Digital Supply Chain Services

From Strategy to Execution

We deliver execution-led supply chain transformation and embedded decision systems that drive measurable ROI.
  • Fast time-to-value (pilot outcomes in weeks, not quarters)
  • Execution-first (not just slides—hands-on delivery)
  • Modular services (standalone projects or bundled transformation)
  • Designed for global operating realities.
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Outcomes clients hire us for

+10 - 33%

Forecast accuracy uplift

-15 - 40%

Stockout reduction

10 - 25%

Working capital release

-8 - 20%

Transportation cost reduction

+15 - 35%

Warehouse productivity improvement

+15 - 35%

Control tower visibility / disruption response improvement

Core Execution Services

AI-driven forecasting that upgrades S&OP performance and improves service levels with a practical, adoption-focused rollout.

Best for:

  • Chronic forecast error / bias and firefighting
  • High promo/seasonality volatility (Ramadan, peak campaigns, etc.)
  • Multi-channel demand signals (retail, ecom, distributor)

Typical deliverables:

  • Baseline vs AI forecast accuracy assessment
  • Pilot forecasting model + KPI dashboard
  • Demand scenarios + planner workflow design
  • Integration plan (ERP/planning tools) + operating cadence

Time-to-value: 2–3 months (pilot-ready)

Readiness checklist:

  • 24 months SKU-level history (ideal)
  • Defined planning cycle (monthly/rolling)
  • ERP access (API or export)
Reduce working capital trapped in inventory while protecting availability using segmentation + multi-echelon logic + AI-driven buffers.

Best for:

  • Overstock and aging inventory
  • Stockouts on A-items while B/C items accumulate
  • No clear service-level policy by segment/channel

Typical deliverables:

  • Inventory segmentation model (behavioral + criticality)
  • Safety stock & reorder logic (policy + parameters)
  • MEIO options (where applicable)
  • Working capital and service trade-off simulation dashboard

Time-to-value: 3–4 months

Readiness checklist:

  • 12–24 months inventory history + movements
  • Lead time variability logs (or receipts history)
  • Channel demand feeds (POS/ecom/distributor)
AI-enabled route, dispatch, and fleet orchestration—built to work even in fragmented 3PL/subcontractor ecosystems.

Best for:

  • Rising last-mile cost and missed OTIF
  • Poor fleet utilization / empty miles
  • No disciplined route planning / dispatch rules

Typical deliverables:

  • Logistics diagnostic (routes, fuel, idle, failed drops)
  • Pilot optimization in one zone/region
  • TMS/telematics integration approach (or interim workflow)
  • Ongoing performance dashboard + operating model

Time-to-value: 3–4 months

Readiness checklist:

  • Route history and delivery outcomes
  • GPS/telematics (ideal) or dispatch logs (minimum)
  • Basic cost data (fuel, tolls, fleet type)

Execution-Led Service Portfolio

AI-enabled supply chain capabilities delivered standalone or as integrated programs.

Supply Chain Strategy & Network Design

Design future-ready supply chain networks aligned to cost, service, and risk.

Best for:

  • Network inefficiencies and rising logistics cost
  • Market expansion or footprint redesign
  • Unclear service vs cost trade-offs

Typical deliverables:

  • Network scenarios & optimization models
  • Cost-to-serve analysis
  • Future-state roadmap

Time-to-value: 8–12 weeks

  • Readiness: Historical shipment & demand data

Warehouse Automation & Design

Execution-driven warehouse design optimized for throughput and scalability.

Best for:

  • Capacity constraints and labor dependency
  • New DC or warehouse upgrades
  • Low pick productivity

Typical deliverables:

  • Inside-out warehouse design
  • MHE & automation selection
  • Throughput simulation

Time-to-value: 10–16 weeks

  • Readiness: SKU, order profile & volume data

Procurement & Sourcing Optimization

Improve sourcing outcomes through analytics and execution discipline.

