This is not another article on supply chain resilience, flexibility, and risk. These topics are still important and I am sure there will be articles and research done for decades on how the pandemic, geo-political events, and extreme inflation have impacted how manufacturers and we as consumers view supply chains. I want to take us back to the discussion that was growing in pockets pre-pandemic and has started to show up again in recent articles and research—the supply chain as a competitive advantage.
When defining the supply chain as a whole, it is not just a single firm and their decisions that are involved; the entire chain is competing. This implies multiple tiers of suppliers through production to the end customer, and includes the disposition of material at the end-of-life for some products and services. This may include hundreds of organizations with the sourcing of material, transformation, and delivery on to the next link in the chain. Historically, and oftentimes today, each entity still isolates their decision-making and analytics, suboptimizing the end to end chain, at the expense of suppliers or customers, by trying to focus only on their part in the ecosystem.
New regulations, frequently spurred by Environmental, Social and Governance (ESG) requirements, are forcing companies to develop greater visibility and traceability within their supply chain ecosystem. This is often a good first step in understanding the partners, especially those outside of tier 1 suppliers, transportation providers, and direct customers, but not what is needed for competitive advantage. This requires visibility and collaboration from most—if not all—of the elements in the chain to understand disruptions, plans, resources, demand, quality, and inventory with capabilities to drive economics for both tactical and strategic decisions. This does not imply that firms give up control or there is open access to their proprietary data assets, rather a highly secure, flexible, and scalable environment is essential to enable ecosystem firms to collaborate effectively.
Supply chain collaboration can be found across partners in balancing inventory and transportation between production and customer shelves to meet changing demand and uncertain supply. Another example is in how key material suppliers provide timing and specification information to production sites to proactively adjust schedules and process parameters.
To go beyond these and drive a competitive advantage, broader collaboration—sharing of data—to identify bottlenecks, cost changes, resource capacity constraints, disruptions in logistics, and predict customer product availability at any stage of the supply chain, in real-time, is the new normal in today’s ever changing world. The next step is getting visibility of this ecosystem and the layering of analytics to move from reactive to predictive and prescriptive models across multiple firms’ supply chains.
An example to consider is the aluminum to automotive supply chain. The supply chain process starts with bauxite mined for aluminum, going through a smelting process, and on to another supplier for casting. Other manufacturers in the chain will combine different parts from multiple suppliers into a subassembly that goes to an OEM for final assembly. The vehicle is then shipped, sold, and goes through years or decades of servicing and use before its end-of-life, where the goal is to recycle the aluminum used in the vehicle. To view this complete chain and support decision-making to reduce supply chain risk requires a number of internal and external data sources, including supplier events, vehicle material lists as they change over time (Time Phased BOM), commodity price changes, partner ESG scores, vehicle (asset) usage data like GPS, or operator profiles to improve customer experience.
Most manufacturing companies need to apply internal and external data sources together to form a complete picture of their ecosystem and enable supply chain resilience. If you are not sure where to start, look at the data you are currently accessing or purchasing from external sources and determine if that is being integrated into the analytics process or just reported in spreadsheets. Next, evaluate the types of ERP data (inventory, goods issue, available to promise, forecasts, etc.) that would improve decision-making and start working with key suppliers and customers to identify mutual benefits for collaboration.
Starting the journey is often the most difficult part; many companies are still focused on integrating their internal data and establishing governance, quality controls, and change management processes. Creating a roadmap with clear objectives and the steps that help drive value from early stages are all keys to success. Developing the complete supply chain into a competitive advantage requires collaboration from multiple stakeholders, both internally and externally, as well as access to data and analytics at the speed and scale needed to enable broader decision-making.
Snowflake empowers manufacturers to collaborate with partners, suppliers, and customers in a secure and scalable way, driving greater agility and visibility across the entire value chain. To learn more about how you can power supply chain visibility with Snowflake visit https://www.snowflake.com/guides/evolving-supply-chain-management-data