How can companies determine the underlying causes of supply chain disruptions? originally appeared on Quora: the place to acquire and share knowledge, allowing people to learn from others and better understand the world.
Answer by Joel McKelvey, Vice President of Product and Partner Marketing at Sisu dataon Quora:
Supply chain disruptions have become increasingly common due to the ramifications stemming from the pandemic and the e-commerce boom. A recent Harris Poll conducted on behalf of Sisu found that a majority of US consumers (89%) have purchased gifts online in the past year, and nearly 3 in 4 (71%) have encountered supply chain issues. And when it comes to supply chain issues, those who encountered these issues faced delivery delays (64%), order processing delays (49%) or orders missing in transit (31%). %).
When you are following a supply chain issue and dealing with disappointed customers, it is difficult to quickly and accurately identify what is the exact cause. It’s a problem people face at every stage of the supply chain (manufacturing, transportation, order fulfillment, etc.).
At Sisu, we know those answers are in an organization’s data. However, technology-driven industries and businesses spend a tremendous amount of time setting up the infrastructure to ensure their data is usable. Tools like Snowflake and Databricks help speed up the process of collecting and consolidating data, but the real problem is the colossal amount of time data analysts spend combing through the overwhelming amount of data points to figure out why. an order was damaged en route. the consumer.
Data doesn’t necessarily drive organizations to the point of making a decision that drives a resolution like changing carrier partners or updating packaging processes. A myriad of businesses face the “last mile problem,” meaning they struggle to get the right information to the right people at the right time to drive impactful change. Once a company is able to identify the “why” behind supply chain disruptions, it can then help those who work on the manufacturing floor, run the shipping department or process orders to make better optimization decisions.
Diagnosing symptoms from data is not an easy task – business decision makers don’t have actionable data in front of them and must wait days or even weeks for their analyst teams to manually review data and derive information from it.
This is where a tool like Sisu can be a company’s greatest asset. Sisu’s Business Intelligence Engine guides decision-making by putting the power of artificial intelligence and machine learning in the hands of data analysts. While legacy reporting and BI workflows are optimized for predefined aggregated datasets, which leave large and complex data underutilized, Sisu helps data analysts quickly and comprehensively analyze billions of data points. of data to bring out statistically significant and relevant information, while eliminating unnecessary noise. With Sisu, analysts and decision makers can quickly uncover what matters most about their burning questions with fast, comprehensive, and actionable insights.
Sisu’s business intelligence engine helps companies extract meaningful insights from their supply chain data. Customers were able to track product damage through bias, slice data based on a product’s size and weight, and compare warehouse, shipping, and receiving vendors, which helped determine that some are better at handling large orders than small ones. With Sisu, customers can also compare packaging solutions for large and small items, allowing them to better structure their logistics contracts with suppliers by having a better understanding of the biases to attribute to which suppliers.
That question originally appeared on Quora – the place to acquire and share knowledge, allowing people to learn from others and better understand the world.