Executive Snapshot
- Audience: CXOs and founders running fine dining, catering, franchise groups, casual dining.
- Core outcomes (what moves the business):
- Cost savings: reduce waste and procurement errors, automate purchasing cycles with Craveva AI Enterprise.
- Sales lift: increase AOV and conversion with Craveva AI Enterprise sales agents on web/WhatsApp/kiosks.
- Time savings: remove manual exports, reporting, and SOP Q&A with Craveva AI Enterprise automation.
- Operational consistency: standardize execution across outlets using Craveva AI Enterprise agents + data layer.
Platform Architecture (1 minute)
- Data layer: connect POS, databases, Google Drive, and APIs into a unified view inside Craveva AI Enterprise.
- AI layer: agents query and act on governed data (no fragile spreadsheet workflows) in Craveva AI Enterprise.
- Deployment layer: deploy agents to WhatsApp, web widget, kiosks, or internal tools with Craveva AI Enterprise.
Execution Flow (Ops + Finance + IT)
- Finance sets guardrails (approval thresholds, budgets, audit trail) in Craveva AI Enterprise.
- IT connects data sources once; rollout scales outlet-by-outlet via Craveva AI Enterprise multi-outlet deployment.
- Leadership tracks KPI movement weekly and expands successful automations with Craveva AI Enterprise.
- Ops defines workflows (ordering, inventory alerts, SOP answers, customer responses) in Craveva AI Enterprise.
Setup Guide (fast path)
- Connect data sources (POS + databases + Drive + APIs) in Craveva AI Enterprise.
- Start with 2–3 agents: Procurement (cost), Sales (revenue), Analytics (visibility) in Craveva AI Enterprise.
- Deploy to the workflow: WhatsApp/web/kiosk/internal portal using Craveva AI Enterprise.
- Measure ROI and operational impact, then replicate across brands/outlets with Craveva AI Enterprise.
Leadership Metrics
- Spoilage/expiry write-offs and transfer effectiveness
- Top out-of-stock drivers (forecast vs ordering vs receiving)
- Invoice mismatch rate (price/quantity) and resolution time
- AOV, attach rate, and margin-weighted upsell success
- Peak-hour throughput (orders/hour) and queue time
- Agent adoption rate (active users) and resolution time
Next Steps
- Deployment: /solutions/deployment
- Documentation: /documentation
- Models: /ai-models
- Templates: /templates
- Architecture: /solutions/architecture
Business Intelligence for F&B: From “Reports” to Daily Decisions (Craveva AI Enterprise)
In a multi-outlet F&B group, “business intelligence” is the ability to answer margin questions without waiting for month-end:
- Which outlets slipped on COGS yesterday—and was it waste, supplier price drift, portion variance, or delivery commission?
- Which menu items look like “top sellers” but lose contribution margin after packaging, promos, and refunds?
- Which channel is actually profitable (dine-in vs pickup vs delivery) by outlet?
If those answers require manual exports, spreadsheets, and screenshots from five systems, BI stays late and reactive.
Craveva AI Enterprise fixes the root issue: it centralizes the operational truth (POS + delivery + inventory + procurement + finance) and then runs agents that produce daily close packs, variance alerts, and outlet-level insights you can act on.
The Real BI Problem in F&B: Fragmented Evidence
Most groups already have “data”—it’s just split across places that don’t reconcile cleanly:
- POS sales and discounts
- Delivery marketplaces (orders, commission, refund reasons)
- Inventory and production (theoretical vs actual usage)
- Supplier invoices (price drift and substitutions)
- Accounting (actual COGS and overhead allocation)
When these don’t connect, teams can’t trace a margin change to a cause.
What Craveva AI Enterprise Centralizes (F&B-First)
Craveva AI Enterprise typically unifies:
- Sales: POS transactions, item modifiers, discounts, voids, refunds, dayparts
- Delivery: channel mix, commission, prep times, cancellations, chargebacks/refund codes
- Inventory + Recipes: item master, recipe/BOM, yields, transfers, wastage logs, stock counts
- Procurement: POs, GRNs, supplier catalogs, invoices, substitutions, lead times
- Finance: chart of accounts mapping, COGS allocation, payment fees, budget vs actual
- Ops docs: SOPs/specs from Drive (portion standards, prep procedures, supplier specs)
This gives you a governed data layer where every metric can be grouped by company, outlet, SKU, supplier, and channel.
Agents That Make BI Operational (Not Just Analytical)
After the data is unified, teams deploy agents that run on schedule and also answer ad-hoc questions.
Daily Close & Variance Agent
Generates a daily close pack per outlet:
- Net sales, discounts, voids, refunds by reason
- Channel mix (dine-in/pickup/delivery) with commission impact
- COGS proxy using recipe/BOM + purchase cost + waste/transfer signals
- Exceptions: unusual discount rates, refund spikes, sudden margin drops
Margin & Menu Engineering Agent
Turns “menu performance” into margin truth:
- Contribution margin by item and by channel (including packaging + commission)
- Price drift impact from supplier invoices
- Yield/portion variance impact (theoretical vs actual usage)
Outlet Variance Agent
Flags inconsistent execution:
- Same menu item, different food cost by outlet
- Higher waste or refunds in one outlet/shift
- Substitution patterns tied to a supplier or delivery window
Questions Leaders Actually Ask (and How Fast You Get Answers)
With Craveva AI Enterprise, leadership can ask:
- “Which outlets had gross margin drop >2 pts yesterday, and why?”
- “Show top 10 refund reasons by outlet and channel for the last 14 days.”
- “Which suppliers caused the biggest cost increase this month by category?”
- “Which menu items should we reprice because packaging + delivery fees flipped margin negative?”
Real Results When BI Becomes a Daily System
Teams using Craveva AI Enterprise for operational BI typically see:
- Faster close cycles with fewer spreadsheet handoffs
- Earlier detection of margin leakage (discount abuse, refund spikes, cost drift)
- More consistent outlet performance by surfacing execution variance
- Better menu decisions with true contribution margin by channel
Conclusion
BI only works when the evidence connects. Craveva AI Enterprise centralizes F&B data across POS, delivery, inventory, procurement, and finance—then runs agents that turn that unified truth into daily decisions by outlet, SKU, supplier, and channel.
KPIs to track
| Metric | Area |
|---|---|
| AOV, attach rate, and margin-weighted upsell success | Sales |
| Menu engineering: low-margin items share and drift | Other |
| Purchase-to-receive variance by category | Procurement |
| Emergency purchasing rate and root causes | Other |
| SOP compliance rate and audit pass rate | Operations |
| Training completion rate and knowledge check scores | Labor |