing that changed is the technology, nothing transformed.

Stop leading with the technology. Start leading with the people using it.

References

Beer, M., & Nohria, N. (2000). Cracking the Code of Change. Harvard Business Review.
Boston Consulting Group (2020). Flipping the Odds of Digital Transformation Success.
Edmondson, A. (2018). The Fearless Organization.
Kotter, J. (2012). Leading Change.
Markus, M. L., & Benjamin, R. I. (1997). The Magic Bullet Theory in IT-Enabled Transformation. Sloan Management Review.
McKinsey & Company (2018). Unlocking Success in Digital Transformations.
MIT Sloan & Capgemini (2017). Achieving Digital Maturity.
Prosci (2020). Best Practices in Change Management.
Schein, E. (2010). Organizational Culture and Leadership.
Vial, G. (2019). Understanding Digital Transformation: A Review and Research Agenda. Journal of Strategic Information Systems.
Westerman, G., Bonnet, D., & McAfee, A. (2014). Leading Digital. MIT Sloan Management Review.

For decades, organisations have treated resistance as the enemy of progress. Something to be managed, mitigated, or overcome. But this framing misses something fundamental about how humans actually experience change.

People don’t resist change by default.
They react when change doesn’t make sense to them.

That reaction might look like hesitation, criticism, disengagement, or silence. It might show up as “negativity” in meetings or slow adoption after go-live. But underneath it is rarely defiance. More often, it’s confusion, uncertainty, or a lack of psychological safety to ask questions out loud.

From a neuroscience perspective, this makes perfect sense. When change is announced without enough context, clarity, or coherence, the brain registers uncertainty as risk. Stress responses activate. Cognitive bandwidth narrows. Sensemaking stalls.

Labelling this response as resistance creates two problems:

1. Leaders misdiagnose the issue.
   
2. People feel blamed for a reaction that is both human and predictable.
   

When resistance becomes the lens, leaders default to control: tighter messaging, louder communication, more enforcement. Ironically, these moves often intensify the very reactions they’re trying to eliminate.

The alternative is to treat reactions as data.

When people question, hesitate, or disengage, they are telling you something about how the change currently lands. What feels unclear. What feels misaligned. What feels unsafe to say.

Effective change leaders don’t fight reactions. They get curious about them.

They create space for people to explore what doesn’t yet make sense, knowing that commitment comes after meaning, not before it. When people can make sense of change in their own terms, resistance rarely needs managing — it dissolves on its own.

Most engagement strategies are built on a simple assumption: if people are involved, they’ll be committed. So organisations run surveys, workshops, town halls, and feedback sessions — and are surprised when buy-in still doesn’t follow.

The problem isn’t effort.
It’s the definition of engagement itself.

Participation and sensemaking are not the same thing.

You can attend every meeting, answer every survey, and still leave without clarity. You can give feedback without understanding how a change fits together, what it means for you, or what matters most right now.

Sensemaking is the process through which people interpret change:

• What is really happening?
• Why now?
• What does this mean for me, my role, and my future?

That process is internal and social. People don’t make sense of change alone. They test ideas in conversation, observe how leaders behave, and watch how decisions are made under pressure. Meaning is formed sideways — not downloaded from slides.

This is where many engagement approaches fall short. They focus on gathering input, not surfacing understanding. They ask for opinions without revealing how people are actually thinking and feeling in real time.

When engagement is designed to support sensemaking, different things happen:

• Questions are welcomed rather than managed.
• Differences in perspective are made visible, not smoothed over.
• Leaders adapt their approach based on what they learn, not what they planned.
  

The goal isn’t consensus.
It’s shared understanding.

Because once people understand what’s happening — and why — alignment becomes possible. Without sensemaking, engagement becomes theatre. With it, engagement becomes momentum.

When change slows down, leaders often reach for motivation. More encouragement. More urgency. More reminders of why the change matters.

But motivation is fragile. Momentum is structural.

