Logistics & Supply Chain Analytics
Your Control Tower Shows What Happened. It Should Show What's About to.
Most logistics control towers are dashboards with a name that implies more than they deliver. Sixty-five per cent of SLA breaches are detectable four or more hours before the customer feels them - in data your TMS and carrier feeds already hold. We connect it, analyse it, and build the intelligence and action layers that turn visibility into actual control.
Logistics Control Tower
Live · Updated 3 minutes ago
OTIF Rate
96.4%
+3.1%
SLA Alerts
3
Active
Load Util.
88.2%
+4.7%
Pick Accuracy
99.1%
-0.1%
Network average
Carrier SLA by Lane
DXB–AUH
97%
DXB–RUH
74%
AUH–JED
91%
SHJ–DXB
99%
FUJ–DXB
88%
DXB–KWI
68%
Freight Cost by Lane (AED/kg)
DXB–AUH
1.2
DXB–RUH
3.8
AUH–JED
4.1
SLA Risk - Active Alerts
Consignment #4471 - Hub dwell 6hr
Action window: 2hr
Carrier B - DXB-KWI trend -12%
Action window: 4hr
WH Zone C - Pick error rate +0.8%
Action window: Watch
65%
Of logistics SLA breaches are detectable 4+ hours before customer impact - in data you already hold
Layer 1
Most organisations have visibility. Layers 2 (intelligence) and 3 (automation) are where the value compounds
$984B
In excess inventory in consumer goods supply chains globally - most of it invisible until the period-end count
The Real Problem
A control tower that can see everything but act on nothing is not a control tower.
Most logistics organisations have built Layer 1: visibility. The dashboard shows shipment status, carrier performance, and OTIF trends. When something goes wrong, it appears on the screen. Usually after it has already affected the customer.
Layer 2 - intelligence - is where most organisations stall. The data to predict a breach is in the system. The model to identify at-risk consignments four hours before impact is not. Supplier performance is managed via email. Freight cost is analysed monthly. Inventory accuracy drifts between counts without anyone noticing until the physical reveals the gap.
Layer 3 - automation - is where the economics change. Exceptions routed to the right person. Carrier escalations triggered without a phone call. Replenishment signals fired before the stockout. That is what a control tower is actually for. We build all three layers - starting with the data foundation that makes them reliable.
SLA breaches visible on the dashboard - after the customer is already affected
The breach happened. The alert fired. The investigation begins. The intelligence that would have caught it four hours earlier was in the system - connected to nothing.
Carrier performance managed by aggregate - lane-level failure invisible
A carrier's overall compliance is 91%. On your most important lane it is 74%. The aggregate hides the problem until a customer complains enough times that someone builds a slide.
Inventory accuracy drifts between cycle counts - shrinkage invisible until the physical
Book stock and physical stock diverge daily. Nobody tracks the drift. By the time the physical count reveals the gap, the variance is months of accumulated loss with no traceable cause.
Freight spend analysed monthly in arrears - lane-level decisions made on stale data
By the time freight cost trends surface, you are three weeks into the following month. Lane-level routing decisions are made on rates from last quarter in a market that moved last week.
Who Feels the Pain
Every function in your logistics operation has a data problem. Each one is different.
Select your role to see the specific challenges your team faces - and exactly what MDI builds to resolve them.
Supply Chain Director
“End-to-end visibility - a slide in the deck, not a live capability”
What We Hear Every Time
Your control tower is a dashboard. It has no control.
Most organisations have built Layer 1 of the control tower: visibility. You can see what is late. What you cannot do is understand why it is late before the customer feels it, route around the problem automatically, or alert the right person with the right context in time to act. Visibility without intelligence is just an expensive way to watch things go wrong.
Sixty-five per cent of SLA breaches are detectable four hours before impact
The data that predicts a delivery breach is already in your systems - a pickup scan that is two hours later than the lane average, a carrier whose on-time rate on this route has been declining for three weeks, a consignment sitting at a transfer hub longer than the SLA-safe window. None of it triggers an alert. The breach happens. The customer calls. The investigation begins after the fact, not before it.
Supplier performance managed via email and spreadsheet - no system of record
When a supplier misses a delivery window or ships short, the exception is handled operationally - a phone call, an email, a note in a spreadsheet. Nobody aggregates those exceptions into a supplier performance score. Nobody spots the pattern. The same suppliers underperform systematically across quarters because there is no data layer that makes it visible until someone has time to build a slide.
