View a complimentary copy of the Magic Quadrant report at e2open.com.

According to Gartner, “Transportation management systems help supply chain leaders optimize transport cost and service and manage disruptions. As requirements shift and the TMS market grows, the vendor landscape has become more complex. Supply chain technology leaders should use this research to help evaluate the TMS market.” The report also states that “TMS solutions enable a shipper to have tighter control of their transportation operations, optimize costs, improve efficiencies, and have improved visibility into the movement of goods.”

“We believe being named a Leader for the fourth consecutive year in the Magic Quadrant for Transportation Management Systems reflects e2open’s continued focus on helping organizations manage increasingly complex global transportation networks,” said Pawan Joshi, Chief Strategy Officer at e2open. “As supply chains face ongoing disruption and evolving logistics requirements, companies need solutions that combine deep industry expertise with broad capabilities and innovation. Our transportation management solutions, combined with the power of the e2open connected supply chain platform and WiseTech Global’s extensive logistics ecosystem, enable companies to improve visibility, optimize transportation decisions, and respond more effectively to changing market conditions.”

E2open’s Transportation Management solution provides end-to-end transportation management capabilities alongside broader logistics functionality, including global logistics orchestration and logistics visibility, as well as integrations to the wider suite of products within e2open and WiseTech. The platform supports a wide range of industries and transportation scenarios, helping organizations manage both domestic and international shipping operations with greater efficiency and control. The solution connects organizations to one of the largest carrier network ecosystems, enabling real-time access to capacity, pricing, and performance data across transportation modes. With built-in AI-driven capabilities such as RateIQ, which analyzes rate signals to predict market benchmarks, e2open helps shippers make more informed planning and procurement decisions.

E2open’s TMS is part of a connected logistics suite that allows organizations to coordinate people, processes, and systems across the global supply chain. The combination with WiseTech Global and shared vision to be the operating system for global trade and logistics including the supply chain, only strengthens the value for customers. Serving more than 22,0002² logistics companies and other industry participants across 193 countries, and connecting more than 500,000 manufacturing, logistics, channel, and distribution partners, e2open together with WiseTech is enabling organizations to improve visibility, reduce costs, and build more resilient supply chains.

Gartner disclaimer

Gartner and Magic Quadrant are trademarks of Gartner, Inc., and/or its affiliates. All rights reserved. Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

About e2open

E2open, a WiseTech Global Group company, is the connected supply chain software platform that enables the world’s largest companies to transform the way they make, move and sell goods and services. With the broadest cloud-native global platform purpose-built for modern supply chains, e2open connects more than 500,000 manufacturing, logistics, channel and distribution partners as one multi-enterprise network tracking over 18 billion transactions annually. Our SaaS platform anticipates disruptions and opportunities to help companies improve efficiency, reduce waste and operate sustainably. Moving as one. Learn more: www.e2open.com.

E2open and “Moving as one.” are the registered trademarks of E2open, LLC. All other trademarks, registered trademarks and service marks are the property of their respective owners.

¹ Source: Gartner, “Magic Quadrant for Transportation Management Systems,” 30 March 2026, Brock Johns, Oscar Sanchez Duran, Manav Jain

² Includes customers on CargoWise and non-CargoWise platforms whose customers may be counted with reference to installed sites, including deduplicated e2open customers.

###

Contacts
Media Contact:
5W PR for e2open
e2open@5wpr.com
908-510-8009

Corporate Contact:
Kristin Seigworth
VP Communications, e2open
Kristin.Seigworth@wisetechglobal.com

Global trade is increasingly unpredictable and complex, posing greater challenges for exporters.

Export controls shift with world events, sanctions broaden, and documentation requirements grow as regulators exchange more information. At the same time, sales teams pursue new markets amid tighter risk limits.

Decisions made in product design, partner selection, pricing, and routing, carry immediate regulatory and financial consequences, compounding an already complex risk landscape. Yet, in many organizations, export processes still rely on manual controls, fragmented systems, or broker-dependent workflows that are also trying to adapt to this scrutiny and speed.

That disconnect is becoming increasingly difficult to ignore.

How export controls and tariff volatility are reshaping global trade management

Exporters operate in a trade environment marked by constraints rather than growth. Export controls, especially those related to dual-use goods, advanced technologies, and sensitive markets, have expanded in both scope and complexity. Sanctions target countries, entities, individuals, and intricate ownership structures, that necessitate comprehensive data to identify.

Meanwhile, regulators have significantly increased transparency efforts. Shared data between customs authorities and government agencies allows for faster detection and resolution of discrepancies. An issue in one jurisdiction can trigger investigations in others. Tasks like screening, licensing, and recordkeeping are now part of a unified enforcement system.

Exporters growth strategies introduce additional compliance complexity that traditional export processes weren’t designed to handle.

Expanding into new regions introduces unfamiliar licensing and documentation demands. Diversifying channels—such as e-commerce and direct-to-consumer approaches—increases transaction volumes and shortens the decision-making window. As a result, previously managed export routes have turned into a more fragmented network.

This combination of regulatory demands and operational fragmentation has altered the risk profile of exporting.

The hidden cost of inadequate global trade management for exporters

Inadequate global trade management creates financial, operational, and strategic costs that extend far beyond compliance penalties.

Many exporters still manage compliance using ERP extensions, spreadsheets, and institutional knowledge. These methods rely on experienced staff and stable trade rules.

Ask yourself:

• Are more than 30% of your export steps still spreadsheet-driven?
• Do shipping or compliance teams spend over an hour reconciling export data for a typical transaction?
• Does your export compliance process rely on specific individuals instead of standardized procedures?
• Do regulatory changes trigger ad hoc fixes rather than systematic adjustments?
• Are partner or broker interventions required after commercial commitments are already made?

Answering ‘yes’ to any of these questions highlights areas where digital global trade management can remove bottlenecks, reduce risk, and support growth.

Manual export processes create late-stage risk

ERP systems are not designed to interpret complex export control laws across different jurisdictions or to adapt swiftly to regulatory updates. Manual screening and license decisions often struggle to keep up with higher transaction volumes or an expanding product range. Broker support, although valuable, usually comes after commercial commitments, limiting its impact.

This leads to a reactive approach. Issues often arise late, when shipments are staged or contracts are signed. Sales and operations teams encounter friction without understanding the root cause. Compliance teams are pressured to serve as the final checkpoint rather than as strategic partners earlier in the process.

Early export screening enables shared accountability

To move from reactivity to resilience, organizations must reframe compliance as a shared accountability across commercial, operations, and compliance teams. Early export checks must be integrated into sales and product development workflows, ensuring that those shaping deals, setting prices, or qualifying customers share responsibility for regulatory outcomes. This approach fosters partnerships and transforms compliance into a value-adding asset.

Secondary impacts of weak export controls

The most visible effects of weak export controls are delays, penalties, and enforcement actions. Less visible are the long-term secondary impacts that accumulate over time.

Revenue leakage is one painful example. Licensing uncertainty or screening delays can slow shipments and erode customer confidence, leading to deal losses. Sometimes, exporters avoid certain markets entirely because the compliance burden outweighs the opportunity.

Operational inefficiency is another issue where manual workarounds and exception handling consume skilled resources that could be used for more valuable analysis. Teams spend time reconciling data instead of focusing on risk anticipation.

Without clear visibility into export restrictions and licensing requirements, leadership lacks confidence in growth plans. Market entry decisions become more conservative, and product strategies adapt slowly. What starts as a compliance safeguard can quietly limit competitiveness.

These costs may not appear on a balance sheet, but they still affect performance.

Why modern global trade management has become a decision infrastructure

Leading exporters are re-evaluating the role of global trade management (GTM) in their organizations. Instead of viewing it only as a control mechanism, they use it as a decision infrastructure that links compliance, operations, and commercial strategy.

Modern GTM platforms centralize export control content, screening logic, and regulatory notices, applying them consistently across transactions. Automation reduces manual effort, but the main benefits are increased speed and confidence. Decisions that once took days can now be made in minutes, with a clearer understanding of risk and options.

AI-enabled global trade solutions, when used appropriately, supports this shift by managing scale rather than judgment. AI-driven document processing, entity matching, and risk flagging allow teams to focus on critical exceptions. The goal is to direct human oversight where it adds the most value, not to eliminate it.

When GTM is integrated early, it informs pricing, customer selection, and routing decisions before commitments are made. Compliance then enables growth instead of acting as a last-minute obstacle.

Key global trade management shifts manufacturers and exporters are making today

Across manufacturing organizations, exporters are reassessing several aspects of their trade operations, such as:

Evaluating export control content

Many manufacturers are evaluating how current and connected their export control content truly is, and how quickly regulatory changes propagate across systems. Lag time introduces risks that are difficult to defend.

Reconsidering ownership models

Manufacturers and exporters are also reconsidering ownership models. Deciding when to use external partners versus in-house capabilities is now driven more by responsiveness and visibility than by cost.

Integrating global trade with other supply chain functions

There is a renewed focus on integration. Export decisions intersect with order management, logistics, and finance. GTM insights can only influence outcomes when they are seamlessly integrated into these processes.

Scaling export operations

Exporters are also re-examining assumptions about scale. Solutions that worked for a limited range of products and markets may not be effective as portfolios diversify, and transaction volumes grow.

These reassessments indicate a broader shift in how export compliance is viewed within organizations.

What exporters should consider when choosing a global trade management solution

Export operations are unlikely to become simpler. Regulatory requirements are increasing, geopolitical dynamics remain unpredictable, and growth strategies require access to new markets under tighter constraints.

