How Snowflake helps optimize the Supply Chain by unlocking the data capabilities
How can data help supply chain?
A successful Supply Chain ensure keeping its customers satisfied and maintains steady profitability. In today’s global business era, retailers and manufacturers use data to improve the supply chain for a competitive edge. Manufacturing companies ranging from hardware tech to automotive have been interdependent on well-timed supply chains to accelerate time to market and minimize storage costs. Retailers, online and traditional businesses rely highly on demand-based supply chains to lessen costs and boost customer satisfaction and trustworthiness.
The supply chain industry must sustain itself with a reliable flow of pertinent, precise data and have the potential to convert the data into valuable and actionable insights. We will discuss further the advantages of Supply Chain improvement and how enterprises often utilize data to enhance the supply chain using various data sources.
What is Supply Chain Management?
Supply chain management oversees the flow of goods and services, including all the related processes that convert raw materials into final products. It includes actively streamlining a business’s supply-side tasks to boost customer value and gain a competitive edge in the marketplace.
The Supply Chain Management key role in an organization is to manage the entire Supply Chain and Logistic Operations to boost efficiency and cut down costs.
Why optimize the Supply Chain?
Due to their supply chain operations, manufacturers and retailers create millions of data points. Supply chain optimization harnesses data from an organization’s systems and applications and external data sources to improve efficiency and performance. Companies that implement supply chain optimization can achieve several benefits.
Benefits of Supply Chain Optimization for Companies
Elimination of Silos:
Due to continuous data streams often stored in multiple locations, just-in-time and demand-based supply chains have made the optimization process even more challenging. Siloed data prevents enterprises from having the visibility they need to identify the cause of problems and find opportunities for further improvement. A governed, unified data repository that can manage semi-structured and unstructured data enables teams to access all relevant data for more accessible analysis.
Enables better Customer Service:
Customers have more choices and preferences, and their expectations for hassle-free fulfilment have increased. That’s especially true in competitive markets. Companies that consistently work to optimize their supply chain reinforce their ability to meet and exceed the ever-increasing customer demands.
According to a survey, more buyers want assurance that their products are sustainable and ethical. They seek manufacturers and retailers that have reduced their environmental impact and adopted ethical labour practices. Access to an accurate, complete view of your supply chain makes it easier to pursue proactive changes, such as shifting production methods to become more sustainable or pressuring a supply partner to improve labour practices.
Adapting to changes such as new competitors, supply chain disruptions, and consumer preference is vital for a manufacturer’s or retailer’s well-being. Data analysis can make anticipating changes easier and adjust your supply chain to stay competitive.
Provides Competitive Edge:
Accessing and interpreting data in real-time powers better and quicker decision-making. These capabilities give organizations a competitive edge over those focused on network design alone.
How to optimize end-to-end Supply Chain using Data
Data can transform your business’s supply chain by providing deep insights into each segment.
Many investors and executives assume that using customer data capabilities to gain an unbeatable competitive edge is no more a challenge. More customers mean more data, which, when analysed with ML tools, allows you to offer a better and more valuable product that attracts more customers. You can collect even more data and marginalize your competitors as businesses with sizable network effects do.
Segments of the Supply Chain
Operational Planning, inventory, and Sales:
The present-day supply chain optimization takes the planning process beyond conventional supply chain management by blending data from pertinent internal and external sources to create a real-time view of the critical elements moulding supply and demand. Assimilating streaming data authorizes supply chain managers to evaluate point-of-sale (POS), inventory, and production volume data concurrently to easily spot misalignments in supply and demand trends. This information helps launch new product offerings by understanding when to put products on sale to meet consumer demand.
Shipment companies were early adopters of analytics tools and techniques, allowing them to plan delivery routes, reduce fuel consumption and increase volumes of product delivery more efficiently. Supply chain analytics enables enterprises identify the best valuable mode of transportation for their products and predict how speedily consumers require them. Augmented data mining tools can help anticipate customers’ availability at home, thereby reducing the number of delivery attempts.
Anticipating supply disruptions and adjusting before problems influence production is vital to successful operations. Supply chain analytics enables enterprises to identify and flag irregularities in supplier delivery patterns. Another application of big data to the sourcing process is the trending data analysis on at hand labour strikes, critical weather, wildfires or financial insolvency that may negatively impact a supplier’s capacity to deliver on time. Being able to forecast and comprehensive contingency planning ahead of time can help businesses maintain consumer product fulfilment and achieve production goals.
Point of Sale (POS):
Retail businesses occupying physical spaces slowed down than their online counterparts to adopt augmented data analytics to boost sales. With POS data trend analysis, retailers can more precisely predict which products to display in high-traffic areas and how they increase sales.
Manufacturing & Warehousing:
Appropriate data usage during the manufacturing stage helps enterprises sustain exceptional product standards. The real-time quality analysis using integrated camera systems and accurate measuring devices can ensure that every production unit meets quality assurance standards before the shipment is made to retailers or consumers. Determining and fixing issues on the manufacturing line in real-time avoids production reruns, saving costs.
Analytics in warehouse management helps businesses optimize inventory management, streamline shipments, measure workforce productivity, and improve several other warehouse aspects. Depending on the data availability, collecting data from a reliable source to generate insights is crucial. The real-time data reports help the leadership team track key warehouse KPIs and make changes where applicable.
How Snowflake help Supply Chain with its increasing data size
As per IDC, the total size of data globally is expected to reach 163 zettabytes by 2025, expanded by the increasing numbers of devices and sensors.
Factors influencing the growth of Data Warehouse requirements for supply chain companies include data mining demand for BI and Data Analytics, disparate data storage, cloud technology expansion in data warehousing, historical customer data for better user experience, and more.
Snowflake as a unified cloud-based data warehouse platform provides fully managed solutions to businesses, offering data scalability for the enterprise’s growth and flexibility to access and extract data seamlessly with speed and efficiency.
Snowflake is a cloud data warehouse that can store and analyse your business data in one unified place. It can automatically scale up/down its compute resources to load, integrate, and analyse data.
Why choose GTL for Snowflake?
GTL is your one-stop Data Warehouse solution that helps you unlock your business data potential with an end-to-end guided evaluation of the Snowflake platform with relevant case studies.
We are one call away from migrating and unifying your siloed data, enabling work globally with seamless collaboration across multiple clouds, and creating potential revenue streams by finding new customers on Snowflake Marketplace.