Why how you start matters more than ever in large-scale transformation – and how to set up for success from the outset

By David Lowson

In Australia and New Zealand, large-scale transformations often fail for the same reason: they start in the wrong place.

Many begin with:

“What do we need to do to implement S/4 (or equivalent technology platform)?”

A more insightful question to ask is:

“What do we need to change in the business – and how do we make that change real?”

Why Australasian organisations can’t afford slow starts or status quo thinking

In Australia and New Zealand, there is very little margin for error in large-scale transformation. Talent markets are constrained, budgets are tightly managed, and many organisations are carrying complex, fragmented ERP landscapes that increase delivery risk.

At the same time, the pace of change is accelerating – AI, hyperscalers and cloud platforms are evolving rapidly – while boards are demanding greater transparency, faster outcomes and clearly measurable value.

In this environment, a hesitant or poorly defined start isn’t something that can be recovered later; it compounds risk, delays benefits and undermines confidence from the outset.

What great large-scale transformation programs do differently to set up for success:

Successful transformation programs take a fundamentally different approach from the outset.

They begin by anchoring decisions in value rather than scope, defining clear KPIs before moving into design so that success is measurable from day one.

They focus early on the critical business capabilities that must change, while protecting the integrity of the digital core to enable long-term agility.

Governance and decision rights are established upfront to avoid drift and rework, and transition paths are explicitly modelled – recognising that transformation happens through manageable stages rather than a through the pursuit of a single, idealised future state.

Most importantly, they prioritise early and frequent delivery of tangible value, building momentum and confidence as the program progresses.

These are the defining characteristics of successful large-scale transformation – both globally and here in Australasia.

Introducing Large Transformation (LTP) shaping – the foundation for success

Making aspiration a reality from day one – the five key steps of LTP shaping:

  1. Frame ambition and value
  2. Map value streams and capability gaps
  3. Define target architecture and clean-core posture
  4. Model business cases that allow for various options and scenarios
  5. Set governance, decision rights and engagement strategy

These five steps will produce six make‑or‑break outputs:

  • A preliminary business case
  • A roadmap
  • An engagement strategy
  • Target architecture
  • Governance foundations
  • Executive alignment

In combination, these foundational elements and artefacts will determine whether your program succeeds or stalls.

Critically, success at this stage depends on strong alignment between business and IT leadership. From the outset, the executive team and technology community must share a clear, common understanding of the nature of the initiative – whether this is a system upgrade, a full transformation, or something in between. Without this alignment, decisions fragment, expectations diverge, and momentum quickly stalls.

Equally important is a shared view of what “good” looks like. In practice, this is not just about delivering a new system, but about standing up a live, stable platform that resolves the most significant business pain points while remaining flexible enough to evolve rapidly.

When organisations align on both the ambition and the desired end state, they create the conditions for faster decisions, clearer trade-offs and sustained delivery momentum.

An action plan for Australasian leaders

Start once – and start well.

At a high level, a successful action plan will consider the following:

1. A short, outcome‑focused inception – plan quickly, but not forever

  • Run a concise inception (weeks to a few months) that defines clear objectives, target value streams, initial scope, estimated costs and tangible benefits.
  • Avoid long “as‑is/to‑be” analyses that push go‑live years out; aim to deliver a meaningful business outcome within 12 months.
  • Use your inception outputs to make concrete decisions about your transformation path – things like architecture choices, required tooling, resourcing model and your business case.

2. Build scaffolding before scale – get the architecture and tooling right

  • Establish the architectural scaffolding early: API gateway, integration archetypes, CI/CD pipelines, automated testing, release orchestration, monitoring and rollback mechanisms.
  • Put governance and API ownership in place so extensions are safe and discoverable.
  • Choose a sovereign/cloud pattern early where compliance or regulation requires it, and prove it in a pilot.

3. Prioritise clean core and API‑first extensibility

  • Treat the SAP core as sacrosanct: remove technical debt and relocate bespoke logic into governed extension layers (BTP or chosen platforms).  
  • Define an API strategy and archetypes so teams can develop in parallel without risking the core.  
  • Implement strict change gating – ensure core changes are rare and controlled and that innovation happens via extensions.

4. Make data a first‑class workstream

  • Include data strategy and migration in the inception: catalogue source systems, map flows to value streams, and identify high‑impact master and transaction datasets.  
  • Prioritise cleaning master data that blocks go‑live or delivers immediate business value (customers, products, pricing).  
  • Use automated profiling, synthetic test data and reconciliation tools to speed migration and validate interim states.

5. Deliver early, and get measurable wins on the board

  • Sequence delivery to produce rapid benefits that fund follow-up waves. Target a credible business release within 12–18 months.  
  • Tie every deliverable to measurable outcomes and track benefits against value streams so trade‑offs are transparent.

6. Use AI and automation to accelerate delivery (with guardrails)

  • Adopt AI for repeatable, high‑value tasks such as spec generation, test‑data creation, regression testing, meeting transcription and code analysis.  
  • Apply AI to analyse legacy estates, recommend refactors, and scaffold extensions – then validate results with domain experts.  
  • Build agentic pilots that automate multi‑system processes where the business case is clear; deploy agents within governed, sovereign environments.

7. Put DevOps and continuous delivery at the heart of your transformation program

  • Shift from a project mindset to product teams owning continuous delivery: smaller, frequent releases reduce risk and surface valuable feedback more quickly.  
  • Automate CI/CD, regression testing and release orchestration so upgrades and enhancements are routine and safe.  
  • Use continuous delivery to make benefits visible rapidly and to refine priorities based on real usage.

8. Secure cross‑enterprise alignment and governance

  • Obtain C‑suite sponsorship and align finance, procurement, HR and business units on the ambition and decision cadence.  
  • Use benefit mapping to create an unambiguous case for change and to surface the consequences of inaction.

9. Talk widely – and choose partners pragmatically

  • Engage independent advisors and a range of system integrators, local and offshore partners, and platform vendors before issuing tenders.  
  • Avoid tendering specifications that lock you into outdated, bespoke approaches; base tenders on architecture and outcomes, not exhaustive functional lists.

10. Build talent and capability locally

  • Invest in local graduate intake, training and early-career rotations to refresh skills and reduce over‑reliance on offshore or ageing cohorts.  
  • Embed data engineers, automation specialists and product owners inside delivery teams rather than siloing capability.

11. Design migration and interim states explicitly

  • Plan for coexistence and interim reconciliations; document interim architectures and set explicit SLAs for reconciliations and cutover activities.  
  • Automate reconciliation and monitoring to detect drift and regressions during phased rollouts.

12. Capture and scale proof points

  • Document reductions in upgrade time, incident frequency and run cost from early pilots. Use these internal proof points to help overcome caution and mobilise broader budgets.

Final thoughts

For Australasian organisations, transformation speed and success come from doing the fundamentals exceptionally well:

  • A short, focused inception
  • The right architectural scaffolding
  • A clean core with API‑first extensibility
  • Rigorous data workstreams
  • AI‑enabled productivity
  • And a product‑driven continuous delivery approach.

These foundations turn Australasia’s geographical position, sovereign requirements and cautious markets from obstacles into competitive advantages – allowing enterprises to deliver business value faster, lower long‑term costs and establish a resilient platform for future innovation.