Practitioner notes on finance, forecasting and AI.
Written from live practice, not commentary, each piece published here first, then discussed on LinkedIn.
What AI actually changes in FP&A: a practitioner's note
A working tour of the full stack: the driver tree (seasonality, lifecycle, marketing, supply side), sensitivity that is no longer a luxury, the living what-if model, and the control environment that keeps AI honest.
AI in financeThe speed-safety gap: pharma's least discussed AI problem
A candidate molecule can now be designed in months; the systems that keep patients safe still run on slower timelines. Speed without governance is risk transfer.
Pharma & AIConfidently wrong: the hard half of AI adoption
Capability was never the constraint; trust was. What actually stops AI being confidently wrong, and why the FDA landed on the same answer.
AI governanceAI in pharma: speed is the headline, economics is the story
AI raises speed, lowers cost, then removes the barriers that protected incumbents. What that does to competitors, pipeline value and moats.
Pharma & AI strategyWorking capital as survival: eleven years without a safety net
Eleven years running a self-funded consumer brand, with no credit line behind it, turned the working-capital fundamentals into survival disciplines. The five that kept the business solvent, and what a mid-market finance function can copy.
Cash & working capitalThe finance function a PE portfolio company actually needs in year one
The operating partner did not buy a month-end reporting pack. They bought decision-speed, and the finance function has one hundred days to prove it can deliver it: cash you can see, unit economics you can trust, one version of the truth.
Private equityThe merger I modelled two years early
In 2010 an MBA team I led built a full acquisition case for Britvic buying A.G. Barr from public information alone. Two years later the real merger followed the same logic, the same leadership answer, and died exactly where we had flagged the risk.
Mergers & acquisitionsPatient-based forecasting, revisited
The demand-modelling discipline built for pharma valuations at GSK, and the finance function a PE portfolio company actually needs in year one.
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