The picture your S&OP meeting
is currently arguing about.
Six-quadrant supply chain dashboard. OTIF, DIFOT, fill rate, in-transit visibility, supplier OTIF, freight cost. Lead and lag together. Built on Microsoft Fabric. The S&OP meeting opens this, not six different exports.
The Problem
Patterns we see in every engagement
S&OP arguments are usually data arguments. Planning, warehouse, customer service and finance each look at a different number for the same week. The dashboard ends that argument — six quadrants, one truth.
Planning, warehouse and customer service each on a different number.
Planning uses an Excel pull from SAP. Warehouse uses the WMS. Customer service uses the CRM. All three are correct at different timestamps. The S&OP meeting argues for 30 minutes before getting to the actual decision.
Alerts that page the whole DL instead of the right person.
When OTIF drops below threshold, the email goes to a distribution list of 14. Nobody owns it. Nothing happens until the next weekly meeting. We wire alerts to the named person who can act, with escalation rules that fire only on real outliers.
S&OP cadence is monthly. The data needs to be weekly.
Demand is moving. Supplier reliability is moving. The monthly cycle does not match the disruption rhythm. The dashboard becomes the venue for the new weekly cadence, not a replacement for the monthly review.
In-transit visibility ends at the dispatch dock.
Once goods leave your DC, you stop seeing them until they arrive. Customer chases happen blind. We integrate carrier EDI 214 messages and visibility providers (Project44, FourKites, GoComet) so ETA accuracy becomes a KPI.
What we build
What we build
Six quadrants on one screen. Each tile drills to the transaction so the meeting does not pause for a query.
Demand signal — POS-out, sell-out, order intake
Replaces
The Tuesday Excel from Sales showing last week's orders with no context for what is happening at distributor or shelf level.
- POS-out feeds from key customers (where shared), distributor sell-out, internal order intake
- Forecast vs actual with rolling 13-week and 52-week comparison
- New-promo lift visible against baseline — promo effectiveness becomes a measured metric
- Customer-level demand pattern shifts surface week 2 of the change, not month 3
Demand signal arrives weekly with named pattern shifts. Planning stops working blind.
Inventory position — DIO, fill rate, on-hand vs perpetual
Replaces
The 'we are mostly fine on inventory' line that hides A-class stockouts in the aggregate.
- DIO per SKU class per location — A-class lean, C-class loose, D-class flagged
- Fill rate order-line and case fill — customer scorecard reconciliation
- Cycle-count variance flagged at SKU level
- Drill from aggregate to specific SKU and lot
Inventory conversations get specific. Working capital decisions get evidence.
Production status — OEE, plan vs actual, quality holds
Replaces
The end-of-week production report that arrives Monday and reports last Wednesday's lines.
- OEE refreshed live from PLC — see oee-dashboard for detail
- Plan vs actual per line per shift — predictive trajectory to end-of-day
- Quality hold count and value held — visible to supply chain, not just quality
- Scrap rate trend so material variance and quality variance separate cleanly
Production data is current. Supply chain plans against real output, not last week's narrative.
Order fulfilment — OTIF, DIFOT, perfect-order rate
Replaces
The OTIF that is computed differently across plants and the DIFOT that customer scorecards measure but your team does not track.
- OTIF measured from dispatch promise vs delivery confirmation — your number
- DIFOT measured from customer PO date vs goods receipt — the customer's number
- Perfect-order rate composite: DIFOT × invoice accuracy × damage-free
- Reconciliation to customer scorecards (Lulu, Carrefour, Coles, Woolworths)
Customer-side metrics surface inside the same dashboard. Chargeback disputes get evidence.
Inbound supply — supplier OTIF (SIFOT), in-transit ETA accuracy
Replaces
The blind spot between PO confirmation and dock arrival where 'where is my container' lives in a WhatsApp group.
- Supplier OTIF (SIFOT) per supplier per category — predicts your DIFOT 2–4 weeks ahead
- EDI 214 carrier message integration for live in-transit ETA
- Visibility provider integration (Project44, FourKites, GoComet) where used
- Exception alert when supplier OTIF drops or ETA slides beyond threshold
Inbound supply pattern is visible at the same cadence as outbound. Supplier conversations get a metric.
Cost and cash — freight $/unit, inventory write-off pipeline
Replaces
The freight cost line on the P&L that finance sees once a month and supply chain never sees in detail.
- Freight cost per unit / per pallet / per container — by lane, by carrier
- Warehouse cost per touch — pick-and-pack labour as proportion of throughput
- Inventory write-off pipeline — what is at risk in next 30 / 60 / 90 days
- Days-on-hand cash — working capital tied up in inventory at SKU class level
CFO and supply chain see the same numbers. Cost conversations stop happening month-end-only.
How we work
From data map to live control tower in 6 weeks
We map the S&OP cadence first. The dashboard supports the meeting — it does not replace it. Without that anchor the dashboard becomes wallpaper.
01
Discover — map S&OP cadence and data sources
Two weeks. Map your S&OP cadence and decision rights. Map the data sources for each quadrant. Score data quality per quadrant. Define alert thresholds with operations and customer service.
02
Prototype — six-quadrant view for one region
Two weeks. Build the six-quadrant executive view for one region or business unit. Parallel-run against the current reporting set for 2 weeks. S&OP meeting opens this. Old reports go on archive.
03
Deploy — all regions, named alerts, named owners
Four to six weeks. Roll out across regions. Wire alerts to named owners with escalation paths. Train each persona — planner, warehouse, customer service, supply chain leadership — on their scoped view.
Technology stack
Lakehouse
Visualisation
Automation
ERP
Transport & Visibility
Operational
Common questions
What buyers ask us
We already have a TMS / WMS dashboard. Why this?
Most TMS/WMS dashboards are operational — they answer 'what is the warehouse doing right now'. The supply chain dashboard is decisional — it answers 'are we going to miss the customer commitment'. Different question, different audience, different shape.
Can we integrate it with SAP Analytics Cloud / SAP BW?
Yes. We have moved several clients off SAC for operational analytics — Fabric is faster and cheaper at this shape. SAC stays useful for SAP-internal statutory reporting. See blog/sap-analytics-cloud-alternative-mid-market.
How do we measure if it is working?
Adoption and decision time. The dashboard is working if the S&OP meeting goes from 90 minutes to 45 and the decisions made get logged. We instrument both on day one.
What about Snowflake / Databricks?
We ship on both when the client estate requires. For most mid-market industrials on Microsoft 365 + Azure, Fabric is the right answer. For heavy data-science workloads or multi-cloud, Databricks may fit. We assess in Discover.
How much does it cost?
Discover USD 10,000–14,000. Prototype USD 22,000–38,000. Deploy USD 50,000–140,000 depending on geography, source count and carrier integration.
Ready to move
Book a 30-minute Supply Chain diagnostic
30 minutes with Amit. No slides. No pitch deck. No obligation to proceed. We walk through your current S&OP cadence and the six quadrants — and where the gap is biggest.