Rethinking planning…Start with how you make decisions

From the July-August 2025 edition of Supply Chain Management Review.

July-August 2025

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By Karin Bursa

In the evolution from enterprise supply chain management to ecosystem supply network management, each decision made results in intended and unintended consequences. Lack of visibility to the unintended consequences and context generally leads to risk and disruption.  Legacy planning systems and siloed spreadsheets simply can’t keep pace with the speed, scale, complexity, and volatility of modern global business. Most of these systems were never designed for today’s data sources and volumes—which are doubling every two years, according to IDC—nor were they built to support intelligent (artificial or human) decision-making at scale.

The leaders we work with every day are feeling that pressure: data is flooding in from internal and external sources, alerts are constant, and analysis paralysis is taking hold. Supply chain team members are exhausted, second-guessing their recommendations, and falling behind on tomorrow’s targets—all because they’re stuck using yesterday’s tools.

But here’s the good news: you don’t have to rip and replace everything. What’s needed is a smarter intelligence layer that connects and augments the systems you already have. Decision Intelligence is that layer — weaving together data and decisions across ERP, supply chain planning, transportation, warehouse, and operations execution systems—turning siloed information into synchronized, real-time action.

Why decision intelligence now?

Decision intelligence (DI) is not a buzzword. It’s a business imperative.

It’s the evolution of how supply chains operate — a shift from analysis to action. DI leverages real-time data, AI, and process automation to continuously optimize decisions, helping your team respond faster, reduce risks, and act with confidence.

Gartner defines decision intelligence as “the practical discipline used to improve decision-making by explicitly understanding and engineering how decisions are made, and how outcomes are evaluated, managed, and improved by feedback.”

Instead of spending hours analyzing what happened last week, DI empowers your team to simulate what could happen tomorrow—and recommends the best action to take in real time to achieve your business goals.

By 2027, 50% of all business decisions will be augmented or automated by AI agents, according to Gartner (Source: Gartner Market Guide for Analytics and Decision-Making Platforms for Supply Chain, 14 January 2025). And for supply chain leaders, the curve is steeper. A recent MIT Sloan/BCG study found that 89% of executives believe AI will be a key competitive differentiator within the next five years.

AI enables us to evaluate massive, complex data streams while providing us with the context to anticipate the cascading impacts (intended and unintended) of decisions across the global ecosystem supply network — avoiding the trap of solving one problem while creating several more…unintended consequences.

And yes, AI is “data hungry.” But when properly trained and fed, AI doesn’t just automate — it elevates. AI agents work around the clock to analyze patterns, make recommendations, simulate alternatives, and, in some cases, take action autonomously.

Key pillars of decision intelligence

• Data-driven decisions. Real-time, historical, structured, and unstructured data fuels smarter, more holistic insights both internal and external.
• AI and automation. Applied logic and machine learning reduce manual effort and accelerate execution.
• Context-aware intelligence. Decisions account for business goals, constraints, and operating environments.
• Scenario planning. Simulations evaluate trade-offs and outcomes before action is taken.
• Continuous learning. Each decision fuels and initiates a feedback loop, constantly improving future choices.

Decision intelligence repositions humans as “decision orchestrators”—designing how decisions are made, with AI executing and optimizing them at scale.

Decision intelligence spans three levels.

• Decision support (human in the loop): AI delivers insights and scenarios. Humans decide.
• Decision augmentation (human in the loop): AI recommends and explains; humans validate.
• Decision automation (human out of the loop): AI makes and executes decisions autonomously with auditable process automation and control.

The challenges we see most often

Across industries and regions, we hear the same issues:

• “We can’t see across silos — the full picture is missing.”
• “Our data isn’t real-time or at the right level of granularity.”
• “We make decisions that conflict across departments and make collaboration impossible.”
• “Our planning cycles don’t align with the speed of disruption.”
• “We’re buried in alerts, but don’t know what truly matters.”
• “Our teams spend more time gathering data than acting on it.”

The fallout? Long days. Slower responses. Risky spreadsheets. Reliance on tribal knowledge. And constant second-guessing.

Let’s talk about spreadsheets. A 2022 McKinsey study found that 73% of supply chain executives still rely on spreadsheets to manage planning—and the Corporate Finance Institute estimates the error rate in spreadsheets to be as high as 88%. That’s a staggering risk when you’re making multi-million-dollar decisions. No wonder leaders are racing to embrace AI and Gen AI—not just for analysis, but to ask smarter questions, detect anomalies, and prescribe next steps instantly.

What’s changing: From analysis to action

New platforms are emerging that fundamentally rethink how decisions are made and executed. These aren’t just dashboards or alerting tools — they’re decision engines, purpose-built for supply chain agility, performance, and resilience.

And perhaps most importantly, decision intelligence does not replace your existing systems—it enhances them. Decision intelligence unlocks the data hidden in your ERP, TMS, WMS, and APS solutions, and orchestrates decisions across them so each action is informed by a broader operational and strategic context. Further, decision intelligence identifies new data and sources that can be leveraged to facilitate ecosystem network collaboration…internally and externally.

These innovative platforms combine:

• cloud-native, hyper-scalable architectures with no-schema flexibility;
• low-code/no-code extensibility to adapt fast without overhauling infrastructure;
• digital twins to simulate end-to-end ecosystem and enterprise network impacts;
• agentic AI that dynamically reasons, recommends, and acts;
• prescriptive guidance that is explainable, traceable, configurable, and auditable; and
• event-driven and ad hoc analysis—not just scheduled planning runs.

And critically, they enable human oversight at scale. AI manages and leverages the repeatable, the routine, and the real-time—while your people focus on the strategic, the nuanced, and the innovative.

Resuscitating S&OP: Is it dead?

Some ask if S&OP is dead. My answer? No—but it needs a serious reboot.

Traditional S&OP is often too slow, too rigid, and too disconnected from the realities of execution. DI does not replace planning—it makes it better… dynamic, real-time, and cross-functional. It integrates and enables demand sensing, supply response, inventory optimization, and risk management into one integrated flow of intelligent (and, collaborative) decision-making.

This is not about killing S&OP. It’s about enhancing and leveraging it to finally become what it was meant to be: a framework for automated or autonomous decision-making support with visibility and context to respond to cascading consequences; especially, unintended ones.

What happens when you get it right?

When companies embrace decision intelligence, they see tangible results.

• Inventory is optimized, reducing working capital and increasing service levels
• Response times drop from days to minutes.
• Teams shift from reactive to proactive, focusing on strategy over scrambling.
• Decisions become explainable and consistent, not gut-based guesses.
• And most critically: your supply chain becomes a competitive advantage.

According to Gartner, companies that excel at decision intelligence outperform peers in operational efficiency and customer responsiveness by more than 25%.

Are you ready to lead the shift?

If your organization’s leadership is still trying to scale tomorrow’s supply chain with yesterday’s technology, it’s time for a new approach.

Decision intelligence does not replace your existing systems — it makes them exponentially smarter. It unlocks their data, orchestrates decisions across functions, and ensures supply network decisions are aligned with your broader business strategy.

It’s time to unlock the full potential of your data, your people, and your operations…extending relationships throughout the enterprise and ecosystem supply network. Because better, faster, smarter decisions aren’t just possible. They’re essential. And they are available now.

About Global Links

Global Links appears in each issue of Supply Chain Management Review. Richard J. Sherman, retired guru of SCM, is the Global Links column editor and collaborator. If you are interested in participating in the column, he can be reached at [email protected].

About the author

Karin Bursa is the CEO of NIRAKIO, LLC and can be reached at [email protected].

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