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How IT Should Define Supplier Readiness Criteria

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Supplier readiness is conventionally owned by procurement and supply chain. They decide what a qualified supplier looks like, using criteria such as financial stability, regulatory compliance, quality certifications, production capacity, and ethicalsourcing. 

Those criteria establish whether a supplier should be in your supply base. However, they say almost nothing about whether that supplier can actually transact with your business (i.e., whether their EDI connection works, whether their documents conform to your requirements, and whether their data lines up with yours) the day after the contract is signed. 

To find the answer, there are several questions to answer within your organization: 

These questions reveal the IT layer of supplier readiness. The other layer is procurement, meaning the sourcing and vendor-management function that qualifies and approves new suppliers: financial, legal, quality, regulatory. Most organizations define the procurement layer rigorously and the IT layer barely at all. The predictable result is a supplier who clears every procurement gate, goes live, and starts generating exceptions immediately. Those exceptions then get owned reactively by IT, supply chain, and operations, long after the point where preventing them would have been cheap and easy. 

The fix is a clearer, more rigorous definition of what IT-side readiness means, written down and enforced before a supplier is approved for production. This article gives IT and integration leaders a practical way to do it: a framework for the integration-side criteria, the sign-off discipline to hold go-live to those criteria, and the cross-functional language to bring procurement and supply chain into a shared definition of what "ready" means. 

Why the Integration Layer Goes Undefined 

Integration layers tend to go undefined due to structural reasons, rather than carelessness or oversight. The first reason is an ownership gap. 

 owns the contract, while supply chain owns the relationship. Transactional readiness, the question of whether a supplier can actually send and receive the documents that move goods and money, falls in the space between them with no default owner. When readiness is everyone's concern and no one's responsibility, it gets the attention an unowned thing always gets, which is none until it fails. 

The second reason is a sequencing assumption. Integration tends to be treated as an implementation detail, something the technical teams handle after the deal closes, rather than a criterion that determines whether the deal should close in its current form. Procurement's criteria, on the other hand, gate approval. Integration is assumed to be solvable, so it is scheduled instead of gated. 

The third reason is a vocabulary gap. Procurement has spent years building mature, documented standards: questionnaires, scorecards, thresholds, audit checklists. The criteria are written down, which means they can be applied consistently and enforced by people who did not personally invent them. IT's requirements usually have no such artifact. What counts as a ready supplier often lives as knowledge only in the heads of an integration team. 

The good news is that all three are fixable, because none is a skill problem. The integration team already knows what a ready supplier looks like. The layer just needs what procurement's already has: an owner, a place in the workflow, and the criteria written down.  

The Framework: What IT-Side Readiness Actually Consists Of 

The integration layer breaks down into five categories. Each is a dimension of readiness, not a task to complete later, and each fails at go-live in a specific, predictable way when you leave it undefined. 

Can the supplier connect at to your EDI, on a protocol you actually support, with working credentials and a transmission path you've tested end to end?

When this is undefined, you discover at go-live that they're on a protocol you don't run, or that credentials were never exchanged, and the first document has nowhere to go. Ready means a successful test transmission over an agreed protocol (AS2, API, VAN, or whatever you support), not a promise that they "do EDI." 

Can the supplier produce and consume the required documents correctly and on time?

 (EDI 856) with accurate content and timing, 

 (EDI 810), and any other documents your flow requires. The failure mode here is the supplier who is technically EDI-capable but doesn'tconform to 

implementation guidelines, so the documents arrive malformed or late. Ready means conformance to your specs, proven in test. 

Does the supplier’s item master records reconcile with your catalog before the first live order?

, pack and case configuration, units of measure, and pricing fields all have to line up. When they don't, orders fall out, ASNs mismatch, and invoices dispute. Ready means a completed reconciliation with discrepancies resolved up front. 

Are the supplier's authentication, encryption, data-handling, and access controls compatible with your requirements and policies? 

This is the category most likely to be skipped entirely, because it surfaces no error message. It just leaves you exposed. Ready means their posture has been reviewed against your standards and meets them. 

Beyond the technical connection, can the supplier actually run at your scale?

This covers volume readiness, a defined exception-handling process, named escalation and support contacts, and a completed test or certification cycle in a non-production environment. Undefined, you find out at peak that the supplier can't handle volume or has no one to call when something breaks. Ready means they've run the full cycle in test and the operational details are documented before go-live. 

