Europe still builds world-class universities. It still produces great engineers. But in AI and robotics hiring, it has stopped producing the strongest candidates. That is the uncomfortable assessment now circulating across global supply chain and technology leadership circles, and the debate it sparked runs far deeper than one recruiter’s experience.

The discussion opened with a hiring anecdote out of Shenzhen. A young headhunter specializing in AI and robotics told peers that ETH and EPFL graduates are no longer her top candidates. She cited a Cambridge graduate who went through nine interviews and failed all nine. The client feedback was consistent. “Too much theory, not enough real building.” The story landed because it confirmed a pattern that operators, researchers, and executives had been seeing independently. Within days, the post by Fei Yu, a trusted talent advisor in executive search, drew commentary from China, Europe, and emerging markets. The consensus was uncomfortable for Europe. The disagreements were mostly about how uncomfortable.

Ecosystem, Not Talent

The central claim that emerged was that this is not a talent competition anymore. It is an ecosystem competition. In AI, execution is becoming the new intelligence. The US leads. China is catching up fast. Europe is behind in speed, capital, and real-world application.

Alexander Shapiro, a Head of Strategy, challenged the premise that Europe still holds the academic edge. “What is your justification for claiming ‘Europe still has world class Universities’ especially in the area of AI research and development? I would agree for classic engineering and finance but not AI.”

The counterargument that surfaced in reply was that European universities are not short on talent. They are short on the ecosystem that lets talent work on real projects. That requires government support, capital, and cross-border collaboration at a level Europe has not mobilized.

Seyed Yousefi, an AI architect focused on ASEAN-EU relations, went further. “Europe is a desert for real AI researcher. It feels like we are just waiting for something to happen. We are losing great inventions and talent because there is no real infrastructure here.”

The Translation Gap

The strongest reframing came from Fadzly Moftar, an operational friction strategist working in ports, shipping, and aviation. “What you’re describing is not a talent gap, it’s a translation gap between knowledge and execution.” Intelligence, he argued, used to be measured by what you knew. In AI and robotics, the metric has shifted to what you can build, deploy, and iterate under pressure. “That’s why some graduates struggle, not due to lack of intelligence, but lack of exposure to real friction.” His prescription for Europe: redesign ecosystems where students become builders early, not just graduates. “Execution is no longer the final step. It is the intelligence itself.”

Tanja Dysli, Chief Operations Officer at TVH, drew the same line from the corporate side. “Many AI use cases I have come across are not embedded to support businesses reality (both in US and EU). There is often a far too long, theoretical and complex project phase and no clear answers from the start how AI can improve a companies P&L, down to specific lines.” Her fix was pedagogical. “If we can teach student to marry tech with everyday business reality it will be a game changer.”

Lisa Durst, a supply chain specialist in sourcing and supplier management, confirmed the pattern spreads beyond AI. “This shift from theory to execution is also very visible in operations and supply chain. It’s not just about knowledge, but the ability to make decisions and deliver in real-world situations.”

The China Speed Premium

Several commenters argued that the real differentiator is tempo, not credentials. Sean Upton-McLaughlin, a 15-year veteran inside Chinese organizations including Huawei and vivo, captured it. “This will be no surprise to those who have worked with Chinese companies. They are very practical, focused on execution at speed, and need to see the end result (money).”

Baojun Shi, focused on industrial tech and robotics, warned European companies operating in China to abandon their posture as “mere ‘technology exporters’” and embrace deep localization in R&D and decision-making. His argument: elevate China from a sales market to an “innovation hub” and “global supply chain command center” or lose relevance in a market “where brand halo no longer guarantees success.”

Olga Alekseenko, a program manager with experience at Nestlé and PMI, pushed back on the speed-as-virtue framing. “Maybe it’s not just about speed. In some environments, there’s more focus on getting things right before moving, which can look slower but also builds reliability.” She asked a question few have answered clearly. Is AI already widely used in Chinese business, or is the difference more about how teams approach building and execution?

The Capital and Policy Layer

Sheng S., an investment research specialist in healthcare and energy, widened the frame. “I think this happens in all intelligence oriented sectors like healthcare and energy not just in robotics. It’s no longer about talent, IPs, governance, capital cost, economy policies and control of supply chains, but a purposely built ecosystem that can connect and serve them.” His harder question: how long before China or the US lock in as the next vertically integrated top dog.

Dr. Martin Lockstrom, a professor and consultant, offered the bluntest verdict. “The AI and robotics race is basically already lost. As long as people in Europe are even thinking about things like 4-day working weeks, don’t bother.” He added the reversal neatly. “The tables have turned. You’re in China for talent, and in Europe for low cost.”

Jules Thevenon, Founder and CEO of The Forge Humanoid Robotics, noted the opposite flow. “I’ve also seen many European companies in high-end technology leaving China because labor costs are no longer attractive. For the same cost, they prefer to build in their own countries.” The talent and cost maps are no longer aligned the way they were a decade ago.

Counterpoints

Not everyone accepted the hype map. Miguel Martins, a semiconductor quality and reliability director with experience at Infineon, NVIDIA, and Analog Devices, challenged the geography itself. “The best candidates are not defined by where they come from, but by what they can carry. And the people who can carry the future are far more widely distributed than today’s hype map suggests.”

Dessy Amirudin, who works in data, digital, and technology at Unilever, asked the question few were addressing. “Any comment for the rest of the world? Non US, Non China, Non EU. Do we still have a chance?”

Takeaways for Leaders

Three lessons run through the discussion. First, the hiring bar in AI has moved from credentials to shipped work. Candidates who can build, deploy, and iterate under pressure win.

Second, the ecosystem beats the individual. Talent without capital, real projects, and policy support does not convert.

Third, complacency is the most expensive cost. The firms that lost ground in Shenzhen lost it to speed, not to better talent.

How is your organization redesigning hiring and development so your people learn on real friction, not on theory?

Continue the discussion on Chain.NET, the global supply chain community, at www.chain.net. Ask questions, join events, and access exclusive resources.

Four planning platforms dominate the enterprise market. Kinaxis, o9, SAP IBP, and Blue Yonder. Combined price tags run from $500,000 to $2 million a year. Time to first value sits between 12 and 18 months. Dedicated teams of three to eight full-time equivalents keep them running. And yet most planning teams still run S&OP in Excel. That is the gap the AI debate now hinges on.

The debate gained traction after Alain Matar, a Senior IBP Leader, Oliver Wight IBP Practitioner, and CSCP holder, posted on LinkedIn that he built a browser-based IBP planning engine from scratch using Claude AI. Nineteen planning steps. Nine forecast models. Thirty-five users. No vendor, no implementation partner, no six-figure license. “Just deep domain knowledge, a clear process design, and AI as the engineering partner.” The post drew planning architects, enterprise consultants, CEOs, and senior practitioners who split sharply on what the build actually proves.

The Knowledge Barrier, Not the Tech Barrier

The supporters argued that AI has collapsed the engineering gap that priced most companies out of real IBP.

Valerie LeBlanc, a digital supply chain transformation leader with an IMD MSc, framed the shift directly. “S&OP and IBP are not software features, they are decision rhythms.” For years, she noted, most organizations bought the tool, struggled with adoption, and fell back to Excel. “Not because people were not skilled, the gap between process complexity and implementation cost was simply too wide to bridge.” Her conclusion: “The technical barrier is gone, the knowledge barrier remains and that one cannot be licensed.”

Smita Giri, a Global Product Manager in Supply Chain, captured the same idea from the engineering side. “We’re shifting from an era of ‘how to build’ to ‘what to build.’ You can have a team of rockstar devs, but if the domain logic is fuzzy, the output will be too.” Her verdict: “Domain expertise is the new superpower.”

Aiden Heke, a data and insights leader, went further. “The emergent AI platform application category is real, the tricky work is understanding the data, the integration approach, and who will manage the application.” He added that this is “not the future, it’s the now.”

Jeremy Basckin pushed the disruption claim to its limit. “It’s game over for the magic quadrant and rightly said. We can implement an end to end planning and control system in 72 hours with far more capability.”

The Architecture Pushback

The critics accepted the compression of prototyping time but rejected the like-for-like comparison.

Rich Bradley, a consulting partner focused on digital reinvention, wrote the most cited rebuttal. “You asked Claude to rank your tool against the platforms it helped you build, using information you provided. That’s quite far from what I would call a benchmark.” He added that o9 and Blue Yonder implementations run 18 months because they span “cross-functional process design, ERP integration across multiple data sources, and organisational change management, it’s not because vendors pad their timelines.” For publicly listed companies, he noted, any planning tool touching financial forecasts has to carry “full audit trails, role-based access controls, and SOX-compliant data retention (seven years minimum under Section 404). That’s not optional and it’s not cheap to build.”

Sridharan M., an enterprise cloud solutions architect, sharpened the point. “A single HTML file can run planning logic. It cannot enforce audit trails, role-based access, concurrent user resolution, or real-time ERP/WMS integration. These aren’t vendor bloat, they’re non-negotiables at scale.” He flagged the deeper risk. “When your planning engine lives inside one person’s prompt logic, you haven’t eliminated vendor lock-in. You’ve created key-person dependency with no versioning, no test framework, and no institutional memory. That’s worse.”

Walter Reynders, an independent SAP IBP expert and trainer, landed the shortest challenge. “Honestly I don’t think it will take me 18 months to configure 19 planning steps and 9 forecast models in SAP IBP. How does your tool integrate with the rest of the IT landscape? Because that is 90 percent of the effort.”

Dr. Muddassir Ahmed, a supply chain consultant and newsletter publisher, drew the scope line. “$1 Billion + buys these complex planning software to achieve multi-site, Multi-legal entities, multi-echelons integrated planning. Which any Vibe Coded App on Claude cannot achieve as this point in time.”

Samuel Prashanth Yelety, a Principal Solution Architect for Kinaxis Maestro and OMP, added the execution question. “Demand planning is not just about simple forecasting, there are even management techniques, Product segmentation and New Product and Supply planning is closely connected with Distribution. Who would troubleshoot issues when the person developing cannot debug the code?”

The Enhance, Not Replace Argument

A third camp rejected the binary framing entirely.

Ash Uchil, a supply chain innovation and decision intelligence leader, proposed the most quoted compromise. “I don’t see Claude replacing these applications but enhancing them much like ServiceNow boldly adopting and embedding LLMs to make their products better. The winning model in the market may not be AI replacing SAP IBP or Kinaxis. It may be AI enhancing those environments by sitting above them, connecting across them, and embedding practitioner intelligence into day-to-day decisions.”

Kannan Ayyar, Chief Growth Officer at TADA, redirected the debate to execution. “The planning gap is real. But the harder problem isn’t building the plan, it’s executing against it. Most manufacturers I talk to have Kinaxis or o9 and still run S&OP in Excel because the system tells them what broke, not what to do about it in the next 4 hours. That’s the unsolved problem.”

Saurabh Pandey, a Lead eOps at L’Oréal India, surfaced the human layer. “Most IBP conversations focus on data, but very little on human behaviour uncertainty. In reality, biases like sales optimism and supply side risk aversion, combined with misaligned incentives to push sales often drive bigger deviations than data or forecasting gaps.”

Takeaways for Supply Chain Leaders

Three lessons emerge. First, AI has shifted the bottleneck from syntax to domain depth. The leaders who can architect their own planning cycle now have a new lever.

Second, enterprise-grade requirements still matter. Audit trails, role-based access, ERP integration, and SOX compliance do not disappear because the code was faster to write.

Third, the most credible path forward may not be replace or build. It may be AI sitting above existing platforms, embedding practitioner intelligence into daily decisions while systems of record keep running.

How is your organization testing AI-built planning tools against the governance, integration, and scale standards your business actually needs?

Continue the discussion on Chain.NET, the global supply chain community, at www.chain.net. Ask questions, join events, and access exclusive resources.

Gartner has entered a new market at a curious moment. Recently, the research giant published its inaugural Magic Quadrant for Supply Chain Strategy, Planning and Operations Consulting. The verdict placed Accenture, Deloitte, McKinsey, and PwC in the Leaders quadrant, EY as a Challenger, BCG as the lone Visionary, and Bain, Capgemini, and KPMG as Niche Players.

The report, authored by Gartner analysts Michael Dominy and Caleb Thomson, replaces the previous Market Guide format with a full Magic Quadrant. Gartner justifies the shift by citing a market with “clearer competitive differentiation and repeatable product-and-service models.” But the timing invites scrutiny. This new quadrant arrives from a firm whose stock has collapsed roughly 64% over the past twelve months, whose shareholders have filed a securities fraud class action, and whose credibility is being openly questioned by the practitioners who once treated its research as gospel.

