The supply chain as we know it is dead. Supply chain tech has drastically shifted over decades from basic, reactive dashboards, to command centers with digital twins that help you decide what to do next, to fully autonomous platforms that make (and execute!) decisions on their own.
Gartner®' December 2025 report, "From Insights to Guided Actions: The Visibility Journey Toward Supply Chain Orchestration Platforms", maps out this evolution and what it means for supply chain leaders.
But here's what most leaders miss: none of these advanced capabilities work without the right data foundation. Most organizations simply aren’t ready.
The 4 stages of supply chain technology evolution
We feel that Gartner® breaks down the evolution of supply chain technology into four major phases:
1. Business Intelligence (Early 2000s): Organizations built traditional data warehouses using mainly structured enterprise data. BI platforms provided insights through descriptive analytics (what happened) and diagnostic analytics (why it happened). While valuable, these systems were retrospective and couldn't enable real-time decision-making.
2. Control Towers (2010s): With the rise of IoT and near-real-time data, companies deployed domain-specific control towers focused on individual functions like logistics and transportation. These tools provided visibility and alerts but remained functionally siloed. They offered "see, understand, act, learn" capabilities within their narrow scope but couldn't support cross-functional decision making.
3. Command Centers (2020s): The evolution toward command centers represented a significant leap. These frameworks connect data from multiple internal and external sources, providing cross-functional insights. Crucially, they leverage a digital supply chain twin to enable simulation, optimization, and response capabilities. However, decisions and execution still remain human-driven.
4. Orchestration Platforms (2030 and beyond): The next frontier: supply chain orchestration platforms that go beyond insights to actually prescribe and perform decisions through existing operational systems. With capabilities like knowledge graphs, generative AI, and agentic AI, these platforms will automate decision-making, rather than just augmenting it.
Why the digital supply chain twin changes everything
At the heart of this evolution is the digital supply chain twin - defined by Gartner® as "a digital representation of the physical supply chain that can be used to create plans and make decisions."
And, according to Gartner®, true digital supply chain twin must include seven essential capabilities:
- Real-time transactions and events from granular data (like ERP transactions)
- Entities, attributes, and parameters (customers, suppliers, products, and their relationships)
- Correlations and configurations between planning, transaction, and event data
- Probability distributions derived from transactional analysis
- Time-phased pegging relationships between orders, inventory, and capacity
- Targets, policies, rules, and constraints that reflect operational realities
- Supply chain visualization that makes all these layers transparent
"A digital supply chain twin is neither a set of data tables in a data warehouse (based on structured data) nor a data lake (based on structured and unstructured data), nor a single data model in an SCP/SCM suite solution."
In other words, you can't fake it. You can't build a true digital twin on top of slow, batch-processed data or fragmented point solutions. You need real-time, granular operational data that's properly associated and continuously refreshed.
The data foundation gap
Most organizations have accumulated a patchwork of supply chain technologies: ERP systems, warehouse management systems, transportation management systems, planning tools, and various point solutions. Each generates valuable data, but that data typically lives in silos.
Traditional approaches to integration - extracting data from source systems, transforming it, and loading it into a data warehouse or lake - create unavoidable lag. By the time your data is ready for analysis, it no longer reflects current reality.
This lag becomes increasingly problematic as you move up the maturity curve:
- Control towers need real-time data to provide meaningful alerts
- Command centers need connected, granular data to power their digital twins
- Orchestration platforms need real-time data to make and execute autonomous decisions
Gartner® emphasizes that "it all starts with building the foundation: a consistent data and applications architecture." Without that foundation, investments in advanced analytics, AI, and orchestration capabilities will underdeliver.
Incorta: The data foundation for the future of supply chain technology
Incorta's Direct Data Mapping™ technology delivers exactly what Gartner® identifies as essential - real-time, granular, connected operational data that can power digital twins, AI models, and autonomous decision-making.
Real-time data for real-time decisions: Incorta connects directly to your ERP, WMS, TMS, and other source systems, delivering live data without the lag that traditional ETL creates. This is the "real-time transactions and events from granular data" that Gartner® describes as foundational for digital supply chain twins.
Preserves relationships across your entire supply chain: Unlike traditional approaches that break apart your data during transformation, Incorta maintains the connections between orders, inventory, capacity, suppliers, and customers. This gives you the "correlations and configurations between planning, transaction, and event data" needed for command centers to simulate scenarios and optimize decisions.
AI-ready from day one: Advanced analytics and AI need detailed, granular transactions with full context - not pre-aggregated summaries. Incorta delivers exactly this, enabling the "probability distributions derived from transactional analysis" that Gartner® identifies as critical for digital twins.
Built to scale with your ambitions: Whether you're launching your first control tower or planning for autonomous orchestration, Incorta grows with you. Connect new data sources and expand capabilities without ripping and replacing your infrastructure - positioning you to adopt command centers, digital twins, and eventually autonomous orchestration as these capabilities mature.
Evaluating supply chain technology investments
If you're evaluating supply chain technology investments, Gartner® offers a useful lens for assessment:
Where are you today? Most organizations are somewhere between early-stage control towers and emerging command center initiatives. Few have truly integrated digital twins that span end-to-end operations.
What's holding you back? Often, the constraint isn't the lack of advanced analytics tools or AI capabilities: it's the quality, speed, and integration of underlying data. This can cause distrust in your data, and hesitation in making faster decisions.
What foundation do you need? Can you access real-time operational data? Can you associate that data across functions? Can you enrich it with external signals? If not, advanced tools will struggle to deliver any value.
How do you future-proof? Build a data foundation that supports your current needs, while enabling future capabilities. A platform that provides real-time access to all operational data, supports advanced analytics, AI, and can incorporate external data sources will serve you whether you're deploying your first Command Center or planning for autonomous orchestration.
Preparing today for the supply chain of tomorrow
Supply chain orchestration platforms are an ambitious vision Gartner® acknowledges is still "a prospective concept with considerable hype in the solution market for the time being."
Autonomous decision making and execution will require technology and organizational change: "Autonomous implementation of supply chain decisions will require reorganizing existing supply chain personas, processes, operating models, and technologies."
But organizations that invest today in modern data architectures that provide real-time, granular, connected operational data will be positioned to adopt advanced capabilities as they mature. Those that continue to build on legacy data infrastructure will find themselves constantly constrained by data lag, silos, and quality issues.
Understand exactly where your supply chain technology fits in the evolving landscape - and how to build the data foundation today you need to win tomorrow.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.
Gartner does not endorse any vendor, product or service depicted in our research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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