In this context, investing in global trade management is less about technology adoption and more about organizational resilience. Exporters that establish GTM as a strategic capability can move faster with fewer surprises. They protect revenue, preserve optionality, and reduce the operational drag of constant exception management. Imagine a future where exporters accelerate cycle times, confidently enter new markets ahead of competitors, and achieve regulatory peace of mind with zero fines or last-minute disruptions. Customers receive on-time deliveries, teams shift focus from fire drills to growth initiatives, and leadership steers with clear visibility. This outcome becomes possible when GTM becomes the backbone of export operations.

Organizations that delay will continue to manage exports through inefficient workarounds.

Independent analyst perspectives, including the IDC MarketScape assessment of global trade management solutions, underscore this shift. GTM is increasingly evaluated on its ability to support integrated, data-centric decision-making, not just regulatory coverage.

For exporters navigating today’s trade environment, this distinction is critical. To learn more about evolving GTM capabilities and available options, download the IDC MarketScape: Worldwide Global Trade Management Applications for Manufacturers and Exporters 2025 Vendor Assessment excerpt.

FAQ: Global trade management for manufacturers and exporters

1. Why is export compliance becoming more complex for manufacturers?

   1. Export compliance is becoming more complex due to expanded export controls on dual‑use and advanced technologies, broader sanctions programs, and increased data sharing between regulators. What was once a country‑based check now often requires product‑level, customer‑level, and ownership‑level analysis across multiple jurisdictions.

2. How do export controls impact product design and classification decisions?

   1. Export controls increasingly influence product architecture, software functionality, encryption features, and component sourcing. Classification decisions made during product design can determine whether exports require licenses, face destination restrictions, or are prohibited entirely—making early GTM involvement critical.

3. What risks come from managing export compliance manually or in spreadsheets?

   1. Manual processes increase the risk of missed screening matches, inconsistent license determinations, delayed shipments, and audit exposure. They also create dependency on individual expertise rather than standardized controls, making compliance difficult to scale as product lines, markets, and transaction volumes grow.

4. When should exporters perform export screening and license checks?

   1. Export screening and license checks should occur before quoting, contracting, or order acceptance, not just before shipment. Performing checks late in the process can result in cancelled orders, renegotiated contracts, or regulatory violations after commercial commitments are already in place.

5. How do sanctions and restricted party screening affect exporters today?

   1. Sanctions now apply not only to named entities, but also to ownership structures, affiliates, and indirect relationships. Exporters must screen customers, intermediaries, and partners continuously, as list changes can occur rapidly and affect existing business relationships without notice.

6. Why isn’t ERP software enough for export compliance management?

   1. ERP systems are designed for transaction processing, not for interpreting evolving export control laws or sanctions regulations. They typically lack real‑time regulatory updates, jurisdiction‑specific logic, and advanced screening capabilities, forcing teams to rely on manual workarounds or external checks.

7. How does global trade management support faster export decisions?

   1. Modern GTM platforms centralize regulatory content and apply it automatically across transactions, enabling faster classification, screening, and license determinations. This allows exporters to respond quickly to sales opportunities while maintaining confidence that decisions are compliant and defensible.

8. What role does AI play in export compliance and GTM?

   1. AI supports GTM by handling scale and complexity, such as document review, entity matching, and risk flagging. When used with human oversight, AI reduces false positives and manual effort, allowing compliance teams to focus on high‑risk decisions rather than routine transactions.

9. What should manufacturers and exporters look for in a GTM solution?

   1. Exporters should look for GTM solutions that provide current export control content, integrated screening and licensing workflows, ERP and order‑management integration, audit‑ready recordkeeping, and scalability. The goal is not just compliance, but the ability to support growth under increasing regulatory constraints.

• What is predictive analytics in supply chain management? Predictive analytics uses historical and real-time data to forecast what is likely to happen in a supply chain, such as demand changes, shipment delays, or potential stockouts.
• What is prescriptive analytics in supply chain management? Prescriptive analytics recommends the best action to take to achieve a specific outcome, factoring in constraints like cost, capacity, service levels, and lead times.
• What is the difference between predictive and prescriptive analytics? Predictive analytics focuses on anticipating future outcomes, while prescriptive analytics focuses on deciding what to do next based on those predictions.
• When should supply chains use predictive vs prescriptive analytics? Use predictive analytics for forecasting, early risk detection, and planning confidence, and use prescriptive analytics when decisions must be made repeatedly at scale and optimized across cost, service, and capacity tradeoffs.

Supply chain analytics have evolved

For years, most supply chain analytics focused on answering a single question: What happened?

Descriptive reporting and dashboards provided historical insight into costs, service levels, and operational performance. While useful, these tools were limited in their ability to support proactive decision-making.

As data volumes grew and disruptions became more frequent, supply chains began adopting more advanced analytics to answer a more forward-looking question: What is likely to happen next?

That shift has brought predictive and prescriptive analytics to the forefront of supply chain decision-making. While they serve different purposes, they work best together; predictive helps teams anticipate what’s coming, and prescriptive helps teams respond with the best next step.

Understanding the difference — and how the two complement each other — is critical for improving planning, inventory management, and logistics performance in today’s supply chains.

What is predictive analytics in supply chain management?

Predictive analytics in supply chain management uses historical and real-time data to forecast what is likely to happen next, such as demand changes, shipping delays, or stockouts.

It looks for patterns across inputs like demand history, lead times, supplier performance, inventory levels, and transportation data. The output is typically a forecast, probability, or risk signal, not a recommended decision.

Predictive analytics helps answer:

• What will demand look like next month?
• Which SKUs are likely to stock out?
• Which shipments are at risk of delay?
• Where is lead time variability increasing?

What is prescriptive analytics in supply chain management?

Prescriptive analytics in supply chain management uses data, constraints, and business goals to recommend the best action to take next, such as how much to reorder or how to reroute shipments.

It evaluates options against real-world constraints like capacity, cost, lead times, service targets, and supply availability. The output is typically a recommended action, optimized plan, or decision suggestion.

Prescriptive analytics helps answer:

• How much should we reorder and when?
• Where should limited inventory be allocated?
• Which routes or carriers should we use to reduce risk and cost?
• How should we adjust sourcing when supply is constrained?

Key differences: Predictive vs prescriptive analytics

Supply chain use cases (with examples)

Predictive and prescriptive analytics show up across the supply chain, often working together within the same workflow.

Demand planning

• Predictive analytics: Forecasts demand by SKU, location, and time period, identifies seasonality, and flags potential demand spikes or drops.
• Prescriptive analytics: Recommends production plans, safety stock levels, and reorder strategies that balance service targets, capacity constraints, and cost.

Example: A consumer packaged goods company uses predictive analytics to forecast a surge in demand for seasonal products ahead of a major retail promotion. Prescriptive analytics then recommends production volumes and safety stock levels by plant and distribution center, factoring in capacity limits and service level targets.

Inventory management

• Predictive analytics: Identifies stockout risk, excess inventory risk, and slow-moving inventory based on demand and lead time patterns.
• Prescriptive analytics: Optimizes reorder points and quantities, and allocates inventory across distribution centers or stores to meet service levels with minimal working capital.

Example: A retailer uses predictive analytics to identify SKUs at risk of stocking out in high-demand regions. Prescriptive analytics recommends reallocating inventory from lower-performing stores and adjusting reorder quantities to protect sales without increasing overall inventory.

Logistics and transportation

• Predictive analytics: Forecasts ETAs, identifies shipments at risk of delay, and evaluates carrier performance trends.
• Prescriptive analytics: Recommends route changes, load consolidation, and shipment prioritization to reduce cost and improve on-time delivery.

Example: An industrial manufacturer uses predictive analytics to identify inbound shipments that are at risk of missing delivery windows due to port congestion. Prescriptive analytics recommends rerouting critical components through alternative ports and prioritizing expedited transport to avoid production downtime.

Supplier risk and procurement

• Predictive analytics: Predicts supplier risk, lead time variability, and potential supply disruptions.
• Prescriptive analytics: Recommends supplier switching, order splitting, or sourcing adjustments to maintain continuity and control cost.

Example: A high-tech manufacturer uses predictive analytics to flag increased lead time risk from a tier-2 component supplier. Prescriptive analytics recommends splitting orders across approved suppliers and adjusting order timing to protect production schedules.

When to use predictive vs prescriptive analytics

Predictive and prescriptive analytics solve different problems. The right approach depends on the type of question you’re trying to answer and how decisions are made in your organization.

Use predictive analytics when:

• The primary goal is forecasting and early warning
• You need visibility into potential risks or demand changes
• Decisions are still made manually by planners
• You want to improve planning confidence before taking action

Use prescriptive analytics when:

• Decisions need to be made repeatedly and consistently
• Tradeoffs matter across cost, service, and speed
• Constraints are complex, such as limited supply, capacity, or minimum order quantities
• You need recommended actions, not just insights

Bringing predictive and prescriptive analytics together

Predictive analytics helps teams anticipate demand shifts, supply risk, and transportation disruptions. Prescriptive analytics turns those signals into decisions, balancing cost, capacity, and service tradeoffs. Together, they support faster, more consistent execution across planning, supply, and logistics, especially when conditions change quickly.

E2open helps companies connect predictive insights to prescriptive decision-making across the end-to-end supply chain, enabling planners and operators to move from “what’s likely” to “what to do next” within a single, connected workflow.

Contact an e2open expert to see how predictive and prescriptive analytics can improve planning, execution, and resilience across your network.