A framework you can't measure is just a list of good intentions. These five categories only become enforceable once each one is written as something you can check and sign off on. 

Start by converting each dimension into pass/fail acceptance criteria. "Can send an ASN" is a judgment call that two people will score differently, but "transmitted three conforming 856s in test within the required timing window" is a fact you can verify. Every criterion should resolve to met or not met, so that approval doesn't depend on who is reviewing or how confident they feel that day. 

Then define the evidence. For each criterion, name the artifact that proves it:  

If a criterion has no artifact behind it, it won’t function as a metric.  

Tier the criteria rather than applying all of them at full depth to every supplier. A low-volume supplier on a handful of transaction types doesn't warrant the same scrutiny as one feeding your highest-volume DCs. Scope the depth to transaction type, volume, and risk, so the gate is rigorous where it matters and proportionate where it doesn't. 

Finally, separate blocking criteria from remediable ones. Some failures stop go-live, full stop with no working connection, no conforming documents, or an item master that doesn't reconcile. Others can go live with a fix on a defined timeline. Drawing that line in advance is what lets you hold firm on what truly blocks production while staying flexible on what doesn't. 

Testable criteria still don't enforce themselves. Without that gate of enforcement, the criteria become documentation that gets consulted after something breaks rather than a checkpoint that prevents it. 

Embed the IT-side criteria as a gate in the onboarding workflow you already have, running parallel to procurement's gates rather than bolted on at the end. A supplier should clear integration readiness on the same path and at the same stage they clear financial and legal review. 

Define the sign-off itself and name who certifies each category, state what "approved for production" actually requires, and make one rule explicit: an unmet blocking criterion stops go-live. 

The hard part is commercial pressure. It’s conceivable that a supplier wants to go live before they're integration-ready, and the instinct will be to waive the gate. Use the remediation track instead: launch on the criteria they've met, with the unmet non-blocking items on a dated plan and an owner. That gives the business a path to move quickly without pretending readiness exists where it doesn't. 

A few predictable objections come up when proposing a readiness gate, along with a few ways the gate fails even after you've built it. 

The goal is not for IT to seize supplier approval; it's to clarify that readiness has always had more than one dimension, and that the integration layer is simply the one IT is equipped to own, the way procurement owns financial and legal and supply chain owns the relationship. 

The practical move is to put the IT criteria on the table alongside procurement, in the same onboarding workflow, and let each function own the layer it's closest to. Make the shared interest explicit: Every team wants suppliers who can transact on day one, and a defined integration gate is how you get them. Position IT as the function that certifies one part of a joint readiness standard, not as a new approver standing between procurement and the deal. The fix isn't more authority for IT, it's a definition of readiness that finally includes the part IT was always responsible for. 

Defining IT-side readiness is the work. Proving it before a supplier reaches production is the payoff. That's where the right tooling matters: a way to onboard trading partners, validate that they conform to your document and data requirements, and confirm they can actually transact before the first live order. 

SPS Commerce Fulfillment is built for exactly that. SPS Commerce Fulfillment: 

It's the gate between "approved by procurement" and "ready to transact," handled by people who do supplier onboarding at scale. 

 turns supplier readiness into something you verify instead of hope for. 

Supplier Data Quality Is the Hidden Cost Limiting Your Manufacturing Operations 

Supplier Data Quality: The Hidden Manufacturing Risk 

Most manufacturers have invested in modern ERP systems, analytics platforms, and AI-powered planning tools. But the data those systems depend on — purchase orders, shipment updates, and invoices flowing in from direct suppliers — is still largely manual and fragmented. When the data is wrong at the source, downstream investments underdeliver. This article explains why the supplier transaction layer is the root cause and what manufacturers can do about it.

You’ve upgraded the ERP. You’ve invested in planning software. You’ve made a strong case for AI. 

And yet the production schedule still slips. Invoice reconciliation still takes too long. And when a supplier shipment goes sideways, the first anyone knows about it is when the line stops moving. 

The technology isn’t the problem. The data feeding it is. 

For most manufacturers, the supplier transaction layer is still largely manual. Purchase orders, order acknowledgments, advance ship notices (ASNs), and invoices flowing between you and your direct suppliers run on email threads, spreadsheet entries, and phone calls. And when data enters your ERP from that process, it arrives late, incomplete, or inaccurate. 