Best for:

  • Capacity constraints and labor dependency
  • New DC or warehouse upgrades
  • Low pick productivity

Typical deliverables:

  • Inside-out warehouse design
  • MHE & automation selection
  • Throughput simulation

Time-to-value: 10–16 weeks

  • Readiness: SKU, order profile & volume data

Operational Excellence & Continuous Improvement

Embed execution rhythm that sustains performance gains.

Best for:

  • Recurring firefighting
  • Inconsistent process adherence
  • Low KPI ownership

Typical deliverables:

  • Process standardization
  • KPI governance model
  • Execution cadence

Time-to-value: 6–12 weeks

  • Readiness: Existing KPI definitions

Supply Chain Visibility & Data Trust

Trusted, real-time visibility across multi-party ecosystems.

Best for:

  • Low shipment visibility
  • Compliance-heavy environments
  • Multi-stakeholder operations

Typical deliverables:

  • Control tower dashboards
  • Blockchain traceability models
  • Alert & exception workflows

Time-to-value: 8–14 weeks

  • Readiness: Event-level logistics data

AI-Powered Movement Optimization

Optimize routing, dispatch, and fleet utilization in real time.

Best for:

  • High last-mile cost
  • Missed OTIF targets
  • Fragmented 3PL ecosystems

Typical deliverables:

  • Route optimization models
  • Dispatch logic & rules
  • Fleet performance dashboards

Time-to-value: 6–10 weeks

  • Readiness: Route & delivery history

Generative AI for Supply Chain Planning

Augment planners with scenario reasoning and decision intelligence.

Best for:

  • Complex planning trade-offs
  • Low planning responsiveness
  • Heavy manual analysis

Typical deliverables:

  • GenAI planning assistants
  • Scenario simulation engines
  • Decision support workflows

Decision support workflows

  • Readiness: Structured planning data

Supply Chain Strategy & Network Design

Design future-ready supply chain networks aligned to cost, service, and risk.

Best for:

  • Network inefficiencies and rising logistics cost
  • Market expansion or footprint redesign
  • Unclear service vs cost trade-offs

Typical deliverables:

  • Network scenarios & optimization models
  • Cost-to-serve analysis
  • Future-state roadmap

Time-to-value: 8–12 weeks

  • Readiness: Historical shipment & demand data

Warehouse Automation & Design

Execution-driven warehouse design optimized for throughput and scalability.

Best for:

  • Capacity constraints and labor dependency
  • New DC or warehouse upgrades
  • Low pick productivity

Typical deliverables:

  • Inside-out warehouse design
  • MHE & automation selection
  • Throughput simulation

Time-to-value: 10–16 weeks

  • Readiness: SKU, order profile & volume data

Procurement & Sourcing Optimization

Improve sourcing outcomes through analytics and execution discipline.

Best for:

  • Capacity constraints and labor dependency
  • New DC or warehouse upgrades
  • Low pick productivity

Typical deliverables:

  • Inside-out warehouse design
  • MHE & automation selection
  • Throughput simulation

Time-to-value: 10–16 weeks

  • Readiness: SKU, order profile & volume data

Operational Excellence & Continuous Improvement

Embed execution rhythm that sustains performance gains.

Best for:

  • Recurring firefighting
  • Inconsistent process adherence
  • Low KPI ownership

Typical deliverables:

  • Process standardization
  • KPI governance model
  • Execution cadence

Time-to-value: 6–12 weeks

  • Readiness: Existing KPI definitions

Supply Chain Visibility & Blockchain Solutions

Trusted, real-time visibility across multi-party ecosystems.

Best for:

  • Low shipment visibility
  • Compliance-heavy environments
  • Multi-stakeholder operations

Typical deliverables:

  • Control tower dashboards
  • Blockchain traceability models
  • Alert & exception workflows

Time-to-value: 8–14 weeks

  • Readiness: Event-level logistics data

AI-Powered Movement Optimization

Optimize routing, dispatch, and fleet utilization in real time.