A Ranking Firm in Freefall Ranks Others

The numbers tell a stark story. Gartner shares closed at $132.69 on July 9, 2026, down from a 52-week high of $409.76 and an all-time peak of $551.80 in November 2024. The stock touched a 52-week low of $124.25 in late June, just days after this Magic Quadrant published. Market capitalization has shrunk from over $40 billion at its peak to roughly $9 billion today. First quarter 2026 revenue actually declined 1.5% year over year, and analysts keep cutting price targets, with some estimates falling from around $253 to under $200.

Worse, a securities fraud class action now covers investors who bought Gartner stock between February 2025 and February 2026, alleging misleading disclosures about contract value growth and Consulting segment performance. The referee handing out consulting rankings is itself accused of misleading the market about its own consulting business.

Supply chain advisor Anna McGovern, author of Antifragile Supply Chains, diagnosed the underlying cause when the decline began: “AI has commoditized good-enough research and slideware. Clients no longer want PDFs after the fact. They want answers in the workflow.” Rich Sains, a procurement transformation leader at Qatar Airways, captured the shift in one sentence: “In the past, as an IT procurement leader I would have asked a Gartner analyst. Now I would ask ChatGPT, Claude or Gemini.”

A Referee With Skin in the Game

Gartner’s business model creates an obvious tension. The firm generates revenue from research subscriptions, advisory services, event sponsorships, and reprint rights, much of it flowing from the very companies it evaluates. Firms ranked as Leaders purchase reprint licenses to promote their positioning. The report itself carries a “Licensed for Distribution” marking.

Gartner insists its research is “produced independently by its research organization without input or influence from any third party.” Industry veterans have grown skeptical. David Linthicum, a prominent cloud and AI strategist and former CTO, describes the model bluntly as “quintessential pay-to-play, almost legalized extortion.” In his words, “enterprises felt obligated to subscribe just to keep up, while vendors felt a quadruple obligation to funnel money into Gartner’s coffers for the privilege of getting featured.”

One French entrepreneur, Eric Wanscoor, put a number on it, recalling that entry into Gartner’s analyses once required roughly 45,000 euros for a startup. Marketing strategist Shelly DeMotte Kramer describes companies “begrudgingly having to pay the Gartner tax and play the game, being held hostage to a relationship that doesn’t deliver real value.”

The consulting quadrant intensifies these concerns. Consulting firms are among the most sophisticated analyst relations operators in the world. When the evaluated firms are also masters of managing the evaluator, the rankings risk measuring analyst relations skill rather than client delivery quality.

A Methodology Built on Self-Reporting

The evaluation criteria reveal structural weaknesses. Much of the underlying data comes from the vendors themselves. Gartner evaluated “the trends that the vendor sees in the market,” “how the vendor approaches customer experience,” and “the vendor’s talent and retention.” Consulting firms have every incentive to present these favorably.

The report even admits its data gaps. Gartner notes that “several providers withheld granular commercial metrics or long-term scale targets” and that “concrete, large-scale production examples of agentic AI remain less common than roadmaps and pilots.” Read that carefully. Providers withheld key data, and pilots got counted alongside production deployments. What exactly is being measured?

The AI emphasis creates circular logic. Every vendor profile celebrates agentic AI, digital twins, and proprietary platforms. Yet Gartner’s own analysis admits these capabilities remain largely unproven at scale. Firms get ranked on promises and polished narratives rather than demonstrated outcomes.

This pattern has history. Linthicum documented multiple Gartner predictions that missed badly, including the forecast that 80% of enterprises would use cloud computing for mission-critical workloads by 2015, a milestone that stretched well into the 2020s. Gartner itself warned that 85% of AI projects would fail to deliver, and now projects that over 40% of agentic AI projects will be canceled by end of 2027. The firm rewards consulting vendors for the very AI visions its own research suggests will largely disappoint.

Arbitrary Gates and Visibility Loops

The inclusion criteria embed structural biases. To qualify, firms need $5 billion in total revenue, at least 1,000 supply-chain-focused consultants, and at least 60% of consultant headcount in North America and Europe. A firm delivering exceptional supply chain consulting primarily in Asia-Pacific fails by design, regardless of quality.

One criterion stands out: providers must appear as a “top 50 vendor for Gartner inquiries.” A firm’s eligibility partly depends on how often Gartner’s own clients ask about it. This creates a visibility feedback loop that rewards incumbency. Firms prominent in Gartner’s ecosystem qualify for evaluation, which increases their prominence, which reinforces eligibility.

Experienced practitioners also question the quadrant’s basic architecture. Erich Gampenrieder, a supply chain leader with nearly three decades across Accenture, Deloitte, KPMG, and Genpact, argues the traditional separation of strategy, planning, and operations “is becoming obsolete.” Planning, he contends, now “connects business strategy, enterprise architecture, technology, transformation, and operations into one integrated management capability.” Dirk Holbach, a Chief Supply Chain Officer with deep transformation experience, agreed on the orchestration point while adding that he “would have some different perspective on the Gartner assessment in terms of who sits where.” When practitioners question both the framework and the placements, the rankings deserve caution.

Executive Cover, Not Insight

Even the function of the rankings gets questioned. Technology executive Tim McConnaughy describes the Magic Quadrant as “an insurance scheme,” where executives buy the ranking so that “when the dust settles they can say, I bought the Magic Quadrant, it’s not my fault.” Linthicum recalls clients admitting they made technology decisions they doubted because “this is what Gartner recommended,” protecting careers rather than companies. Thomas Audibert, a French procurement technology founder, describes the model as “a self-reinforcing loop: vendors pay Gartner, Gartner validates, executives feel safe.”

A ranking that functions primarily as executive cover measures nothing about delivery quality. It sells absolution, not insight. Consultant Miroslav Pitlanic sharpened the point: Gartner “got comfortable selling answers when the market started valuing questions.”

Gartner’s own recommendations quietly undermine its quadrant. The report advises buyers to interview proposed staff, secure approval authority over team members, and demand that acquired specialists staff projects because “the acquired firm, not the large global provider, has the specialized expertise.” It concedes that expertise “varies by geography” at Accenture, is “more mature in North America” at Deloitte, and “differs by region” at KPMG. If quality varies this much within each firm, a single quadrant position tells a buyer almost nothing about a specific engagement with a specific team.

A Different Model Is Possible

The deeper lesson is that vendor and provider evaluation needs a new foundation, one where placement cannot be bought and where the methodology serves buyers rather than the ranked. This is exactly the gap the Global Supply Chain Council is addressing with the GSCC Vendor Radar (radar.gscc.app), a supply chain software vendor discovery tool built on a strict editorial independence rule: no paid placement, ever. Vendors cannot buy their way onto the radar or into a better position. Instead of abstract two-by-two axes, the Vendor Radar organizes solutions around four buyer-job quadrants that reflect what practitioners actually need to accomplish, and every listed vendor passes through a verification pipeline before appearing.

The premise is simple. When the evaluator takes no money from the evaluated, buyers can finally trust what they read. And the model is designed to travel. GSCC is exploring extending the same independent, verification-based approach to a Consulting Radar, applying the no-paid-placement principle to the very market Gartner just attempted to map. If consulting firms want visibility with buyers, they would earn it through verified capabilities and practitioner feedback, not analyst relations budgets.

Key Takeaways

Gartner’s inaugural consulting Magic Quadrant arrives from a firm in crisis. The stock has lost roughly 64% of its value over the past year, while a securities fraud class action alleges misleading disclosures about the very contract value and consulting metrics that underpin its credibility.

The methodology relies heavily on vendor self-reporting and rewards AI roadmaps over proven results. Gartner admits providers withheld commercial data and that production-scale agentic AI examples remain rare, yet AI vision features prominently in the rankings. Given Gartner’s documented history of missed predictions, buyers should discount vision-based placements heavily.

The structural conflicts are unresolved. Reprint revenue, the “Gartner tax,” visibility-based inclusion criteria, and arbitrary revenue thresholds mean the quadrant measures analyst relations prowess and incumbency as much as delivery quality. Practitioners increasingly bypass analysts entirely, asking AI tools the questions they once paid Gartner to answer.

Independent, verification-based models with no paid placement, like the GSCC Vendor Radar and a potential future Consulting Radar, point to where provider evaluation is heading. Treat any quadrant as a starting longlist, then rely on staff interviews, sample deliverables, and independent references to make the actual decision.

Do you still rely on analyst rankings when selecting consulting partners, or have AI tools changed how you research providers? Would a no-paid-placement model like the GSCC Vendor Radar, extended to consulting firms, earn your trust faster? Share your perspective in the comments below.

BCG’s report AI Is Already Moving the Logistics Industry Forward shows clear progress in how AI is being applied across logistics, from transport planning to warehouse operations and forecasting.

But scaling remains the real challenge.

In this Executive Audio Briefing, Michael Jung and Jess Williams explore why most AI initiatives in logistics deliver val…

Read more

Somewhere right now, a supply chain analyst is pulling data from an ERP, a TMS, a WMS and three spreadsheets nobody wants to admit still exist. They are reconciling numbers. Formatting slides. Building a deck for a Monday morning review that will arrive too late to change anything.

The meeting will follow a familiar script. Leaders will spend 80 percent of the time understanding what happened last week. Fill rates. On-time delivery. Freight cost overruns. Supplier nonconformances. By the time someone asks “what should we do about it,” the hour is up.

This ritual plays out every week in supply chain organizations around the world. Hundreds of hours spent assembling the rearview mirror. Almost no time left to look through the windshield.

It does not have to work this way.

The real problem is not data. It is thinking time.

Most supply chain leaders are not short on information. They are short on time to think about what the information means. The data exists. The dashboards exist. What is missing is a layer between raw metrics and strategic decisions.

That layer used to require a team of analysts or an expensive consulting engagement. Today it requires a 30-minute conversation with a large language model.

Not a chatbot. Not a glorified search engine. A properly configured AI supply chain strategist that understands your frameworks, knows your context and reasons through problems the way a seasoned Chief Supply Chain Officer would.

What an AI CSCO actually looks like

You do not need a consulting firm. You do not need custom infrastructure. You do not need a six-figure budget or a six-month implementation timeline.

You need three things.

First, a system prompt. This is the personality and expertise layer. Tell the model it is a senior supply chain strategist with deep expertise across procurement, logistics, demand planning and risk management. Give it frameworks. SCOR metrics. Total cost of ownership thinking. PESTLE dimensions for risk assessment. The Kraljic matrix for category strategy. Whatever mental models you use in your own decision-making, encode them explicitly.

Second, context. Upload your freight rate trends. Paste in your supplier performance data. Feed it your inventory aging report or your latest S&OP deck. The model does not need live access to your ERP. It needs the same information you would hand a sharp consultant on day one of an engagement.

Third, good questions.

“Which three suppliers represent the highest concentration risk in my electronics category?” “If transit times on our Asia-to-Europe lanes increase by 12 days, what is the downstream impact on safety stock for our top 20 SKUs?” “Draft a recommendation for our S&OP meeting on whether to dual-source our five highest-risk single-sourced components.” “Review this freight RFQ response and flag anything that looks off compared to current market benchmarks.”

A well-prompted model will not just answer. It will reason through the problem, identify assumptions, flag what it does not know and structure its response the way a good CSCO would brief a board.

Why this matters now

The gap between supply chain organizations that use AI for decision support and those that do not is widening fast. Not because the technology is expensive. Because the barrier has shifted from budget to knowledge.

Enterprise AI platforms cost millions and take months to deploy. A personal AI supply chain advisor costs almost nothing and takes 30 minutes to build. The difference in capability is smaller than most people assume. The difference in speed is enormous.

The professionals who will lead supply chain functions five years from now are not waiting for IT to approve a platform. They are building their own thinking tools today. Testing prompts. Refining frameworks. Learning what works when you feed a model your actual category data versus generic industry benchmarks.

This is not about replacing the supply chain leader. It is about giving that leader a thought partner that never sleeps, never forgets the framework and can process a 50-page supplier assessment in seconds.

Where to start

Build your AI CSCO in stages. Start with one use case. Pick the meeting you dread preparing for. The monthly business review where you spend two days pulling data and building slides nobody reads past page five. The quarterly supplier review where half the analysis arrives after the decisions have already been made.

Upload that data. Write a prompt that describes the analysis you wish someone would do for you. Iterate. Refine. Add more context in the next round.

Within 30 minutes you will have something that would have taken a consulting team two weeks and a substantial invoice to deliver.

Within a month of regular use you will have a customized supply chain intelligence layer that knows your categories, your risks, your metrics and your decision-making style. It will remember that you care about landed cost not unit price. That your CEO always asks about single-source exposure. That your Southeast Asia suppliers tend to underperform on quality in Q3.

The tool is already here. The only question is whether you build your version this week or wait another quarter for someone else to build it for you.

What does your weekly or monthly supply chain review process look like? Have you started using AI to accelerate your analysis or are you still building decks the old way? Share your experience on Chain.NET.

