Experts Explain: Why Visibility Alone Is Not Enough in WMS and TMS

Warehouse and transportation operators generate more data than ever. Yet many still struggle to turn visibility into consistent execution at enterprise scale. The core dilemma is the persistent gap between knowing what is happening and acting effectively in real time on labor shifts, exceptions, inventory issues, and operational disruptions.

Visibility Falls Short

Amy Dean of SC Codeworks replied in writing to The Supply Chainer. SC Codeworks delivers warehouse management systems focused on efficiency and real-time visibility.

Dean explained that operators now evaluate technologies based on concrete operational needs. AI conversations have shifted toward measurable value in labor shortages and decision-making. Solutions gaining traction provide real-time labor metrics, live dashboards, and actionable insights from the warehouse floor.

She highlighted one of the most common execution gaps: lack of real-time labor productivity visibility. Many still rely on lagging reports. As labor costs rise, the ability to adjust during a shift — rather than after — has become critical. Dean added that inventory accuracy remains one of the strongest predictors of implementation success. Even advanced systems cannot overcome poor foundational data.

Amy Dean, Vice President of Operations, SC Codeworks, “Inventory accuracy remains one of the strongest predictors of implementation success.”

Breaking Silos and Change Management

Bruce Shields of ABS Tag & Title pointed to the limitations of visibility alone.

"Companies have invested significant capital in technology over the last several years, only to find that visibility does not fix execution challenges," Shields said. Success depends on breaking down operational silos between TMS, fleet platforms, and back-office functions such as title, registration, and compliance.

He noted that underestimating implementation complexity and change management remains a frequent gap at enterprise scale. Organizations achieve stronger results when they evaluate the total lifecycle of assets and processes rather than deploying standalone systems.

From Visibility to Orchestration

Eshaan Jain of T-Mobile (via Mphasis) described the move toward autonomous orchestration. In yard and transportation management, legacy rule-based engines often fail under volatile conditions. Jain identified contract leakage as one of the largest execution gaps at enterprise scale.

"The biggest execution reality standing out at enterprise scale is data model disconnection," he explained. Without clean mapping between legacy ERPs, WMS, and modern AI layers, even promising autonomous systems stall.

Rich Pleeth of Finmile added that operators no longer want another dashboard.

They seek systems that actively identify problems, recommend actions, and make decisions in an agentic way. AI is most effective in exception management, predictive ETAs, and dynamic optimization.

Pleeth noted that at enterprise scale, operational complexity is consistently underestimated. Integrating legacy systems accumulated over years of growth often proves harder than the initial technology deployment itself.

The experts agree on one point. Technology investments deliver limited returns unless foundational data quality, system integration, and workflow realities are addressed first. Operators that pull ahead treat orchestration as a continuous execution challenge rather than a software installation project. This gap between visibility and effective action will continue to shape priorities in the coming quarters.