Best for:

  • High last-mile cost
  • Missed OTIF targets
  • Fragmented 3PL ecosystems

Typical deliverables:

  • Route optimization models
  • Dispatch logic & rules
  • Fleet performance dashboards

Time-to-value: 6–10 weeks

  • Readiness: Route & delivery history

Generative AI for Supply Chain Planning

Augment planners with scenario reasoning and decision intelligence.

Best for:

  • Complex planning trade-offs
  • Low planning responsiveness
  • Heavy manual analysis

Typical deliverables:

  • GenAI planning assistants
  • Scenario simulation engines
  • Decision support workflows

Decision support workflows

  • Readiness: Structured planning data

Technology That Delivers Measurable ROI

We apply AI and advanced analytics only where they remove friction, improve decisions, and produce measurable supply chain results.

Data Foundation

Operational data unified from ERP, WMS, TMS, IoT, and partner systems—cleaned and structured for execution.

ERP

WMS

TMS

APIs

Decision Intelligence

AI-driven models that evaluate trade-offs, test scenarios, and recommend executable decisions.

AI

Scenario Modeling

Forecasting

Planner Workflows

Embedded directly into daily planning and execution workflows—not standalone dashboards.

In-Workflow Decisions

Overrides

Alerts

Governance & Trust

Built-in controls, auditability, and governance applied only where risk and scale require it.

Controls

Auditability

Compliance

Measurable Value

Lower operating cost, released working capital, higher service levels, and faster decision cycles.

ROI

KPIs

Time-to-Value

Technology is never deployed for its own sake. Every component must support execution, adoption, and measurable financial impact.

Delivery models

Diagnostic Assessment (2–4 weeks)

  • Rapid assessment
  • Quantified opportunities
  • Roadmap + pilot scope

Pilot / Proof of Value (6–12 weeks)

  • Build + test in one region/category
  • KPI baseline vs improved outcome
  • Adoption plan

Scale & Transform (3–9+ months)

  • Rollout + integration
  • Governance + operating model
  • Capability transfer

Not sure where to start? Book a 30-min discovery call.

Book a 30-Min Discovery Call
Execution-Led Supply Chain Technology Consulting

Digital Chain Acceleration Program

Wave 1

Diagnostics & Forecasting

S&OP maturity + AI-driven demand planning

Wave 2

Execution Optimization

Logistics + inventory + warehouse AI + blockchain components where needed

Wave 3

Resilience Building

GenAI planning + control tower + ESG compliance

How we work (and why it sticks)

Outcome-first KPIs

Measurable results agreed upfront—before any execution starts.

Practical data approach

Works with imperfect ERP and real-world data constraints.

Adoption built-in

Planner-friendly workflows, override controls, and training.

Governance & cadence

Not a one-off study—embedded operating rhythm.

Modular execution

Start small. Scale only what proves value.

Vendor-neutral

Support selection & RFPs without pushing tools.

Frequently Asked Questions

We typically work with mid-market and enterprise organizations, including public-sector entities and complex logistics operators.
We do both. Execution is core to our model—we design, pilot, and stay engaged through implementation, not just advisory slides.
Yes. We frequently run pilots using interim workflows, data extracts, or parallel tools before full system integration.
Order history, inventory data, basic master data, and operational logs. We design solutions that work with imperfect ERP realities.
Pricing depends on scope and engagement type. We offer fixed-fee projects, time & materials, and retainer-based execution support.
Absolutely. We work alongside existing ERP, WMS, and TMS platforms and design execution layers that integrate cleanly.
Yes. We are vendor-neutral and support tool evaluation, RFP creation, and selection without pushing specific software.
Logistics, supply chain, defense, public sector, mobility, manufacturing, and complex distribution networks.

Ready to unlock measurable supply chain ROI?

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