Published by
Published on
May 11, 2026
Authored by Nate Rosier, Chief Customer Officer at enVista
Tariff and freight volatility, nearshoring mandates, rising oil prices and AI disruption are hitting supply chains all at once. Whether they want to or not, supply chain executives are being forced to redesign their networks — or let the market do it for them. The reality in the modern supply chain is that rather than being an occasional hurdle to overcome, disruption has become the industry’s new baseline.
To succeed in such constant volatility, supply chain leaders need to change their mindsets from, “do we need to redesign our supply chain?” to, “are we redesigning our supply chain often enough?” This mindset shift is what drives the most meaningful results from redesigns, like up to 15 percent or more in total supply chain cost reduction.
In times of market volatility, completing a supply chain design that delivers significant cost savings become even more imperative. In this blog, we will talk about what causes suboptimization in a supply chain and where the most cost savings can be found in a redesign.
Suboptimization across the supply chain is often a symptom of poor data. Businesses undergo many changes as they develop and grow. New systems are added, SKUs are adjusted and acquisitions occur. Often, over time, data systems have been stitched together by many people using different methods.
Across inventory levels, SKU profiles, freight spend and more, many organizations either don’t have the data, have it spread across several disparate systems or don’t know how to operationalize it to make decisions. When this happens, the root cause of overspending becomes masked in a way that a supply chain design is uniquely equipped to unmask.
For example:
The modeling process of network design exposes inaccuracies in SKU, supplier or transportation data, highlighting opportunities to improve data integrity across the organization.
The new world of supply chain design uses continuous scenario modeling and AI‑assisted analysis to provide answers in hours instead of weeks. AI can now synthesize fragmented data across systems and evaluate hundreds of network scenarios in the time it would otherwise take just to gather the inputs.
This can enable supply chain leaders to operate with a future-focused approach and to make sound, data-driven business decisions.
While the starting point of your supply chain will play a role into how significant of savings a design will give you, most organizations can benefit from cost savings in a few recurring areas.
Inventory is one of the largest capital investments for product-based businesses, and it is also one of the most common root causes for high operational costs. The majority of supply chains have some serious cost saving potential tied up in poor inventory allocation. This is because poorly positioned inventory can cause:
Without network‑level visibility, a lot of organizations simply have no real idea how much they’re spending on freight costs each year. Supply chain design uses cost-to-serve modeling to break down spend by lane, mode and customer, enabling more accurate budgeting and rate negotiation
Network modeling reveals:
Intentional transportation design can also cut inbound spend by more than half by minimizing waste, reducing freight costs and preventing unnecessary touches.
These insights often unlock transportation savings without sacrificing service, simply by aligning inventory and fulfillment strategies to true demand patterns.
Warehouse space is incredibly limited, and many facilities are either nearing or past the recommended 85 percent utilization level. This is a fast-track to inflated operational costs.
As distribution centers (DC) reach capacity, travel times lengthen, touches increase and labor productivity suffers. Many facility leaders think they’re saving money by avoiding off-site storage costs, but the duplicate movements that result from facility congestion can be equally expensive in variable labor costs.
Keeping your distribution centers within effective capacity across footprints, flow paths and transportation routes can save you 10 to 20 percent of your operational costs. Supply chain design exposes capacity constraints and what’s causing them, helping warehouse operators avoid unnecessary expansions while restoring efficiency.
Improved visibility across the business can reduce your gap between expected and actual costs to two percent
Lead time is a hidden cost multiplier. Most organizations track lead times in silos, like procurement, inbound and outbound, but customers experience only one — from order to delivery.
Supply chain analysis often shows total lead times are one to two days longer than expected, driving:
This is where modern supply chain design has fundamentally changed. AI‑assisted modeling can now synthesize lead‑time data across procurement, inbound, facilities and transportation, then run hundreds of scenarios to understand how even small reductions at one node impact inventory, transportation and service across the network.
Reducing lead time across multiple nodes creates a compounding effect: less inventory, lower transportation costs and better service.
A lot of organizations operate in deep siloes across departments. A supply chain design aligns supply chain, finance, IT and leadership teams around shared goals and performance metrics.
When combatting silos, a coordinated approach for both strategy and implementation may initially increase costs in one or two areas of the business but create a much larger net benefit for the organization. For example, switching to store-ready pallets may increase labor in the distribution center, but it improves service levels and reduces in-store labor by much more.
These kinds of tradeoffs can often save companies millions of dollars across their supply chain networks.
