In a prior Supply Chain Matters posting we shared our Ferrari Consulting and Research Group’s major themes as to what industry and global supply chains should expect in 2022 and beyond.
We stated that the supply chain challenges that occurred in 2021 are not going away any time soon and will linger well into 2022 and in some areas, will likely spill over to 2023. Elements of high uncertainty remain, especially in the potential emergence of new Covid-19 variants such as Delta, Omicron or other variants.
There are growing concerns relative to building inflation or higher interest rates among economies which will weigh in on supply chain investment decisions. Thus, C-Suite discussions will center on whether to take a conservative, aggressive or risk balanced stance in needed investments and transformational needs.
The mission for businesses and their supply chain teams is 2022 and beyond will be in seeking ways to restore enhanced agility, resiliency and reduced risk factors across supply chain mission critical processes. A further reality is that 80 percent of eventual supply chain costs are a product of the supply chain structure, hence the need for continual and ongoing analysis.
The theme for 2022 is therefore one of Reexamination in a number of areas.
In the area of strategic materials and production sourcing, our prediction is that businesses and their supply chain teams will have to reexamine existing sourcing and customer fulfillment strategies. Decisions will have to weighed for either restoring more direct control of material flow that is aligned with servicing key regions of product and customer demand. Other needs will be in assessing and mitigating risk or adding more overall supply and fulfillment resiliency.
These factors will include supply chain strategic or tactical network strategy, deployment and decision factors. Analysis and decision-making could relate to existing vs. alternative options in materials sourcing, or the feasibility and impacts of moving sourcing to domestic or near-shored options. In areas of operational customer fulfillment clusters or networks, analysis would involve multi-channel inventory pooling or tired level staging. Each analysis has cost, service level and risk mitigation factors that must be quantified and weighted, utilizing supply chain network design techniques.
Evolution of Supply Chain Network Design Technology
The evolution of supply chain network design practices and methodologies began several decades ago with consulting firms and dedicated operations research teams within large companies. Back then, design models were complex and were developed by mainframe-based software approaches in order to have the computing and data management horsepower to perform a thorough analysis. Supply chain designs were reevaluated periodically, often taking weeks to develop, in order to respond to significant shifts in demand driven by new products, shifts in required customer service levels or merger and acquisition events that required end-to-end supply chain analysis.
The technology then evolved to include the presence of a packaged application that enhanced added compute power on the desktop to solve basic supply chain design problems related to cost to serve, customer service level or supply chain wide cost reduction opportunities. Users remained mostly operations research or specialty consulting firms, and the use cases remained singular event driven. Over time, select analyst or planning individuals among a company’s supply chain management teams became users of the technology as a means to analyze problems posed by business executives or sales and operations planning teams.
During a period of supply chain technology consolidation, many of these software applications were acquired either by ERP providers, optimization tools-based providers, or by best-of-breed supply chain planning software firms, who began leveraging the technology as an adjunct to other planning, procurement sourcing, inventory management or analysis of overall supply chain optimization processes.
Despite continued advancements in software engineering, in-memory, and visualization technologies, use cases for supply chain network design tended to stay in the domain of the supply chain network analyst, often residing in a center-of-excellence services model. The software remained leveraged for periodic analysis and directed tasks related to supply chain planning and longer-term decision-making. There tended to be a disassociation with operational fulfillment or logistics data and decision-making processes, but that has changed of-late.
Increased geopolitical and tariff risk factors, the existence of global-wide pandemic, a consequent explosion of online fulfillment preferences by B2B customers and consumers, along with noticeable changes in weather patterns leading to more severe storms and climate related events have resulted in a multitude of industry supply chain impacts. The notions of reexamination now require ongoing and continual analysis of product demand and supply networks and their impacts to key operational and business outcomes. They now must include all levels of data, planning and operational in scope.
A New Breed of Supply Chain Network Design Technology
Evolving information technology and data analysis capabilities are resulting in the opportunity for a new generation of supply chain network design analysis and decision support needs. They include:
- Cloud-based serverless architecture utilizing highly scalable Graph database technologies that are currently deployed today to support social media and interactive platforms. Graph databases provide analysis and results in an order of magnitude quicker than previous iterations of network design.
- Predicated on gaming technologies in providing continuous solvers supported by interactive graphics and layering, linked by drag and drop design tools that can support near real-time decision and team-based collaboration needs.
- Streamlined modeling techniques that make the creation and iteration of models accessible to application users who do not have extensive operations research and data science backgrounds.
- Built-in support for real-time access to needed data related to facility, transportation, logistics, lead-time or other data that can reduce the overall effort required in building interactive supply chain models.
- Serving as the basis for augmented visibility and decision-making capabilities such as supply chain control towers applied to planning and operational execution.
- Augmenting management of supply chain configuration with analysis of carbon and sustainability footprint impacts.
The impact is a tool that can support faster and more responsive supply chain network modeling which can be complementary to and an extension of existing integrated business or sales and operations planning processes, multi-echelon inventory deployment and optimization analysis, or demand and supply network scenario and simulation modeling.
One example of the availability of this renaissance of supply chain network design analysis comes from Starboard Solutions. This technology provider was founded on the principle of making supply chain design fast, powerful, and catered to the needs of supply chain leaders and their respective team leaders.
The company launched its Starboard Navigator in 2016 on the basis on decades of experience in methods, techniques, and technologies used to re-design of supply chains among multi-industry settings. Starboard now has over 1400 users across 70 customers representing Auto, Consumer Goods, Retail, Industrial Products, Consulting, and Real Estate. Noted customers include Porsche, Deloitte, CBRE, Flexe, Geodis, Miele, One Network, and Topco, among others.
Effective, responsive and timely supply chain design has always been important, and in the months to come as businesses undertake supply chain reexamination and new directions, even more so. Modern supply chain network design and analysis technology like Starboard will be the disruptive and likely more cost-effective technology that will allow industry and globally based supply chain management teams to make their product demand and supply networks more responsive and timelier to continuous business changes.
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