Key takeaways

• What is modern S&OP? Modern S&OP is a connected, continuous planning process that unifies demand, supply, inventory, logistics, and finance on a single, real-time data foundation.
• Why does S&OP need modernization today? Legacy, spreadsheet-driven methods can’t keep up with volatility. Modern S&OP enables real-time visibility, faster decisions, and stronger cross-functional alignment.
• How does modern S&OP improve performance? It supports scenario modeling, synchronized plans, and rapid adjustments that improve service levels, reduce costs, and create more predictable operational outcomes.
• What challenges do organizations face with legacy processes? Siloed data, slow cycles, manual workflows, inconsistent assumptions, limited scenario capability, and weak financial alignment all hinder effective decision-making.
• What trends are reshaping S&OP today? AI-driven forecasting, real-time data integration, digital twins, collaborative planning tools, and expanded financial and sustainability considerations are transforming how teams plan and respond.
• How does e2open enable modern S&OP? E2open provides a unified, network-based platform that connects data, partners, and processes, empowering organizations to plan continuously, align easily, and move as one.

Why S&OP needs to be modernized today

Legacy S&OP processes weren’t built for today’s level of volatility. Manual data collection, spreadsheet-driven analysis, and a monthly meeting cadence create slow, siloed planning that can’t keep up with rapid shifts in demand, supply, or cost. Different functions often work from conflicting assumptions, and decisions end up reactive instead of proactive.

Modern pressures, such as shorter product cycles, global disruptions, supply constraints, and inflation, require real-time visibility and cross-functional alignment. Organizations need S&OP that operates continuously, not once a month. The shift is clear: move from meeting-based, backward-looking processes to a connected, technology-enabled planning approach that adapts as conditions change and keeps the enterprise aligned.

What modern S&OP looks like

Modern S&OP is a connected, collaborative, technology-enabled process that operates continuously rather than once a month. Instead of stitching together spreadsheets and departmental reports, teams plan on a unified data foundation that reflects real-time market realities. Advanced forecasting, scenario modeling, and AI-powered insights help organizations anticipate change, evaluate trade-offs, and align cross-functional decisions with both operational and financial goals. 

The difference from legacy S&OP is stark. Traditional models rely on limited visibility, manual updates, and siloed inputs that often conflict. Modern S&OP brings together demand, supply, inventory, logistics, and finance on a single platform, enabling teams to collaborate based on shared assumptions, synchronized plans, and a unified view of constraints and opportunities.

Key characteristics of modern S&OP include:

• Real-time visibility: Live data from across internal operations and multi-tier partners fuels more accurate forecasting and faster decision-making.
• Integrated planning: Demand, supply, production, inventory, and financial plans are connected, eliminating disconnects between strategy and execution.
• Scenario planning: Teams can model “what-if” situations instantly to understand potential impacts and choose the best path forward.
• Cross-functional alignment: Finance, sales, operations, and supply chain work from the same numbers, the same constraints, and the same objectives.
• Continuous, always-on cadence: S&OP becomes an active process rather than a monthly event, enabling proactive decisions instead of retrospective analysis.

Modern S&OP ultimately provides one connected system of insight and action. The result is greater agility, more predictable performance, and a supply chain that can truly “move as one.”

Core elements of a modern S&OP process

Modern S&OP brings every part of the business onto a connected planning framework. Instead of isolated spreadsheets or function-specific assumptions, organizations rely on shared data, shared metrics, and shared accountability to build one unified plan. The following components form the backbone of that approach:

Demand planning & forecasting

Creates a single view of expected demand using real-time signals, analytics, and shared assumptions across teams. This provides a stable foundation for decisions and reduces the variability that undermines downstream planning.

Supply & capacity alignment

Matches demand with available manufacturing, supplier, and logistics capacity to prevent constraints and production bottlenecks. This alignment ensures the business understands true feasibility before committing to customer or financial targets. 

Inventory strategy

Balances working capital and service levels across the entire network, not just individual nodes. By optimizing inventory holistically, organizations avoid overstocks in some locations and shortages in others.

Financial integration

Connects operational decisions to revenue, margin, and budget goals so the organization evaluates trade-offs with full context. This linkage keeps planning grounded in business priorities and improves accountability across functions.

Scenario planning & risk evaluation

Models “what-if” situations to compare options, understand impacts, and prepare proactive responses to disruption. Teams can stress-test decisions in advance rather than reacting after problems emerge.

Cross-functional collaboration & governance

Establishes shared metrics, shared data, and a consistent cadence that keeps sales, operations, supply chain, and finance aligned. Strong governance ensures that decisions flow quickly and that the organization moves in lockstep as conditions change.

Common challenges in legacy S&OP (and how modernization solves them)

Challenge #1: Siloed data and disconnected systems

Legacy S&OP relies on separate spreadsheets, offline reports, and partial data extracts that never quite align. This creates conflicting views of demand, supply, and financial expectations.

How modernization solves it: A digital S&OP platform brings all data — internal, partner, and market — into one environment, creating a single source of truth that every function can trust.

Challenge #2: Slow planning cycles

Monthly or quarterly cycles cannot keep pace with rapid shifts in demand, supply disruptions, or changing business priorities. By the time plans are finalized, they’re often outdated.

How modernization solves it: Real-time visibility and continuous planning replace slow, meeting-based cycles. Teams update assumptions and plans as conditions change, not weeks later.

Challenge #3: Manual, error-prone workflows

Spreadsheets and email-driven collaboration introduce delays and increase the risk of mistakes. Valuable time is spent reconciling numbers instead of analyzing insights.

How modernization solves it: Automated data flows, integrated workflows, and AI-enabled insights reduce manual effort and free teams to focus on decision-making.

Challenge #4: Inconsistent assumptions across functions

Sales, operations, supply chain, and finance often work from different versions of the truth, leading to misaligned plans, mismatched targets, and last-minute adjustments.

How modernization solves it: A connected S&OP framework aligns every function to shared assumptions, shared KPIs, and shared plans — removing friction and improving accountability.

Challenge #5: Limited ability to model scenarios

Traditional tools can’t run “what-if” analysis quickly or at scale. Teams are forced to make decisions without understanding trade-offs or potential consequences.

How modernization solves it: Digital S&OP platforms enable instant scenario modeling, allowing leaders to test alternatives, compare impacts, and choose the best path before issues escalate.

Challenge #6: Weak alignment between operations and finance

Operational plans often conflict with financial goals, leading to budget surprises, margin erosion, or unrealistic service-level expectations.

How modernization solves it: Integrated financial planning ensures that every scenario, forecast, and supply decision ties directly to revenue, margin, and cash-flow targets.

Modern S&OP eliminates the limitations of outdated processes and replaces them with a connected, real-time planning environment that strengthens alignment, improves responsiveness, and supports predictable business performance.

Modern trends enhancing S&OP processes

Today’s most effective S&OP processes are shaped by a wave of innovations that make planning faster, smarter, and more connected across the enterprise. These trends expand the scope and impact of S&OP, enabling organizations to operate with greater agility and confidence.

• AI-driven forecasting and automated insights: Artificial intelligence elevates forecasting beyond historical patterns by incorporating real-time demand signals, market shifts, and supply variability. Automated insights surface risks and opportunities earlier, helping teams make more informed decisions with less manual effort.
• Real-time data integration across the enterprise: Modern S&OP relies on live connections to ERP, supply, logistics, and partner systems. This real-time visibility delivers a unified view of performance and ensures that plans reflect what’s happening now—not last month’s numbers.
• Digital twins and scenario modeling: Digital replicas of the supply chain allow teams to visualize constraints, test alternatives, and evaluate the impact of decisions before executing them. Rapid scenario modeling turns uncertainty into actionable insight and strengthens resilience.
• Collaboration tools that unify partners and internal teams: Cloud-based collaboration environments bring sales, supply chain, operations, finance, and external partners into one shared workspace. With consistent data and coordinated workflows, cross-functional alignment becomes the norm rather than the exception.
• Greater emphasis on financial planning, sustainability, and end-to-end visibility: S&OP is expanding beyond traditional supply planning to include financial impacts, environmental considerations, and transparency across multi-tier networks. Organizations can now balance profitability, service levels, and sustainability goals within a single, integrated planning process.

Modernize your S&OP with e2open

Modern S&OP requires more than faster spreadsheets or better meetings; it requires a connected foundation that unifies data, decisions, and teams across the entire enterprise. That’s where e2open stands apart. By combining network-based visibility, real-time insights, and integrated planning applications on a single platform, e2open enables organizations to move beyond static, siloed processes and operate with true agility.

If your organization is ready to modernize S&OP, e2open provides the technology backbone to make it possible, connecting your extended supply chain, elevating decision-making, and helping your business move as one. 

See how e2open modernizes S&OP from end to end →

The difference today is the speed and connectedness of complexity. Decisions in sourcing, classification, valuation, or routing now directly impact pricing, inventory, and brand risk. Yet, in many organizations, global trade management (GTM) remains a compliance safeguard rather than a source of strategic insight.

This gap is increasingly costly.

How tariff volatility and regulatory change are redefining global trade for retailers and importers

The luxury of having months to plan for tariff changes is gone. Tariff policy changes are now continuous rather than episodic. Retailers and importers have faced frequent, sometimes daily, shifts in tariff applicability and interpretation, resulting in ongoing uncertainty. Regulatory scrutiny has also intensified, as agencies issue changes more frequently, leading to inconsistencies in filings to surface quickly and trigger delays.

