MIT Center for Transportation & Logistics Research has found that how supply chains are designed is responsible for most supply chain problems. Traditional supply chain design has focused on standardization and efficiency, which lead to economies of scale, centralized distribution and just-in-time, lean manufacturing. However, the rise of trends like globalization, outsourcing and e-commerce have placed significant strain on supply chains. In a world where we have both delocalized production and same-day delivery, our global supply chain model has been stretched too thin.
Despite this, companies are not rethinking their legacy models: We’re still using the same basic paradigms of efficiency and cost minimization when designing our supply chains.
The deficiencies we see in supply chains today are due to outdated methods and approaches to supply chain design. We need to use a more holistic approach to succeed in today’s business environment:
- Move from a cost- to a value-driven approach. Supply chains are not only a cost center but a driver of competitive advantage. Rather than focusing on cost minimization, companies should focus on long-term value creation. Given the current competitive environment, it is absolutely crucial to consider the interaction between supply chain design choices and revenue management.
- Move from a siloed to a collaborative approach. More stakeholders need to be involved in the process. Supply chain design should no longer be confined to the logistics department; it should include other functions, like sales, finance, and marketing.
- Move from an event-based to a continuous design approach. Traditionally, we redesign our supply chains every few years in response to some specific event, like changes in the market or corporate strategy. Given the pace of change today, this approach is obsolete. We need to continuously monitor our supply chain design and adapt it.
- Embrace the power of data and analytics. Traditionally, supply chain design tools used aggregate data and were constrained by computational power. Now, however, we have the ability to use new methods like machine learning and network science to analyze highly complex supply chains. This allows us to have a much more accurate understanding of our supply chains, incorporating (1) more granular data reflecting real-life operations, (2) tactical and operational planning decisions that were typically left out of supply chain studies, and (3) a much larger set of future scenarios, allowing us to make supply chains more resilient.
In the near term, a lot of companies are aware of the problems, but they don’t necessarily have the solution yet. Supply chains are at the center stage of corporate strategy and there is a lot of excitement and a lot of experimentation happening, particularly around new products and services enabled by new designs. And, thankfully, the requirements to incorporate risk and uncertainty are now much clearer. But this experimentation is not always supported by a data-driven approach, and companies have largely not readjusted their organizational structures to allow for these new design principles.
Outlook: The next few years will allow us to identify winning strategies. An intentional, analytics-driven approach will be key. Specifically: Striking a balance between customer-centricity and global operations, leveraging new business models and collaborative relationships to build in design flexibility , accounting for risk and uncertainty in a more structural manner, and setting up organizational structures to account for a link between supply chain design and other decision-making.