Ten years ago, supply chain leadership focused on three things: cost, service, and inventory. Today, the role has expanded to include geopolitics, tariffs, network resilience, AI-driven decisions, sustainability, and operational risk.

The job title may still say supply chain. The mandate is increasingly enterprise resilience.

“In many companies, operations has become the front line of enterprise risk management,” wrote Lisa Brown, a Chief Supply Chain Officer with over $180 million in value creation. “The role is evolving from efficiency leader to enterprise operator. And this shift is just getting started.”

The observation sparked extensive discussion among supply chain executives about what the profession has become, what it requires, and why so many organizations are hiring for a role that no longer exists.

The Scope Has Expanded Dramatically

Nuha Luqman, who works in supply chain and procurement for energy ecosystems, captured the magnitude of the shift. “The scope of supply chain leadership has expanded dramatically, but many job descriptions still reflect a world where stability was the default.”

She described the new reality. “Today’s leaders are expected not only to optimize flows, but to anticipate disruptions, interpret global signals, and translate uncertainty into operational decisions. The skill set has quietly shifted from operational excellence to strategic risk navigation.”

Angad Reyar, a global supply chain and eCommerce leader with 26 years of experience and $1.2 billion delivered, proposed a new title that better reflects the role. “Today’s mandate is closer to ‘Chief Network Risk Leader’: someone who can price geopolitical risk into design choices, use AI without outsourcing judgment, and keep track of margin, resilience, and sustainability.”

Tomasz Tyras, a senior supply chain and operations expert, identified what has fundamentally changed. “What has changed most is not only the scope of the role, but the consequence of getting it wrong. Supply chain is no longer a back-end efficiency function. It is where margin, revenue continuity, customer trust, and risk exposure now meet in real time.”

The Hiring Gap

KS Operations, a supply chain management solutions provider, identified a disconnect that explains why performance breaks down. “What I’m seeing is companies still hiring for execution roles, while expecting enterprise-level thinking. That gap is where performance starts to break down.”

They pinpointed the real shift. “The real shift is accountability. Supply chain leaders today are not just managing flow, they’re owning resilience, decision speed, and business continuity.”

Tyras expanded on why hiring processes miss the mark. “Many hiring processes miss the mark. They still screen for functional excellence, while the business actually needs decision quality under volatility. The strongest leaders today are not just operators of flow. They are translators between geopolitics, finance, commercial priorities, and execution.”

Brad Ferrell, an end-to-end supply chain recruiter, confirmed this shift from the hiring side. “I see this as well with clients. Instead of hiring managers asking candidates about savings and bottom-line accomplishments, it’s more about how they have adapted to the external environment.”

Not New, But Newly Critical

Jamie Mayer, a transformational supply chain executive with Lean Six Sigma Black Belt certification, offered historical context. “From being around a while, business continuity plans should have always been in place in supply chain which should cover resilience and managing operational risks. At least post 9/11 if not before, geopolitical risks are not new.”

He acknowledged the renewed focus. “I think COVID brought these back to the forefront but they are not new concepts.”

Björn Holmgren, Global Supply Chain Design Manager at Inter IKEA Group, framed it differently. “It’s not old or new, it is the same but the tradeoff and decision drivers have changed.”

Stanislav Gaida, an operational excellence leader in global supply chain and manufacturing transformation, challenged the framing of old versus new. “I would not fully agree that the 10-year-old model is old, it’s just different dimensions of the same. Every resilience program, every BCP will have a bill at the end, which will change balance of cost, service, cash. So it is not OR, it is AND.”

He emphasized what skilled executives must now deliver. “More than ever proper articulation and decision making of trade-offs is what skilled SC executives should drive in their organizations.”

Cost Still Matters

Craig Yao, Director of Supply Chain and Operations, reminded that fundamentals haven’t disappeared. “Every level of service has a cost, and every level of service has a different effect on net margins and profitability, and where service and cost break even, cost will continue to be part of supply chain management, maybe in a slightly different way.”

Jorge M., a global supply chain operations and transformation leader, framed the choice organizations face. “That’s the difference between considering your supply chain a ‘cost center’ vs a ‘competitive advantage.’ One is a race to the bottom. The other one looks at ROI.”

The Orchestration Challenge

Patrick Webb, Senior Director of Intelligent Industry and Supply Chain Transformation, introduced a useful metaphor. “I think the term ‘Orchestration’ has become more relevant across supply chains. The composer consistently adds more instruments and the conductor leads this deeper complexity.”

He noted the tools have evolved too. “However, the evolution of the instruments such as AI, robotics, integrated applications and human education bring the symphony together in a much more refined manner than 10 years ago. Today’s supply chain leader still needs to learn the colours and practice in the best use of these tools to succeed in overall operational performance.”

Mitchell Taylor, from Supply Chain Excellence, raised an infrastructure concern. “The transition to ‘enterprise operator’ requires a level of functional depth many organizations lack. Most are trying to run this new model on infrastructure that isn’t built to support AI-driven decisions.”

The Career Implications

Guillermo Silva, early in his supply chain career, asked what capability junior candidates should build to be useful in this newer version of the role.

Brown responded with a clear priority: “Decision-Making With Imperfect Information. The most valuable operators today will be the ones who can analyze incomplete signals quickly, understand trade-offs between cost, service, inventory, and risk, make sound decisions under uncertainty, and adjust quickly when conditions change.”

Her conclusion: “Supply chain professionals have to become decision-makers, not just planners.”

JP Doggett suggested the role description needs even more additions. “I’d add tech market analyst, big ticket negotiator, influencer, change management specialist and psychologist to that description.”

The Organizational Consequences

Jan Steenberg, President of CILT and Senior Partner at TCS, asked what the consequences of this change will be.

Brown outlined several implications. “The biggest consequence of the evolving supply chain role is that operations is moving from a support function to a strategic leadership function.”

She predicted structural changes ahead. “More CEO/COO roles will require more direct supply chain experience. Supply chain leadership will have expanded skillset requirements. Supply Chain, Finance, and Strategy structures will integrate or at least sit closer together. There will be greater accountability in Supply Chain leadership as decision making rights are redefined.”

Corey Weekes, an SCM executive and author, asked whether CEOs and CFOs recognize this shift. Brown acknowledged work remains. “It is a work in progress.”

The Tariff Example

Subhash Chowdary, founder of a company innovating financial supply chains, highlighted tariffs as a prime example of the new complexity. “Tariffs certainly add a lot of work across the enterprise again and again as they change faster than an enterprise can respond.”

Brown agreed, pointing to technology as part of the solution. “This is where the control tower designed for the needs of the business is best suited. The right solution can assist with scenario building and decision speed tremendously. It is not to replace people but to enable visibility across the enterprise to remove the obstacles of decision layers and enhance the value of the outcome.”

The Bottom Line

Diego Muñoz Hernandez, an Executive MBA with multinational operations experience, captured the stakes. “Supply chain is no longer just about optimizing flows. It has become the operating system of the business. The real shift is from managing efficiency to orchestrating resilience, data-driven decisions, and risk across the enterprise. Companies that still hire for the ‘old’ role will struggle to compete in the next decade.”

Hemant Agarwal, founder of LocatR, summarized the transformation. “We’ve moved past the era where supply chain was just a back-office cost center. It’s now the literal frontline of enterprise risk management.”

Abdulmajeed Al Sheraim, a procurement and contracting leader, framed where supply chain now sits. “Supply chain roles have evolved far beyond cost and service metrics. Today, they sit at the intersection of risk management, strategy, and resilience, making supply chain leaders key contributors to enterprise-level decisions.”

The title may still say supply chain. The job has become something else entirely.

Continue the discussion with supply chain and operations professionals on Chain.NET.

A procurement director manages spend across 500 suppliers. A logistics manager optimizes routes for a distribution network. A supply chain analyst forecasts demand for a manufacturer.

These are good jobs. They have salaries, titles, and security.

But increasingly, supply chain professionals are asking a different question: Why work for someone else’s supply chain when I can build one for others?

AI is making that transition possible in ways it wasn’t five years ago.

The traditional barriers to starting a supply chain business - specialized expertise, capital requirements, technology infrastructure, industry gatekeepers—are collapsing. A procurement professional with deep knowledge of supplier risk can now build an AI-powered risk monitoring tool without hiring engineers. A logistics expert can create an optimization platform without massive infrastructure investment. A demand planner can launch a forecasting service without building proprietary algorithms.

The gatekeepers are disappearing. The tools are democratizing. The moment is now.

Why Supply Chain Leaders Are in a Unique Position

Supply chain work is uniquely suited to founder transition because the domain expertise is the moat.

A technology founder must learn both code and business. A supply chain founder already understands the problem deeply. They know where suppliers fail. They understand the cost of inventory mismanagement. They’ve experienced the friction in procurement workflows firsthand.

What they lacked—the ability to build technology quickly—AI now provides.

A procurement professional can describe their ideal supplier risk assessment tool to Claude or another AI system. The AI builds it. They test it with their network. They refine it based on feedback. Within weeks, they have a prototype. Within months, they have a customer.

The capital requirement drops from millions to thousands. The timeline compresses from years to months. The expertise requirement shifts from “know how to code” to “know supply chain deeply.”

Specialized expertise becomes the differentiator. Gatekeepers lose power.

The Three Paths Supply Chain Professionals Take

Path 1: Build Tools for Your Industry. A logistics professional creates an AI agent that optimizes delivery routes and reduces fuel costs by 15%. They package it as a service and sell it to regional carriers. Revenue potential: $50,000-$500,000 annually depending on market size.

Path 2: Become a Specialized Consultant. A CSCO with 20 years of experience uses AI to accelerate her consulting practice. She builds diagnostic tools, assessment frameworks, and benchmarking models. She packages her knowledge as services backed by AI-powered analysis. Her effective hourly rate doubles because AI handles the data processing and analysis.

Path 3: Solve a Niche Supply Chain Problem. A procurement manager notices that mid-market manufacturers struggle with contract compliance. She builds an AI system that reads contracts, monitors compliance, and flags risks. She targets a narrow market—food and beverage manufacturers in North America—and captures 20-30 customers in year one.

All three paths share a pattern: deep domain expertise plus accessible AI tools equals viable business.

What’s Actually Changing

The old model required procurement and logistics professionals to stay in one company, climb the ladder, and retire as VPs or directors.

The new model offers a choice window. You can stay in your current role and use AI to expand your impact. Or you can take your expertise, build a specific solution for a specific problem, and create equity in your own venture.

Neither path is wrong. Both are now viable.

What’s changing is the gatekeeping mechanism. You no longer need:

• Massive capital. An AI-powered supply chain tool can launch for under $50,000 in infrastructure and development costs.

• Engineering expertise. You describe the problem. AI helps you build it. You don’t need to hire a CTO.

• Venture capital blessing. You can bootstrap with customers and grow profitably without external funding.

• Proven startup track record. Your supply chain expertise IS your credential.

What you do need:

• Deep domain expertise. You must know the problem better than anyone else.

• Clear customer understanding. You must know exactly who has the problem and how much they’ll pay to solve it.

• Ability to communicate. You must articulate the problem and solution clearly.

• Patience for sales. Selling to supply chain leaders requires relationship building and trust.

The 90-Day Founder Test

If you’re serious about exploring the founder path, here’s a realistic timeline.

Days 1-30: Validate the Problem. Talk to 20 procurement and logistics professionals about a specific problem you want to solve. Document exactly how they experience the problem today and what they’d pay to solve it. If you can’t find 20 people who care deeply, the problem isn’t big enough.

Days 31-60: Build a Prototype. Use AI tools to build a minimum viable solution. It doesn’t need to be perfect. It needs to demonstrate the core idea. Show it to five customers and iterate based on feedback.

Days 61-90: Secure Your First Customer. Don’t aim for perfection. Aim for a paying customer, even if they pay a modest amount. One customer validates the business model. Three customers validate product-market fit.

If you reach day 90 with paying customers and a clear path to more, you’ve validated the founder opportunity. You can then decide whether to go full-time or continue building part-time while maintaining your current role.

The Skills That Matter Most

As AI automates more of the transactional supply chain work—invoice matching, basic forecasting, routine vendor evaluation—the skills that create founder opportunity shift.

Strategic Judgment. Understanding trade-offs in supplier selection, network design, and risk management. These decisions require judgment that AI informs but doesn’t replace.

Stakeholder Relationships. Building trust with executives, vendors, and team members. This is where founders succeed or fail.

Pattern Recognition. Seeing problems that others don’t see yet. Noticing inefficiencies that others accept as normal.

Communication. Explaining complex supply chain concepts clearly to people who don’t live in supply chain every day.

These are the skills AI cannot replace. They’re also the skills that make founder opportunities real.

Moving Fast Before the Window Closes

The moment where supply chain professionals can leverage AI to build ventures is real but time-bound.

In two years, every consultant, tool vendor, and startup will be doing this. The competitive advantage of being early—having domain expertise plus AI capability before others do—will diminish.