Trade complexity has also increased. Omni-channel fulfillment, cross-border ecommerce, and diversified sourcing have introduced more shipment types, entry scenarios, and potential points of failure. For example, the suspension of the U.S. de minimis threshold has pushed many low-value shipments into formal customs processes, raising the bar for documentation, classification accuracy, and duty calculation at scale.

Layer in elevated sustainability and ethical sourcing requirements, along with pressure to use trade incentives like bonded warehouses, foreign trade zones, and duty drawback, and now trade is a focal point for financial, legal, and operational risk.

This environment is now the baseline for retailers and importers.

Why traditional global trade management approaches are breaking down

Many organizations still use a patchwork of ERP extensions, broker relationships, and manual workarounds to manage global trade. These methods are not suited to the speed or interdependence of today’s trade environment.

By design, ERP systems prioritize transactional integrity instead of regulatory nuance. They struggle with frequent tariff changes, complex rules of origin, and scenario-driven landed cost modeling. Brokers extend valuable expertise but often act after commercial decisions are finalized. Spreadsheets and point solutions fill gaps but add latency and inconsistency.

This leads to a reactive approach. Trade teams focus on reconciling discrepancies, responding to holds, and explaining margin erosion after it occurs. Sourcing and pricing teams lack visibility into duty exposure or incentive eligibility, while finance absorbs avoidable variability.

This is not a question of effort or expertise, but a structural limitation.

The hidden business risks that leaders often underestimate

The most visible risks of inadequate GTM are penalties, shipment delays, and compliance violations. Less visible impacts, however, can be more damaging over time.

First, cost volatility becomes entrenched. Without the ability to quickly simulate landed costs across sourcing, routing, and valuation scenarios, organizations default to conservative assumptions. Margins erode quietly, or costs are unevenly passed on, leading to pricing irregularities across channels.

Second, sourcing agility declines. While many retailers diversify their supplier base to reduce geopolitical risk, onboarding new suppliers introduces classification uncertainty, greater origin complexity, and documentation risk. Without scalable GTM, diversification increases exposure rather than resilience.

Third, organizational trust erodes. Conflicting trade, logistics, or finance data undermines confidence, slows decisions, and increases exceptions. What should be a control function becomes a bottleneck.

Finally, leadership visibility narrows. Executives see disruptions but often miss their root causes. Trade issues appear as symptoms in inventory, revenue, or service metrics, disconnected from the underlying regulatory or policy drivers.

These second-order effects compound quickly.

How GTM is evolving from a compliance tool into decision infrastructure

Leading retailers and importers are rethinking the function of global trade management. Instead of seeing it only as a compliance safeguard, they treat GTM as decision infrastructure spanning compliance, logistics, and finance.

This shift demonstrates a broader understanding that trade decisions are interconnected. Classification affects trade incentive eligibility, routing impacts duty timing and cash flow, and valuation strategies influence transfer pricing and supplier negotiations. Each decision affects multiple functions.

Modern GTM platforms reflect this evolution. They ingest frequent regulatory updates, apply them consistently across transactions, and model outcomes before commitments. Automation reduces manual effort and enables faster analysis and earlier intervention.

Practical use of artificial intelligence supports this evolution. AI-driven document handling, classification, and risk screening reduce friction in high-volume environments.

For example, customs documentation that once took hours of manual review can now be processed in minutes with integrated AI tools. Predictive functions help teams anticipate issues rather than react to them. The value lies in scale and speed, not novelty.

How retailers and importers are rethinking global trade management strategies

Current market observations show that many retail and import organizations are reassessing their approaches.

Many are evaluating how current their trade content is and how quickly changes are reflected across systems. Delays of days or weeks are unacceptable when tariff applicability can change overnight.

Others are reconsidering their reliance on brokers versus direct filings, balancing control, and agility with internal capacity. The goal is not to eliminate partners, but to identify where direct visibility and responsiveness are most important.

There is renewed focus on using trade incentives as strategic tools rather than tactical afterthoughts. Duty deferral, first-sale valuation, and free trade agreement qualification require detailed data and disciplined execution. When managed systematically, they can significantly offset cost pressures.

Finally, organizations are emphasizing integration. GTM must not operate in isolation; its insights prove valuable only when they inform sourcing, planning, and financial decisions.

This shift is less about technology selection and more about operating model maturity.

Why delaying global trade management investment increases risk and cost

It may be tempting to view GTM investment as discretionary, especially when budgets are tight and priorities compete. However, this underestimates the structural realities of today’s trade environment.

Volatility is not decreasing. Regulatory expectations are not easing, and supply chains are not becoming simpler. Each year of delay widens the gap between decision speed and trade reality and puts late adopters even further behind competitors who choose to make an investment in GTM.

The question is not whether global trade management matters, but whether it can keep pace with the business it supports.

Independent assessments, such as the IDC MarketScape for worldwide global trade management for retailers and importers, reflect this shift in emphasis. GTM is no longer evaluated solely on compliance coverage, but on its ability to support integrated, evidence-based decision-making across the enterprise.

For leaders in compliance, sourcing, and operations, this is a strategic inflection point.

Why global trade management teams and technology must become agile

Investing in GTM is not about eliminating disruption, but about establishing the agility to absorb it without jeopardizing the business. Agility depends on visibility into trade exposure, the ability to model alternatives, and the discipline to act on insight rather than instinct.

Retailers and importers who make this shift position themselves to respond faster, protect margins more effectively, and reduce the operational burden of constant exception management. Those who do not will continue to manage trade as a series of ongoing surprises.

FAQ: Global trade management for retailers and importers

1. What trade risks do retailers most often overlook until something breaks?

   1. Retailers commonly underestimate how much SKU‑level accuracy matters. Small errors in HTS classification, country of origin, or product descriptions can quietly erode margins across thousands of items. Other risks include inconsistent supplier documentation, last‑minute assortment changes, and reliance on legacy “that’s how we’ve always done it” processes that don’t hold up during audits, peak season, or tariff shifts.

2. How are changing de minimis rules affecting cross‑border e‑commerce shipments?

   1. For retailers shipping direct‑to‑consumer, de minimis tightening means low‑value parcels are no longer low‑risk. More shipments now require formal entry, duty payment, and accurate data upfront, increasing landed cost and fulfillment complexity. Retailers are being forced to rethink cross‑border DTC models, near‑shore fulfillment, bulk import + domestic ship strategies, and pricing assumptions that once relied on duty‑free thresholds.

3. When should retailers rely on brokers, and when do they need more direct control?

   1. Customs brokers are essential for executing entries and handling local filings, especially at volume. But retailers should keep control over product classification decisions, origin strategy, valuation methods, and duty‑savings programs. If a decision affects margin across an entire assortment or season, it’s too strategic to outsource blindly. Brokers execute well—but retailers must own the logic.

4. Which trade incentive programs can retailers use to offset rising duties?

   1. Retailers with steady import volume often benefit from Foreign‑Trade Zones (FTZs) for duty deferral and rate reduction, especially for seasonal inventory. Duty drawback is valuable for omnichannel brands that re‑export or ship internationally from U.S. distribution centers. Bonded warehouses help with inventory timing and cash flow, while temporary import programs support samples, pop‑ups, and returns. These programs can materially protect margins when used correctly.

5. What should retailers look for in a modern GTM platform?

   1. Retailers need GTM platforms built for high SKU counts and constant assortment change. Key capabilities include SKU‑level classification, origin and supplier data management, real‑time tariff visibility, scenario modeling for sourcing decisions, and clean integration with ERP, PLM, and logistics systems. The goal is to make trade data usable for merchants, sourcing, and finance—not just compliance teams.

6. How can AI help global trade teams move faster without increasing compliance risk?

   1. AI helps retail trade teams by automating repetitive SKU work, reducing false positives in screening, and surfacing only true exceptions that need review. This is critical when assortments refresh every season. With proper controls, AI improves consistency and speed while keeping humans focused on judgment calls—allowing teams to support faster launches, quicker sourcing pivots, and tighter margin control without increasing compliance exposure.

Executive Summary

As global trade teams move through 2026, they face a convergence of regulatory change, geopolitical uncertainty, and rising expectations for data accuracy that makes this year a true inflection point, perhaps unlike any before.

Preparations for HS 2027, the transition of carbon border mechanisms from reporting to financial impact, heightened forced labor regulation, and increasingly strict pre-arrival data requirements are all reshaping how trade compliance must operate.

At the same time, the recent U.S. Supreme Court ruling limiting presidential tariff authority has added legal complexity without reducing tariff volatility, reinforcing that uncertainty remains the defining feature of the trade landscape.

For global trade professionals, success in 2026 will depend less on reacting to individual regulatory changes and more on strengthening foundational capabilities: high-quality data, cross-functional collaboration, and systems that enable earlier, more confident decision-making.

This article outlines the key developments shaping 2026 and the practical implications trade teams must address now to remain compliant, resilient, and competitive.

Why 2026 is a turning point for global trade compliance

For global trade professionals, 2026 signals a pivot, not just a continuation. Converging regulatory, geopolitical, and operational changes are now becoming enforceable and directly impacting daily trade operations.

This matters because global trade has reached a point where reactive compliance is no longer sufficient – if it ever was.

The organizations that will navigate 2026 successfully are those that understand these 3 critical things:

1. What’s changing.
2. Why it’s changing.
3. How today’s decisions shape tomorrow’s resilience.

Trade compliance has always required attention to detail. What’s different now is the scale, speed, and interconnectedness of those details.

