Build a Competitive Supply Chain Automation Strategy That Avoids Costly Mistakes

Automation and robotics adoption is accelerating. Choosing the best-fit software will keep you from falling behind. 

Having the right automation software for your warehouse environment is critical — and elusive

By 2028, 80% of warehouses and distribution centers will deploy some form of warehouse automation equipment, creating major opportunity and complexity. As MHE and smart robotics adoption grows, choosing the right software is critical. The right logistics technology drives advantage; the wrong choice risks delays, cost overruns and lost revenue.

Join us for this webinar: Building AI as the Foundation for Supply Chain Competitive Advantage

Learn More About the Gartner Warehouse Stratification Tool

Fill out the form to connect with Gartner and explore how to build a smarter supply chain automation strategy for your organization.

By clicking the "Continue" button, you are agreeing to the Gartner Terms of Use and Privacy Policy.

Maximize success with an aligned technology strategy

Understanding how warehouse automation software fits into your specific environment is essential to choosing the best options. Start by following these steps.

Assess the complexity of your warehouse or distribution center

Warehouse complexity is the key driver of warehouse management scale and scope. Although size may seem the most obvious indicator, other factors — such as constraints, layout and location, volume of work, cycle time throughput, adaptability, types of work, MHE automation, variability and product characteristics — also shape warehouse complexity.

Determine complexity at the facility level. Then develop an automation strategy that considers the needs of each warehouse in your network and where automation could improve operations.

Weigh automation software types by their functions

Understanding the various software types is the first step to finding the best fit for your warehouse environment. The main types include the following:

  • Programmable logic controllers (PLC) activate and manage individual devices (like conveyor controls and carousels) to ensure commands are executed. 

  • Material flow control (MFC) optimizes load handler routing, sequencing and transportation.

  • Robot control systems (RCS) or robot fleet management systems (FMS) route ISRs in the warehouse operation to prevent “traffic jams.”

  • Warehouse control systems (WCS) manage storage and retrieval by translating business transactional information into real-time automation instructions.

  • Warehouse execution systems (WES) build on a WCS’s near-real-time insight, but add business process logic to this layer.

  • Warehouse management systems (WMS) handle business transactions like inventory management and receiving, picking, packing and shipping orders. Enhanced WMS focuses on process integrity and productivity improvement.

  • Enterprise resource planning (ERP), an integrated suite of business applications, may include some warehouse management capabilities.

  • Multiagent orchestration (MAO) platforms integrate and assign work between business applications, robot fleets and other automated and physical agents.

  • Unified (or universal) control systems (UCS) are emerging applications that aim to unify control between conventional MHE systems, ISRs and other technologies.

Define your environment to guide warehouse automation software selection

Warehouse automation — and its associated software — can range from minimal to extensive. For example:

  • Simple warehouses with no WMS might use ERP directly connected to basic automation (PLCs/MHE vendor’s systems).

  • In low-automation warehouses, WMS can connect to PLCs/robots, sometimes using VDA 5050–compliant robots for basic transport without an MAO platform.

  • In moderate-complexity, high-automation warehouses with one MHE vendor, the WMS might integrate directly with the vendor’s MFC/WCS.

  • For complex, moderately/highly automated sites with one main MHE vendor, the WMS might integrate with the vendor’s WCS, ideal for new (“greenfield”) sites.

  • Complex sites with extensive automation from multiple vendors can use WMS with embedded/separate WCS for flexibility.

  • Warehouses with mixed automation maturity and brands might use independent WCS for optimized integration, but clarify accountability.

  • Highly complex or blended manual/automated environments could use WES (or enhanced WCS) for advanced orchestration and optimization.

  • In multirobot, multivendor environments, MAO platforms simplify the integration and orchestration of diverse robotics.

What to do next

By virtue of its rich data assets and highly repeatable processes, the supply chain is inevitably moving toward an AI-driven future. Leading CSCOs will pursue a two-pronged approach by delivering AI-enabled value today through narrow, practical use cases while also building the blueprints that establish the foundations for tomorrow’s AI-driven supply chain. This is critical to delivering on the mission critical priority of architecting the AI driven supply chain. 

The steps in that journey include:

  • Becoming part of the enterprise‑level AI conversation by overcoming peers’ underestimation of supply chain’s strategic role through increased AI literacy, stronger cross‑functional competencies and partnerships that drive joint‑win deployments.

  • Building a supply chain AI roadmap that balances long‑term transformation and near‑term ROI by assessing AI maturity, identifying and prioritizing use cases, anticipating risks and aligning investments to measurable outcomes.

  • Building an AI‑ready workforce by preparing leaders and frontline teams for the uneven impact of AI across functions, redesigning workflows, roles and organizational structures, and linking upskilling, hiring and partnering to supply chain business needs.

  • Developing an AI‑enabled trading partner ecosystem through shared data frameworks, integrated workflows and transparent governance that supports trust, collaboration and joint value creation across the end‑to‑end network.

  • Enabling AI‑driven workflow and process change by understanding how AI transforms business processes, decision making and operating models through decision augmentation and automation.

  • Establishing a robust data foundation for AI by applying AI‑powered tools to improve data quality, adopting modern architectures such as lakehouses and data fabrics, and using natural‑language interfaces to accelerate insight generation and decision support.

  • Reconciling the desired AI future state with the existing supply chain technology stack by defining integration strategies, evaluating vendor capabilities and making informed build‑versus‑buy decisions across plan, source, make and deliver.

For more on how Gartner helps drive success on this and other mission critical priorities for CFOs, speak to us today.

Supply chain automation FAQs

What are the challenges of choosing the right warehouse automation equipment and software?

The distribution environment is constantly changing. Without carefully evaluating automation options against both current and planned warehouse environments, supply chain technology leaders have often spent large sums on equipment and software that don’t flex to changing demands. This can lead to millions of dollars in wasted capital expenditure — sometimes even lost revenue.

What is an ideal approach to choosing supply chain automation technology?

Ideally, software solutions should support both highly automated and hybrid manual and automated environments. Remaining flexible in managing change — such as demographics and labor, customer demands, and emerging technologies across the warehouse environment — is also important.

Drive stronger performance on your mission-critical priorities.

Talk to Us