Supply chain leaders with entrepreneurial instincts should move now. Not necessarily to go full-time as founders. But to test the opportunity. To validate customer need. To build proof of concept.

The cost of waiting is higher than the cost of experimenting.

Are you thinking about starting a supply chain venture?

What supply chain problem would you solve if you had the tools and capital to do it? Have you noticed inefficiencies in your industry that no existing solution addresses well? What’s holding you back from exploring the founder path?

Share your thinking in the comments. Your insights might be the spark someone else needs to move forward.

Join the Chain.NET community for strategic discussions on supply chain entrepreneurship, AI-enabled ventures, and the future of independent supply chain professionals. We host regular forums where procurement and logistics professionals share experiences building side ventures, consulting practices, and technology solutions.

Connect with peers exploring the founder path. Visit www.chain.net and check our events calendar at www.chain.net/c/events for upcoming sessions on supply chain entrepreneurship, building and scaling ventures, and positioning yourself for the next phase of your career.

Every supply chain decision between 2020 and 2025 made sense at the time. Nearshoring to reduce dependency on a single region. Dual-sourcing to protect against supplier failure. Inventory buffers to absorb demand swings. Digital monitoring tools to see further ahead.

A recent study from HFS Research, authored by Ashish Chaturvedi, Executive Research Leader covering supply chain operations and retail, puts a number on what those decisions actually produced. The firm estimates that 12% to 18% of supply chain cost in consumer goods companies is now structurally hidden. It does not appear in any single budget line. It lives in inflated cost-to-serve on long-tail SKUs, redundant warehousing for promotional inventory, and carrier fragmentation across channels.

HFS calls this “structural complexity drift.” The gradual accumulation of redundant nodes, overlapping capabilities, and conflicting optimization targets. Each layer added during the disruption years was individually rational. Collectively, they created architectures that are more expensive, slow to adapt, and hard to govern.

The data makes the point sharply. Complexity creates three compounding effects. First, cost leakage at 12% to 18% that hides across budget lines. Second, decision latency that slows every choice touching the supply chain by a factor of three to five. Third, what HFS calls “resilience theater,” where organizations maintain eight backup co-packers and five demand-sensing platforms but cannot activate the right response when a key retailer changes order patterns. Redundancy without coherence is not resilience.

The pattern extends well beyond consumer goods. Any company that expanded its supply chain footprint during the disruption years faces the same structural question. Where did we add capability, and where did we just add cost?

Five domains where complexity concentrates

HFS identifies five domains where supply chain complexity tends to concentrate: Network, Supplier Base, Product and SKU, Process and Planning, and Technology and Data. Each has distinct causes, symptoms, and cost profiles.

The Product and SKU domain carries disproportionate weight. SKU proliferation, promotional complexity, and retailer-driven assortment requirements compound on each other. One question from the HFS diagnostic makes the point: if you eliminated the bottom 20% of SKUs by revenue contribution, how would your supply chain cost structure change? Most leadership teams know the answer intuitively. Few have run the numbers with full supply chain cost loaded in.

In Process and Planning, the research highlights a simple test: how many hours per week does your planning team spend reconciling data versus making decisions? If the answer is more than 20, complexity has eaten your planning capacity.

Technology and Data is equally revealing. How many systems in your organization produce a version of “demand forecast”? Which one does leadership trust? If you built your supply chain tech stack from scratch today, how much of the current stack would you replicate?

From diagnosis to action

The HFS framework provides a structured path through four modules. Module 1 is the complexity diagnostic itself, scoring each domain across cost impact, resilience impact, and decision impact. Module 2 offers a library of seven rationalization levers across four intervention types: Eliminate, Consolidate, Standardize, and Automate. Module 3 compares three scenario archetypes (Surgical at 6 to 12 months, Accelerated at 12 to 24 months, Structural at 24 to 36 months) and produces a decision-sequenced roadmap. Module 4 establishes governance.

The governance module matters more than most leaders expect. HFS found that organizations that rationalize successfully but skip governance see 60% to 80% of complexity return within 18 to 24 months. Each addition is small. A new co-packer for a retailer-exclusive SKU. A line extension launched without a corresponding retirement. A planning tool adopted by one region. Collectively, they reconstitute the complexity that was rationalized.

The research frames governance around four pillars: complexity budgets with hard limits per domain, quarterly rationalization reviews with decision authority, clear decision rights specifying who can add complexity and who is accountable, and incentive alignment ensuring that performance metrics do not reward volume additions without accounting for cost-to-serve.

What leadership teams should take away

First, complexity is not a feeling. It is measurable. Score your organization across the five domains and you will see where the hidden cost concentrates.

Second, the highest-ROI moves are often subtractive. Exiting tail suppliers, retiring underperforming SKUs, and compressing planning cycles deliver faster results than adding new tools or platforms.

Third, governance is not optional. Without it, rationalization is a project with a start and end date. With it, rationalization becomes an operating discipline.

How much of your supply chain architecture was built in response to a disruption that has already passed? What would you change if you scored each domain honestly?

Try the free diagnostic

The GSCC Decision Lab has adapted this framework into a free self-assessment tool. Score your five complexity domains in 10 minutes and get your complexity radar, heat map, and priority ranking at https://complexity.gscc.app.

GSCC members get the full Excel toolkit on the Decision Lab: scoring worksheets with conditional formatting, the complete lever library, scenario comparison frameworks, decision-sequenced roadmap templates, and the governance operating model. Start your 14-day free trial at www.chain.net/checkout/individual-membership. No credit card required. See all benefits at https://gscc.co/benefits.

We want to hear from you. Share your feedback, your scores, and your experience with supply chain complexity.

Continue the discussion on Chain.NET, the global supply chain community, at www.chain.net. Ask questions, join events, and access exclusive resources.

The procurement technology market has never been hotter. Vendors promise AI-powered insights, automated workflows, and dashboards that deliver instant visibility. Chief Procurement Officers face constant pressure to modernize. Boards approve budgets for digital transformation.

And yet, implementation after implementation fails to deliver the promised value.

According to a growing number of procurement leaders, the problem isn’t the technology. It’s the assumption that software can fix what’s fundamentally a people and process problem.

“A new piece of procurement technology won’t fix your organisation,” wrote recently Tom Mills. “I still believe most Procurement challenges are people and process issues disguised as tech problems.”

The statement sparked extensive debate among practitioners who have lived through failed implementations and watched organizations repeat the same mistakes.

The Control Mechanism Problem

Chris D., a former CPO and enterprise value creation leader, traced the dysfunction to procurement’s origins.

“Procurement didn’t start as a value engine. It started as a control mechanism,” he wrote. “Purchasing was built as the choke point because organizations didn’t trust engineers, operators, finance, or suppliers. So we built gates. Approvals. Three bids. Policy walls.”

The implications for technology adoption are significant. “The function was built and evolved around mistrust. And when you design around mistrust, you get policing, not partnering. Compliance, not outcomes. Cost control, not value creation.”

He identified the core issue with layering technology on top of this foundation. “Software only scales the philosophy underneath it. If the foundation is control, tech just accelerates control.”

Automating Chaos at Scale

Practitioners shared cautionary tales from the field.

Timothy Jinks, a global sourcing and category management leader, recalled a failed platform implementation. “I remember we installed a new platform, and it was supposed to be the second coming. We got oversold and under delivered. Leadership is sold that everything will now be automated with little interaction.”

Alastair Williams, a senior procurement professional, offered a memorable formulation. “If you automate Chaos, you just get Chaos at scale.”

Andy Mayer, who works in sourcing and procurement advisory, put it simply. “Bad process in good technology is still bad process.”

Hamilton Lindley, VP of Procurement, Compliance and Risk, described inheriting a procurement function where rigid processes meant nobody followed them. “The first instinct from leadership was to buy a platform. But technology layered on top of broken relationships just automates the dysfunction faster.”

He found value only when technology served a different purpose. “We installed a platform that freed up time for conversations that matter. Modernizing procurement starts with the relationship. The technology just makes room for more of it.”

The Sequence Matters

Multiple commenters emphasized that sequence determines success.

Romain Ducrocq, a global indirect procurement leader, outlined the hierarchy. “Process before tech and governance before process. If decision rights, demand ownership and risk appetite aren’t clear, we simply automate misalignment faster.”

Charles Entinger, a supply chain operating model architect, drew on ERP implementation experience. “Net tech does not solve problems in the foundation. Governance, process, structure, these are all must-do’s first. Anyone who has implemented an ERP knows that.”

He recommended a specific approach. “Best practice: build a manual system and a process around it to pressure test what you are trying to do. If the discipline shows up and the results are as expected, move to implement your solution. Otherwise, you are not done with governance, process, and structure.”

Mark Strange, founder of Möbius Nexus, added a layer to the analysis. “Most organisations do not fail because of technology or even relationships. They fail because the operating model was never consciously designed. When decision rights, governance, supplier segmentation and stakeholder incentives are unclear, tech becomes a scapegoat.”

His conclusion: “Tools amplify clarity. They also amplify confusion. Fix the architecture first. Then let technology scale what works.”

The Alignment Illusion

Mandeep Singh, who spent 13 years on the buyer side, identified a common misconception about what alignment actually means.

“Most procurement teams think alignment means getting people to follow the process, when it actually means designing a process that fits how people already work,” he wrote. “I spent years trying to force internal customers into procurement workflows that made sense to me but felt like bureaucratic overhead to them.”

His breakthrough came from changing the question. “I stopped asking ‘how do we get them to use our system’ and started asking ‘how do they actually make buying decisions when we’re not in the room.’ Once I mapped that real journey, I could build bridges between their natural workflow and our compliance needs.”

Tomasz Tyras, a senior supply chain and operations expert, diagnosed why adoption fails. “Procurement tech rarely fails because the UI is bad. It fails because the operating model stays untouched: unclear decision rights, no disciplined intake, and stakeholders treat the tool as ‘procurement’s system’ instead of a business capability.”

The result is predictable. “Adoption becomes compliance theatre and the dashboards just report yesterday’s behaviors.”

The Relationship Gap

Clerk Chat, a business communications platform, identified the capability that gets skipped fastest. “Most teams survey suppliers annually, file the results, and change nothing. Asking how the relationship actually feels, then acting on it, is a different discipline entirely.”

Mills framed the opportunity cost. “The most underleveraged lever in most organisations isn’t software. It’s relationships. And Procurement must be the architect of how those relationships create value. Not a system administrator. Not a policy enforcer. A value driver.”

Serhii Sviridenko, founder of a process discovery company, noted AI’s limitations. “While AI can automate your business process, AI does not know your intention, and it is definitely powerless in building a genuine relationship with a supplier.”

Olga Catena, a supply chain expert, summarized the pattern. “Many teams hide structural or relationship problems behind new tools.”

The Golden Triangle

Tanya W., a senior procurement transformation advisor who describes herself as “massively pro-tech,” endorsed a specific sequence. “If you consider the whole Process-People-Tech golden triangle, the tech should be the last piece of the puzzle.”

Nico Bac, founder of Digital Procurement Now and former Source to Pay Digital Transformation Lead at P&G, offered a different framing. “I think procurement is about 2 things only: People and Platform. Process is secondary to that. The only thing that is important in process is that any part of the procurement process has been dramatically simplified.”

He acknowledged, however, that many procurement organizations work with poor technology. “This has to change and NOW is the time to do that.”

Sacha R., a director at a procurement consultancy, drew on decades of watching technology waves arrive. “If you’ve been around procurement and supply chain long enough you’ve seen the advent of MRP to ERP to eSourcing to integrated systems etc. None of that stuff has ever been of any benefit if we can’t figure out: what is the problem we’re trying to solve, working with the client team to deliver a decent scope, and keep all the multitudes of stakeholders together and working with each other.”

His conclusion: “None of which is achieved directly with tech, but by people and relationships, and some technical skills.”

The Philosophical Transformation

Chris D. described the required shift. “Modern procurement must shift from choke point to value architect. Early engagement, commercial leadership, supplier co-creation. Design to enable and instill trust back into the organization, trust the end users.”

His vision: “Federated purchasing with center-led sourcing. Systems that enable this win the day. The real transformation isn’t digital. It’s philosophical.”

Strahinja Jovanovic, a supply chain expert, called for more voices willing to challenge assumptions. “Tech-first procurement constantly fails but nobody admits it. Your ‘fundamentals first, tech second’ framework should be required reading before ANY platform purchase.”

Tyras offered the litmus test. “Technology scales what you already are, value driver or admin layer.”

Mills summarized the imperative for an era of AI hype and automation overload. “You don’t need more screens. You need clarity. You need strong human connection. You need a procurement function that fixes the fundamentals first and lets technology amplify what already works.”

Continue the discussion with procurement and supply chain professionals on Chain.NET.