Classification, origin, valuation, emissions data, forced labor risk, and advanced data requirements are no longer isolated disciplines. They are becoming interdependent components of a single risk picture; one that customs authorities, regulators, and enforcement agencies are increasingly able to see end-to-end.

In short, this year is not about adding another checklist item. It’s about strategically rethinking how your trade teams operate.

Key global regulatory pressures shaping global trade

A defining feature of our current trade environment is that pressure is not coming from a single source. It’s emerging simultaneously across multiple regions, often with varying objectives and overlapping data requirements.

Trade professionals are managing:

• Shifting tariff and trade remedy regimes
• Expanding due diligence and forced labor expectations
• Climate-related reporting and payment mechanisms
• Increased scrutiny of classification and origin accuracy
• Tighter timelines for submitting complete and correct data

While each development can be examined independently, they ultimately compound one another. An error or gap in one area increasingly creates downstream exposure elsewhere.

That’s why 2026 is different: this is the year when data quality marks the foundation of compliance, not just a supporting function.

Tariff uncertainty: What the U.S. Supreme Court ruling means for trade compliance

The recent U.S. Supreme Court decision rejecting President Trump’s use of the International Emergency Economic Powers Act (IEEPA) for tariffs has added further complexity to the 2026 trade environment.

In February 2026, the Court ruled that IEEPA does not authorize unilateral presidential tariffs, reaffirming Congress’s control. This invalidated tariffs under IEEPA, but did not signal a general retreat from tariffs as policy.

The administration immediately replaced these duties using other constrained authorities, such as Trade Act Sections 122, 232, and 301.

For global trade professionals, tariff uncertainty persists: rates, legal rationales, and timelines may shift, yet companies must still adapt rapidly. Thus, tariff engineering, scenario modeling, and classification accuracy remain essential.

Harmonized System update: How to prepare for HS 2027

The next major Harmonized System (HS) update takes effect on January 1, 2027. These next few months mark a critical preparation period for trade teams.

HS changes are not simply administrative updates. They affect:

• Product classification logic
• Duty rates and trade remedy exposure
• Free trade agreement qualification
• Import and export licensing requirements
• Internal product master data

For companies with large product portfolios, HS changes require systematic review and remediation, leaving little room for last-minute fixes. Waiting until the last few months of the year increases the risk of misclassification, shipment delays, incorrect duty payments, and audit exposure.

The organizations that manage HS transitions well treat classification as strategic data, not static reference information. That means starting early, validating product mappings, and ensuring that downstream systems — from ERP platforms to customs filing tools — are well aligned before the effective date.

Carbon border compliance in global trade: from reporting to cost

Another major shift this year holds is the evolution of carbon-related trade mechanisms, particularly in Europe. What began as a reporting exercise is now moving into a phase where financial consequences are real and unavoidable.

This introduces new risk: emissions data must be accurate and defensible, supplier information becomes key, trade and sustainability teams must cooperate, and cost modeling must include carbon exposure.

This is not simply an environmental issue — it is a trade data challenge. Customs authorities are increasingly interested in how emissions data aligns with product declarations, origin claims, and supply chain transparency.

The practical implication of carbon compliance is clear: trade professionals must work collaboratively with sustainability teams. Otherwise, crucial data that teams rely on may overlap, causing inconsistencies that are likely to draw scrutiny.

Forced labor compliance: New enforcement and proof requirements

Forced labor enforcement continues to intensify, particularly for imports linked to high-risk regions and materials. However, enforcement activities aren’t the only things changing. Now there is an expectation of proof.

Authorities are moving beyond basic documentation reviews and toward:

• Detailed supply chain mapping
• Evidence-based risk assessments
• Transaction-level traceability
• Ongoing monitoring rather than one-time attestations

For global trade teams, the key takeaway is that supplier declarations alone are no longer sufficient. Compliance programs must clearly demonstrate how risks are identified, mitigated, and regularly reassessed.

Data maturity matters. Companies with fragmented systems and manual processes will struggle to respond quickly and confidently to inquiries. Those with integrated data and clear audit trails will be better positioned to demonstrate compliance.

Pre-arrival data requirements: How customs authorities assess risk earlier

Customs authorities worldwide are placing greater emphasis on the quality of pre-arrival data. The logic is straightforward: earlier visibility allows earlier risk assessment.

From a trade operations perspective, this raises the bar:

• Data must be complete before goods move
• Errors are detected sooner — and penalized faster
• Manual workarounds become increasingly risky

This trend reinforces a broader reality: compliance is expanding farther “left” or “upstream” in the supply chain. Decisions made at the sourcing, procurement, and product setup stages increasingly determine whether shipments move smoothly.

Trade professionals are being asked to influence upstream processes — often without direct authority — which makes collaboration and clear communication essential. To support these demands, technology is increasingly central to effective compliance.

Why technology alone cannot solve global trade compliance complexity

Technology is often described as the solution to trade complexity. In a perfect world, it would be.

In reality, it enables teams to be their best-informed, most effective selves. By automating repetitive, manual tasks and using tools that surface risks early, your team can address pressing issues faster and with greater precision.

Systems can also help:

• Centralize and standardize data
• Assist with classification
• Apply consistent rules at scale
• Surface risks earlier
• Support defensible audit trails

While technology can do a lot, it cannot compensate for unclear ownership, poor data governance, or reactive processes.

 

As trade teams evaluate tools and platforms, the most important question is not “what features does this system have?” but rather “does this help us make better decisions earlier?”

In 2026, value comes from visibility and consistency—not just automation. Key takeaway: Prioritize processes that offer greater data transparency and reliability. With this in mind, let’s consider how leading trade teams are setting themselves apart.

Best practices for building resilient, data-driven trade compliance teams

Across industries, high-performing trade teams share these characteristics as they prepare for this trade year:

1. They invest in data quality first.
   Rather than chasing every new requirement individually, they focus on improving the accuracy and consistency of core trade data.
2. They break down internal silos.
   Trade, procurement, sustainability, and IT teams collaborate more frequently and earlier.
3. They plan regulatory change as a program.
   HS updates, carbon mechanisms, and forced labor requirements are treated as ongoing disciplines rather than one-off initiatives.
4. They prioritize understanding.
   They can articulate not just what their data says, but how it was derived and why it can be trusted.

Key Takeaway: Preparation fosters confident compliance

Global trade has never been static, but the pace and interconnectedness of change heading into 2026 make preparation more important than ever.

This is not about predicting every regulatory outcome. It’s about building the foundational capabilities — data, processes, and collaboration — that allow trade teams to adapt with confidence.

Organizations that take these next several months to invest in preparation will be better positioned to use compliance as a strategic lever against competitors who do not. Those who delay may find themselves reacting under pressure, with limited options and increasing exposure. In global trade, confidence is earned long before goods reach the border.

As you look ahead to the rest of 2026, which global trade compliance challenge is putting the most pressure on your team right now?

Curious how others are tackling these challenges? Watch our on-demand webinar, “Global Trade in 2026, hosted by the American Association of Exporters & Importers, to see how your peers are turning last year’s compliance lessons into smarter customs strategies this year.

Have a specific challenge or question? Contact us to start a conversation about how your organization can build a more resilient, data-driven global trade compliance strategy.

FAQ: Global Trade Compliance in 2026

What are the biggest global trade compliance risks in 2026?

The biggest global trade compliance risks in 2026 stem from convergence rather than any single regulation. Trade teams are navigating tariff uncertainty, preparations for the HS 2027 Harmonized System update, expanding forced labor enforcement, carbon compliance requirements, and stricter pre-arrival data expectations—often at the same time.

What makes these risks more difficult to manage is how interconnected they have become. Classification, origin, valuation, emissions data, and supply chain transparency now influence one another. A weakness in one area can quickly create exposure in another.

In 2026, compliance risk is increasingly a data risk. Organizations with inconsistent, fragmented, or poorly governed trade data face higher enforcement exposure and less flexibility when regulations change.

How will the HS 2027 Harmonized System update affect importers?

The HS 2027 update will require importers to reassess product classifications across their portfolios. While the update does not take effect until January 1, 2027, 2026 is the critical preparation window.

HS changes affect more than tariff codes. They can influence duty rates, trade remedy exposure, free trade agreement eligibility, licensing requirements, and internal product master data. For companies with large or complex product catalogs, these impacts compound quickly.

Importers that treat classification as strategic data—rather than static reference information—are better positioned to manage the transition. Early planning reduces the risk of misclassification, shipment delays, incorrect duty payments, and audit exposure.

What is carbon compliance and how does it impact trade costs?

Carbon compliance refers to trade-related mechanisms that require companies to report—and increasingly pay for—emissions associated with imported goods. What began as a reporting exercise is now evolving into a cost and risk consideration for global trade teams.

As carbon border mechanisms mature, emissions data must be accurate, defensible, and aligned with product, origin, and supplier information. This introduces new cost modeling challenges and increases the importance of supplier data quality.

Carbon compliance is not only a sustainability issue. It is a trade data challenge. Misalignment between emissions data and customs declarations can raise scrutiny and increase compliance risk.

How are forced labor regulations changing global trade enforcement?

Forced labor enforcement is becoming more rigorous and evidence-driven. Authorities are no longer relying solely on supplier declarations or high-level documentation.

Instead, enforcement is shifting toward detailed supply chain mapping, evidence-based risk assessments, transaction-level traceability, and ongoing monitoring. There is now an expectation of proof, not just policy statements.