The gap between what your systems can do and what your supplier data actually delivers is a cost most manufacturers aren’t measuring. But they feel it every day. 

Investment in manufacturing technology is accelerating. But more spending on planning and analytics tools hasn’t closed the gap. According to PwC’s 2026 Digital Trends in Operations Survey of 767 U.S. operations and supply chain leaders, 87% say poor data quality has impacted their organization’s ability to achieve value from digital initiatives, and 89% say their technology investments haven’t fully delivered the expected results. 

Gartner highlighted data quality and data readiness as major barriers to scaling AI in supply chain at its 2026 Supply Chain Symposium. For manufacturers, that starts with the connection between them and their direct suppliers. 

Some manufacturers have established connections with their top-tier strategic suppliers. But for most, a much longer tail of direct material suppliers remains unconnected. These are the commodity suppliers providing the ingredients, raw materials, or components that keep production lines running. They communicate via email. They send PDFs. They confirm purchase orders by phone. And when something changes, they may not communicate at all until someone on your team chases them down. 

That unconnected tail is where production risk accumulates. It’s where invoice reconciliation breaks down. And it’s where the data gap is widest, precisely because it’s the part of the supplier network that’s hardest to reach and most expensive to manage manually. 

The cost shows up in four places manufacturers know well. 

Production delays. Without reliable ASN data, your team doesn’t know what’s actually in transit until it doesn’t show up. Production schedules built on incomplete inbound visibility are schedules built to slip. 

Procurement hours. When purchase order acknowledgments come back through email, or don’t come back at all, someone on your team is spending hours each day tracking down confirmations, chasing late shipments, and manually entering data into your ERP. We see customers describe procurement follow-up as a near full-time job before they automate it. 

Finance exceptions. When supplier invoice data doesn’t match the purchase order or the receipt, your finance team absorbs the cost of resolving it. Three-way match becomes a manual reconciliation exercise, payment cycles slow down, and working capital sits tied up in unresolved payables. 

Forecasting blind spots. Inaccurate inventory and order data makes reliable cash flow forecasting difficult. When you don’t know what’s coming in, planning what goes out becomes a best guess. 

ERP systems are designed to process structured data, and they do that well. What they aren’t designed to do is reach outside your four walls and bring your supplier community into automated, standardized data exchange, especially when many of those suppliers lack the technical infrastructure to connect on their own. 

But the challenge goes beyond technology. Even when the right solution is in place, someone has to manage the supplier side of the equation. Who is reaching out to each supplier to communicate the change? Who is confirming their technical readiness? Who is tracking onboarding progress and keeping the project moving when a supplier goes quiet? For most manufacturing teams, those questions don’t have a clear answer, and the coordination burden falls on procurement or IT staff who are already stretched thin. 

Getting a strategic supplier onto EDI is a solved problem. Getting tens or hundreds of direct material suppliers connected, regardless of their starting technical capability, is where most solutions stop short and manual workarounds creep in. 

McKinsey’s latest global supply chain research shows that most companies still lack visibility beyond tier-one suppliers, and that visibility into deeper tiers has declined since 2022 and has not yet recovered. Manufacturers haven’t failed to invest in technology; rather, many have invested in systems that depend on clean data without addressing the underlying visibility and data foundations those systems rely on. 

What Fixing the Data Foundation Looks Like

Solving the supplier data problem at the source means connecting the full direct supplier community to automated, standardized transaction exchange. Purchase orders, order acknowledgments, ASNs, and invoices should flow accurately into your ERP from every supplier, regardless of where they start technically. 

SPS Commerce Manufacturing Supply Chain connects manufacturers to their direct supplier communities and standardizes how material, order, shipment, and invoice data flows into the ERP, without requiring heavy customization or additional IT effort. Critically, SPS takes on the supplier engagement work directly, handling outreach, readiness assessments, onboarding, and ongoing support for every supplier in the network. Your team doesn’t have to manage the change conversation, track supplier progress, or troubleshoot connectivity issues on your own. 

In practice, we’ve seen customers cut the time spent on buy-side ordering tasks by more than half and dramatically reduce the manual follow-up that procurement teams describe as consuming most of their day. On the finance side, cleaner inbound data upstream means fewer invoice exceptions to resolve downstream, and faster payment cycles as a result. Manufacturers going through ERP migrations have also used SPS to bring their full supplier and co-manufacturer networks into automated workflows at go-live, without operational disruption. 

