Large transformation programs are complex by nature. But after years of working with difficult transformation programs, we have found that organizations often make that complexity much harder to manage than it needs to be.<\/p>\n
Complexity is not always the problem. Unmanaged, and often self-created, complexity is.<\/p>\n
A practitioner\u2019s perspective<\/p>\n
Some years ago, after helping turn around a large global SAP Customer Experience program, I was contacted by several customers asking a surprisingly simple question: what did you do differently?<\/p>\n
My answer was a set of practical keys to success, which I refined through discussions and workshops with customers over the years. The pattern was remarkably consistent. Weak governance and pragmatic change management were recurring problems. But an even more fundamental issue appeared again and again: many organizations had invested in a solution without a sufficiently clear and shared understanding of what they wanted to achieve with it.<\/p>\n
Once that first question is unclear, everything downstream becomes harder.<\/p>\n
Start with the outcome, not the transformation<\/p>\n
Transformation programs tend to generate activity very quickly.<\/p>\n
Workstreams are created. Governance boards appear. Solution workshops are scheduled. Backlogs grow. Training plans are developed. New roles and responsibilities are defined.<\/p>\n
All of that may be necessary. But before asking how to transform, organizations need to be able to answer a much simpler question: what are we actually trying to improve?<\/p>\n
Strengthen your team with specialized expertise from the Advanced Success Plan<\/p>\n
Is the ambition profitable growth? A fundamentally different customer experience? A new service or business model? Greater operational resilience? Better use of data across the enterprise? The ability to scale into new markets?<\/p>\n
Without that shared value intent, different teams start optimizing different things. Business stakeholders describe desired outcomes, implementation teams focus on solution scope, and users are eventually trained on functionality without always understanding what should change in their daily work. The result can be a very busy transformation program with surprisingly little transformation.<\/p>\n
Keep the business, solution, and people connected<\/p>\n
Over time, I started using a simple model to explain this: the transformation triangle. <\/p>\n
A transformation needs three perspectives to stay connected:<\/p>\n
Business: Why are we changing? What outcomes, value drivers, processes, and measures matter?<\/p>\n
Solution: What capabilities, technology, integrations, data, and implementation choices are needed?<\/p>\n
People: Who needs to work differently, what support do they need, and how will adoption be sustained?<\/p>\n
None of these works well in isolation. A technically excellent solution with weak business alignment becomes an expensive implementation. A strong strategy without a workable solution remains a presentation. And a well-designed process that people do not understand or adopt remains, at best, another PowerPoint slide.<\/p>\n
This thinking later became part of the Cloud Mindset Workshop, available to order in the Advanced Success Plan version for SAP Customer Experience solutions. The workshop helps translate the business, solution, and people perspectives into practical topics covering business outcomes, governance, processes, rollout, change management, enablement, and adoption.<\/p>\n
A skills gap is not always a training gap<\/p>\n
This also changes how we should think about skills gaps.<\/p>\n
The immediate reaction is often to provide more training or bring in more technical specialists. Sometimes that is exactly what is needed, but many transformation gaps are broader capability gaps.<\/p>\n
A project may have excellent product experts but still struggle because nobody can translate business objectives into process priorities. A strong implementation team may still fail if decision rights are unclear. End users may know how to navigate a solution but not understand why their role has changed.<\/p>\n
Skills therefore span all three sides of the triangle: business judgement, process knowledge, product expertise, data and integration capability, governance, change leadership, and adoption.<\/p>\n
The objective should not be to create experts in everything. It should be to make sure the organization has the right capabilities at the right moment, and that those capabilities work together.<\/p>\n
Governance should reduce complexity, not add to it<\/p>\n
Governance is another area where organizations can accidentally create more complexity than they remove.<\/p>\n
Good governance does not mean more meetings, more steering committees, or larger RACI matrices. It should make a few things very clear: Who decides? What needs to be decided? Based on which outcomes and measures? How are dependencies and risks escalated? And when should the plan change?<\/p>\n
Governance needs to come early because execution becomes difficult when ownership, priorities, and decision-making remain ambiguous. The purpose of transformation governance is not to manage complexity for its own sake. The purpose is to make complexity manageable.<\/p>\n
Autonomous CX raises the stakes<\/p>\n
AI and autonomous capabilities add another dimension.<\/p>\n