Can You Transform One Part of an Organisation Without Changing the Others?

When I ask whether you can transform one part of an organisation without changing the others, I suspect some people will immediately think I’m talking about departments. Can you transform finance without changing manufacturing? Can you transform supply chain without involving sales? And while those are perfectly reasonable questions, they’re not quite what I have in mind.

I’m thinking about something that sits beneath the organisational structure, and which I believe has a far greater influence on whether transformation succeeds: people, processes, data and technology. Four elements that exist in every organisation, regardless of its size, industry or structure, and which are so interconnected that I find it difficult to imagine changing one without at least considering what needs to happen across the others.

Yet I’ve noticed how easily we can become focused on changing just one of them, particularly when that change involves implementing new technology. An organisation decides it needs to transform because its systems are outdated, its processes are inefficient or its people have developed increasingly creative workarounds. The business case is approved, a program begins, and before long the transformation becomes synonymous with the technology project that initiated it. And I find myself wondering whether we’ve lost sight of what we were actually trying to achieve.

An organisation is an ecosystem

One of the things I’ve learned through more than twenty years of working with organisations is that the problems we experience in one part of a business don’t necessarily originate there. Something might appear to be a technology problem because people are struggling to complete their work in an existing system, but when we explore what’s happening, we discover different teams following different processes, inconsistent information or unclear responsibility for decisions. Replacing the technology won’t necessarily resolve those issues.

Equally, what appears to be a people problem might have very little to do with people’s willingness or capability. We might have highly capable employees working within processes that make their jobs unnecessarily difficult, or people expected to make informed decisions without reliable information. And then we wonder why performance isn’t improving.

People bring the knowledge, skills, behaviours and judgement required to operate the business. Processes establish how work is performed, how decisions are made and how activities connect across functions. Data provides the information needed to operate, measure and improve performance, while technology enables, supports and sometimes constrains how all of that happens. Each influences the others, and the effectiveness of the organisation depends on how well they work together.

I’ve encountered situations where different functions are each doing what they believe is right, yet the overall business outcome is poor because nobody has sufficiently considered what happens between them. Sales might make commitments based on information manufacturing doesn’t recognise. Manufacturing might plan production using assumptions that differ from procurement’s, while finance reports against data interpreted differently across the business. Each function can believe it’s operating effectively while the organisation as a whole experiences inefficiency, frustration and unnecessary cost. It’s often at these intersections that some of the greatest opportunities for transformation exist.

What happens when we change one element without considering the others?

Let’s take an ERP implementation, because it’s an example many executives will recognise. An organisation has spent years operating with outdated systems, fragmented information and workarounds, so it concludes that it needs a modern ERP. And it probably does. But implementing that ERP introduces decisions extending well beyond technology: how work should flow through the organisation, which processes should be standardised, what information needs to be captured, who owns it and which rules determine how it’s maintained and used.

These are business decisions with implications for how people will work long after the implementation team has finished. If the organisation hasn’t established its desired future ways of working, there’s a risk that decisions about how the business should operate will be made through configuring the technology. I don’t think there’s anything inherently wrong with adopting standard ERP processes; they may be considerably better than existing practices. But consciously adopting a process because it supports the desired operating model is different from accepting it simply because that’s how the system has been configured.

The consequences often become apparent only when people start working in the new environment and discover that an important requirement was overlooked, information isn’t available where it’s needed or a process that works well for one function creates extra work elsewhere. The organisation then introduces workarounds, modifies the system or redesigns processes that could have been considered earlier. It’s particularly frustrating when the investment was intended to eliminate precisely those problems.

And then there’s artificial intelligence

The enthusiasm for AI provides another interesting example. There are extraordinary opportunities emerging, particularly with agentic systems that can undertake activities, make recommendations and interact with other systems with increasing autonomy. But I sometimes wonder whether the excitement about what the technology can do is moving faster than our willingness to examine what we’re asking it to work with.

Consider an organisation whose data is incomplete, inconsistent or poorly governed. Departments might use different definitions for the same information, product records might be duplicated, and business rules might exist in people’s heads rather than being clearly established. Introducing AI doesn’t automatically resolve those problems and may make their consequences greater. An AI system can process information faster or automate decisions, but useful outcomes still depend on the quality and meaning of the information available to it.

Greater autonomy also raises questions about the processes and decision-making authority within which AI operates. What decisions can the system make? Which rules must it follow? When should a person intervene, and who is accountable if something goes wrong? Those questions span people, processes, data and technology. I find myself coming back to a fairly simple observation: just because the AI looks clever doesn’t mean the information it’s working with is equally intelligent. We could simply be automating existing problems at a much greater scale.

Does everything need to change?

I don’t believe it does, and this is an important distinction. Some organisations have mature processes, strong data governance and capable people constrained by outdated technology, so their greatest investment may genuinely need to be in modernising systems. Others might have excellent technology but struggle with inconsistent ways of working, unclear accountabilities or behaviours that undermine collaboration. Their priorities will be different.

Recognising the interconnected nature of an organisation shouldn’t become an argument for making every transformation unnecessarily large or complicated. We don’t need to change everything simply because everything is connected. We do need to understand how the elements work together, identify where change is required and ensure the changes we make are supported by the rest of the organisational ecosystem. Sometimes that means redesigning a process, clarifying business rules, improving data quality or developing people’s capabilities, and sometimes it means recognising that something is already working well and should be preserved.

Perhaps we need to reconsider where transformation begins

The more experience I’ve gained, the more interested I’ve become in what happens between the individual elements of an organisation. A person completing an order isn’t experiencing people, processes, data and technology as four separate things. They’re following a process, interacting with technology, creating or using data and making decisions that may affect other people or functions. If the process is unclear, they may make assumptions. If the data is unreliable, they may verify it manually. If the technology doesn’t support the activity, they may create a workaround. Multiply those interactions across hundreds or thousands of people and seemingly small inconsistencies can have significant consequences.

It’s why I believe we need to spend more time at the beginning of transformation programs asking what we actually want the organisation to be capable of doing differently when the work is complete. Once we answer that properly, we move beyond the system we want to implement and start exploring how the organisation needs to operate, what its people need to do, what information they require and how decisions should be made across the business. Those conversations often reveal that the original problem was only one part of a much larger picture.

I understand the desire to move quickly towards a solution, especially when problems have been discussed for years and people are frustrated by the lack of progress. But understanding how the organisation operates today, where problems originate and what needs to be different in the future is part of achieving meaningful change. Without it, we risk investing significant time and money in solutions that address visible symptoms while leaving underlying causes largely untouched.

I don’t believe every transformation needs to change everything, but I do believe every transformation needs to understand the organisation as a whole. People, processes, data and technology form the ecosystem through which it functions, and the opportunity lies in understanding their relationships well enough to make deliberate choices about what needs to change, what should remain and how the elements can work together to deliver the outcomes we’re investing in. Perhaps that’s where we should begin: with a genuine understanding of how the organisation works today, and a shared vision of how we want it to work tomorrow.