For global trade teams, this means compliance programs must clearly demonstrate how forced labor risks are identified, mitigated, and reassessed over time. Data maturity and audit-ready systems are increasingly essential.

What is pre-arrival data and why are customs authorities focused on it?

Pre-arrival data refers to the information customs authorities receive before goods physically arrive at the border. This includes classification, origin, valuation, and other key trade data elements.

Customs authorities are prioritizing pre-arrival data because earlier visibility enables earlier risk assessment. Errors can be identified sooner, and enforcement actions can occur before goods are released.

For companies, this shifts compliance further upstream. Decisions made during sourcing, procurement, and product setup increasingly determine whether shipments move smoothly or face delays and penalties.

How can companies manage ongoing tariff uncertainty?

Tariff uncertainty remains a defining feature of the global trade environment, even as legal authorities and policy mechanisms evolve. Rates, legal justifications, and timelines may change, but the operational impact remains.

Companies manage tariff uncertainty best by focusing on what they can control. This includes strong classification accuracy, scenario modeling, tariff engineering, and consistent trade data governance.

Rather than reacting to each change in isolation, resilient organizations build foundational capabilities that allow them to adapt quickly and make informed decisions earlier in the supply chain.

When people talk about the future of supply chain planning, the conversation always drifts toward technology, especially artificial intelligence, or toward macro forces like tariffs, trade policy, and the volatility they introduce. But the most important part of the future isn’t technology or geopolitics. It’s the planner.

At the center of every supply chain, regardless of how advanced the tools become, there is still a person making decisions. And as supply chain planning evolves, the role of that planner is changing faster than many organizations realize.

When we talk about the planner of the future, “of the future” doesn’t mean some distant, theoretical world a decade from now. It means the near future, where some planners already are because the manual work is fading into the background. In many organizations, planners still spend most of their time collecting data, reconciling spreadsheets across disconnected systems, and firefighting exceptions just to keep the day’s plan afloat.

When the right tools automate and augment that work, the role fundamentally changes. The planner becomes less reactive and more strategic: an orchestrator of decisions focused on shaping demand, assessing risk, and weighing tradeoffs across the supply chain.

The planner of the future is defined not by producing plans, but by designing the decision logic, priorities, and tradeoffs that guide the supply chain.

Why the supply chain planning role is changing now

The planning role has already changed for some organizations and will continue to evolve. Two forces are driving that shift.

The first is the environment planners operate in. Supply chains today are more volatile, complex, and interconnected than ever. Demand patterns can shift quickly, and disruptions rarely remain isolated. When one node breaks, the impact ripples across suppliers, logistics partners, and customers.

In this context, planning becomes a competitive differentiator. Organizations that can sense changes and respond quickly outperform those relying on manual, spreadsheet-driven processes that were never designed for this level of complexity.

The second force is an inflection point in technology. Artificial intelligence in planning is not new, but recent advances have expanded what is possible and accelerated executive attention. Generative AI has heightened expectations, but it represents only one part of a broader set of capabilities that includes machine learning, optimization, and heuristics.

What has changed is the speed, scale, and accessibility of these tools, and the way they are reshaping the role of the planner.

How the planner’s day-to-day work is changing

In traditional planning environments, planners spend much of their day pulling data from multiple source systems and trying to reconcile it into something usable. They make countless small, tactical decisions while simultaneously trying to keep the plan from breaking. Do I have the right parts for this order? Do I have the capacity this week?

Over time, that effort adds up and becomes the standard for the role. The result is that planners get buried in the details and rarely have the space to step back and assess the bigger picture.

In a modern planning environment, the day starts very differently.

Planners begin with a baseline plan already in place, built overnight as data is automatically pulled from source systems into a common format and run through the planning engine with capacity and material constraints fully considered.

Rather than spending the day chasing hundreds of exceptions, planners work from a set of pre-configured scenarios and compare them side by side, evaluating tradeoffs like service versus cost or different ways to allocate limited supply. When constraints arise, as they always do, planners test demand prioritization rules across customers, product groups, and profitability segments to deliberately shape the outcome. They then spend their time collaborating upstream and downstream with a clear understanding of the constraints and the ask.

This is how the role is elevated: the system handles the small, repetitive work, and planners focus on the big decisions like running scenarios, evaluating tradeoffs, prioritizing objectives, and aligning the supply chain around them.

What enables the planner of the future

The difference in a planner’s day comes down to the balance between what the planner is doing versus what the planning system is doing.

There’s no shortage of supply chain planning tools on the market, and many are very good at what might be called “unconstrained planning.” In these environments, planners are given a high degree of manual control: they can move a production order, override a recommendation, and work through a long list of exceptions, one change at a time.

On the surface, this feels empowering, like control. In practice, it often pulls planners into a series of small, tactical decisions that violate underlying constraints. It’s hands-on. It’s slow. It keeps the planner focused on the trees rather than seeing the forest. And the truth is, the right software is simply better suited to do this work than people.

Only some tools are particularly good at constrained planning, which takes a fundamentally different approach. Instead of asking planners to manage the “messy middle,” these tools are designed to respect material, capacity, and network constraints automatically and simultaneously. These systems enforce priorities, select alternative resolutions, and keep the entire network synchronized as conditions change.

The planner’s role shifts to defining the right inputs: constraints, priorities, and resolution options. Then they focus on evaluating the outcomes the system produces.

If the results aren’t acceptable, planners don’t manually tweak individual orders or alternative processes. They adjust the decision logic, such as the rules that govern how demand is prioritized and how product flows, allowing the system to regenerate the plan.

Put simply, the tool is planning. The planner is steering.

This approach matters because the plan must remain realistic and achievable across the entire network. For example, when priorities change, the impact ripples.

If we decide Customer A must be served ahead of Customer B, we don’t just move one production order. We trigger a chain reaction.

The finished-goods schedule changes, which means the upstream subassembly schedule has to change with it. That upstream subassembly order must fit in a time slot with available capacity. That slot must have the components available. If the components are not available, the downstream plan can’t just “hope it works.” Everything has to move together, in sync, or the plan breaks.

The skills that define the planner of the future

The question of which skills will define successful planners going forward really matters, because it shapes how organizations recruit, develop, and invest in talent. At a foundational level, planners still need strong process and technology skills: a clear understanding of objectives, supply chain planning principles, analytical ability, and a grasp of how planning systems actually work.

Beyond that, cross-functional experience is critical. Planners must understand how decisions ripple through the supply chain, and how a change in one area affects another. A classic, simple example is total cost of ownership: securing a lower unit price from a supplier is great, but if it comes with an extended lead time, it likely will drive higher safety stock costs. Without that systems-level awareness, local “wins” create global problems.

The more interesting skill, and one that is not discussed often enough, is creativity.

Planning technology is ultimately limited by the information we give it, and the human advantage lies in asking better questions: What additional signals might matter? What other data could improve the model?

Take e2open’s Demand Sensing solution as an example. It ingests a wide variety of inputs and uses machine learning to determine which inputs are most predictive of future demand.

In one real case involving ice cream demand, the system ultimately discovered that the real driver of demand was not that day’s temperature, but the change in temperature from the day before.

The system only found that pattern because a planner had the creativity to ask what additional inputs might matter and feed those into the model for evaluation. That is the human skill: imagining what data might improve the model so the technology can go find the patterns.

Preparing organizations for the future of supply chain planning

As the planner of the future takes shape, it’s increasingly clear that the role no longer resembles what it once was. The question is whether the title “planner” still fits at all. The work is no longer about producing plans, but about defining objectives, setting priorities, and designing the decision logic that guides the supply chain.

In that sense, the planner of the future looks less like a scheduler and more like a decision architect—someone who shapes how the system thinks, and ultimately what it produces.

FAQ: The planner of the future

What is the planner of the future?

The planner of the future is a decision architect, not a scheduler. Instead of manually building and fixing plans, this role focuses on defining priorities, constraints, and tradeoffs that guide how the supply chain responds to change. The system generates the plan, and the planner steers the decisions behind it.

How is the role of supply chain planner changing?

The supply chain planner role is shifting from reactive execution to strategic decision-making. As automation and AI handle data collection, reconciliation, and exception management, planners spend more time running scenarios, evaluating tradeoffs, prioritizing demand, and aligning stakeholders across the supply chain.

Why is supply chain planning changing now?

Supply chain planning is changing due to two forces: increased volatility and advances in technology. Supply chains are more complex and interconnected, making manual planning unsustainable. At the same time, modern planning technologies—including constrained planning, machine learning, and AI—can process complexity at speed and scale, reshaping how planners work.

What skills will supply chain planners need in the future?

Future supply chain planners need strong analytical skills, systems thinking, and cross-functional awareness. Beyond technical knowledge, creativity becomes critical—planners must imagine new data inputs, ask better questions, and shape how planning systems make decisions. Communication and collaboration skills also grow in importance as planners align teams around tradeoffs.

Will AI replace supply chain planners?

AI will not replace supply chain planners, but it will change what they do. Planning systems are better suited to handle repetitive, constraint-heavy calculations. Planners remain essential for defining objectives, interpreting outcomes, and deciding what the supply chain should optimize for.

How is constrained planning different from unconstructed?

Unconstrained planning relies heavily on manual intervention and exception management, often ignoring real-world constraints until problems surface downstream. Constrained planning solves the plan end to end, ensuring that changes in priorities, supply, or demand ripple realistically through the entire network.

How smarter stackability logic helps FTL shippers cut costs without changing their freight.

