The Power of Supply Chain Analytics
In today's tough economy, companies can't afford to wait to find out that a particular plant isn't producing work orders on time or that a certain supplier hasn't been reliable. Rather, today's businesses demand real-time visibility into their supply chain to manage day-to-day operational performance. No wonder, then, that supply chain management and analytics is fast gaining recognition as a mission-critical component in any supply chain management solution.
What is the Main Need for Supply Chain Analytics?
"The need for supply chain analytics is within the top three priorities for [companies]," said Nari Viswanathan, a principal analyst at research firm Aberdeen Group. "In fact, we have found a correlation between companies that are showing best-in-class behavior toward supply chain analytics and those that are demonstrating best-in-class behavior toward operational performance."
The Importance of Choosing the Right ERP for Supply Chain Analytics
So how can supply chain analytics solutions from vendors such as Cognos, Dimensional Insight, IBM, Oracle and SAS help? For starters, the right solution can help you track your most profitable products, flag production problems, identify product quality issues, better forecast raw material needs, establish more accurate lead times to fulfill orders, highlight outstanding supplier balances and more. This is accomplished by pulling together information from disparate silos into one ERP solution including accounts payable, inventory control, vendor management and production analysis to produce an in-depth and holistic view of the supply chain — bottlenecks and all.
For example, a company may be experiencing high transportation costs. Of course, it would be easy to assume that these price hikes are a result of rising fuel prices. But a supply chain analytics tool can be used to drill down into the supply chain for a more in-depth understanding of cause and effect. As a result, a company might discover that fuel charges aren't ramping up production costs, but rather suppliers are expediting products via high-priced couriers.
"Visibility is key," said Viswanathan. "It's not enough to know that your transportation costs are rising. You need to be able to drill down and identify the real causes."
Another useful application of supply chain analytics is in creating "what-if" scenarios. For many companies, being prepared for unexpected changes requires keeping enough inventory on hand to meet monthly variations in customer supply and demand — a costly contingency plan. However, by using real-time analytics to simulate what-if scenarios, a company can assess the impact of replacing suppliers, switching from train to truck transportation modes, establishing new routes, increasing product prices and so forth.
The Power of Automatic Alerts in Supply Chain Analytics
Many supply chain analytics tools include automatic alerts. For example, if orders for a particular product fall below forecast levels, a plant manager can request to receive an alert so that the necessary adjustments can be made. But there's a flip side to receiving notification of production snafus, warns Viswanathan. "Alerts are becoming increasingly important as it becomes more difficult for companies to keep tabs on what's impacting their business," he said. "But alerts can also be dangerous. Too many alerts can create problems." After all, no one wants to receive an alert every time there's a slight modification in the supply chain. That's why Viswanathan recommends users configure supply chain analytics tools so that alerts are not just informational, but are based on production specifics.
Fortunately, supply chain analytics isn't just about gathering the nitty-gritty details of a company's production cycle. Rather, if deployed and leveraged properly, the right tool can turn data into unique insights that reduce costs, streamline operations and bolster customer satisfaction.