My perspective on business transformation

Transformation in practice

Work on international supply chains, integrated planning and collaboration across teams has shaped how I look at change. These three anonymised situations explore how decisions in one part of an organisation affect work elsewhere.

These reflections connect practical transformation questions with the central argument of The Coherent Enterprise: value depends on how the parts of an organisation work together. AI provides a new test of those relationships.

A shared plan requires shared decisions

Integrated planning brings market demand, production capacity, stock and logistics into the same discussion. A choice that looks attractive for one location can create waiting, extra transport or a delivery problem elsewhere. The planning question therefore reaches beyond the boundaries of an individual department.

A common planning system can make those dependencies visible. The organisation still needs to agree what takes priority when goals conflict, which data a decision relies on, and who can resolve a disagreement between locations. Local performance measures can otherwise keep pulling a shared plan in different directions.

I start by examining one concrete planning decision. Which customer commitment is at stake? What changes for the people who have to carry it out? Who can accept a local disadvantage when it improves the result across the whole chain? These questions connect strategy with daily planning work.

For AI, this raises a planning question: can a model’s recommendation become an executable shared plan when locations use different definitions, priorities or decision rights? The planning process and the AI application need to develop together.

The whole chain determines whether a solution works

In an international supply chain, an order connects customer service, stock, transport, compliance and invoicing. Each application may perform its own task correctly while the order still gets stuck between systems or teams. A missing data definition, an unclear handoff or an unavailable business expert can hold up the wider flow.

That makes acceptance an organisational question as well. Can the right person complete the work with the right information and permissions? Are the instructions, training and support ready for the same process version? Do the people who will operate the process have enough time to test it before release? These dependencies belong in the delivery plan.

I follow a representative order through the complete chain, including exceptions. This shows where technical integration, data ownership and ways of working need to meet. It also helps distinguish software that is ready from an operation that is ready to use it.

For AI, the question becomes: does faster work in one step improve the complete order flow? An agent also depends on usable data, permissions, exception handling and an accountable person. Those connections shape whether its output can become an operational result.

Teams need a shared outcome

When several teams work on a common platform, each team can have a clear backlog and still depend heavily on the others. A change to one module may require data, interfaces and decisions from another. Team-level progress alone gives an incomplete picture of what users can actually do.

The organisational questions become concrete: where are conflicting priorities resolved, who owns the result across modules, and when do teams demonstrate an integrated piece of working functionality? Role clarity matters here, including the authority, knowledge and available time that let people fulfil their responsibilities.

I examine dependencies alongside the work itself. A useful discussion connects team priorities to a shared outcome and makes cross-team decisions explicit. It asks what the organisation must change so that people can collaborate effectively, rather than expecting a meeting schedule to resolve every dependency.

For AI, I ask which shared outcome faster team delivery serves. If priorities still conflict across teams, more output can add to the coordination load. Shared decisions and feedback help test whether the enterprise is improving as teams adopt AI.

Six perspectives on the same change

I use these questions to explore how a transformation affects the organisation. Each answer can change what the other parts need to do.

Strategy and choices
Which outcome matters, and which trade-offs are we prepared to make to achieve it?
People and their work
What changes in daily work, and what do people need in order to carry responsibility and learn?
Processes and handoffs
How does work reach a useful outcome, and where do waiting, rework or exceptions interrupt it?
Structure and ownership
Who can decide across organisational boundaries, and do responsibilities match the way the work flows?
Infrastructure and dependencies
Can applications, interfaces and environments support the complete process, including its exceptions?
Data and its meaning
Do people use the same definitions, and who is responsible for the quality of the information behind a decision?

Following the connections

My starting point is a concrete piece of work and the outcome it should deliver. I follow the decisions, handoffs and information it needs, and then examine what this asks of the organisation. That is how I connect business transformation with enterprise coherence: by making the relationships between choices and execution discussable.

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