Strategic Network Design
‘Beware, lest you lose the substance
by grasping at the shadow.’
Why Strategic Network Design is Essential
In an era of extreme volatility, Strategic Network Design is no longer optional; it is the foundation of resilience. Organizations must move beyond static planning to dynamic architectures that withstand global disruptions.
According to Deloitte and PwC, companies that prioritize end-to-end supply chain visibility and structural agility report significantly higher margin resilience and outperform competitors by 20% in market responsiveness.
EY research confirms that firms adopting advanced network modeling achieve significantly higher EBITDA margins compared to those relying on legacy, fragmented planning methods.
A robust network design ensures performance optimization by aligning physical assets with fluctuating demand signals.
Core Considerations in Network Design
Effective design requires a holistic evaluation of the entire value chain.
Core considerations include:
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Total Landed Cost: Analysing the full economic impact of sourcing and distribution
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Total cost-to-serve analysis: Driving profitability at the product and customer level
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Customer Proximity: Balancing service level agreements (SLAs) against logistics overhead
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Geographic footprint optimization: Reducing lead times and logistics costs
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Multi-echelon sourcing: Alleviating dependency on single-region suppliers
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Risk Mitigation: Identifying single points of failure within the supply chain
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Regulatory Compliance: Future-proofing operations against changing trade policies
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Sustainability Objectives: Reducing carbon emissions in line with corporate policies
The Power of the Digital Twin
Creating a Digital Twin allows for high-fidelity simulation of your entire supply chain. By modelling real-world constraints in a virtual environment, you can quickly stress-test scenarios before committing capital, ensuring data-backed decision-making.
PwC highlights that leaders utilizing digital twins achieve a 30% reduction in operational expenditures by identifying inefficiencies that remain invisible in traditional spreadsheets.
Network Modelling Tools
To execute complex designs, our team of highly experienced and respected engineers leverage market-leading, sophisticated analytical platforms - technologies that are recognized in Gartner® Magic Quadrant™ for Supply Chain Planning:
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AIMMS SC Navigator: A powerful, scalable environment that facilitates prescriptive analytics, allowing teams to solve intricate supply chain problems and drive strategic alignment.​
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Optilogic (Cosmic Frog): A cloud-native platform that enables rapid, large-scale supply chain design and risk simulation with unmatched computational speed.​
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Sophus X: A specialized tool designed for high-fidelity capacity planning and network optimization, providing granular control over complex logistics variables.​
Our super-users - with decades of network modelling experience - have built countless complex end-to-end supply chain network models utilising these tools, delivering significant value for our customers.
Key Benefits of Strategic Network Design
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Cost Efficiency: Streamlining node locations and distribution flows results in improved service levels and substantial bottom-line savings
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Superior Agility: Real-time modelling capability enables ability to rapidly pivot operations during market shifts
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Maximised Resilience: Proactive identification of vulnerabilities ensures business continuity​
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Data-Driven Decisions: Eliminating guesswork through rigorous mathematical modelling
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Competitive Advantage: Faster time-to-market, superior service consistency with strategic placement of assets reducing working capital requirements
How can we help?
We will always take time to listen to our customers to understand:
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current network performance inc. real pain points
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business issues experienced due to inconsistent / inaccurate data, flows or processes
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your specific needs and requirements for Strategic Supply Chain modelling
Contact us to discuss your specific requirement(s) with one of our experienced team.​
