Balancing Complexity and Benefit to Optimize Your Supply Chain
June 3rd, 2012 3:15 pm Category: Optimization, by: Alan Kosansky
Supply chain managers are tasked with making the critical decisions to improve supply chain operations by taking costs out of the system while improving customer service and profitability. The best managers rely not only on their experience but also on data-based decision-making. Making the best decision to minimize supply chain costs and maximize profit requires accuracy in your data.
However, don’t confuse accuracy with precision. Too many decision makers throw out the baby with the bath water when they shun data based decisions because the data does not precisely reflect the detail of their operations. Wise supply chain managers and analysts understand that for many decisions, aggregated and/or averaged data can accurately reflect the cost/benefit tradeoff of critical decision and point in the direction of near-optimal decisions. For example, modeling manufacturing capability and capacity at the product family level is often accurate enough to make the right supply and demand balancing decisions. Another example: even when optimizing detailed scheduling operations within a single plant it is important to find the right level of detail to model so as to balance accurately capturing the realities of the manufacturing operations and being able to evaluate a large number of production sequencing options in order to find the optimal schedule.
Finding the right level of data detail to inform accurate decision tradeoffs while searching for the optimal decisions is an art as much as a science. It requires experience and expertise in both supply chain operations and optimization modeling.
This is my passion, so let me know what experiences you’ve had, and how you have found that balance to achieve optimal performance in your supply chain operations.