Demand planning, written from inside the operation.
Not commentary. These are the problems I have actually had to solve running planning across China–MENA–GCC: Ramadan demand curves that break standard seasonality, Red Sea rerouting that rewrites your safety stock overnight, and S&OP meetings that quietly turn into reporting sessions. Written for practitioners, not for search engines.
A high-value gifting SKU sells 1–2 units a month, then 18 in the National Day week. ABC calls it C-class and a flat seasonal index smooths the spike into nothing. Half its annual demand lives in four weeks — and the system cannot see any of it.
Ramadan moves roughly eleven days earlier every Gregorian year, and almost every forecasting system assumes seasonality repeats on a fixed calendar. How to model the stock-up, the in-month category divergence, the Eid peak and the trough.
Rerouting is not a freight problem with an inventory side effect — it is a variance problem with a freight headline. What +14 days does to pipeline inventory, safety stock and your effective forecast horizon, with the arithmetic.
Explode a finished-goods order through its bill of materials, net off stock and open POs, apply MOQ rounding and back-schedule every purchase order from the required date. Names the single component that gates your date.
The whole chain in one view, from forecast collection to delivered case. Solid lines carry material, dashed lines carry information and payment. Click any step for its owner, inputs, outputs, lead time and failure mode.
Safety stock, EOQ, reorder point, MAPE, inventory turnover and carrying cost. The arithmetic behind most of the articles here, in a form you can put your own numbers into.
Naive baseline vs moving average vs Holt's double exponential smoothing, tested on 23 months of MENA consumer goods demand with rolling-window cross-validation. ~30% MAPE reduction against the baseline; best category at 6.4%.
Demand planning dashboard for a UAE commercial vehicle distributor. ARIMA, Holt-Winters and an ML ensemble side by side, replacing a manual Excel S&OP with live, decision-ready analytics.
A high-value gifting SKU sells 1–2 units a month, then 18 in the National Day week. Half its annual demand lives in four weeks — and an annual-average seasonal index is structurally incapable of seeing any of it.
Ramadan moves ~11 days earlier every Gregorian year, and almost every forecasting system assumes seasonality repeats on a fixed calendar. Those two facts are incompatible. How to model the four-phase demand shape properly.
Most GCC demand planning is still “last year plus a percentage.” Here's why that persists — and what genuinely good planning looks like against Ramadan surges, 90-day lead times and key-account concentration risk.
S&OP fails for one reason almost every time: it becomes a reporting meeting instead of a decision-making forum. Here's the architecture that changes that, and what 18 months of transformation actually looked like.
AI meaningfully improves demand planning in three places. Where the hype outruns reality is the assumption that better algorithms remove the need for human judgment. An honest assessment from someone who builds both.
+14 days of transit is not “a delay”. It is a permanent working-capital transfer and a variance problem — and the variance term is what actually drives your safety stock. Includes the GCC trap most planners fall into.
The UAE sits 33km from the Strait of Hormuz, beside a Red Sea corridor that saw +323% freight rates, and dependent on Black Sea wheat. Resilience here is not a backup plan in a drawer — here's what it actually requires.
A quantitative analysis of how geopolitical conflict translates into real cost and lead-time impact for GCC operators — with deep dives into the Red Sea crisis, the Ukraine-Russia war and Strait of Hormuz scenarios.
A 5% forecast accuracy gain cuts emergency air freight by AED 800K–1.2M a year. A 10% reduction in inventory days releases AED 3–5M in working capital. How to build the case in numbers a CFO will act on.
Execution is necessary but not differentiating. Transformation means diagnosing why a system underperforms, designing a better one, and sustaining it when conditions shift. What that distinction looks like in practice.
A concept study simulating demand shocks, the container crisis and Red Sea disruption across a regional distribution network — built around what GCC distributors actually faced between 2020 and 2024.
Free calculators for safety stock, EOQ, reorder point, MAPE, inventory turnover and carrying cost — no signup. Or get one operator's read on the Asia → Jebel Ali corridor each week.
Vinayak Bhadani — Demand planning & S&OP in Dubai, building supply chain tooling for GCC operators. Every model here is public: the code and commit history are on GitHub.