The Benefits of Flat Supply Chain Costs around the Optimum

End-to-end optimization evaluates trade-offs in the supply chain such as  that between cost and service while taking into account many constraints and factors that influence the design and flow of the supply chain. An optimization approach carries the advantage of enabling a decision-maker to understand the best business solution to reducing costs while maintaining service levels or maximizing profits within constraints

Some of the most common applications of optimization in business include supply network design and inventory optimization. Supply chain risk, revenue management, asset utilization and other analyses can be pursued in a similar fashion.

An interesting feature of optimization stated as Rule 5.2 in the book Operations Rules is that supply chain cost is always flat around the optimum. This means that there are a range of options with similar cost results not just one “perfect” optimized solution. Therefore, you can select the alternatives that provide other benefits such as flexibility, sustainability and localization without impacting the bottom line.

Optimization helps you do the following:

  1. Encourage a Scenario mindset – the realization that there is no perfect answer to a question encourages a mindset of looking at various scenarios which will lead to better understanding of the trade-offs and to enhanced decision making. The process of defining and running scenarios is very beneficial to the understanding of trade-offs and innovative thinking.
  2. Tolerate Imperfect data – not all data is critical in order to make certain decisions. There are a range of options with similar overall costs, not just one “perfect” optimized solution. An optimization model is not equally sensitive to all of the input data. It does all not need to be perfect either. Sensitivity analysis that compares different scenarios will help the modeler decide which data should be precise and which data can be “good enough”.
  3. Include different forecasts – related to the imperfect data is the fact that we are planning for the future. This means that most of the data is not about today but about the future where we have less information and certainty. This includes not only demand but changes in labor and transportation costs etc. which are even harder to predict.
  4. Enable risk mitigation – to quote Operations Rules “A key challenge in risk management is to design a supply chain that can respond to unforeseen events without significantly increasing costs. The flatness around the optimum enables selection of networks that provide more capacity at little added cost.”
  5. Include sustainability considerations – from carbon footprint,  cap and trade costs to other environmental factors the decision can include these considerations sometimes at an insignificant cost impact.
  6. Local representation – example 5.2 in Operations Rules discusses a consumer packaged goods company that was evaluating its global manufacturing footprint. The optimal plan did not leave any plants in North America and Europe, creating long and variable lead times to important global markets. The analysis showed that the difference in total cost between the optimal solution with 23 plants and that with 30 plants was not very significant, allowing the company to take into consideration other qualitative factors.
  7. Allow for more flexibility – a successful strategy includes enough flexibility in the system to account for many of the factors above.

Including all of the relevant considerations is crucial to the design of a winning supply chain strategy. The final decision is not just about the one best answer.  The flatness around the optimum helps leaders  understand the trade-offs and effectively evaluate alternatives