Every investment you make in planning, analytics, or AI depends on the quality of the data those tools receive. When your supplier transaction layer is automated and connected, the data flowing into your ERP is structured, timely, and complete. Planning tools work from accurate inputs. Production schedules reflect what’s actually in transit. Finance teams spend less time resolving exceptions and more time on the decisions that move the business forward. 

Cleaning up the supplier data layer isn’t a workaround. It’s what makes the rest of your technology investments deliver what you paid for. 

SPS Commerce Manufacturing Supply Chain connects to major ERP systems, including NetSuite, SAP, Infor, Microsoft Dynamics, Sage, and Acumatica, and is backed by a network of more than 400 system automation partners. Ten of the top 10 U.S. Food & Beverage manufacturers trust SPS Commerce. 

Ready to fix the data problem at the source?

See how SPS Commerce Manufacturing Supply Chain connects your full supplier community to automated, accurate procure-to-pay workflows without heavy IT lift. 

The Supply Chain Acronym Cheat Sheet: 50+ Terms from EDI to LTL 

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Supply chain acronyms are the operating language behind how product moves from a supplier to the shelves of a store. Whether you’re dealing with an EDI transmission, a freight appointment, or shipment methods, these terms are not just jargon. They are the operational signals by which your business executes orders, moves inventory, and gets paid. 

We’ve grouped key supply chain acronyms by where they show up in the day-to-day workflow: 

Electronic Data Interchange (EDI) is the foundation of how retailers, suppliers, carriers, and warehouses exchange information. Purchase orders, shipment notifications, invoices, and payment details all flow through EDI systems, making it one of the most critical components of supply chain operations. 

Missing acknowledgments, inaccurate shipment notices, or rejected invoices can delay orders, disrupt fulfillment, create compliance issues, and ultimately slow down payment. Understanding common EDI terms can help you communicate more effectively with trading partners, troubleshoot issues faster, and reduce costly disruptions throughout the order-to-cash process. 

Once orders are received, suppliers must accurately pick, ship, document, and invoice every transaction. Small errors during this stage can create larger downstream issues, including delayed payments, invoice disputes, chargebacks, and reconciliation challenges.  

This stage governs how inventory is planned, replenished, and positioned across the supply chain. It connects demand signals to production and purchasing decisions, ensuring the right product is available in the right place at the right time. 

Errors or blind spots in this stage can quickly lead to stockouts, excess inventory, missed or missed sales, all of which directly impact service levels and working capital. 

This section covers the movement of product through carriers, distribution centers, and retail networks. It is one of the most execution-sensitive parts of the supply chain, where timing, capacity, and cost directly determine whether inventory arrives as planned. 

Learning supply chain acronyms is not about memorizing terminology. These terms are part of the daily conversations across operations, logistics, sales, compliance, and finance teams. Understanding them helps teams communicate more effectively, identify issues faster, and avoid costly mistakes. Speaking the language of the supply chain makes it easier to navigate the complexity behind getting products to market. 

The supply chain industry is full of specialized terminology, and these acronyms are just the beginning. If you're looking to understand more terminology, explore our additional acronym guides below: 

How The Best Operators Catch Preventable Chargebacks Early 

How the Best Operators Catch Preventable Chargebacks Early

 often surface as a financial issue because that is where the impact becomes visible. They show up as deductions from retailer payments, cut into revenue, create more work for internal teams, and make it harder to protect margins. However, the events that lead to those deductions usually occur much earlier. 

A chargeback tied to a shipment shortage, compliance violation, or receiving discrepancy often originates in 

 electronic data interchange (EDI) transactions, shipment documentation, or retailer-specific requirements. By the time a chargeback reaches accounts receivable, the item data, transaction, or shipment error that created it has already moved through the supply chain. 

This distinction matters for supply chain leaders because it influences how organizations respond to the problem. Companies that consistently reduce deductions focus on the operational processes that generate chargebacks rather than relying exclusively on recovery efforts after the fact. 

As brands expand across retailers such as Walmart, Target, Kroger, Costco, and Amazon, the number of compliance requirements, transaction types, and trading partner relationships increases. Managing that complexity requires infrastructure that supports accurate data, compliant transactions, and consistent execution at scale. 

