Supply Chain strategy
Connect your operational priorities to your business goals. Explore network design, resilience and a practical roadmap for change.
Our services
Make the next move count.
Combining Supply Chain expertise with AI to solve complex business problems, turn data into meaningful measures and enable faster, better-informed decisions.
From discussion to direction
Working through the challenge, together.
Consultancy starts with a shared understanding. Explore priorities, test assumptions and develop a practical route from business objectives to operational change.
Discuss your priorities →Operational improvement
Reduce waiting, excess stock, unnecessary handling and rework across planning, inventory and logistics. Improve flow and tackle the causes of waste.
Transformation & delivery
Translate strategy into coordinated action through governance, stakeholder alignment and measurable implementation plans.
An engagement shaped around you
A clear route
from challenge to change.
The scope, deliverables and measures of success would be agreed around your business needs.
01 / Discover & diagnose
Review available data, processes and stakeholder perspectives to establish the starting point.
02 / Design & prioritise
Develop options and a phased roadmap with clear dependencies and ownership.
03 / Support & review
Support implementation and assess progress against the agreed objectives.
Explore our knowledge
Find expertise for your challenge.
Explore our connected areas of expertise, from warehouse operations to business intelligence and change.
Explore Expertise →Better flow. Less waste.
Keep work moving.
Remove what adds no value.
A smoother Supply Chain starts with understanding where work, stock and information stop—and why.
Waiting for approvals, operational delays, excess inventory and unnecessary handling all consume time and resources. Damaged, expired or obsolete stock creates further waste through rework, write-offs and disposal.
We help map the end-to-end flow, distinguish value-adding work from avoidable activity and investigate root causes. Lean and Six Sigma techniques can support this work where appropriate: value-stream mapping to expose delays, data analysis to understand variation, and structured improvement cycles to test changes.
The aim is a more frictionless flow of goods and information, balanced with quality, safety, resilience and customer service. Measures such as lead time, stock ageing, damage and first-time-right performance help teams assess progress and sustain improvements.
Explore Supply Chain improvement →Resilience · Digital transformation · Sustainability
Translate changing priorities into practical decisions.
A more resilient network.
Explore sourcing diversification and location choices such as nearshoring, reshoring and China Plus One. Balance geographic risk with capability, customer service and total cost.
Explore Supply Chain management →Connected processes and data.
Build end-to-end visibility and process-led ERP requirements. Consider procure-to-pay automation and practical AI adoption where data, controls and integration support the business case.
Explore enterprise systems →Evidence-led sustainability.
Connect waste reduction, traceability and transport efficiency with better operational information. Define the data and responsibilities needed to support decarbonisation and wider environmental, social and governance (ESG) priorities.
Explore reporting and insight →Scope is agreed around your requirements, with specialist assurance, emissions accounting or sourcing advice brought in where needed. Traceability supports evidence; it does not by itself prove ethical sourcing.
AI & algorithm development
Turn complex problems into better decisions.
Use AI to help develop, test and refine algorithms around a clearly defined business problem.
Forecasting demand, allocating resources, scheduling work and balancing inventory involve competing priorities and constraints. We can help frame the problem and shape an approach that combines AI, mathematical optimisation and business rules where each is appropriate.
Start with the decision to improve, the data available and the limits the solution must respect. Develop and test candidate algorithms against a baseline, then review accuracy, feasibility and business value with the people who will use the results.
Human oversight, data protection and ongoing monitoring form part of the design. The aim is a useful, explainable decision process, with delivery scope and specialist development support agreed for the engagement.
Explore AI and decision support →New technology. Long-standing challenges.
From insight to coordinated action.
We actively explore how AI and software agents can help solve persistent Supply Chain problems—reducing manual effort, anticipating disruption and moving decisions into delivery.
Anticipate and prioritise.
Forecasting models can estimate demand or delivery risk. Agents can bring those outputs together with stock, orders and supplier updates, flag exceptions and direct attention to the most urgent issues.
Evaluate the options.
Optimisation algorithms can compare inventory, capacity, scheduling and transport choices against agreed constraints. Agents can assemble the inputs, request calculations and present options for a business decision.
Coordinate the next step.
Within authorised workflows, agents can prepare replenishment proposals, chase missing information, create follow-up tasks or draft customer updates. Higher-impact actions—such as placing orders, changing commitments or releasing payments—can require human approval.
For example, a potential late inbound shipment could trigger an agent to check affected customer orders, request alternative supply or transport options, and prepare a recovery recommendation. Once approved, connected systems can carry out permitted steps and record the outcome.
We start with a bounded use case, measurable outcomes and a comparison with today’s process. Data quality, access permissions, testing, monitoring and a clear escalation route determine how much autonomy is appropriate. Technology should earn its place through useful results.
Discuss an AI or agent opportunity →