Meta Robinson

Supply chains are more volatile and interconnected than ever, but many planning processes still rely on disconnected systems, manual analysis, and spreadsheet-based interventions. This white paper explores how network optimization, supported by advances in optimization technology, workflow design, cloud computing, and AI, can help planning teams evaluate cross-functional trade-offs, respond faster to change, and move from static plans to continuous, decision-driven supply chain planning. Inside the White Paper: – Why traditional planning systems and network optimization evolved separately, and why that separation limits decision quality in today’s supply chains. – How network optimization helps evaluate cross-functional trade-offs across sourcing, production, inventory, transportation, fulfillment, service, cost, and capacity. – Why continuous network optimization is different from one-time strategic modeling, and how it can support recurring tactical and operational planning decisions. – How AI and configurable workflows can make optimization more usable for planners without requiring them to become modeling experts. – How planning systems and network optimization can work together in a feedback loop that improves decisions over time. Click here to download

Brought to you in partnership with the Journal of Business Logistics   Companies are investing heavily in safety technology. Trucking fleets now rely on cameras, collision warnings, lane alerts, adaptive cruise control, and automated braking to reduce crashes and protect drivers. That investment assumes a straightforward outcome. More technology should lead to safer behavior. It does not always work that way. Research in the Journal of Business Logistics shows that the same technologies designed to improve safety can also undermine it. The difference comes down to how drivers experience the tools and how managers use them. The problem is not the system. It is the interaction around it.   How safety technology fails in practice The study points to two common patterns that show up across fleets. The first is avoidance. Some drivers ignore or disable alerts. They cover inward-facing cameras or override automated features. This behavior shows up when the system feels intrusive or disconnected from real driving conditions. Frequent warnings and false alarms create frustration. Experienced drivers, in particular, may feel the technology challenges their judgment rather than supports it. When that happens, drivers do not adapt to the system. They route around it. The second pattern is…