Why Supply Chain Decision-making Is So Challenging

Why Supply Chain Decision-making Is So Challenging

Why Supply Chain Decision-making Is So Challenging

Feb 17, 2025

steve

"Global supply chains are broken." At least that's the opinion Dave Clark, founder and CEO of Auger, shared in a LinkedIn post. He explained, "Too many [supply chains] are still being run on Excel. Operators spend countless, frustrating hours battling endless spreadsheets stitched together from disjointed, outdated 'Franken-software.' It’s inefficient, chaotic, costly, sub-optimal and completely unfit for the modern world." Clark believes technology can overcome the challenge. Adrian Gonzalez, President of Adelante SCM, is skeptical. He writes, "I’ve seen armies of smart people and billions of dollars invested to create that one silver bullet solution that will finally, finally solve all the waste and inefficiencies that exist in supply chain management. Yet, here we are, still mired in waste and inefficiencies despite decades of technological advancements. Why? Because the real problem to be solved is not a technology one."[1] So, what's the real problem? According to Gonzalez, the real problem is "getting companies to trust each other more and collaborate." He explains, "Heck, many companies still have trust issues internally between different functional groups. Logistics doesn’t trust Sales, and Sales doesn’t trust Manufacturing, and Manufacturing doesn’t trust Procurement … and they all continue to focus on their siloed functional metrics, which is what their performance reviews, paychecks, and bonuses depend on." You have to admit he makes a good argument.

 

Collaboration in the Supply Chain

 

Gonzalez isn't the first expert to decry the lack of collaboration in the supply chain or to recognize how collaboration could make a substantial contribution to smoother operations. Back in 2019, Naveen Poonian, President of iBASEt, wrote, "For years, the belief that the seamless, transparent, and real-time flow of communication can improve the results of supply-chain collaboration has been the holy grail of business: frequently aspired to, but seldom achieved. ... If successful collaborations were to become more common, they could have an impact that ripples throughout the world economy."[2] He went on to explain why more collaboration doesn't take place:

 

"The problem in many cases is that the relationship between buyer and seller is antagonistic, or at least conducted at arm’s length, rather than being one of collaboration. Each party has its own transaction, process, and uncertainty costs, frequently leading to higher-than-necessary inventory levels, differing product codes, and conflicting administrative arrangements. There’s often a lack of trust, marked by a reluctance to work as partners or share sensitive information. Business secrets and confidential information are still very much a part of commerce today. Moreover, business partnerships change over time, and in a volatile economy with high levels of uncertainty and risk, those changes can come about abruptly."

 

Sound familiar? Not much has changed over the past half-dozen years. Nevertheless, experts are still stressing the importance of collaboration. For example, last year Deloitte analysts wrote, "Supply chain collaboration is key to building an agile and responsive supply chain that can withstand unforeseen challenges. By working together, supply chain partners can gain visibility into each other’s networks, identify, manage, and mitigate risks proactively, develop contingency plans, and innovate to adapt to changing market conditions."[3] As Gonzalez pointed out, however, collaboration is based on trust and, in today's trade war climate, trust is hard to come by.

 

Despite the current business climate, Gurram Gopal, a Professor in the Stuart School of Business at the Illinois Institute of Technology, is sanguine about the future of supply chain cooperation. He writes, "For decades, industry leaders have touted the transformative potential of supply chain collaboration. Yet true end-to-end collaboration has remained elusive due to technological and organizational barriers. However, the tide is turning. As companies increasingly migrate their IT systems to the cloud, the potential for seamless information sharing and coordinated decision-making is closer than ever. Coupled with advances in artificial intelligence, these changes promise significant productivity gains and unprecedented supply chain cooperation."[4]

 

The Advance of Technology

 

Frankly, it's difficult to know whether collaboration across the supply chain can blossom in the current business landscape. What we do know is that technological advances can augment human decision-making and improve intra-organizational collaboration between human decisionmakers and thinking machines. Hanlie Smuts, a professor in the Department of Informatics at the University of Pretoria, explains, "Most organizations have more data than they know how to exploit effectively, and to a large extent, there is still gap between impact and big data. ... A key opportunity to achieving this impact is to create valuable knowledge from big data, and consequently enabling winning strategies in a competitive world."[5] She adds, "Researchers found that, to create valuable knowledge from big data, at least four enablers must be considered." Those enablers are:

