A spike in demand is a question, not an instruction.
A large retail network takes a great many decisions every day about assortment, purchasing, distribution, prices, promotion and the use of warehouse capacity. Mantikon is designed to analyse the chain not as a collection of independent shops but as one distributed system.
- Next waveDesigned as an application area; a demonstrated world model in this domain comes first.
- Who decidesRetail COO, category managers, commercial director
- Typical sourcesPOS, WMS, ERP, master data, demand forecasts, promotion calendar
- 01
Explain the spike
Mantikon establishes how far a change is seasonal, weather-driven, promotional or local before anything is reordered.
Evidence - 02
Compare the responses
Additional purchasing, reallocation between stores and a change to the delivery plan are compared on margin, transport cost and the risk that the spike is short-lived.
Alternatives - 03
Connect the consequences
A change in assortment affects stock, transport load, staffing need and overall profitability; the brief carries all four.
Trade-offs
A worked
example
Illustrative scenario, not a customer case.
In one region an unexpectedly high demand appears for a group of goods. The commercial agent forecasts the change in sales, the economic agent assesses margin, the logistics agent prices moving stock between stores, and the risk agent questions whether the surge will last.
The result is a coordinated plan for the network rather than a local reorder, with the assumption that would make it wrong stated explicitly.
The same model analyses the causes of write-offs, stock-outs, excess inventory and underperforming promotions.
Scope and
measures
Example workflows
Demand anomaly response · replenishment and reallocation · assortment review · promotion effectiveness.
Evaluation metrics
Out-of-stock rate · write-offs · stock turnover · margin per decision · forecast accuracy.
Discuss a retail decision use case