The biggest reason that primary cost drivers are overlooked in supply chains is because they’re fragmented across the business. When decisions are made function by function instead of end‑to‑end, organizations optimize locally and overspend globally. Supply chain design reframes decisions around total system impact, forcing tradeoffs across factors like cost, service levels, capacity and long-term resilience to be evaluated objectively.
Take this scenario as an example:
A national distributor notices transportation costs increasing year over year. With oil prices rising and freight budgets under pressure, leadership pushes the logistics team to cut costs quickly. The VP of Logistics zeros in on carrier rates, launching a carrier optimization initiative to negotiate better pricing and reduce costs per mile.
On the surface, this strategy appears sound. But because the decision is made in isolation, it overlooks a larger structural issue: inventory has been positioned far from where customer demand actually exists. As a result, delivery routes have become longer and more fragmented, increasing miles driven, creating more split shipments and inflating transportation spend regardless of carrier rates.
In this scenario, renegotiating contracts delivers only marginal savings because the true cost driver isn’t transportation execution; it’s inventory allocation. Without a network‑level supply chain assessment, these root‑cause issues remain hidden, and transportation costs continue to rise even as individual functions optimize their own budgets.
As disruption becomes more of a baseline in global supply chains, consistent redesign is going to be even more important for maintaining peak cost and service level alignment. High-functioning supply chains should revisit their network strategy at least every two to three years, or when:
It’s best to establish a regular design cadence, ensuring assumptions stay current and strategy remains aligned with execution.
Double digit cost savings are buried in almost every supply chain network. You’ll find them in siloed decision-making, inefficient warehouse footprints, misaligned inventory allocation and delayed lead times. Supply chain design exposes these savings.
When applied continuously, supply chain design becomes a decision‑making framework that:
enVista’s supply chain consultants use advanced analytics, digital twins and decades of operational experience to help organizations reduce costs, improve performance and build long-term resilience in their supply chains.
enVista is sponsoring Optilogic’s OptiCon 26 User Conference from June 2-4! In our breakout session at the event, we will talk more about how to design supply chain networks for measurable cost reductions.
For more tips in the meantime, read our blog post, “13 Surprising Benefits of a Supply Chain Network Design.”
Ready to transform your supply chain from a cost center into a competitive advantage? Let’s Have a Conversation®
Authored by Nate Rosier, Chief Customer Officer at enVista
Tariff and freight volatility, nearshoring mandates, rising oil prices and AI disruption are hitting supply chains all at once. Whether they want to or not, supply chain executives are being forced to redesign their networks — or let the market do it for them. The reality in the modern supply chain is that rather than being an occasional hurdle to overcome, disruption has become the industry’s new baseline.
To succeed in such constant volatility, supply chain leaders need to change their mindsets from, “do we need to redesign our supply chain?” to, “are we redesigning our supply chain often enough?” This mindset shift is what drives the most meaningful results from redesigns, like up to 15 percent or more in total supply chain cost reduction.
In times of market volatility, completing a supply chain design that delivers significant cost savings become even more imperative. In this blog, we will talk about what causes suboptimization in a supply chain and where the most cost savings can be found in a redesign.
Suboptimization across the supply chain is often a symptom of poor data. Businesses undergo many changes as they develop and grow. New systems are added, SKUs are adjusted and acquisitions occur. Often, over time, data systems have been stitched together by many people using different methods.
Across inventory levels, SKU profiles, freight spend and more, many organizations either don’t have the data, have it spread across several disparate systems or don’t know how to operationalize it to make decisions. When this happens, the root cause of overspending becomes masked in a way that a supply chain design is uniquely equipped to unmask.
For example:
The modeling process of network design exposes inaccuracies in SKU, supplier or transportation data, highlighting opportunities to improve data integrity across the organization.
The new world of supply chain design uses continuous scenario modeling and AI‑assisted analysis to provide answers in hours instead of weeks. AI can now synthesize fragmented data across systems and evaluate hundreds of network scenarios in the time it would otherwise take just to gather the inputs.
This can enable supply chain leaders to operate with a future-focused approach and to make sound, data-driven business decisions.
While the starting point of your supply chain will play a role into how significant of savings a design will give you, most organizations can benefit from cost savings in a few recurring areas.