 

● Data Analytics. "Data analytics is the process of exploring datasets in order to draw inferences from the information contained in the datasets." ● Data Management. "Data management as an enabler is the practice of collecting, keeping and using data securely, efficiently and cost-effectively." ● Data Platform. "The enabler data platform denotes an integrated technology solution that enables data management for strategic business purposes." ● Data-driven Ethos. "Data-driven organizational ethos is an organization’s commitment to gather data that can foster conclusive decision-making concerning all aspects of the business, ensuring it becomes part of the organization’s competitive advantage." Smuts concludes, "From an organizational perspective, decision-makers are now empowered to derive actionable insight based on the analysis of big data datasets through advanced analytics." Every supply chain professional knows today's supply chains are complex. Most of them welcome artificial intelligence-powered solutions that help address that complexity. For example, the Enterra System of Intelligence™ is a cutting-edge approach that combines the power of a human-like reasoning and trusted generative AI with glass-box machine learning and real-world optimization to drive intelligent decision-making and fuel business growth. The Enterra System of Intelligence is a set of integrated cross-enterprise business applications that break down traditional organizational siloes between marketing, sales, supply chain and planning functions. This unique System of Intelligence acts as an autonomous “brain” within an organization, enabling real-world optimization and decision-making across the value chain at market speed, with the subtle judgment and expertise of an organization’s best subject matter expert or data scientist. The system persists the accumulated business logic, ways of working and practices of an organization in a proprietary-for-the-client Generative AI that allows for leverage across business functions, geographies, and lines of business.

 

Concluding Thoughts

 

The staff at SCMDOJO predicts that, in the future, supply chain professionals will lean heavily on automated decision-making. They explain, "The next wave of AI innovation is here: autonomous AI agents. Agentic AI refers to proactive, self-learning systems capable of making independent decisions, solving problems, and continuously adapting to changing conditions. This leap in AI capabilities is revolutionizing industries, and AI-driven supply chain management is no exception. ... Supply chains are dynamic and complex, requiring continuous decision-making across multiple functions, from procurement and inventory management to logistics and demand forecasting. Agentic AI takes this a step further by enabling autonomous supply chain systems. They can proactively identify risks, optimize processes in real time, and even negotiate supplier contracts without human oversight. These AI agents leverage real-time data, predictive analytics, and generative AI to enhance resilience, reduce costs, and improve overall efficiency in AI-driven supply chain resilience."[6] People will be rightfully skeptical about decisions being made "without human oversight"; however, there myriad routine, rules-based decisions that should be made autonomously so that humans can concentrate on non-routine decisions.

 

Gonzalez is probably correct that looking for a single silver-bullet solution for today's complex supply chain challenges is a fool's errand. He concludes, "Simply put, many of the problems that persist in supply chain management boil down to a lack of trust between people, functional groups, and trading partners, and because every company continues to look out only for itself instead of taking a truly collaborative approach focused on creating shared value across their supply chain network. I don’t know how to solve this trust and collaboration problem, ... but I know that technology alone won’t do it." That's what makes supply chain decision-making so challenging.

 

Footnotes [1] Adrian Gonzalez, "The Supply Chain Problem $100 Million and Smart Executives Can’t Solve," Talking Logistics, 11 December 2024. [2] Naveen Poonian, "Overcoming Obstacles to Supply-Chain Collaboration," SupplyChainBrain, 4 November 2019. [3] Lisa Walker, Vijay Natarajan, and Simpson Selwyn, "Harnessing the power of supply chain collaboration," Deloitte Blog, 7 March 2024. [4] Gurram Gopal, "The Clouds Are Lifting: The Future of Supply Chain Collaboration," SupplyChainBrain, 3 February 2025. [5] Hanlie Smuts, "Collaboration of human and machine for knowledge work," IT Web, 30 March 2021. [6] Staff, "Agentic AI in Supply Chains: The Future of Decision Making," SCMDOJO, 16 February 2025.