Metrics Optimization Modeling Procurement 
Supply Chain Shaman
JANUARY 7, 2025
Each supply chain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions. To build an outside-in model, and use new forms of analytics, we must start the discussion with the question of, “what drives value?” My advice?
Supply Chain Shaman
APRIL 18, 2023
For organizations layered in functional metrics and driving a cost agenda, this is a tough nut to crack. During the pandemic, companies struggled with planning systems turning off the optimizers, and using the technology as a system of record. Steps to Take Here are three steps to take: Adaptive Modeling. Higher variability.
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Logistics Viewpoints
MAY 19, 2022
Supply chain optimization has also improved in significant ways that can address these trade-offs better than before. Analytical techniques like linear programming can create the mathematically “optimal” plan, but these methods must be implemented well to avoid creating other challenges. Supply chain optimization for today’s realities.
Supply Chain Shaman
JANUARY 2, 2023
In traditional advanced planning applications (APS) for a manufacturing company, the forecasting model’s role is to generate a time-series forecast in the tactical horizon (outside of lead time). (An In traditional planning taxonomies, the tactical forecast is modeled, and the operational signal is calculated using consumption logic.
Logistics Viewpoints
APRIL 6, 2023
Procurement and Supply Chain Management are essential functions that can help companies navigate these challenges, but they are often siloed and operate in separate departments. Their metrics are often misaligned as well – supply chain focuses on service and procurement focuses on the cost of acquiring materials and services.
Logistics Viewpoints
JULY 23, 2024
Without sufficient data, AI models can’t uncover meaningful patterns, make accurate predictions, or provide valuable insights for informed decision-making in complex and dynamic environments. At the same time, feeding your AI models too much data can also be a problem. Data is the lifeblood of AI in the supply chain.
Supply Chain Shaman
JUNE 6, 2013
Closing the gaps happens when there are aligned metrics, clarity of vision and aligned planning processes. This includes optimization and discrete event simulation. Metrics Alignment. Most companies operate well within functions, but struggle to build strong horizontal processes. They lack cohesion.
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