What We Build For You
We build the intelligence and automation layers that your control tower is currently missing. Layer 2 (intelligence) adds predictive SLA breach detection - flagging consignments at risk 4+ hours before impact based on real-time signals across your carrier, warehouse, and transport data. Layer 3 (automation) closes the loop - routing exception alerts to the right person with the right context, triggering carrier escalations, and generating incident records without manual intervention. Supplier performance becomes a scored, tracked, governed discipline - not an email thread.
SLA breach detection 4+ hours before customer impact - predictive, not reactive
Supplier performance scored and tracked - every miss, every week, in one view
Exception management automated - right alert, right person, right context
The MDI Operating Model
Unify → Predict → Act. The three layers your control tower is missing.
Visibility is Layer 1. Intelligence is Layer 2. Automation is Layer 3. We build all three - on a data foundation that makes each layer reliable.
01
UNIFY
One Operational Data Layer Across Every Node
We connect your TMS, WMS, carrier data feeds, ERP, and supplier systems into a single governed data layer on Microsoft Fabric. Every shipment event, every warehouse transaction, every carrier scan, and every PO movement lands in one place - with lineage, schema enforcement, and a shared reference master that all functions read from.
- ›TMS + WMS + carrier API integration
- ›SAP TM, Oracle TMS, Manhattan, Blue Yonder, JDA / Blue Yonder, SAP EWM connectors
- ›Supplier PO and lead-time data integration
- ›Freight invoice and cost data pipeline
02
PREDICT
SLA Breaches Detected Before the Customer Feels Them
On a unified data foundation, we deploy predictive intelligence across your logistics network. Sixty-five per cent of SLA breaches are detectable four or more hours before customer impact - from pickup scan delays, carrier performance trends on specific lanes, and consignment dwell time at transfer hubs. We make that detection automatic.
- ›SLA breach prediction - 4+ hours before customer impact
- ›Carrier performance trend analysis by lane
- ›Inventory accuracy drift detection between cycle counts
- ›Freight cost anomaly detection by lane and carrier
03
ACT
Exceptions Routed. Actions Automated.
The intelligence layer is only useful if it closes the loop. We connect predictive signals to automated actions: exception alerts routed to the right person with the right context, carrier escalations triggered automatically, Power Automate workflows for warehouse replenishment and cross-dock routing, and executive dashboards updated in real time.
- ›Exception alerts - right person, right context, right time
- ›Automated carrier escalation workflows
- ›Warehouse replenishment signals via Power Automate
- ›Control tower Layer 3: action, not just visibility
Capabilities
Six analytics capabilities that move
the metrics that matter in logistics.
65%
of breaches detectable 4h+ early
OTIF & Carrier Performance Analytics
On-time in-full tracked by the hour, by lane, and by carrier - not assembled on Friday. Carrier SLA compliance broken down by route, service type, and time window. The renewal negotiation and the routing strategy are both grounded in lane-level truth, not aggregate averages.
4h+
before customer impact
Predictive SLA Breach Detection
Real-time signals - pickup scan timing, carrier trend data, hub dwell time - compared against lane-specific thresholds to flag at-risk consignments hours before impact. The customer call is pre-empted. The alternative routing decision is made while it can still change the outcome.
Task-level
productivity tracking
Warehouse Performance Intelligence
Pick accuracy tracked by zone, SKU, picker, and shift - automatically flagging error-rate outliers before customer complaints trigger the investigation. Labour productivity measured at task level: time per pick, idle time, travel time, and congestion patterns by location.
Live
not monthly in arrears
Freight Cost & Lane Analytics
Freight spend visible by lane, carrier, and cost centre - updated as invoices process, not three weeks after the period closes. Load utilisation reconciled: planned versus actual cube per vehicle movement. Cost per kg and cost per unit tracked at lane level, not blended across the network.
Actual
not contracted lead times
Supplier & Procurement Analytics
Supplier on-time delivery rate calculated from actual goods-received data - not from contract terms. PO fill rate tracked against commitment automatically, every line, every period. Actual lead times versus contracted lead times: the number that drives safety stock decisions.
Continuous
not at count time
Inventory Accuracy & Control
Inventory accuracy tracked continuously between cycle counts - drift flagged from daily movement reconciliation, not discovered at the physical count. In-transit inventory value tracked by shipment and by ageing, updated from carrier scan data. Shrinkage visible before the write-off.