Slava Pisanka, an ERP consultant with over 20 years of implementation experience, sparked a conversation recently on LinkedIn. His message was direct: the polished senior consultant who wins the deal is rarely the one doing the work.

The pre-sales team is sharp, knowledgeable, and responsive. The implementation team that shows up after the contract is signed? Often junior consultants and offshore resources, with senior staff stretched thin across multiple projects.

This is not a secret. It is the standard business model for large consulting firms, including the Big 4. Margins drive the staffing decisions. Junior resources cost less. Senior consultants rotate between engagements as supervisors, not doers.

The results are predictable. Longer timelines. Poor quality. Fragile system architecture. And clients left spending months after go-live fixing what should have been built correctly from the start.

Pisanka shared a firsthand example. A supply chain planning module was so poorly implemented that his team spent six additional months reimplementing it after go-live.

The boutique advantage

Compare that with a boutique ERP firm Pisanka worked with later. The same people who ran discovery were present at kickoff. They stayed through go-live and post-launch support. The client never had to ask “who are you again?”

That continuity matters. When the team that understands the business context is the same team configuring the system, fewer assumptions get lost. Fewer handoffs mean fewer errors. Feedback loops are faster.

Several practitioners echoed this in the comments. Barry Callaghan, founder of a boutique consulting firm, shared that his team was twice replaced by Big 4 firms for “risk mitigation,” only to be invited back later to rescue both projects. Richa Thakur, a Business Central consultant, pointed out that smaller firms often deliver better outcomes because the same experienced people stay involved from start to finish. They just struggle to compete with brand power.

Brand names do not guarantee quality

The old logic of choosing a big firm to reduce risk is breaking down. Winnie Nguyen, a CEO focused on business transformation, put it well: big brands used to de-risk decisions. Now they have become the risk themselves. Clients are getting smarter and asking for outcomes, not logos.

Sascha Wind added another layer. A well-known firm name often serves as cover for the CIO. If the project fails, they can say they chose the top supplier. The real failure, he argued, goes unrecorded and simply shows up as an extra line item in the finance department.

It is not just about seniority

The conversation went deeper than “juniors bad, seniors good.” Several commentators stressed that the real issue is governance and delivery structure.

Carol Sloan, a senior ERP integration leader, made a point that drew 30 reactions on its own: whether the team is junior, senior, offshore, or boutique, success depends on who owns architectural decisions and who is accountable when trade-offs are made. Talent distribution is a risk. Lack of structural ownership is a failure.

Yvonne Baloyi, an SAP transformation leader, agreed. Challenges arise when discovery, design, and build are fragmented across different teams. When continuity of business context and architectural intent breaks down, quality suffers regardless of firm size.

Hasan Khan Jadoon went further. He spent months reimplementing GL structures built by junior consultants who had never experienced a month-end close in the industry they were configuring. His advice: make sure the consultants have lived in the function they are configuring, not just studied the module.

The client’s role matters too

Several voices pushed back on placing all blame on consulting firms. Zaid Al-Qassab argued that the client company plays an equally big role. Without an experienced internal team that understands business needs, follows the project closely, and tests the system before go-live, even good consultants will struggle.

Tanya W., who works at a Big 4 firm, offered a balanced view. Not all large firms offshore the majority of work. Her firm uses experienced senior managers to lead workstreams. Her advice to buyers: do not decide on cost alone. Define the delivery team early. Vet them. Set minimum experience requirements for key roles. And do not accept a blended bill rate that hides five junior analysts behind 0.1 FTE of a senior.

Alper Aladag raised the budget question directly. Many companies push for the lowest implementation cost possible. That pressure naturally leads to junior-heavy delivery models. You cannot expect a senior-only team on a junior-level budget.

What you should do

The takeaways from this discussion are clear and practical.

First, ask the question before signing: will the people in this room be the ones at go-live? If there is hesitation, that is your answer.

Second, get named resources written into the contract. If the proposal uses “representative bios” instead of actual names, expect a different team on day one.

Third, watch for blended bill rates. Break down who is doing the work and at what allocation. A low average rate often masks a team weighted toward junior resources.

Fourth, build internal capability. Do not outsource all knowledge to the integrator. Your own team should understand the system well enough to hold the partner accountable.

Fifth, consider boutique firms seriously. They may lack brand recognition, but they often deliver tighter teams, more accountability, and better continuity from discovery to support. As Christine Blyth put it: smaller firms have more to prove because they cannot rely on their logo.

The conversation Pisanka started is not new. But the scale of agreement, from Big 4 insiders, boutique founders, independent consultants, and clients, signals that the industry is ready for a different standard. One where who does the work matters as much as who signs the deal.

What has your experience been with ERP implementation teams? Did the team that sold you the project stick around for delivery? Continue the discussion on the global supply chain community Chain.NET at www.chain.net, where you can ask questions, join events and discussions, and access exclusive resources.

The supply chain profession has spent decades refining safety stock formulas, demand forecasting algorithms, and inventory optimization models. Yet many companies still struggle with the same problem: too much of the wrong inventory and not enough of the right.

The reason, according to a growing consensus among supply chain executives, is that organizations are asking the wrong question. They ask “How do we reduce inventory?” when they should be asking “What operating model are we choosing to run?”

Read more

SAP dominates enterprise resource planning software with a market position that appears unassailable. The German software giant runs operations at thousands of the world’s largest companies. Its S/4HANA platform generates billions in recurring revenue. Competitors struggle to displace SAP once it embeds in an organization.

Yet Eric Kimberling at Third Stage Consulting recently compared SAP’s current trajectory to two iconic tech failures: Blockbuster ignoring streaming and BlackBerry dismissing the iPhone. Both companies dominated their industries until they did not.

The comparison provokes strong reactions. Some dismiss it as consultant hyperbole. Others recognize unsettling parallels. The central question matters more than the debate: will SAP adapt to the future or be overtaken by it?

The Composable Architecture Shift

The enterprise software market is moving toward composable architectures where organizations assemble best-of-breed components rather than deploying monolithic platforms. This architectural shift challenges SAP’s core business model.

SAP still pushes single-stack ERP implementations. The company positions S/4HANA as the comprehensive solution that handles finance, supply chain, manufacturing, sales, and human resources through integrated modules. This integration creates both value and lock-in.

Composable alternatives allow organizations to select specialized applications for each function and connect them through APIs and integration platforms. Financial planning from one vendor. Supply chain planning from another. Manufacturing execution from a third. Each component excels at its specific function.

Jakob Bent Smed, an independent advisor specializing in ERP readiness, observes the market shift firsthand. “I’m seeing the same shift as an independent advisor. Organizations are quietly moving toward more composable, flexible setups, with microservice-based ERP as a perfect example. They want speed, adaptability and less lock-in.”

The debate centers on whether integration benefits outweigh specialization advantages. SAP argues that tightly integrated modules eliminate data silos, reduce integration complexity, and provide unified governance. The integration depth accumulated over decades creates competitive moats.

Composable advocates counter that specialized applications deliver superior functionality, faster innovation, and lower switching costs. Organizations gain flexibility to replace underperforming components without replacing the entire stack.

Barry Preston at a digital strategy consultancy noted the pattern from his implementation experience. “Micro services sound great. They’ve been around for a long time now. The weak point in all of it is in the connections, the integrations needed to create a complete workflow, rather than just islands of functionality. I was implementing SMB systems back before SMB ERP was a thing. We sold individual best-of-breed systems, cobbled together with chains of data integrations, as a great selling point. Truth was, it was the only option we had.”

Yet integration technology has advanced dramatically. Modern iPaaS platforms, API management tools, and event-driven architectures reduce integration friction. What required custom code ten years ago now deploys through configuration.

Stephane Azoulay at NetSuite reframed the debate. “The composable versus monolithic debate often misses the point entirely. The question isn’t architecture for architecture’s sake. It’s whether your platform can genuinely evolve with your business without requiring a forklift upgrade every few years. I’m seeing something different emerge: platforms born in the cloud, built with a unified data model, designed to be extensible and AI-ready from the ground up.”

The Echo Chamber Problem

SAP operates within an ecosystem of partners and analysts whose business models depend on SAP’s continued dominance. Implementation partners build practices around SAP technology. Analysts cover SAP extensively because clients demand it. The ecosystem insulates SAP from uncomfortable market feedback.

Stefan Rask outlined how this manifests. SAP releases, renames, and repackages products faster than customers and consultants can absorb. SAP Cloud Platform became BTP. BW became Datasphere. Ariba became SAP Business Network. Constant rebranding creates confusion even among SAP employees.

The cloud transition accelerates without adequate customer preparation. SAP pushes RISE and GROW migration programs, AI tools, Industry Cloud, and sustainability applications at high speed. Releases arrive every few months. The learning curve steepens beyond what the ecosystem can support.

Multiple overlapping solutions exist for the same purposes. Automation, integration, analytics, and data management all feature competing SAP products. Customers struggle to understand what is strategic, what is optional, and what will be replaced in the next release cycle.

Thomas Wilson observed the result. “Core ERP? SAP is the king and no one can challenge that. However, their product portfolio has exploded out of proportion, that the clients and system integrators are completely confused, not just with regard to what has to be implemented or adopted but also the names of the products which keep changing every other day.”

Azoulay identified why this pattern persists. “When your ecosystem partners’ livelihoods depend on complexity and multi-year implementations, there’s little incentive to advocate for simplicity.”

This confusion serves SAP’s interests short term by creating consultant dependency and switching friction. Long term it erodes trust and opens opportunities for simpler alternatives.

The Quarterly Returns Trap

S/4HANA generates massive recurring revenue. Existing customers pay maintenance fees. Cloud migrations create services revenue. The business performs well by traditional metrics.

This success creates strategic paralysis. Meaningful pivots toward composable architectures or fundamentally new business models threaten current revenue. Executives optimize for quarterly results rather than decade-long market shifts.

Raphaël Delstanche identified the root cause. “The list of the S curve victims is very long: Compaq, MySpace, Xerox, Polaroid, Toys R Us, Borders Group, Nokia. I see at least three reasons for it: The fear of cannibalization and the cash cow dilemma, organizational inertia and strategic blind spots, culture and leadership resistance to change. But the top reason is the intense focus on quarterly returns management as a primary driver of corporate short-termism, which systematically undermines long-term investment, R&D, and genuine innovation.”

Clayton Christensen’s innovator’s dilemma plays out in real time. SAP’s current customers demand incremental S/4HANA improvements. New market segments want fundamentally different architectures. Serving existing customers well prevents serving future customers at all.

The company has resources to invest in new directions. But organizational incentives favor protecting existing revenue over cannibalizing it. Sales teams sell what they know. Partners implement what they have practiced. Customers resist change that does not leverage sunk costs.

The Competitive Reality

AI-native platforms and composable architectures are not theoretical threats. They are production systems winning competitive deals.

Workday disrupted human capital management by building cloud-native from inception rather than migrating legacy code. ServiceNow expanded from IT service management into enterprise workflow through modern architecture. Salesforce owns customer relationship management through continuous innovation and ecosystem building.

These companies do not compete on SAP’s terms. They do not promise comprehensive ERP suites. They excel at specific domains and integrate with whatever surrounds them. This focused approach enables faster innovation, better user experience, and more flexible deployment.

Duncan Jones identified a structural advantage SAP previously enjoyed. “One of the big drivers of SAP’s success was its Fifth Column of career SAP implementers whose careers depended on persuading their current employer to embrace SAP’s erroneous single source of truth religion. Unfortunately for SAP, many of those zealots are now retired or retiring.”

As experienced SAP professionals age out of the workforce, fewer advocates remain to champion SAP in client organizations. New generations of IT leaders lack emotional attachment to SAP and evaluate alternatives more objectively.

Horace Tee offered nuanced perspective. “SAP is a great solution for certain enterprise sizes, but it is not for everyone. Just like BMW is a great driving machine, but it doesn’t mean that everyone needs a BMW for the same driving experience. When SAP finds itself in this situation, it creates opportunities for many tier 2, local, and regional players to enter the market for localized ERP solutions.”

Why SAP Might Survive Anyway

The Blockbuster and BlackBerry comparisons have limits. Piyush Agarwal at LTIMindtree noted the fundamental difference. “BB and Blockbuster could be disrupted quickly because they served and were paid by individuals. SAP operates within complex large enterprise landscape not nearly as simple to break.”

Kimberling agreed. “If this were a consumer facing technology, my prediction would’ve already materialized. But since it’s a business focused technology, it’s going to take longer to see this shake out.”

SAP’s installed base creates enormous inertia. Replacing core ERP is massively disruptive and expensive. Most organizations will optimize existing SAP implementations rather than replace them. This installed base generates cash flow for decades even if SAP wins no new customers.