Shipping full truckloads means you’re already paying for the entire trailer, whether you use all that space or not. That’s why capacity utilization is one of the most reliable ways to reduce transportation spend without renegotiating a single rate. With the right stacking logic built directly into your TMS, those savings start to show up quickly and predictably.

Pallet stacking intelligence provides a practical, rules-based way to use the trailer space you already have, improving rating accuracy, routing decisions, and measurable transportation savings through efficiency.

Why capacity utilization drives FTL cost reduction

FTL shippers pay by the truck, not by the pallet. Every extra pallet you can fit into a trailer reduces the number of loads needed to move a fixed volume of freight.

Take a real-world example: Increasing average pallets per load from 22 to 34 resulted in about 61 fewer loads per year on a 3,800-pallet network. At roughly $2,400 per load, that’s about $145,000 in annual linehaul savings, before touching carrier rates.

That’s the kind of impact that makes capacity utilization one of the highest ROI levers in most transportation value assessments.

Six ways pallet stacking intelligence reduces FTL transportation costs

1. Fewer loads for the same volume
   More usable pallet space per truck means fewer trucks overall. As the example above shows, even modest improvements compound into major reductions in load count.
2. Lower linehaul spend
   Linehaul is the biggest cost bucket in any FTL budget. Even small gains in trailer utilization translate directly into significant savings.
3. Better carrier and mode selection
   When loads consume fewer pallet spaces, they often qualify for cheaper routing guide tiers, enabling more competitive carriers to be selected.
4. More accurate rating
   If a planner estimates space incorrectly, rating systems often overcharge. Capturing pallet space data at the order, shipment, and equipment levels eliminates “phantom space” and aligns ratings with actual usage.
5. Reduced accessorials and fewer handling events
   Higher utilization can reduce loading/unloading events, touch points, and congestion, helping minimize handling-related charges.
6. Sustainability and efficiency gains
   Fewer trucks mean fewer emissions, less dock activity, and better use of carrier capacity.

What makes pallet stacking intelligence “intelligent”?

Pallet stacking intelligence uses item and pallet attributes—dimensions, weights, fragility, and stackability flags—plus shipper-defined rules to determine when pallets can be safely stacked. The TMS then optimizes load plans around those combinations.

A few things set this approach apart from manual stacking:

• Rule-driven, data-aware decisions that respect product restrictions and safety limits
• Integration with rating and routing guides, keeping pricing and execution aligned
• Optimization and autobuild support, enabling consistent results without extra overhead

How pallet stacking intelligence improves rating accuracy

Many carriers price based on trailer space, not pallet counts. By calculating pallet space accurately, pallet stacking intelligence helps eliminate overpayments caused by conservative planning assumptions. Because the TMS captures data on pallet space from the order through the equipment, rating stays aligned with the true utilization.

How pallet stacking intelligence improves routing guide performance

Routing guides often include pallet space thresholds. When stackability improves, loads may qualify for different (often cheaper) service tiers or carriers. Advanced Optimization keeps routing guide selection aligned with the optimized load plan, so planners don’t get mismatches between what fits and what gets priced.

The story becomes simple:

What industries benefit the most from pallet stacking intelligence?

Pallet stacking intelligence delivers value across multiple industries—especially those that move predictable, high-volume lanes via FTL:

• Manufacturers, the largest FTL users in the U.S. (31.55% market share in 2025), with steady, repeatable lanes
• Retail and wholesale shippers, moving replenishment loads into and out of distribution centers
• Food and agriculture producers, which often max out weight before cube and benefit from controlled handling
• Construction suppliers, shipping dense, heavy materials to job sites on firm schedules

Each of these shipper types already pays for full trailers. Increasing usable pallet space delivers immediate, meaningful upside.

The bottom line: Why pallet stacking intelligence delivers fast ROI for FTL shippers

Pallet stacking intelligence is one of the simplest, fastest ways for FTL shippers to unlock real transportation savings. Instead of relying on manual judgment, the TMS applies consistent, data-driven rules to improve stacking decisions, increase capacity utilization, and align planning with rating and routing logic. The result is measurable, repeatable cost reduction with the freight you already have.

Ready to see what pallet stacking intelligence could do for your network?

If you want to dig deeper into how e2open TMS helps shippers improve utilization, cut linehaul costs, and align planning with rating and routing logic, we’d be happy to walk you through it.

Contact us to explore whether pallet stacking intelligence is a fit for your operation.

Sustained volatility means complex supplier networks need more than visibility

Manufacturers today manage global, multi-tier complex supplier networks that change faster than most planning systems can keep up with. Raw material scarcity, changing trade regulations, and sudden demand shifts put pressure on supply chain teams. Yet many manufacturers’ supply chains still rely on siloed, internally focused planning solutions that weren’t designed for these modern supply chain complexities.

During our live webinar, Charles Brennan, Senior Analyst at Nucleus Research and Dan Stidsen, Senior Director of Solutions Consulting at e2open, discussed how manufacturers are responding to these challenges by modernizing their supply chain planning. The discussion was centered around a recent report from Nucleus Research.

Why the current geopolitical landscape is reshaping supply chain strategy

The impact of geopolitics has evolved from affecting procurement to becoming a broader planning challenge for companies, notes Brennan. “Trade restrictions and tariffs are reshaping sourcing decisions. A single policy shift can change landed costs or supplier viability overnight which is why organizations are leaning harder into aspects such as scenario planning.”

These geopolitical pressures are also accelerating structural shifts in supply chains. Nearshoring and nationalization trends are transforming supply chains and accelerating network designs as companies rethink how and where they operate. “Companies are reconsidering where they build, where they source, and how they rebalance costs with resilience,” says Brennan. As an example, Europe faces growing regulatory complexity, with ESG requirements demanding deeper visibility into supplier networks.

However, supply visibility and tracking risk within your networks isn’t enough. Whether it’s rebalancing inventory, adjusting capacity, or shifting suppliers, Brennan notes that organizations need structured plans to act on these risks. “Companies that embody agility are the ones that treat planning as a dynamic capability that adjusts as geopolitical shifts unfold in real time.”

Trend alert: Rising demand for integration between supply chain planning and execution

For a long time, planning and execution lived in silos, but that’s changing.

“We’re seeing a demand from customers for integration between supply chain planning and execution systems – everything from manufacturing to warehouse and transportation,” says Brennan. “The goal is to unify forecasting, production, logistics and fulfillment, so when a disruption is identified, a plan automatically triggers a coordinated action across the network.”

“We’re moving towards a world where planning and execution happen in one continuous loop.”

– Charles Brennan

Why traditional planning is no longer working

Traditional planning focuses on operations within the four walls of an organization, and internal data, like sales history, inventory, and production capacity.  Understanding historical demand patterns and production schedules is valuable, but on their own, they no longer tell the full story.

The challenge is connecting those internal signals with what’s going on externally, both upstream with suppliers and downstream in the channel. When planning relies on siloed, internally focused planning solutions, it becomes difficult to account for supplier constraints, shifting consumer behavior, or disruptions occurring in the multi-tier network.

Traditional planning works well in stable environments. But it quickly breaks down when conditions change. Sudden demand shifts, material shortages, supplier capacity issues, or disruptions all introduce uncertainty that static plans can’t absorb.

The growing need for outside-in planning

“Most disruptions don’t actually happen to our business directly, but to our partners upstream and downstream which ultimately impact our business. That’s where you have the most exposure,” says Stidsen. Outside-in planning enables organizations to focus on early detection and proactive responses rather than reacting after the fact that something happened.

Stidsen points to an example of how outside-in planning works in practice: “Downstream into the channel, brand owners will use point of sale information from the retailers they sell into, because that allows them to see early demand signals. This in turn enables them to make better inventory positioning decisions and that helps them consider how they might need to be repositioning inventory.” Upstream, manufacturers collaborate with suppliers to understand constraints and align on what can realistically be delivered.

Real-world case studies: Making the case for supply chain planning software

Nucleus Research interviewed e2open customers to understand their challenges, why e2open supply chain planning software was selected, and the measurable business value they achieved. Two of these use cases were discussed in detail in the webinar.

How a global automotive manufacturer saved millions

Before working with e2open, a major luxury automotive manufacturer relied on manual processes and limited planning tools which hindered real end-to-end supply chain visibility and slowed decision-making. With 16,000 Tier 1 suppliers and around 5,000 aftermarket suppliers, they needed a better way to connect and manage these partners.

“They wanted a solution that could provide supplier confirmation tools to ensure that order acceptance and commitment tracking had the visibility,” says Brennan. He adds that they also wanted logistics visibility to monitor the movement of goods in real time, and advanced planning functionality to create efficient, resilient production plants.

The automotive manufacturer evaluated several supply chain management vendors. “They selected e2open for its manufacturing-specific strengths. And that it is a comprehensive, integrated solution that provides tools beyond supply chain planning,” says Brennan.

Multi-echelon inventory optimization (MEIO) can deliver quick wins

To generate early value and build momentum, the manufacturer began their transformation with Multi-Echelon Inventory Optimization (MEIO). The initial deployment focused on a controlled set of non-sequenced parts, such as fasteners, brake components, and accessories, across supplier stocking locations and assembly plants.

“We intentionally started small,” says Stidsen. “The objective was to identify excess inventory without increasing risk, and to demonstrate that optimization across the network could work in practice — not just in theory.”

The results were immediate. Excess inventory was identified and safely set aside during the pilot, building confidence within the organization. As the scope expanded to more than 80,000 parts, the manufacturer achieved a 13% reduction in inventory, while maintaining service levels.