Momentum is the felt sense that progress is happening. That effort leads somewhere. That movement is possible. In the brain, momentum is reinforced by evidence of progress — not speeches about intent.

Behavioural science shows that people are more likely to persist when early actions feel achievable and successful. Small wins build confidence. Confidence fuels continued effort. Effort creates more progress.

When momentum is missing, even capable teams hesitate. Tasks feel heavier. Doubt creeps in. Energy drains — not because people don’t care, but because the path forward feels uncertain or overwhelming.

Leaders don’t create momentum by cheering louder.
They create it by designing better experiences.

That means:

• Breaking change into visible, meaningful steps.
  
• Making progress observable, not assumed.
  
• Recognising effort early, not just outcomes at the end.
  
• Removing friction before asking for more energy.
  

Momentum also isn’t uniform. Different people need different signals to feel confident moving forward. Some look for proof. Others look for process clarity. Others watch how leaders show up under pressure. When momentum design ignores this, progress becomes uneven and fragile.

Sustainable change doesn’t rely on motivation spikes.
It relies on momentum that compounds.

When people can see that the change is working — even imperfectly — they keep going. Not because they’re motivated, but because forward motion now feels natural.

Most projects don’t fail suddenly. They fail predictably. And yet we still act surprised when they do.

Not because the work is impossible but because the warning signs were there from the beginning, quietly accepted as “normal.”

Decades of research show that projects fail in highly repetitive, painfully consistent ways.

The Standish Group’s CHAOS research has repeatedly found that only ~30% of projects are considered successful. The rest are either challenged, over budget, delayed, under-delivering, or fail outright. In this context, failure doesn’t just mean the project was hard or didn’t go exactly as planned. It means the project did not deliver the required outcome.

Project failure is not the anomaly. It is the pattern.

Many of the practices we’ve accepted as “normal” quietly set projects up to struggle from day one. The warning signs appear early, get politely ignored, and are later rewritten as “unexpected challenges.”

Here are seven of them.

1. No One Can Clearly Explain Why the Project Exists

The “why” is your north star.

Why are we doing this?
Why now?
Why this instead of something else?

When the purpose is vague, everything becomes negotiable resulting in scope drifting, priorities shifting and decisions stalling.

Unclear goals, shifting priorities, and lack of alignment with organisational strategy are consistently identified as primary drivers of project failure (PMI, Pulse of the Profession).

A project without a clear why doesn’t explode. It slowly erodes.(PMI; Prosci, 2020).

Clarity of purpose is not a nice-to-have. It is the foundation every future decision should return to.

2. The Solution Was Chosen Before the Problem Was Understood

This is where projects quietly lock in risk before they understand what they are trying to solve. The tool becomes the answer. The organisation bends around it.

When the solution is chosen before the problem is clear, discovery becomes justification. Requirements are written to fit the product. Gaps are labelled “future improvements” instead of signals the solution does not fit.

Projects with unclear early requirements and premature commitment to solutions are more likely to experience scope instability and costly rework (Flyvbjerg & Budzier, 2011). Similarly, initiatives driven primarily by technology, rather than clearly defined business problems with measurable outcomes, frequently underdeliver on value (McKinsey & Company, 2018).

If discovery starts after procurement, you are not designing a solution. You are defending one.

3. The Timeline Was Based on Optimism, Not Reality

When deadlines are locked in early, driven by executive pressure, financial cycles, regulatory commitments, or public announcements, before the work understood.

Political pressure in early forecasting distort initial estimates and contribute to cost overruns and schedule delays (Flyvbjerg & Budzier, 2011). Behavioural science calls this the planning fallacy where teams consistently underestimate effort and complexity even when history tells them otherwise. (Kahneman & Tversky, 1979).

Timelines built around technical readiness rather than organisational readiness can also produce poor outcomes

Essentially, the system might be ready to go live. But the business isn’t. 

When timelines are dictated by technical readiness alone, time for training, process redesign and sensemaking are deferred until after implementation, when change is harder and options are narrower.