Richard Whittington, SAP’s global head of media and communications, pushed back on the narrative. “It’s important to always be reinventing yourself, being obsessive about delivering excellence and customer focus at scale. For Blockbuster it was their punitive late fees, BlackBerry didn’t embrace the ecosystem and got out-app’d, and for SAP had we stayed on-premise rather than having the courage to risk our existing business model you may have been right. But we didn’t.”

The cloud transition extends SAP’s relevance. S/4HANA Public Cloud represents genuine modernization even if the architecture remains fundamentally monolithic. Small and medium implementations now cost under one million dollars and deploy in months rather than years. This affordability expands SAP’s addressable market.

Kathiravan Subramaniam defended the innovation trajectory. “I don’t think the comparison is correct. SAP is already in this path of innovating to become AI native. Recent example is SAP Ariba moving to BTP.”

Risk-averse customers prefer proven platforms over promising startups. Compliance, audit, and governance requirements favor established vendors. Global footprints and local presence matter for multinational implementations. SAP advantages in these dimensions are real.

Rajender Gaddam questioned the premise. “SAP is reinventing and capturing back analytics and AI space. It appears every other month someone has a post about SAP is dead. Can you honestly believe that Fortune 500 companies can survive without SAP?”

The Future Scenario

Andres Vargas predicted how this resolves. “SAP will be the older mainframe that all big companies will use as record data and in front of that, many AI applications interacting with the customer.”

Kimberling agreed this represents the likely trajectory.

This outcome preserves SAP’s core business while acknowledging its architectural limitations. SAP becomes the system of record. Modern applications handle customer interaction, analytics, and innovation. Integration layers connect the two worlds.

Whether SAP views this as success or failure depends on perspective. The company maintains massive installed base revenue. But it surrenders the innovation layer to competitors. Strategic value migrates away from core ERP toward surrounding applications.

The Unanswered Question

Joselina Peralta at Stractix reframed the strategic challenge. “Even if SAP pivots, will their customers be structurally ready to move with them? Because here’s the reality: Composable tech doesn’t land in fragmented operating models. AI doesn’t scale inside siloed decision rights. And ERP upgrades don’t create transformation, they expose the lack of it.”

She continued. “This isn’t about SAP alone. It’s about the org’s ability to absorb, align, and act with or without legacy constraints.”

This insight exposes why SAP might survive despite strategic missteps. Customer organizations lack capability to implement composable alternatives successfully. They need integrated platforms not because integration is technically superior but because their organizational maturity cannot handle composition complexity.

SAP’s future depends less on technology strategy than customer evolution. If customer organizations build capability to assemble and govern composable architectures, SAP’s integration advantages diminish. If customers remain organizationally immature, SAP’s monolithic approach continues delivering value.

The market will decide through thousands of implementation decisions over the next decade. Some organizations will successfully adopt composable models and demonstrate superior agility and innovation. Others will struggle with integration complexity and retreat to monolithic simplicity.

SAP’s challenge is not whether to adapt. The challenge is whether adaptation happens fast enough and thoroughly enough to remain relevant when customer capability catches up to composable promise.

The warning signs are real. The outcome remains uncertain. And that uncertainty is precisely what should concern SAP executives most.

Looking for unbiased ERP and digital transformation guidance? Visit Chain.NET to connect with supply chain and IT professionals sharing real-world experiences with SAP, composable architectures, and enterprise transformation. The future is being decided now.

Procurement professionals spend years mastering supplier negotiations, contract terms, and market intelligence. But according to a growing chorus of practitioners, the skill that determines success or failure has nothing to do with external vendors.

It’s the ability to win over internal stakeholders who would rather bypass procurement entirely.

“Most people don’t ignore procurement because they’re malicious,” observed Tom Mills, “Mavericks are usually impatient or just want to get it done. And the harder you push, the harder they resist.”

The observation sparked extensive debate among procurement leaders about why compliance-based approaches fail and what actually works to build internal influence.

The Enforcement Trap

Matthias Svetic, a German market communication advisor, framed the core problem. “Enforcement creates compliance at best. It never creates commitment. The shift from policing process to understanding pressure is where procurement professionals actually start building influence.”

He identified the prize for getting this right. “That influence is what gets you invited into conversations earlier, before the decision is already made and the supplier is already signed.”

Tomasz Tyras, a senior supply chain and operations expert, diagnosed why stakeholders bypass procurement in the first place. “Maverick spend is rarely a procurement problem first. It is usually a speed problem, a trust problem, or a usability problem. People bypass functions that arrive late, speak in policy, or add friction without reducing risk.”

Mark L. Robinson, who transitioned from USDA to private sector procurement, confirmed that policy itself can be the culprit. “Bad policy is one of the main reasons people try to bypass procurement. I saw a lot of that when I worked for USDA.”

Better Questions, Not Louder Enforcement

Mills proposed specific language shifts that change stakeholder dynamics.

Instead of “You should have involved procurement earlier,” try “What outcome were you hoping to achieve with this supplier?”

Instead of “Why didn’t you follow the process?” try “What pressures were you facing when you made that decision?”

“The wrong question triggers resistance,” Mills wrote. “The right one creates space for collaboration.”

Strahinja Jovanovic, a supply chain and inventory expert, illustrated how this plays out in practice. “Stakeholder bypasses procurement, orders direct. Procurement finds out. Enforcement: ‘You violated policy.’ The stakeholder goes quiet, the problem goes underground. Exploration: ‘What were you facing?’ opens why they bypassed, surfaces the real barrier.”

He warned about the downstream effects of enforcement. “Enforcement stops visible maverick spend but creates invisible workarounds.”

Hamilton Lindley, VP of Procurement, Compliance and Risk, added a caution about even well-intentioned questions. “The trap even good questions miss is that they still feel like interrogation if the person doesn’t feel heard first. You have to actually understand why they bypassed you before asking what they were trying to achieve.”

The Deal That Works

Leslie Dailey, a procurement and contracts leader, shared a practical approach that has delivered results. “I make deals with my leaders and stakeholders. You bring me in early, you be the expert and I will take care of the paperwork.”

The framing matters. “This lets them know I understand the pain points, and I understand their needs and urgency. This has been wildly successful for me.”

She identified a common complaint she addressed head-on. “One of the biggest issues I had heard before is we say no at the wrong time or too late in the game, so I flipped the script and they partner with me just to get it done.”

Mandeep Singh, who works in contract manufacturing, described his two-minute approach. “I’ll ask what deadline they’re protecting, then I’ll offer one concrete move that helps today, like locking the scope in one paragraph, getting the supplier to confirm dates in writing, or building a simple approval path so their request doesn’t bounce around.”

His insight: “Once they feel you’re reducing their stress, not adding to it, they stop bypassing procurement on their own.”

Understanding the Stakeholder Change Curve

Mills introduced a framework for meeting stakeholders where they are. “Not every stakeholder is ready to engage. Some are in: ‘I don’t need procurement.’ Others are in: ‘Maybe procurement could help.’ If they’re in pre-awareness, your role isn’t to enforce policy. It’s to build credibility and plant seeds.”

He identified quiet signs that stakeholders are opening up: involving procurement earlier in conversations, asking for input on supplier decisions, referencing procurement internally, shifting from bypassing to collaborating. “Those are all the signs of progress being made and you should see them as a win.”

Chantell L., founder and CEO of RenewedHER Procurement Group, captured the dynamic. “The biggest shift happens when the conversation moves from policing the process to understanding what the stakeholder is actually trying to solve. When people feel heard first, they’re far more open to seeing how procurement can help them get there.”

The Incentive Problem

Dr. Tobias Riehm, a market designer specializing in game theory and negotiation architectures, offered a structural perspective that went beyond communication skills.

“Resistance to procurement often isn’t just about communication or trust. It’s about incentives,” he wrote. “Many stakeholders operate in a different payoff structure: speed, technical performance, or internal KPIs may dominate cost optimization. From their perspective, bypassing procurement can therefore be a perfectly rational strategy.”

His prescription went further than relationship-building. “The most effective procurement organizations don’t just influence behavior. They redesign the incentive structure and the decision process so collaboration becomes the dominant strategy.”

The Mandate Question

Dr. Mario Büsch, a procurement strategist and advisor, raised a point about organizational support. “It is equally the responsibility of the procurement management team to work with the Board to establish and strengthen a clear mandate for procurement.”

Ashwin Nayak, a procurement professional, described the inherent tension. “Leadership expects procurement to manage gatekeeping priorities of compliance, savings, etc., which often are contrary to the dynamic goals of the internal stakeholders, often requiring agility and timelines as immediate as yesterday.”

Sarah McGillicuddy, a procurement consultant, distilled stakeholder engagement to two keys. “Listen to them, create opportunities and space to really listen, and deliver results. When you prove your value, stakeholders come to you with curiosity or conviction, not because they have to follow the rules.”

The Perception Problem

Michael Shields, Vice President of Procurement at Tropic, acknowledged an uncomfortable truth. “Admittedly our reputation in procurement isn’t always the best.”

He outlined a two-pronged solution. “We need to be improving how people perceive us. It’s tackling the problem from both sides. Improve the value we offer plus do a better job of helping people see it. In my experience, that’s a recipe for success.”

Magdalena Jimenez Carrillo, an indirect purchasing manager, described the daily reality. “Working in Procurement sometimes feels like being in permanent negotiation mode. And not just with suppliers. A big part of the job is the subtle, behind-the-scenes negotiation we do every day with our internal stakeholders.”

Mills confirmed this is the underestimated challenge. “The biggest underestimated challenge for procurement professionals is actually internal, not external. Not enough people talk about this.”

Where Trust Comes From

Chandranath Chakraborty, a senior procurement and transformation executive with experience at Disney, Nike, Unilever, and P&G, framed the stakes clearly. “When we lead with enforcement, we become a hurdle to be cleared. When we lead with curiosity, asking about the pressures a stakeholder is facing, we become an architect of their solution.”

He summarized the difference between compliance and trust. “Compliance might get the contract signed, but trust is what gets you invited to the meeting where the strategy is actually born.”

Nuha Luqman, who works in supply chain and procurement for energy ecosystems, offered a memorable formulation. “Procurement influence often grows through curiosity rather than control. The right question can open more doors than the strictest policy.”

Howard Richman, a global procurement transformation leader and co-author of “Procurement Confidential,” invoked a classic principle. “Seek first to understand, then to be understood.”

Tyras described what success looks like. “The turning point comes when procurement starts being seen not as control, but as a faster path to a better decision. In strong organizations, compliance is the outcome, not the opening line. The real win is when the business involves procurement early because it sees judgment, market intelligence, and problem-solving value there.”

Mills acknowledged that the transformation isn’t always one-directional. “Coaching a stakeholder into awareness takes time. The breakthrough often happens after the conversation ends. And sometimes, the mindset that changes most is procurement’s.”

Continue the discussion with procurement and supply chain professionals on Chain.NET.

The procurement profession talks a good game about supplier relationships. Partnership. Collaboration. Win-win. But according to experienced practitioners, the gap between rhetoric and reality is where trust goes to die.

A recent discussion among supply chain executives catalogued seven common mistakes that damage supplier relationships, often without procurement teams even realizing it. The comments that followed revealed an industry grappling with how to balance commercial discipline with the respect that builds durable supplier ecosystems.

“Procurement only wins with suppliers when it treats the relationship like a long-term performance system, not a series of tactical wins,” wrote John Cross, an AI-driven procurement and transformation leader. “The moment ego, opacity, or faux-partnership creep in, you trade short-term gains for long-term risk.”

The Seven Mistakes

Simon Frost, a procurement consultant specializing in sustainable procurement and cost modeling, outlined behaviors that undermine supplier trust.

Talking “win-win” when you mean “we win, you survive.” Suppliers can detect insincerity. The tip: understand what’s actually valuable to them, share what matters to you, and trade value-based variables rather than just hammering on price.

Not paying to agreed terms. “Your suppliers are not your bank,” Frost wrote. “Late payment erodes trust and breeds resentment.”

Aiman Nadeem, a global sourcing expert, put it more sharply. “If you delay payment while preaching partnership, credibility evaporates instantly. Cash flow hypocrisy is remembered longer than any contract clause.”

Being overly familiar. Supplier relationships are commercial, not personal friendships. Frost advised knowing where the imaginary line sits, being friendly and respectful, but maintaining professional distance.

Declaring partnership when it isn’t. True partnership involves high interdependency and shared risk over extended periods. “Don’t declare partnership if it isn’t,” Frost wrote. “It’s phoney. Instead say: ‘we value our relationship’ and let your positive actions do the talking.”

Boasting about winning. Frost reported hearing procurement professionals declare “We nailed them!” after negotiations. This bravado, he warned, is dangerous. “A wounded supplier will come back to bite you. Even if you got what you wanted, remain humble.”

Expecting suppliers to fix your ESG. Environmental, social, and governance compliance is a shared responsibility, not a compliance baton to pass. The recommendation: set achievable standards, learn new skills together, collaborate on improvements, and share data transparently.

