Supply-chain planning & technology · 14 years
Fourteen years across SAP IBP, o9, Kinaxis and OMP — building the analysis behind planning decisions in pharma cold chain, FMCG and energy. Reproducible, from first principles.
ScrollSelected work
Three open analyses. Each begins with the question a planning leader actually asks — then computes the answer, end to end, on labelled synthetic data.
“Which node, if it fails, hurts most — and for how long?”
Time-to-Recover and Time-to-Survive stress testing across the network, in the Simchi-Levi tradition. Failure modes ranked by exposure, not by anecdote.
“Is our forecast actually adding value — and where is it worst?”
Forecast Value Added in the Gilliland sense, paired with ADI/CV² demand segmentation after Syntetos–Boylan–Croston. The forecast earns its keep, or it goes.
“Base, upside, constrained — what do we commit, and what does it cost?”
Scenario reconciliation with rough-cut capacity, in the Wallace and Oliver Wight tradition. One number the executive meeting can actually sign.
Principles
“The forecast is a decision, not a prophecy.”
“Every number computed, not asserted.”
“Seed everything. Same inputs, same answer.”
“Judgment over code craft. Bounded claims.”
About
I have spent fourteen years inside supply-chain planning — first as a functional consultant, then leading delivery at a Big Four consulting firm, across SAP IBP, o9, Kinaxis, OMP and classic S&OP. Pharma cold chain taught me that a plan is a promise with a temperature range. FMCG taught me speed. Energy taught me what happens when the constraint is real.
These days I build the analysis behind planning decisions: resilience stress testing, forecast-quality diagnostics, integrated business planning — and, increasingly, applied AI in planning workflows. Everything reproducible, everything from first principles. All demo data on this site is synthetic and labelled as such.
I write about applied automation and planning at automationdiary.com.
Contact
If your planning organisation is asking one of the questions above — or a harder one — I would genuinely like to hear it.