Beyond inventory savings, the impact extended to risk mitigation. Optimized buffer positioning reduced exposure to assembly line shutdowns and minimized the need for costly expediting. To date, the automotive manufacturer has reported approximately $15 million in operational savings, driven largely by improved inventory optimization and faster disruption response.

“Connected planning changed how decisions were made. With earlier visibility into constraints and the ability to act on them, the organization improved production efficiency, model mix decisions, and overall supply chain resilience.”

– Charles Brennan

How an equipment manufacturer reduced inventory and increased OTIF performance

Over the past 30 years, a $40 billion equipment manufacturer specializing in mechanical and electronic security and locking technologies grew heavily through mergers and acquisitions. This resulted in a fragmented environment and disconnected tools with a legacy ERP system that had limited forecasting and production planning capabilities.

They needed an end-to-end platform to manage and unify operations across two supply chains: one for traded goods and one for configured components. “What they required in a planning solution is demand and supply planning, inventory management, and sales and operational planning capabilities,” says Brennan. They needed multi-tier supply chain collaboration for sustainability and mining source visibility. And chip production transparency for upstream supply assurance.”

“When they evaluated the market, e2open was selected for its intuitive, trustworthy, end-to-end platform, combining strong functionality with ease of use,”

– Charles Brennan

By leveraging e2open solutions, the company saw measurable operational impacts, including a 30% reduction in aged inventory. This allowed the organization to clear nearly three decades of accumulated inefficiency.

“They were able to dynamically reallocate stock across their warehouses, helping them improve supply chain connectivity. As a result, they improved on time and in-full rates. They went from 88% to 95%, and this is driven by better visibility and control.” Brennan adds, “Overall, this allowed them to have faster planning cycles, enhance agility, and provide stronger operational alignment.”

Boost planner productivity and forecast accuracy with AI-powered demand sensing

People and AI work together to drive better outcomes in complementary ways. The equipment manufacturer used demand sensing, e2open’s real time forecasting solution, to apply AI and generate a highly accurate baseline forecast.

Once that baseline was established, demand planners refined the forecast using their own judgment and input from the sales team. However, despite significant time and effort, improvements in forecast accuracy stalled. “It wasn’t clear how their manual adjustments were translating into better results,” says Stidsen. “So, we implemented forecast value add, which allows us to measure the true impact of human changes to the forecast.”

For some products, forecast overrides by the planner improved the accuracy because planners added important business context that the system didn’t have, like new product launches. But in many other categories, those manual adjustments made the forecast less accurate. “This provided clear direction on where planners should focus their efforts and where the forecast should be handled autonomously by the forecast engine,” says Stidsen. “In terms of the impact, this allowed planners to focus on where they’re adding the most value, and improved forecast accuracy overall.”

More accurate forecasts with demand sensing often lead directly to inventory savings.

“The more accurate the forecast is, the more likely we have inventory where and when it’s needed, which means we need less safety stock to buffer against any uncertainty.”

– Dan Stidsen

Implementing a supply chain planning solution

Why now is the time to invest in connected planning

“The supply chain has become a true differentiator for a lot of customers. They’re not competing against each other anymore – they’re competing against each other’s extended value chains,” says Stidsen. “The faster and more efficiently they can get products to their customers, the stronger their competitive position is.”

Stidsen points out that we’re at an inflection point with technology. Every executive is now asking how AI is being applied to their business strategy.  “Generative AI has opened everyone’s eyes to what technology is really capable of,” says Stidsen. “But it’s important to recognize that generative AI is only a piece of the technology pie.” He suggests focusing on the outcomes you want to achieve, and that will drive the right technology to use.

Three best practices for deploying a supply chain planning solution

1. Balance team composition: Achieving the right balance between internal teams and external consultants is essential for successful deployment. Brennan notes that consultants can help accelerate the project, but overreliance can create long-term dependencies. “On the other hand, relying solely on internal teams can stall the project, especially if the organization lacks technical expertise or bandwidth to maintain the momentum. The sweet spot we’ve found is to maintain that hybrid model.”
2. Adopt a bite-sized implementation approach: Rather than rolling out the entire solution at once, use a phased implementation strategy instead. Start with smaller, manageable components. Pick one core area like demand planning, and once it hits a certain level of operational maturity, then move on to the next phase, such as supply chain planning or inventory optimization. “Each phase becomes a quick win, and this helps organizations build high confidence, provides value early, and keeps that executive sponsorship strong throughout the entire journey,” says Brennan.
3. Validate value at each phase: Before moving to the next stage or deployment phase, validate that the current one is delivering measurable results. As an example, Brennan states, “If you’ve just deployed demand planning, take time to measure forecast accuracy, cycle time, or exception management improvements. Once the KPIs are stabilized, then move on to the next layer of planning. This creates a solid foundation where every stage builds on proven outcomes, rather than just assumptions.”

Biggest untapped ROI potential in supply chain planning implementation

Beyond improvements in forecasting accuracy and inventory, Brennan sees connecting planning to execution as being the most significant untapped potential for organizations, realizing faster ROI and quicker time to value.

“When decisions are made, this behavior spreads throughout the entire supply chain. You push that visibility deeper into the supplier network, and you get ahead of these constraints,” says Brennan. “Tying into how your plan is going to affect your execution is where I see organizations lacking. They often use systems that don’t integrate well with each other, and they look at it as separate functions within an organization.”

How to ensure long-term improvements with planning software

Beyond identifying aged inventory and reducing inventory costs, organizations must focus on sustaining these benefits and compounding value in years two, three, and beyond.  According to Brennan, long-term success comes down to strong data governance, clear ownership of the platform, and a mindset of continuous expansion. “These are the biggest ways organizations continue to realize ROI as they move on their deployments.”

“Organizations that are able to realize a ton of value in year one, continuously look at their supply chain as an evolution.”

– Charles Brennan

Sustained improvement also requires strong executive alignment, setting clear expectations, tracking/measuring progress against defined goals, and driving adoption across the organization. If you’re considering adopting a Connected Planning strategy, there are a few considerations to keep in mind:

• Questions to ask: Why are we making an investment? What problems are we solving? What outcomes do we expect?
• Establish a baseline to measure against: Focus on whatever matters most to your organization, whether it’s forecast accuracy, service, or inventory. Set the target, track it, and make the results visible.
• Automation changes how people work, so it’s important to have transparency: Show people how the system is making decisions and how their insights are also reflected in the system.

Finally, organizations need to invest in tools that support continuous improvement beyond the initial implementation. “You need a system that can learn, adapt, and evolve over time,” says Stidsen. He points to e2open’s next generation of demand sensing as an example, where teams can create scenarios to test different models using different inputs rather than locking into a single approach. “The big gains don’t last forever, but small improvements over time add up,” he adds. “This creates a cycle of learning, measurement, and continuous improvement, so the value’s not fading after year one, it’s compounding.”

How to drive long-term value with connected supply chain planning

Connected supply chain planning is no longer a “nice to have” for manufacturers, but a requirement for successfully competing in an environment defined by volatility, geopolitical disruption, and complex, multi-tier networks.  Organizations that connect operations across demand, supply, inventory, and execution outperform those relying on fragmented, siloed approaches.

When it comes to achieving real value in supply chain planning, Brennan and Stidsen reinforced these key takeaways for manufacturers:

• Take a sustained, phased approach. The most successful organizations understand that transformation is a journey. Focus on quick wins, then build momentum and expand the capabilities over time.
• Anchor planning outcomes. Be clear about the outcomes you want to drive and the business metrics that matter. Decisions need to get better, faster, and more connected, while remaining open to how those outcomes are achieved.
• Connect planning to execution. Ensure plans drive real-world actions across your supply chain network.
• Invest in systems that evolve. AI-enabled capabilities like demand sensing, scenario planning, and MEIO can help organizations adapt as business conditions change.

In a world where companies are competing against each other’s extended value chains, connected supply chain planning becomes a powerful differentiator. The manufacturers that treat planning as a dynamic, adaptive capability are the ones best positioned to improve resilience, accelerate growth, and deliver sustained value year after year.

For deeper insights and hear the full discussion, watch webinar on demand, Unlocking Value: Research Insights on Supply Chain Planning. Or download a copy of the full report, Nucleus Research: Assessing the Value of e2open Supply Chain Planning for Manufacturers.

If you’d like to connect with an e2open expert about how to drive long-term value with connected supply chain planning, contact us today.

FAQs: Supply chain planning for manufacturers

1. What is connected supply chain planning?

Connected supply chain planning integrates forecasting, production, inventory, and logistics into a unified process. It enables real-time collaboration across suppliers, manufacturers, and partners to improve agility and resilience.

2. How does demand sensing improve forecast accuracy?

Demand sensing uses AI and real-time data signals, such as point-of-sale (POS) and market trends, to create highly accurate forecasts. This improves forecast accuracy, increases planner efficiency, and reduces buffer stock by placing the right inventory in the right location upfront.

3. What are the benefits of multi-echelon inventory optimization?

Multi-echelon inventory optimization (MEIO) optimizes inventory across multiple tiers of the supply chain, reducing excess stock while maintaining service levels. Benefits include lower inventory carrying costs, improved cash flow, and reduced risk of service disruptions.

4. How quickly can manufacturers expect to see positive results from supply chain planning implementation?

It depends on the size of the implementation and how the organization approaches the deployment. “Typically, we see payback period within a 6-month range. That is when we’ve seen a lot of organizations starting to realize value from their supply chain planning deployment,” says Brennan.