Why Chargebacks Increase as Operations Become More Complex 

For many suppliers, deductions represent a meaningful source of bottom-line constraints. 

The financial impact is only part of the challenge. Every chargeback creates additional work for finance, operations, customer service, and supply chain teams. Deductions can also affect retailer scorecards that influence future business performance. 

As organizations grow, chargebacks often highlight recurring data and compliance issues that may not appear in traditional supply chain metrics. A pattern of deductions can reveal weaknesses in transaction accuracy, item data management, shipment visibility, or compliance processes long before those issues show up elsewhere. 

Common Root Causes Across Retailer Compliance Programs 

Retailers use different terminology for their compliance programs and performance metrics. Walmart measures performance through programs such as On Time In Full (OTIF) and the Supplier Quality Excellence Program (SQEP). Other retailers maintain their own scorecards, compliance standards, and vendor requirements, such as Amazon’s Vendor Central or Target’s Partners Online Portal.  

Despite those differences, many chargebacks originate from the same operational challenges. 

Retail operations depend on accurate and consistent product information across multiple systems, and that begins with careful awareness of item data.  

Discrepancies involving dimensions, pack quantities, product attributes, or item master records can create problems during ordering, fulfillment, receiving, and invoicing. A small data inconsistency can eventually result in a compliance deduction, shipment dispute, or invoice discrepancy. 

Electronic Data Interchange Transaction Errors 

Electronic data interchange (EDI) serves as the foundation for communication between suppliers and retailers. 

Purchase orders, acknowledgments, invoices, and shipping documents move through a network of systems and business rules. Changes to system configurations, retailer requirements, or enterprise resource planning (ERP) environments can introduce errors that affect transaction accuracy throughout the order lifecycle. 

Across retailer ecosystems, SPS Commerce frequently sees chargebacks that trace back to transaction errors earlier in the process. What appears as a fulfillment issue on a retailer scorecard may originate from incomplete, delayed, or inaccurate transaction data. 

Advance ship notices (ASNs) help retailers plan receiving activities and reconcile shipments. 

When shipment information does not align with what arrives at the distribution center, retailers may identify shortages, overages, or receiving exceptions. These discrepancies often lead to deductions even when products were shipped on time. 

Together, item data, EDI transactions, and ASN accuracy form a common thread across many retailer compliance programs. Understanding those connections helps supply chain leaders focusimprovement efforts where they can have the greatest impact. 

The Expanding Role of Revenue Recovery Technology 

The market for deduction management technology has evolved significantly in recent years. 

AI-powered tools and automation platforms can help suppliers identify claims, gather documentation, and manage disputes more efficiently. For organizations managing a large volume of deductions, these capabilities can improve recovery rates and reduce administrative effort. 

Recovery remains an important part of the process, particularly when deductions are invalid or unsupported. 

At the same time, organizations still invest time investigating claims, coordinating documentation, and managing disputes after the deduction has occurred. Many supply chain leaders are evaluating recovery and prevention together because both contribute to stronger financial performance. 

Recovery helps reclaim revenue, but the best operators understand that prevention reduces the number of deductions that require attention in the first place. 

Organizations that improve compliance performance over time often use chargeback data as an operational feedback mechanism. 

Rather than reviewing deductions solely by retailer or dollar amount, they identify recurring patterns and investigate root causes. This approach helps teams address process gaps before they become larger compliance challenges. 

Each deduction provides information about how orders, shipments, and data move through the organization. The goal is to use that information to strengthen processes over time. 

Reducing Information Silos with Visibility 

Chargebacks often persist because information is spread across multiple organizations and systems. 

One of the biggest challenges in reducing chargebacks is that no single team sees the entire process. Retailers focus on compliance and receiving performance, logistics providers focus on fulfillment, finance teams manage deductions, and supply chain leaders monitor execution. When information is distributed across different organizations and systems, connecting a chargeback to its underlying cause becomes far more difficult. 

Without visibility across orders, shipments, transactions, and retailer requirements, identifying root causes becomes difficult. Teams can spend considerable effort resolving individual deductions while missing the larger patterns driving recurring compliance issues. 

Organizations that achieve sustained improvements typically invest in stronger connectivity between systems and trading partners. Greater visibility helps teams identify recurring issues earlier, prioritize corrective action, and measure results over time. 

