Your supply chain management system: Maximizing agility
Supply chain efficiency is the cornerstone of a healthy CPG business. It can often mean the difference between leading a market and being left behind. For big companies, complexity is at an all-time high, and organizations typically need a supply chain management system that caters to geodiverse markets, some of which are undergoing extreme changes.
Analytics and data can help CPG companies achieve these objectives. Here are a few ways that businesses can optimize the agility of their supply chain management systems.
Value through insight
In the past, supply chain and enterprise companies acquired and partnered with business intelligence firms, notes Forbes. For the most part, these companies relied on their own data with pre-populated dashboards and one-size-fits-all analysis. Even though companies could access this information in near real-time, it wasn't enough.
Instead, organizations should pull data from multiple third- and first-party sources, not just from the supply chain vendor. These perspectives will add contextual details that are otherwise hidden. Forbes cites Palmer Foundry as an example, as the company uses statistical processes to analyze "external scrap," defined as damage caused by variables that are external to manufacturing. The Palmer Foundry team is using this information to reallocate resources, make workforce adjustments, modify incentives and monitor capital spending.
CPG leaders have always known that a supply chain management system can add value, explains IndustryWeek. Thanks to analytics and data, organizations can access a perspective they otherwise might not have considered. Analytics can illuminate possible process- and cost-optimization opportunities that are not otherwise intuitive. Businesses can now delve deeper into the supply chain to find gaps that can be filled to produce savings and create more efficient processes.
The cost side of the equation introduces new, untapped competitive advantages, as well. For instance, McKesson discovered that the company could move more SKUs further away from customers and adjust modes of transport to reduce costs. With this optimization, the company was able to save over $1 billion.
While other business lines have an aggregate-level view of the supply chain, few have insight into their systems' intricacies. Data democratizes this information and allows stakeholders to tap into unseen opportunities.
Emerging markets introduce new opportunities, but also new complexities. CPG leaders are operating in volatile markets with diversified product portfolios, according to Genpact. Even more challenging is the process of managing the rising number of suppliers worldwide.
Data can optimize the intersection of speed, efficiency, quality and risk. Analytics simplifies the initial screening and ongoing management processes. Through a scoring process, CPG leaders can rank-order their suppliers through multiple lenses, such as financial analysis and capability constraints.
Thanks to this data, CPG businesses can evaluate suppliers from multiple perspectives beyond pure cost. With this information, companies are well-positioned to find their ideal vendors and partnerships.
Data and analytics make the supply chain more holistic. Rather than optimizing costs, organizations can find the right balance of quality, security, safety and other relevant variables. As supply chain operations become increasingly complex with many moving parts in uncertain markets, this holistic view becomes essential.
Facing a mix of fragmentation and new global market opportunities, companies need a full and comprehensive view of their supply chains. When companies analyze available data to glean new insights, understand where complexities must be alleviated and uncover hidden patterns, they gain a new perspective and can uncover the organization's most efficient path forward.
Take the next step in sharpening your supply management process. Connect with analytics professionals to learn more about IBM's Consumer Products Industry Solutions.