Early Warning Signals in Large
Digital Transformation Programs
SECOND EDITION
By Cornelius Greyling
Florida, USA
Abstract
Major program failures do not usually arrive as sudden cataclysmic events. They do not hit a wall at high speed. More often, large-scale digital transformations gradually enter a degraded state where delivery remains active, governance stays in place, and reporting remains largely yellow. This paper defines that condition as “Program Drift”: the gradual loss of alignment between governance, plans, decisions, and execution while work continues and formal controls remain in place. Decision latency is a major mechanism, but drift also develops through planning divergence, unvalidated work, assumption-based continuation, fragmented ownership, and apparent closure that does not change execution. The paper also points to a limit in the dominant predict-and-control strain of project management. Traditional controls assume that with enough rigor, decomposition, and method discipline, delivery remains broadly manageable. In large transformations, that assumption captures only part of the problem. Drawing on practitioner experience across enterprise transformations and large ERP deployments, this paper highlights early warning signs of drift that can appear well before delivery failure is detected. It also discusses why these signs are ignored, how the very processes meant to address them can sometimes make the problem worse, and how Program Drift can be recognized early without adding more processes or tools.
Scope and Basis
This paper draws on repeated practitioner observations across large-scale enterprise transformation programs in banking, utilities, automotive, energy, retail, and other sectors, with particular attention to SAP and S/4HANA change. The patterns described here are presented as a qualitative diagnostic model intended to improve early visibility and intervention. Direct empirical research isolating decision latency as a standalone causal variable in large ERP or transformation programs remains limited. Most stronger evidence reaches the issue indirectly, through governance quality, role clarity, alignment, intervention timing, and decision-right allocation. That matters because those are the mechanisms through which lagging or missing decisions appear in real programs. Available evidence still points in a consistent direction: stronger governance is associated with lower delay, earlier recognition improves recovery odds, and ineffective decision structures are repeatedly linked to schedule and quality deterioration[1] [2] Research on early warning signs in complex projects already shows that weak signals are often visible before formal failure is acknowledged (Williams, Klakegg, Walker, Andersen, & Magnussen, 2012). This paper builds on that foundation but shifts the lens to active delivery in large transformation programs, where the issue is not only whether weak signals are detected, but whether governance can still convert those signals into timely decisions and coordinated action.
- Program Drift and Decision Capacity
1.1 Motion is not Control
“He who lets the sea lull him into a sense of security is in very grave danger.” – Hammond Innes
Mariners have an old problem that is easy to underestimate: a ship can appear to be making good progress and still be drifting off course. The danger is not the absence of motion. It is motion in the wrong direction, detected too late (Dekker, 2011). At sea, “set” is the direction of the current and “drift” is its speed.[3] A navigator who mistakes movement for control may discover the error only when the next fix shows the vessel is no longer where the chart assumed it should be. Experienced navigators often sense earlier that “something is not lining up” before the deviation becomes large. But that instinct is usually pattern recognition built on instruments, visual cues, timing, and sea conditions, not some vague gut feeling.
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Editor’s note: Second Editions are previously published papers that have continued relevance in today’s project management world, or which were originally published in conference proceedings or in a language other than English. Original publication acknowledged; authors retain copyright. This paper was originally presented at the 18th Project Management Symposium at the University of Texas at Dallas in May 2026. It is republished here with permission of the author and conference organizers.
How to cite this paper: Greyling, C. (2026). Program Drift: Early Warning Signals in Large Digital Transformation Programs; Originally presented at the 18th Project Management Symposium at the University of Texas at Dallas in May, republished in the PM World Journal, Vol. XV, Issue VIII, August. Available online at https://pmworldjournal.com/wp-content/uploads/2026/08/pmwj167-Aug2026-Greyling-Program-Drift.pdf
About the Author
Cornelius Greyling
Florida, United States
Cornelius Greyling is a senior project and program leader with nearly 30 years of experience working on large, complex digital transformation programs. His career began in Swiss financial services and has since taken him across Europe, Latin America, and the United States, leading enterprise transformations across a wide range of industries. He has held senior delivery and leadership roles at SAP, Natuvion, SNP, and international consulting organizations. His work focuses on how large transformation programs lose control while continuing to appear active, structured, and governed. He is PMP-certified and the author of Designed to Drift. He can be contacted through linkedin.com/in/greyling
[1] Khalid et al. found significant negative relationships between project governance and project delay (β = – 0.418), and between IT governance and project delay (β = -0.292).
[2] The UK Infrastructure and Projects Authority identifies ineffective decision-making as a recurring transformation challenge and states that ineffective decision-making bodies can severely affect schedule and quality of outcomes.
[3] In maritime navigation, “set” refers to the direction of the current and “drift” to its speed.