Proof Stats
Numbers that come from logistics operations, not analyst estimates.
65%
Of SLA Breaches Detectable in Advance
Detectable 4+ hours before customer impact - from pickup scan delays, carrier trend data, and hub dwell time. Most organisations have the data. They do not have the intelligence layer to read it.
3 Layers
Control Tower Maturity Model
Layer 1 is visibility - most orgs have it. Layer 2 is intelligence - few have it. Layer 3 is automation - almost none. The value compounds at each layer. The investment in Layers 2 and 3 is where the ROI is.
$984B
In Excess Supply Chain Inventory
In consumer goods supply chains globally. The portion in transit - goods shipped but not received, invoiced but not delivered - represents working capital that is managed by nobody between period-ends.
Korpack
Packaging Manufacturing & Distribution · GCC
Challenge
Order management, production scheduling, and dispatch operated in separate systems with no shared data layer. On-time delivery tracked manually in Excel, weekly, always late. No visibility of where in the process an order had gone wrong.
Solution
Connected order management, production planning, and dispatch into a live end-to-end pipeline. OTD reporting automated from source data. Material yield tracked by run - giving operations and procurement a shared number to work from.
Results
Live
Order-to-Ship Visibility
Automated
OTD Reporting
Eliminated
Manual Tracking
Operations Team, Korpack
Direct Client
Technology Stack
Built on Microsoft Fabric. Integrated with your existing systems.
Microsoft Fabric
Unified data platform - Lakehouse, Delta Lake, real-time ingestion
Power BI
Control tower dashboards - OTIF, carrier, warehouse, freight cost
Azure Data Factory
TMS, WMS, carrier API, and ERP data integration pipelines
Power Automate
Exception routing, carrier escalation, replenishment workflows
Copilot Studio
Exception resolution assistant for logistics operations teams
TMS Integration
SAP TM, Oracle TMS, JDA / Blue Yonder - read-only, no config changes
WMS Connectors
Manhattan, Blue Yonder, SAP EWM, Infor, 3PL Central - standard and custom APIs
Azure ML
SLA breach prediction and carrier performance trend models
Common Questions
Questions logistics teams ask before they engage us.
What is the difference between a control tower and what you build?
Most control towers are Layer 1: visibility. You can see what is happening. What MDI builds adds Layers 2 and 3. Layer 2 is intelligence - predictive SLA breach detection, carrier trend analysis, inventory drift flagging. Layer 3 is automation - exceptions routed automatically, escalations triggered without a phone call, replenishment signals fired before the stockout. The layers are cumulative and built in order.
Can you integrate with our existing TMS without disrupting live operations?
Yes. We connect to SAP TM, Oracle TMS, and other transport management systems using read-only data extraction. No changes to your TMS configuration. The analytics and automation layer is fully separate from your transactional system. Live operations are never touched.
Which WMS platforms can you integrate with?
We have standard connectors for Manhattan Associates, Blue Yonder, SAP EWM, and Infor WMS. For other platforms we use standard API or database extraction. The typical integration timeline for a WMS data feed is 2–3 weeks from connector setup to first data in the Fabric layer.
How does SLA breach prediction actually work?
We build a predictive model on your historical shipment data - learning which signals on each lane correlate with late deliveries. Pickup scan timing relative to the lane average, carrier on-time trend over the trailing 30 days, consignment dwell time at transfer hubs relative to SLA-safe windows. The model runs continuously against live data and flags consignments that are trending toward a breach - before the breach window closes.
What does Phase 1 look like for a logistics operation starting out?
Phase 1 is typically a 10–12 week sprint: data foundation (TMS + WMS + one carrier feed), one primary use case (OTIF or SLA breach prediction), and an operations dashboard. The proof point is seeing a predicted breach caught before it impacts a customer - which typically happens in the first 4–6 weeks of live operation.
Start Here
Book a 30-minute Logistics Data Assessment.
We'll map your current data environment against the three control tower layers, identify where your most detectable SLA breaches are coming from, and outline what a Phase 1 intelligence layer looks like in your specific context.
30 minutes - your network, your data sources, your SLA structure
We identify which breaches are detectable in your current data
You leave with a Phase 1 control tower scope, whether you engage us or not
No slides. No generic deck. A direct operational conversation.