Inventory is one of the largest capital investments for product-based businesses, and it is also one of the most common root causes for high operational costs. The majority of supply chains have some serious cost saving potential tied up in poor inventory allocation. This is because poorly positioned inventory can cause:
Without network‑level visibility, a lot of organizations simply have no real idea how much they’re spending on freight costs each year. Supply chain design uses cost-to-serve modeling to break down spend by lane, mode and customer, enabling more accurate budgeting and rate negotiation
Network modeling reveals:
Intentional transportation design can also cut inbound spend by more than half by minimizing waste, reducing freight costs and preventing unnecessary touches.
These insights often unlock transportation savings without sacrificing service, simply by aligning inventory and fulfillment strategies to true demand patterns.
Warehouse space is incredibly limited, and many facilities are either nearing or past the recommended 85 percent utilization level. This is a fast-track to inflated operational costs.
As distribution centers (DC) reach capacity, travel times lengthen, touches increase and labor productivity suffers. Many facility leaders think they’re saving money by avoiding off-site storage costs, but the duplicate movements that result from facility congestion can be equally expensive in variable labor costs.
Keeping your distribution centers within effective capacity across footprints, flow paths and transportation routes can save you 10 to 20 percent of your operational costs. Supply chain design exposes capacity constraints and what’s causing them, helping warehouse operators avoid unnecessary expansions while restoring efficiency.
Improved visibility across the business can reduce your gap between expected and actual costs to two percent
Lead time is a hidden cost multiplier. Most organizations track lead times in silos, like procurement, inbound and outbound, but customers experience only one — from order to delivery.
Supply chain analysis often shows total lead times are one to two days longer than expected, driving:
This is where modern supply chain design has fundamentally changed. AI‑assisted modeling can now synthesize lead‑time data across procurement, inbound, facilities and transportation, then run hundreds of scenarios to understand how even small reductions at one node impact inventory, transportation and service across the network.
Reducing lead time across multiple nodes creates a compounding effect: less inventory, lower transportation costs and better service.
A lot of organizations operate in deep siloes across departments. A supply chain design aligns supply chain, finance, IT and leadership teams around shared goals and performance metrics.
When combatting silos, a coordinated approach for both strategy and implementation may initially increase costs in one or two areas of the business but create a much larger net benefit for the organization. For example, switching to store-ready pallets may increase labor in the distribution center, but it improves service levels and reduces in-store labor by much more.
These kinds of tradeoffs can often save companies millions of dollars across their supply chain networks.
The biggest reason that primary cost drivers are overlooked in supply chains is because they’re fragmented across the business. When decisions are made function by function instead of end‑to‑end, organizations optimize locally and overspend globally. Supply chain design reframes decisions around total system impact, forcing tradeoffs across factors like cost, service levels, capacity and long-term resilience to be evaluated objectively.
Take this scenario as an example:
A national distributor notices transportation costs increasing year over year. With oil prices rising and freight budgets under pressure, leadership pushes the logistics team to cut costs quickly. The VP of Logistics zeros in on carrier rates, launching a carrier optimization initiative to negotiate better pricing and reduce costs per mile.
On the surface, this strategy appears sound. But because the decision is made in isolation, it overlooks a larger structural issue: inventory has been positioned far from where customer demand actually exists. As a result, delivery routes have become longer and more fragmented, increasing miles driven, creating more split shipments and inflating transportation spend regardless of carrier rates.
In this scenario, renegotiating contracts delivers only marginal savings because the true cost driver isn’t transportation execution; it’s inventory allocation. Without a network‑level supply chain assessment, these root‑cause issues remain hidden, and transportation costs continue to rise even as individual functions optimize their own budgets.
As disruption becomes more of a baseline in global supply chains, consistent redesign is going to be even more important for maintaining peak cost and service level alignment. High-functioning supply chains should revisit their network strategy at least every two to three years, or when:
It’s best to establish a regular design cadence, ensuring assumptions stay current and strategy remains aligned with execution.
Double digit cost savings are buried in almost every supply chain network. You’ll find them in siloed decision-making, inefficient warehouse footprints, misaligned inventory allocation and delayed lead times. Supply chain design exposes these savings.
When applied continuously, supply chain design becomes a decision‑making framework that:
enVista’s supply chain consultants use advanced analytics, digital twins and decades of operational experience to help organizations reduce costs, improve performance and build long-term resilience in their supply chains.
enVista is sponsoring Optilogic’s OptiCon 26 User Conference from June 2-4! In our breakout session at the event, we will talk more about how to design supply chain networks for measurable cost reductions.
For more tips in the meantime, read our blog post, “13 Surprising Benefits of a Supply Chain Network Design.”
Ready to transform your supply chain from a cost center into a competitive advantage? Let’s Have a Conversation®
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