Lineage is a publicly traded, global temperature-controlled industrial REIT and logistics provider, operating one of the world’s largest cold storage networks. With a footprint spanning hundreds of facilities across North America, Europe and Asia-Pacific, Lineage serves thousands of customers across food production, retail, and distribution. At this scale, managing complex, high-throughput warehouse operations and end-to-end supply chain flows requires real-time visibility and decision-making to keep the global food supply chain moving efficiently.

The Challenge

Lineage is actively rolling out its proprietary warehouse execution system, LinOS, with a goal to deploy across 250+ warehouses in the next 3 to 5 years. As LinOS scales across Lineage’s warehouse network, the volume and complexity of operational data have increased significantly, putting pressure on data science and operations teams to understand how changes to tasking algorithms impact site performance.

KPI monitoring, anomaly detection, and root cause analysis were still largely manual. Incidents were often flagged reactively by operators, trends were difficult to interpret across sites, and investigations required stitching together analysis across multiple notebooks and workflows —making it hard to quickly understand what changed, why it changed, and where to focus.

The Solution

Summation partnered with Lineage to have an always-on insights layer for LinOS, designed around how their teams monitor and improve warehouse performance. By combining site data with Lineage’s operational context, Summation generated structured, exec-ready analysis of KPIs such as pallet per hour, units per house, labor utilization, and task execution.

The platform enabled two core workflows: proactive monitoring and fast investigation. Teams could automatically surface anomalies across sites and time periods, then drill from signal to root cause using traceable analysis — without relying on manual, one-off workflows.

“As LinOS scaled, we needed a faster, more systematic way to monitor performance and investigate issues across sites. Summation helped us move from reactive analysis that took weeks to repeatable workflows to understand performance in minutes.”
— Elliott Wolf, VP & Chief Data Scientist, Lineage

The Impact

The pilot enabled Lineage to shift from reactive, manual analysis to proactive, system-driven performance monitoring and investigation. Anomaly detection across 10 sites was reduced to ~5 minutes, while anomaly investigation across those same sites was completed in ~15 minutes —significantly accelerating time-to-detect and time-to-understand.

Just as importantly, Summation created a repeatable foundation for scaling analysis alongside LinOS. As more sites are onboarded, Lineage teams can standardize how performance is monitored, anomalies are surfaced, and insights are generated — reducing manual effort while improving speed and consistency of decision-making.