Hiding information. Procurement teams often keep cards close to their chest, building resentment. The guidance: appreciate that sharing information can help you, trade information to get information, and never try to hoodwink suppliers.

Frost proposed a simple test for every interaction: “Would I like to be treated like this?”

The Comments Added Three More Mistakes

Industry practitioners expanded the list with observations from their own experience.

Nuha Luqman, who works in supply chain and procurement for energy ecosystems, identified a common failure. “One I’d add: managing suppliers only when there’s a problem. Real partnerships are built in the quiet moments, not just in negotiations or escalations. Consistency builds more trust than any ‘win.’”

Alberto Mentesana, a director of procurement and supply chain in oil and gas, added another. “One mistake I would add: treating suppliers as interchangeable commodities when they are actually strategic capabilities.”

He elaborated on what makes supplier management effective. “The biggest mistake organizations make is treating supplier management purely as a price negotiation exercise. Price matters, but sustainable performance comes from mutual understanding of value, transparency, and long-term alignment of interests.”

Farzaneh S., an industrial procurement manager with over 15 years of experience, contributed a third addition. “I’d add: treating every supplier the same. Segmentation changes everything.”

The Balance Between Friendly and Professional

Mary Ruth Williamson, a procurement and strategic sourcing practitioner focused on direct materials, offered a counterpoint to concerns about being too distant. The bigger problem, she argued, is the opposite.

“So many procurement folks actually believe and act like the supplier is their friend,” she wrote. “Then they give away too much info, don’t hold them responsible for performance and don’t keep them honest about price. It’s one of the biggest errors I see inexperienced procurement teams make.”

When asked which of her own mistakes she’s had to overcome, Williamson acknowledged an evolution. “Early in my career it was probably hiding information. As experience grows, you learn that sharing certain information can make your supplier a better partner and can show your commitment to the relationship.”

The Phoney Partnership Problem

The issue of declaring partnership prematurely drew significant comment.

Mário Delmaestro Junior, a general manager at REMA TIP TOP Middle East, highlighted why this matters. “The point about ‘declaring partnership when it isn’t’ really stands out. True partnerships are built through shared risk and long-term behaviour, not labels.”

Samuel Mutuku, a procurement and supply chain specialist, agreed. “Declaring partnership prematurely is a common trap. Actions always speak louder than words. Mutual commitment is demonstrated, not announced.”

Javeria Javed, a BBA student interested in supply chain, asked a practical question: “What’s the clearest signal that a supplier relationship has genuinely moved from transactional to strategic?”

Jehanzeb Alam, a procurement and supply chain leader focused on ESG integration, offered an answer. “Supplier relationships that I have seen are built on shared problem solving, when both sides feel safe to be transparent, including risk, constraints and future plans. Which essentially makes the relationship strategic.”

Communication Reveals Character

Toni Le Rigoleur, who works on SAP Ariba and procurement solutions, observed that how procurement communicates reveals underlying motivations.

“Buyers often miss this and just ask and negotiate with nothing in exchange and call it a win-win,” he wrote. “But more often than not, you can also feel it in their way of communication. Are they speaking from ego? Fear? Trust? It all changes how relationships are made in business.”

Chantell L., founder and CEO of RenewedHER Procurement Group, emphasized that behavior during difficult times defines relationships. “So much of this comes down to basic respect and self-awareness. The commercial edge matters, but how people show up day to day, especially when things are tight, is what suppliers actually remember.”

Maturity Means Balance

Carlos Eduardo Carvalho da Silva, a global strategic sourcing specialist, defined what procurement maturity looks like. “Maturity in Sourcing is about balancing firm commercial discipline with genuine, value-based collaboration. It’s the only way to move beyond simple transactions.”

Annette Ng’ang’a, a senior procurement and supply chain specialist, framed the fundamental shift required. “Procurement is more relational than it is transactional and therefore we should strive to have very amazing ones with suppliers.”

Stan Moskovtsev, CEO of Zinit and a McKinsey alum, noted that problems extend beyond the seven mistakes listed. “I’ve seen challenges arise when expectations aren’t aligned, when feedback loops are missing, or when long-term strategic value is overlooked in favor of short-term wins.”

Kishore Kunal, a global procurement leader managing a $250 million-plus CAPEX portfolio, endorsed the core principle. “The ‘would I like to be treated like this?’ test is especially powerful. Simple, uncomfortable, and very effective.”

The Long Game

Industry Roll, a procurement community account, distilled the discussion to its essence. “Many points narrow down to one simple thing: be a good person, be humble and honest. Quick wins don’t matter. The long running ones do, because they create true partnerships.”

Procrewment added one final caution. “Overemphasis on cost today can reduce responsiveness and innovation tomorrow.”

Arrigo Tosi, a procurement manager, acknowledged the gap between knowing and doing. “These are the basis but not every time respected.”

The response from Frost captured why that gap persists. “If we’re the ones who respect these type of principles, then we will shine out above others who aren’t.”

In an era of supply chain disruption, the practitioners who treat supplier relationships as strategic assets rather than adversarial negotiations may find themselves with more resilient, more responsive, and ultimately more valuable supply bases than those still celebrating tactical wins.

Continue the discussion with procurement and supply chain professionals on Chain.NET.

Supply chain leaders have a forecasting obsession. They pour millions into advanced planning systems. They chase AI pilots. They build dashboards nobody uses. Then they wonder why service levels stay flat and inventory keeps climbing.

A recent report from Boston Consulting Group, “Supply Chain Planning 2026: Why AI Alone Isn’t Enough,” surveyed more than 180 planning leaders across industries and regions. The findings confirm what many practitioners already feel in their gut. Over 70% of companies have invested in advanced planning systems (APS). Yet few consider themselves best-in-class. The gap between leaders and laggards keeps growing. BCG’s conclusion: technology is not the constraint. People, processes, and organizational readiness are.

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When Finance presents to leadership, they talk about growth. When Sales presents, they talk about wins. When Operations presents, they talk about performance.

When Procurement presents, they talk about savings percentages and compliance adherence.

That disconnect, according to a growing chorus of supply chain executives, explains why procurement struggles for strategic recognition despite managing billions in corporate spend.

“We’re selling aspirin to people who don’t think they have a headache,” observed Juan F. P., founder of Success Procurement Consulting, in a post that sparked vigorous debate among procurement professionals worldwide.

The diagnosis resonated. But the proposed cure, a fundamental shift in how procurement communicates value, generated even more discussion about whether the problem runs deeper than language alone.

The Translation Problem

Marcel Van Wonderen, a procurement and supply chain transformation advisor and former IBM executive, framed the challenge bluntly. “Leadership doesn’t reject procurement. They reject irrelevance.”

He added a memorable observation: “No one remembers a percentage saved. But they do remember the product launch that happened with important third party content.”

Muhammad Arham Khan, a procurement professional specializing in renewable energy, captured the shift required. “Procurement doesn’t need louder voices. It needs better translators. When we convert savings into shareholder value, risk into resilience, and sourcing into strategy, the room listens.”

The original post proposed concrete changes: Replace “€4.8M category renegotiation” with “the reason Product Launch X stayed on budget.” Kill the 40-slide quarterly deck and replace it with three stories the CFO can repeat to the board without procurement in the room.

Tomasz Tyras, a senior supply chain and operations expert, expanded on this framework. “Procurement often reports in ‘internal metrics’ while leadership listens in ‘business outcomes.’ Savings percentage and compliance are fine, but they do not explain what stayed on track, what risk was avoided, or what speed was unlocked.”

He offered a litmus test for effective communication. “The move is to translate every procurement win into one of three board dialects: cash, risk, or growth. If it cannot be repeated by the CFO in one sentence, it is not a message yet.”

Beyond Communication: A Structural Problem

Not everyone agreed that better storytelling solves the underlying issue. David Castro Yáñez, an operations leader focused on productivity and implementation, challenged the premise.

“I agree with the overall point, but I think the issue goes beyond communication or language,” he wrote. “The real challenge is how Procurement KPIs are defined and how performance is measured. If the function is assessed primarily on savings, it will naturally report savings.”

He identified the root cause. “The need to ‘translate’ that into broader business impact signals a structural misalignment, not a communication gap. This starts with rethinking Procurement’s strategic objectives and KPIs, led by the CPO, so that value creation is embedded in how performance is measured, not retrofitted in how it is presented.”

Elvira Tiurina, a procurement leader with experience on LNG and EPC mega-projects, confirmed this misalignment exists widely. “We have 30+ slides deck and it is awkward to tell we do our job well. The main question is the value. If 50% of procurement KPIs don’t match business needs, so... You understand what I mean.”

The response acknowledged an uncomfortable truth. “If 50% of Procurement KPIs don’t match what the business actually cares about, the problem isn’t storytelling. It’s alignment. A 30-slide deck is usually a symptom, not the cause. We create more slides when we’re unsure our metrics prove relevance.”

The Data Storyteller Imperative

Fabian Landsinger, a procurement lead specializing in aviation training devices, identified a capability gap. “Turning data into stories is a key future competency. Procurement overall is still struggling to express its true strategic value. It’s on us to develop more ‘Data Storytellers.’”

Stefan Lenhart, who fixes broken supply chains for SMEs, illustrated what effective translation looks like. “Your CFO couldn’t care less about order lot size optimization. They will care if you can trace that to a six-digit working capital reduction.”

He warned of the consequences of failing to adapt. “If procurement pros are unable to translate what we’re doing into numbers and facts that show an impact to the business, the function will always remain sidelined.”

Saleh Aljneibi, a senior procurement and contracts manager in government administration, distilled the maturity journey into one sentence. “Procurement maturity isn’t just capability. It’s narrative alignment with enterprise priorities.”

The Emotional Dimension

Rahul Vashistha, a former board member at Nestrade Procurement with global leadership experience, added nuance that purely rational approaches miss. He identified several challenges procurement must navigate beyond language.

“Managing the emotions of sense of possessiveness of budget owners. Withdrawal symptoms of losing commercial ownership. Perception that procurement is COST and/or SERVICE focus and NOT BUSINESS focus.”

His prescription: “Establish that Procurement understands business as much as business stakeholders and works with business, for business.”

Alfred “Vaughn” Melson, a senior sourcing specialist, suggested borrowing techniques from an unexpected source. “Explore how to apply emotional intelligence. YouTube ‘Chris Voss Hostage Negotiator’ and move to the head of the table where you, procurement, belong.”

His insight: “If someone has to defend their position, they will. If they feel understood, they’ll reconsider it themselves.”

Letting Go of Credit

One of the most counterintuitive recommendations from the original post drew significant support: make procurement’s wins belong to everyone. Let the business take the external credit. Earn the internal trust.

Marina Ayad, a procurement professional based in the UAE, endorsed this approach. “This approach not only builds trust, but also positions you as a true business partner, creating real value for the wider organization rather than focusing on departmental recognition or personal pride.”

Amalia Sepulveda Corzo, a supply chain manager with 18 years of experience across oil and gas, energy, mining, and agribusiness, summarized the required transformation. “The shift isn’t operational. It’s narrative. And that starts by speaking in business outcomes, framing trade-offs in strategic terms, and connecting every initiative to EBITDA, growth, or risk.”

Proactive Presence

The original post recommended a behavioral change: stop waiting for invitations to strategy meetings. Bring one relevant insight per week. Short. Unsolicited. Useful.

Olugbenga Odusanya, a global supply chain and procurement thought leader, framed the opportunity. “Procurement earns strategic influence when it speaks the business language of value, risk, and impact, not just savings metrics and compliance numbers.”

Peter Gyurak, a procurement consultant and trainer, offered a reality check about what leadership actually values. “The ‘Table’ doesn’t care about the process of procurement, only the byproduct of it.”

Maria Del Pilar Cristobal Rico, a procurement manager focused on complex negotiation and risk mitigation, emphasized the listening component. “It is crucial to learn how leaders truly listen and to adapt our message in accordance.”

The Path Forward

The debate revealed a profession wrestling with its identity and influence. Some see the solution in better communication. Others point to structural changes in how procurement is measured. Most agree that the status quo, where procurement presents savings percentages to executives who think in terms of growth, wins, and performance, cannot continue.

None of the proposed solutions require new tools, additional budget, or transformation programs. They require changing how procurement communicates value. Or, as one practitioner put it, unlearning how procurement teams are taught to communicate and learning how leaders truly listen.

The question facing every procurement professional: Are you reporting what you saved, or showing what you made possible?

Continue the discussion with procurement and supply chain professionals on Chain.NET.

The warehouse automation industry has a reputation problem. And according to executives who gathered at some recent logistics events, it’s largely self-inflicted.

Conversations in hallways and meeting rooms revealed a troubling pattern: expensive automation projects failing, operators pulling the plug on multi-million dollar investments, and a growing reluctance among companies to attempt automation again after getting burned.

