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From Initiatives to Outcomes: Seeing Transformation as a System
1. From Initiatives to Outcomes Transformation is often described through what organisations do : the initiatives they launch, the programmes they fund, and the technologies they introduce. Progress is tracked through activity — plans delivered, milestones reached — and success is frequently inferred from motion. Yet the presence of movement does not always translate into the outcomes transformation is intended to produce. Over time, many organisations experience a subtle but
iandempsey8
Feb 15 min read
Why Transformations Struggle: It’s Not the Tech — It’s the Operating Model
1. A Familiar Pattern: When the Technology Works but the Change Doesn’t Many transformation initiatives follow a reassuringly familiar path... Systems are implemented successfully. New capabilities are technically available. Delivery milestones are met. Training is completed and communications are issued. On paper, the transformation appears to be progressing exactly as planned. And yet, months later, the results feel underwhelming. Benefits arrive more slowly than expected.
iandempsey8
Jan 316 min read
Transformation as a Discipline: Why Outcomes, Coherence and Judgement Matter
Many transformation initiatives deliver exactly what they set out to deliver. Systems go live. Operating models are approved. New ways of working are launched. On paper, progress is clear and measurable. And yet, months later, the organisation often feels much the same. Decisions are still made the same way. Old behaviours resurface. Old workarounds creep in. The value that justified the investment remains frustratingly out of reach. This disconnect is not unusual, and it is
iandempsey8
Jan 304 min read
AI Adoption Déjà Vu: Why We’re Repeating the Same Mistakes Again (and What to Do Instead)
Every few years, a new technology arrives that promises to transform everything. ERPs were going to standardise the enterprise. CRMs were going to “own the customer”. RPA was going to automate the back office. Big data and machine learning were going to make every decision “data-driven”. Now it’s AI’s turn. What’s striking, looking across these waves, is not the technology itself – it’s how predictably organisations mishandle it. The tools change. The pattern doesn’t. Right n
iandempsey8
Jan 296 min read
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