The operational demands associated with retailer compliance increase as businesses grow. A brand managing a small number of products and retailer relationships may be able to absorb occasional process inconsistencies. Growth introduces additional complexity through new trading partners, retailer requirements, distribution networks, and product assortments. 

As complexity increases, chargebacks often grow faster than revenue unless supporting processes and systems evolve alongside the business. 

Investments in item data management, EDI accuracy, shipment visibility, and compliance processes help organizations maintain performance as retailer networks expand. These capabilities become increasingly important as suppliers move from managing a handful of retailer relationships to operating across multiple channels and fulfillment environments. 

Chargebacks provide valuable insight into the health of retail operations because they capture the downstream consequences of upstream decisions and processes. 

Organizations that consistently reduce deductions approach chargeback management as part of a broader operational strategy that includes data quality, transaction accuracy, fulfillment execution, and visibility across trading partners. They’re proactive, and that helps save money down the line.  

As retailer requirements become more complex, many suppliers are investing in stronger operational infrastructure to improve data accuracy, automate retailer communications, and increase visibility across orders and shipments. 

 helps suppliers strengthen the processes that influence compliance performance upstream, while SPS Revenue Recovery helps recover eligible deductions that still occur. Together, these capabilities support a more proactive approach to chargeback management and help organizations scale with greater confidence. 

Agentic AI in Supply Chain: The Day-to-Day Impact

Agentic AI might sound futuristic, but it’s a technology that is becoming more widely adopted every day. It’s being applied to a wide range of planning, replenishment, logistics, and customer service workflows across 

. It promises efficiency gains like faster exception handling, fewer manual touches on routine tasks, and quicker responses to issues as they emerge. 

But those promises don’t always translate into impact. It can be a challenge for supply chain leaders to discern which agentic capabilities bring true value to their business and which just look impressive in a software demo.  

In this article, we’ll discuss how agentic AI is actually being used in supply chain operations today, what it could realistically change in your team’s day-to-day work, and the foundation needed to deliver meaningful results. 

 is a form of artificial intelligence that relies on rules, data, and systems to analyze and take action. These AI “agents” rely on machine learning models to mimic human decision-making. Oftentimes, agents are created to perform a very specific task with clear decision-making logic.  

While these agents are often referred to as “autonomous,” that isn’t the whole picture. In real-world applications, AI agents often operate within tight guardrails: 

A helpful way to view agentic AI right now is as highly specialized digital coworkers. Agents can watch data, make routine decisions, and execute repeatable tasks at scale, but they still depend on your team for strategy, judgment, and optimization as your business evolves. 

How Is Agentic AI Being Used in the Supply Chain? 

In 2026, agents are automating repetitive tasks and making decisions within guardrails. When these agents are implemented in high‑volume, rules‑driven workflows, they can shorten the length of tasks from hours to seconds and take on millions of routine actions. 

Let’s take a look at how that’s playing out in practice. 

How Agentic AI Is Changing Day-to-Day Supply Chain Management

CH Robinson: Agentic AI at Scale in Logistics

 runs a “fleet” of more than 30 AI agents across the shipment lifecycle, in areas like pricing, order intake, freight classification, appointment scheduling, truck posting, and shipment tracking. Agents read emails, interpret tenders, classify 

, set thousands of dock appointments, and respond to tracking requests in seconds instead of hours.  

Collectively, they’ve automated millions of individual shipping tasks and contributed to a reported 30% productivity lift since 2023. For employees, that means far fewer repetitive keystrokes and status checks, and more time spent on exceptions, problem-solving, and more strategic work. 

Unilever: Building an AI-First Foundation

 is a great example of integrating AI into processes and workflows, not simply layering it on top. Unilever recently entered a partnership with Google Cloud to migrate enterprise apps and data onto a single platform. In addition, the partnership offers access to tools like Vertex AI and Gemini to build “AI‑first” capabilities across marketing and consumer engagement. 

Behind the scenes, Unilever has already run hundreds of AI projects and trained tens of thousands of employees, applying AI to use cases like reducing manufacturing waste and improving social engagement. Unilever's new agentic ambition is to move from isolated pilots to a system of intelligence that can reason over unified data, take defined actions, and support decisions at every link of the value chain. 

ThredUp: AI-Assisted Inventory Management

 is a good example of how AI can take over a very specific, high-friction piece of supply chain work and make it more scalable.  