Benefits are far more likely to be realised when organisations invest in readiness, capability building, and structured change support before implementation (PMI; Prosci, 2020).

Lock in the deadline too early, and you may overlook the effort, capacity, and readiness required to meet it.

4. Everyone Is Overcommitted

One of the most persistent delivery myths is that people can do project work “on top of their day job.”

They can’t, or at least not sustainably.

Over time, the cost shows up elsewhere, either through slower decisions, rushed outputs, declining quality, or burnout.

Cognitive psychology research shows us that multitasking and constant task switching reduce performance and increase delays (Kahneman, 2011). This persistent priority conflict and unrealistic resourcing assumptions are strongly associated with poor project performance. (PMI, Pulse of the Profession).

If people are not formally allocated to the project, the project is not truly resourced. It is just running on borrowed time.

5. Stakeholder Engagement Happened… Technically

When stakeholders are engaged after the solution is chosen, the plan is built, and the timeline is locked. They are not being engaged. They are being informed. 

Stakeholder involvement during problem definition and decision-making is strongly associated with stronger commitment and improved project outcomes (Beringer, Jonas & Kock, 2013; Yang et al., 2011).

Even when engagement starts early, it must be continuous and meaningful. Sporadic or symbolic engagement does little to improve alignment or decision quality (Freeman, 1984; Bryson, 2004).

People don’t disengage because they dislike change.
They disengage because they were never truly included.

6. Decision-Making and Governance Are Unclear

A project can have weekly steering committees, polished dashboards, and colour-coded RAG statuses and still be unmanaged.

When governance becomes routine instead of a decision-making discipline, problems and risks get raised, but nothing happens. This results in risks not being mitigated and decisions and ownership not being clear. 

Unclear decision rights, slow escalation, and weak accountability are strongly associated with cost overruns and delivery failure (Too & Weaver, 2014).

Meetings do not keep a project on track.
Clear ownership and timely decisions do.

7. Change Management Arrives Late

Adoption failure is one of the quiet killers of projects.

A system can be implemented on time and still fail to deliver benefits if people are not ready to work differently.

Organisational and people-related factors are consistently shown to be dominant drivers of underperformance, even when technical delivery is sound (McKinsey & Company). Projects with effective change management are significantly more likely to meet objectives, stay on schedule, and stay within budget (Prosci, 2020).

When change engagement starts early teams have time to build clarity, capability and confidence before implementation. 

When it starts late, projects enter recovery mode. Workarounds multiply. Confidence drops. Value is delayed.

Psychological safety is also critical for early issue escalation and adaptive decision-making. When people do not feel safe raising concerns, small issues remain hidden until they become expensive problems.

Projects do not fail because change is difficult.
They fail when organisations treat adoption as an afterthought rather than a condition for success.

Final Thought

What makes these signs dangerous is not that they are rare. It’s that they feel normal. Each sign reflects the same pattern we continue to see: we ignore human and organisational realities in favour of tidy plans and optimistic assumptions.

Projects rarely collapse because of a single catastrophic decision. They unravel because small, early signals were tolerated instead of addressed.

The good news? These patterns are predictable. Which means they are preventable.

Confront them early, and you increase your chances of delivering real outcomes and benefits.

References

Beringer, C., Jonas, D., & Kock, A. (2013). Behavior of internal stakeholders in project portfolio management.
Bryson, J. (2004). What to do when stakeholders matter.
Edmondson, A. (2018). The Fearless Organization.
Flyvbjerg, B., & Budzier, A. (2011). Why Your IT Project May Be Riskier Than You Think. Harvard Business Review.
Kahneman, D. (2011). Thinking, Fast and Slow.
Kahneman, D., & Tversky, A. (1979). Intuitive prediction: Biases and corrective procedures.
McKinsey & Company. (2018). Unlocking Success in Digital Transformations.
PMI. Pulse of the Profession Reports.
Prosci. (2020). Best Practices in Change Management.
Standish Group. (2020). CHAOS Report.