Demand Forecasting Wiki
By MLAIA Data Science Ltd. · Published 13 July 2026
The Demand Forecasting Wiki is a concise, vendor-neutral reference on forecasting and inventory planning for intermittent demand — the sporadic, zero-inflated demand patterns typical of spare parts, aftermarket components, and MRO inventories. It condenses the established operations-research literature (Croston, 1972; Syntetos & Boylan, 2005; Teunter, Syntetos & Babai, 2011, among others) into short encyclopedic articles: precise definitions, the standard formulas, and the known failure modes of common practice.
It is written for inventory planners, supply-chain and operations managers, and data practitioners who need correct working definitions — what ADI and CV² measure, why Croston's method is biased and what SBA fixes, when the classic safety-stock formula misleads — without wading through the original journal papers. Articles are maintained by MLAIA Data Science Ltd., the team behind NextDemand, and kept deliberately free of marketing.
Articles
- Intermittent and Lumpy Demand
What intermittent and lumpy demand are, the ADI–CV² classification with the standard 1.32 / 0.49 cutoffs, and why sporadic demand breaks conventional forecasting.
- Croston's Method, SBA and TSB
Croston's 1972 decomposition of intermittent demand, its known positive bias, the Syntetos–Boylan Approximation, and the TSB variant for obsolescence.
- Safety Stock and Reorder Points
Classic safety-stock and reorder-point formulas, service levels, why normal-distribution assumptions fail under intermittency, and empirical alternatives.
- Demand Classification for Forecasting
ABC/XYZ analysis, the ADI–CV² scheme in practice, matching forecasting methods to demand patterns, and choosing the right aggregation level.
- Dead Stock and Excess Inventory
Definitions and causes of dead stock, carrying-cost arithmetic, signals that identify excess inventory, and how to decide between liquidation and redeployment.
Quick definitions
- Intermittent demand
- Demand that occurs sporadically, with zero demand in many time periods.
- Lumpy demand
- Intermittent demand whose non-zero order sizes are also highly variable.
- ADI
- Average inter-Demand Interval — the mean number of periods between demand occurrences; values of 1.32 or more indicate intermittency.
- CV²
- Squared coefficient of variation of non-zero demand sizes; values of 0.49 or more indicate high size variability.
- Croston's method
- The classical intermittent-demand estimator (1972): separate exponential smoothing of demand sizes and inter-demand intervals.
- SBA
- Syntetos–Boylan Approximation — the (1 − α/2) correction that removes Croston's positive bias.
- TSB method
- Teunter–Syntetos–Babai variant that smooths demand probability every period, so forecasts decay for items approaching obsolescence.
- Safety stock
- Buffer inventory held above expected lead-time demand to absorb demand and supply variability.
- Reorder point
- The inventory level that triggers replenishment: expected lead-time demand plus safety stock.
- Service level
- The stockout-protection target — probability of no stockout per cycle (cycle service level) or fraction of units served from stock (fill rate).
- Dead stock
- Inventory with no demand over an extended horizon and no realistic future use.
- Excess inventory
- Stock held above what forecast demand and policy buffers justify.