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From static plans to adaptive decision-making. By Will Lovatt
Traditional supply chain planning is often built on linear assumptions and rigid frameworks, particularly in manufacturing. But in an age of systemic shocks and continuous disruption, static planning is no longer enough. Leading organizations now need to shift to adaptive, simulation-driven environments to drive strategic decisions at the C-suite level. Enter digital twins: decision ecosystems that evolve in real-time, integrate AI for relevant insight, and support continuous redesign.
Rigidity with static tools
Traditional planning tools are no longer fitfor-purpose. Spreadsheets, ERP modules and legacy APS systems are often slow, siloed and overly reliant on static assumptions. They fail to reflect real-world complexity and are unable to adapt quickly to change. The result is decision latency, misaligned incentives and a growing gap between strategic ambition and operational execution across the supply chain.
Organizations are also running their supply chains based on pre-defined policies, and they are executing operations within those guardrails. While the business moves on, policy remains static, falling out of sync with the real needs of the business, and potentially causing significant and unnecessary operational friction.
Businesses should be asking themselves whether they can recognize and challenge these constraints. For example, a stocking policy may require inventory to be held in bulk in a specific location, but as demand patterns change it may be the case that this is no longer the right decision.
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