ThredUp has thousands of unique SKUs to process each day. Their inbound team used to spend time manually dealing with tagging hierarchies to capture basics like brand, size, care instructions, and attributes. Now, in-house visual AI tools read garment images and identify those details in seconds, allowing team members to focus on handling, quality inspection, and photography. That shift delivered an immediate productivity lift of about 10%.  

Where To Start: A Practical AI Adoption Path for Supply Chain Teams 

 with agentic AI without overhauling your entire tech stack or overwhelming your team? A good rule of thumb is to start narrow to identify and prove value, then expand. 

Step 1: Identify One or Two High Friction or Repetitive Workflows 

Look for processes that are painful, predictable, and happen every day or every week. These are usually great areas to implement an agent. 

If your team is spending a lot of time doing the same checks, sending the same emails, or updating the same fields, that’s a strong signal that optimizations can be made. 

Step 2: Define Rules and Success Metrics 

Before implementing an agent, it’s important to create a clear standard of what “good” looks like. 

That could mean spelling out things like: 

This gives the agent something concrete to follow and gives you a way to judge whether it’s actually helping. 

To safeguard your business from the risk of inaccurate actions from the agent, it’s crucial to test the agent heavily before releasing it to your wider organization. Early on, instead of having the agent take action, you can ask it to make recommendations. 

Then, compare the agent’s recommendations against what your team would have done historically. If the agent gets things right, you can build confidence in the tool. If it gets things wrong, this is a signal to refine the rules or data inputs. 

Step 4: Gradually expand automation scope 

Once the agent is consistently making good recommendations in a narrow area, you can begin to automate tasks within guardrails. The goal should be evolution, not a massive overhaul of how tasks are completed within your organization. To responsibly scale this technology, you should focus on steadily shifting well‑understood, repeatable work from humans to agents, while keeping humans in charge. 

Agentic AI should be used as a multiplier of the knowledge and talent within your organization, not a "cheat code" that replaces people or fixes broken processes. For leaders looking to implement these tools, the focus should be on areas where your team is overwhelmed with repeatable work and decisions that follow clear patterns. 

Ultimately, the winners won’t be the ones with the flashiest agentic AI solutions, but rather the businesses that quietly plug agents into the right workflows and free their people to focus on the decisions that require human judgment. 

Ready To Embed AI into Your Supply Chain? 

Agents are only as good as the network and data they’re built on. With SPS Commerce MAX, you’re tapping into the world’s most powerful intelligent retail network that can see issues coming, guide day-to-day workflows, and take action where it counts. 

 can plug into your existing operations and help your team move from reacting to problems to preventing them. 

KeHE’s Compliance Program: Inbound Routing Guide Overview

KeHE's Compliance Program

 is one of the largest grocery and natural distributors in the United States. With 19 distribution centers and more than 31,000 retailer partners, a consistent supply chain requires a clear set of guidelines for how suppliers move merchandise from their facilities into a KeHE DC or warehouse.  

These guidelines are laid out for KeHE suppliers in the 

, and cover everything from preferred carriers to unloading discrepancies. 

The instructions found within the Inbound Routing Guide apply to all purchase orders issued by KeHE. Getting these details right is a big deal, as noncompliance can result in chargebacks and other fees.   

the supplier to have these details. Each supplier is responsible for forwarding the Inbound Routing Guide to its logistics department, its carrier(s), and anyone else involved in moving merchandise from the supplier to KeHE.  

If you’re considering partnering with KeHE, this article provides:

The KeHE Inbound Routing Guide Rundown 

KeHE's Inbound Routing Guide can be broken down into 10 core questions: 

1. What are KeHE’s transportation options? 

KeHE divides their shipping and transportation options into two main categories: 

KeHE has two preferred carriers it recommends to its suppliers: 

 According to KeHE, suppliers that use a carrier from this list for prepaid shipping: 

2. How can KeHE suppliers schedule a delivery appointment? 

Every truckload delivered to KeHE requires an appointment scheduled through 

. Suppliers are expected to follow this process: 

Orders shipped via FedEx or UPS Ground 

need a C3 appointment, while orders shopped via freight service on FedEx Freight or UPS Freight 

need one. In both cases, lumper fees apply. 

3. What are KeHE’s shipping document requirements? 

KeHE requires suppliers to include two different documents with all shipments: 

This is the BOL example used in the Inbound Routing Guide: 

BOL example from KeHE's Inbound Routing Guide.