Designing a supply chain network to optimize profit is not simple. There are many complex interactions to consider. These include tradeoffs between:
Other forms of analytics help supply chain managers determine reasons for past performance or predict future trends. But only prescriptive analytics offer optimization capabilities needed to determine the right decisions. Here are six steps for designing supply chain networks to optimizing profits.
The first step is defining your supply chain objectives. These include answering questions like:
These questions focus attention on what you want the supply chain to achieve, not how you intend to achieve it.
They purposely exclude questions like where, when, and how because those form part of the solution.
It's essential to understand your constraints. A constraint is a factor that limits the ability to do something directly or indirectly. They're easily overlooked, but ignoring constraints results in solutions that aren't feasible or practical.
Obvious constraints include financial and budgetary constraints or production capacity limitations. Less obvious ones include regulatory restrictions and interdependencies.
When considering the constraints, look beyond the supply chain if possible. Consider production and sourcing constraints, even unique tariffs, duties, and geographical limitations that impose restrictions on what can be done within your network.
Once you've determined constraints and objectives, prepare a model of the supply chain network. We're referring here to mathematical supply chain modeling, not traditional simulation modeling methods that only utilize predictive and descriptive analytics. The model needs to reflect supply chain nuances and include limits and constraints.
Ideally, it should be a complete digital representation of the value chain at large, often called a digital planning twin. For example, a digital supply chain twin that's being used for supply chain network optimization should include any pieces of the business that are impacted by or could impact the future resilience of the network, such as:
Using the optimization capabilities of prescriptive analytics, perform scenario analysis on your supply chain digital twin to evaluate different options as they relate to your network. Scenario analysis can answer questions such as what are:
These questions are measured against your business objectives and in particular, the goal of optimizing profit. Use supply chain optimization to determine the best configuration for each element of your supply chain design.
A common question is whether to model part or all of the supply chain. There's no easy answer to this, especially when starting out. If, for example, you only model procurement, you can more quickly get the model up and running. But on the other hand, it can't provide end-to-end answers, nor can you use it to optimize the entire supply chain. This means you won't optimize profit.
Don't forget to consider supply chain resilience. By this, we mean the ability to keep the supply chain running during extreme disruption. Many organizations made the mistake of assuming the risk of a pandemic such as COVID-19 was minimal. Their carefully crafted supply chain optimization processes were found wanting during the national and global disruptions resulting from steps taken to prevent and reduce infection.
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