“Automation is not a problem, inept implementation is,” summarized Ken Ackerman, a warehousing consultant and author of four industry books. His blunt assessment captures a sentiment spreading across the logistics sector.

The technology works. The sales process doesn’t.

The Square Peg Problem

Kevin Lawton, host of The New Warehouse Podcast, sparked an industry-wide discussion after sharing observations from multiple conversations about failed projects. His diagnosis pointed to a fundamental misalignment between what’s being sold and what operations actually need.

“What I’m seeing is that many solution providers were focused on the sale and not necessarily focused on the right solution at the time even if that solution was not theirs,” Lawton wrote.

James Palmer, a leader in automation and robotics, agreed emphatically. “What we are seeing is a result of under qualified, inexperienced sales people pushing a portfolio of products not fit for purpose. To solve the problem you need to understand the problem.”

Jakob Beer, a warehouse automation specialist, offered a sharper critique of how the industry frames its offerings. “There are no ‘solutions’ on the market, only products. The solution needs to be engineered based upon customer requirements, and it entails much more than a bunch of robots. Mistaking products or technology for solutions is one of the reasons why projects fail.”

He added a sobering observation: “The number of failed projects is much higher than one might expect. Many failed projects, as measured by ROI, aren’t even recognized as failures. Many projects deliver much less than promised.”

Follow the Money

Several industry veterans traced the problem to its financial roots. Michael Myers, whose software helps warehouses improve cost efficiency, identified venture capital as a contributing factor.

“We cheer when solution providers raise tons of VC capital, then we’re surprised when capital automatically becomes sales pressure,” he wrote. His comment drew significant engagement from professionals who recognized the dynamic.

Ottavio Saluzzi, who has worked on automation projects across five continents over nearly 20 years, expanded on this theme. “In the age of AI and automation, too many ‘solutions’ are being driven by sales pressure, VCs, and investors pushing tech companies to grow revenue at all costs. It’s all about top-line growth to prove relevance or secure the next funding round.”

He shared a telling anecdote about maintaining integrity under pressure. A prospect asked his team for shuttles. “The answer was, as it should have been, ‘let’s look at the data first, run the numbers, the result will suggest the solution.’ And the result was that the client didn’t even need automation. Ye olde unfancy manual warehouse would have done.”

Missed sale? Perhaps. But Saluzzi noted that wrong implementations devastate vendor reputations, pointing to major market share shifts among providers as evidence of eroding trust.

Automation Exposes, It Doesn’t Fix

Cecilia George, a senior recruitment consultant specializing in the sector, identified a fundamental misconception driving failures.

“Warehouse automation often gets treated like the shiny new toy, but in reality it doesn’t really fix broken operations, but rather exposes them,” she wrote. “Too many projects fail because companies assume automation will solve fundamental process, data or layout issues.”

She proposed a different success metric. “The real measure of success is not ‘does this technology work?’ It’s ‘is this warehouse automation ready?’”

The prerequisites she listed, including clear operating processes, clean master data, realistic throughput assumptions, change management, and internal capability, often go unaddressed before equipment arrives.

Rich Hough II, a logistics consultant, observed the human element frequently gets overlooked. “The main issue in most cases is that the value of people is not being adequately calculated in most implementations. In some cases, empowering people with new technology tools and training up to address skill gaps is much better ROI vs replacing headcount with automations that sound good on paper but rarely deliver real world benefit as advertised.”

The Simulation Timing Problem

Amy Greer, a principal simulation engineer, identified a troubling trend in how companies approach validation.

“We are seeing a trend where companies want to simulate AFTER making the decision. That is, companies are wanting to use simulation for digital twins,” she explained. “This is a great use case for simulation, but digital twinning a bad design is not going to fix the bad design.”

Her recommendation: simulate very early in the design phase and refine as decisions progress. “Not all automation has a positive ROI, and some of our most helpful projects are the ones when we help a customer avoid a bad automation choice.”

The Career Risk Factor

Ben Hopkins, who runs The Warehouse Underground community, highlighted an underappreciated dimension of failed projects: career consequences.

“Someone’s role, their job, being at stake if things roll out poorly. The pressure becomes immense quickly and scapegoats are a real thing sadly,” he wrote. “Go through these scars a few times and it’s easy to see how people can have a ‘never again’ attitude on automation investments.”

He noted the absence of reliable vetting resources. “Because there is no easy way to vet these things ahead of time, there isn’t a ‘Yelp’ or ‘Angie’s List’ for this, they’re at the mercy of taking the vendor word for it.”

The AI Distraction

Several commenters questioned whether artificial intelligence will deliver on its warehouse promises. Marco Gebhardt, managing director of a family-owned intralogistics company, expressed skepticism.

“I don’t see that AI solves problems in SMB that automation would address,” he wrote, later adding: “A lot of what is currently labeled as ‘AI’ is essentially advanced mathematics, heuristics, and optimization algorithms. Things operations research has been doing for decades. It’s now often rebranded as AI because it sells better.”

Anthony Allwood, founder and CEO at Systems Logic, was more direct. “AI is the latest .COM style gold rush. It’s absolutely a valid and valuable technology, but it’s often being over-hyped, with investment pressure sometimes pushing entrepreneurs to compromise their moral compass.”

Simple Often Beats Sophisticated

Adrian Betts offered an automotive analogy that resonated with operators. “People are putting Ferrari cams in motorhomes. It’s gonna be a pig. An oversized solution for situations that’ll never occur.”

Jared Call, who works in warehouse automation service, distilled decades of industry wisdom into one sentence: “Automating inefficient processes will just mean you’re doing the wrong things faster.”

Jamie Callihan shared examples of overengineering. “We have learned to ask if the process needs to be ‘orchestrated’ or not. One example we see a lot is that items that need to be replenished can be handled by operators, rather than by fancy software. Send the full cart, send the empty cart back. No Wi-Fi, laptops, or engineers needed.”

The Path Forward

The consensus among practitioners points toward a more disciplined approach. Donald Ponticello emphasized data-driven decision making. “Too many operations invest in automation without truly understanding where the biggest opportunities or pain points actually are. You don’t have to automate everything on day one, but you do need to be strategic about where you focus.”

Douglas Grandi, a project manager, argued for modularity. “Instead of making a large upfront investment based on uncertain future growth and projecting a 2-3 year ROI, it is more strategic to invest in automation aligned with the operation’s current capacity. Technology should be complementary and expandable.”

Multiple voices endorsed working with agnostic consultants and integrators, particularly for first-time automation projects. As Lawton noted, innovation in the industry advances through success and understanding of proper fit, not through forcing technology into operations where it doesn’t belong.

The warehouse automation industry isn’t facing a technology crisis. It’s facing a trust crisis. Rebuilding that trust will require vendors willing to walk away from bad-fit deals and operators willing to invest in operational readiness before writing checks for robots.

Continue the discussion with supply chain and logistics professionals on Chain.NET.

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Supply chain leaders have talked about digital transformation for years. Now they are putting real money behind it. Nearly half of all companies implementing AI in their supply chains report cost reductions of at least 10%. The technology is moving from pilot projects to production at scale.

A recent IDC report surveyed 488 supply chain professionals and found that AI adoption is expected to grow from 50% to 86% within three years. The research also revealed that 80% of companies now consider AI either important or very important across all areas of the supply chain. This marks a clear shift from experimentation to operationalization.

Legacy Systems Block the Path Forward

The biggest obstacle to AI adoption is not strategy or budget. It is old technology.

IDC found that 46% of companies cited legacy systems as a trigger for upgrading their supply chain management applications. These older on-premises systems lack the flexibility and scalability that modern AI requires. Another 41% pointed to poor integration between new applications and legacy implementations as a major pain point.

The problem runs deep. Supply chain organizations report that legacy IT continues to drag down their responsiveness. When disruptions hit, slow systems translate to slow decisions. Cost increases, transportation delays, unpredictable deliveries, and volatile demand patterns all persist. Companies know they need to respond faster. Their technology cannot keep up.

This creates a vicious cycle. Organizations focused on cost efficiency at the expense of resiliency (35% admitted this) now find themselves unable to adapt quickly. They lack visibility into their supply chains. They cannot see where and how to respond effectively.

Three Types of AI Are Reshaping Operations

The report distinguishes between three categories of AI now entering supply chains: traditional AI and machine learning, generative AI, and agentic AI.

Traditional AI leads adoption today. About 74% of companies already use it. Another 26% plan to implement it within 18 months. These systems handle tasks like demand forecasting, inventory optimization, and predictive maintenance.

Generative AI follows close behind. Currently 41% of companies use it, with 59% planning adoption in the next 12 to 18 months. IDC projects generative AI adoption in supply chains will grow from 25% to 37% within three years. Companies apply it to process automation, real-time decision support, and exception management.

Agentic AI represents the newest frontier. Only 31% of companies use it today, but 69% plan to adopt it soon. This technology enables autonomous decision-making in specific domains. Most companies (30%) believe AI agents should make decisions in most areas with human oversight for critical issues. Another 29% want all decisions approved by humans.

The research emphasizes that benefits are maximized when supply chains combine all three types. Traditional AI provides the analytical foundation. Generative AI accelerates human productivity. Agentic AI enables faster autonomous responses. Together they create a more capable and responsive operation.

The Cloud Connection

AI requires modern infrastructure. IDC found that over 80% of respondents say modernizing their applications in the cloud is important to fully benefit from AI innovations.

The numbers tell the story. Today, 52% of companies deploy traditional AI in the cloud. That figure rises to 62% within 24 months. For generative AI, current cloud deployment stands at 65%, climbing to 77% in two years. Agentic AI shows similar patterns: 64% cloud-deployed today, 73% in 24 months.

Cloud platforms provide the computing power and data accessibility that AI demands. On-premises systems struggle to deliver the speed and scale needed for real-time supply chain decisions. Companies that delay cloud migration also delay their AI capabilities.

Where Companies See the Biggest Returns

Supply chain planning leads the list of realized benefits. Process automation for increased efficiency tops the chart at 32%. Improved predictive analysis follows at 21%. Real-time decision-making comes in at 17%.

In fulfillment and logistics, cost reduction leads at 25%. People productivity improvements reach 19%. Reduced delivery lead times and transportation route optimization each deliver meaningful gains.

The aggregate impact is substantial. IDC found that 48% of companies implementing AI report at least a 10% reduction in supply chain costs. Another 40% show a 10% improvement in productivity. And 35% demonstrate a 10% improvement in innovation delivery.

These are not marginal improvements. A 10% cost reduction across a global supply chain can mean tens or hundreds of millions of dollars in savings. Productivity gains compound over time. Innovation improvements create competitive advantages that persist.

Investment Levels Are Rising

Companies are backing these benefits with significant capital. About 23% plan to spend between $1 million and $9.9 million on AI-powered supply chain initiatives in the next 12 to 18 months. Another 9% plan investments of $10 million to $50 million.

Looking further out, spending accelerates. In the 18 to 36 month window, 31% of companies plan to invest $1 million to $9.9 million. Another 12% target the $10 million to $50 million range.

Most organizations (63%) are willing to spend as much as 20% of the total cost of replacing their supply chain management systems on AI capabilities. Only 7% expect AI functionality at no added cost. Companies recognize they must pay for these capabilities.

Key Takeaways

First, AI is no longer optional for supply chain competitiveness. Companies implementing these technologies report significant cost reductions, productivity gains, and faster innovation. Those who delay risk falling behind.

Second, legacy systems are the primary barrier. Organizations cannot unlock AI benefits while running outdated technology. Cloud migration is a prerequisite for advanced AI deployment.

Third, success requires a holistic approach. Traditional AI, generative AI, and agentic AI each contribute different capabilities. The greatest benefits come from combining all three within an integrated platform.

What is your organization’s biggest obstacle to AI adoption in supply chain? Is it legacy systems, budget constraints, talent gaps, or something else? Share your experience in the comments.

Continue the discussion on Chain.NET (www.chain.net).

As autonomous agents take over procurement and logistics work, the seat-based SaaS pricing model that shaped enterprise software for 30 years no longer works. What’s replacing it will be far more complex - and far more expensive.

For three decades, the software industry operated on a simple formula. You licensed a seat. You paid per user. You got a reasonably stable product, updated quarterly.

That model works fine when humans are the primary users. It breaks completely when agents are.

Most procurement and supply chain software today still charges per user. You add a procurement specialist, you pay for another seat. You hire a logistics coordinator, your costs rise accordingly. Acumatica’s pricing is customized based on factors like industry edition, user count, transaction volume, and selected features rather than fixed per-user fees, with the General Business Edition starting at $6,000 per year including five user licenses and 1,000 monthly transactions. That model persists across the industry.

But when agentic AI becomes operational—when suppliers are evaluated by agents, RFQs are drafted by agents, sourcing decisions are orchestrated by agents—counting seats becomes meaningless. The agents ARE the users.

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