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AI-Enabled Merchandising Hub — Real-time Inventory & AI Replenishment Hub

Emart24 · Posted 1 year ago

Retail and e-commerceConversational AI / ChatbotsPredictive Analytics / ForecastingAnomaly Detection / Fraud DetectionSearch & Knowledge Retrieval
Budget
To be determined
Timeline
Not specified
Closed on
29 Nov 2025, 23:59 ICT

Problem statement

Xilnex (store POS/inventory) and Business Central (HQ finance) are not integrated. Merchandisers lack a single, real-time view of stock, replenishment decisions are slow and manual, RTV and planogram management are inefficient, and Finance receives noisy postings. We need a central hub that links both systems, provides real time stock visibility, and delivers AI-assisted replenishment, RTV automation and planogram suggestions while producing clean postings for Business Central.

Expected outcomes and success metrics

- Real-time stock update speed across stores & HQ - Target: Pilot ≤ 5 min → Scale ≤ 1 min. - Stock on shelf - Target: Pilot ≥ 90% → Scale ≥ 95%. - Stock-outs / OOS - Target: Reduce 30% in pilot → 45% at scale. - Over-stock / excess - Target: Reduce 20% in pilot → 35% at scale. - Forecast error - Target: ≤ 20% in pilot → ≤ 15% at scale. - Auto-replenishment coverage - Target: ≥ 50% in pilot → ≥ 75% at scale. - Store fulfilment rate - Target: ≥ 96% in pilot → ≥ 98% at scale. - Time to place orders - Target: Shorten by 40% in pilot → 60% at scale. - RTV accuracy - Target: ≥ 85% accurate in pilot → ≥ 90% at scale. - RTV Time - − 35% time in pilot → − 50% at scale. - Planogram compliance - Target: ≥ 85% in pilot → ≥ 93% at scale. - Finance auto-match - Target: ≥ 85% auto-match in pilot ≥ 95% at scale

Current process

Systems & integration: Xilnex is used for store POS/inventory and Microsoft Business Central for finance. RTV is handled manually, and planogram reviews are spreadsheet-based. There is no automated integration between these systems. Store-level SOH visibility: There is no real-time view of stock on hand at the store level. Stores place orders based on experience and judgement. After promotions, unsold stock requires time-consuming manual counts, leading to delays and, at times, product expiry or missed return windows. Procurement & replenishment (Dry Stock): Procurement relies on daily email reports from the 3PL (Aging Stock, Order Fulfilment, Shipping Summary, Receiving Fulfilment/Summary, Store Sales in units, Supplier Lead Time, and Delivery Schedules vs warehouse receiving). These are largely compiled manually. Planogram updates: Updates to stores are slow. Trend analysis and guidance are manually compiled by store cluster (e.g., transport hubs, CBD, street stores, universities). End-to-end visibility: There is no real-time linkage from store SOH → procurement’s multi-channel stock view → merchandisers’ category sales view. This limits timely decisions and optimization of assortment and opportunities by cluster.

Current solution

- Systems & integration: Xilnex is used for store POS/inventory and Microsoft Business Central for finance. RTV is handled manually, and planogram reviews are spreadsheet-based. There is no automated integration between these systems. - Store-level SOH visibility: There is no real-time view of stock on hand at the store level. Stores place orders based on experience and judgement. After promotions, unsold stock requires time-consuming manual counts, leading to delays and, at times, product expiry or missed return windows. - Procurement & replenishment (Dry Stock): Procurement relies on daily email reports from the 3PL (Aging Stock, Order Fulfilment, Shipping Summary, Receiving Fulfilment/Summary, Store Sales in units, Supplier Lead Time, and Delivery Schedules vs warehouse receiving). These are largely compiled manually. - Planogram updates: Updates to stores are slow. Trend analysis and guidance are manually compiled by store cluster (e.g., transport hubs, CBD, street stores, universities). - End-to-end visibility: There is no real-time linkage from store SOH → procurement’s multi-channel stock view → merchandisers’ category sales view. This limits timely decisions and optimization of assortment and opportunities by cluster.

Target users and impacted teams

Merchandising & Category Managers Store Operations & Store Managers Supply Chain / Logistics Planners Finance (GL / COGS reconciliation) IT / Integration teams Inventory Audit team

Data availability and readiness

TBD

Integration, deployment and infrastructure

TBD

Relevant AI technologies

Conversational AI / ChatbotsPredictive Analytics / ForecastingAnomaly Detection / Fraud DetectionSearch & Knowledge Retrieval