Advanced analytics helps manufacturers extract insights from their data and improve operations and decision-making. But for manufacturers, it’s often challenging to perform analytics with ERP data. Because of the high rate of M&A activity in the industry, manufacturing enterprises often struggle with multiple ERP instances. A fragmented resource planning system causes data silos, making enterprise-wide visibility virtually impossible. And in many ERP consolidations, historical data from the legacy system is lost, making it challenging to do predictive analytics.

At Snowflake, we often see manufacturing companies with siloed ERP data environments struggle to answer critical business questions such as:

• Global spend: What did I spend globally last month with a supplier?
• Value of improving production: Predictive maintenance is improving uptime — what was the impact on revenue?
• Sales trends: How much did I sell to my top 10 global customers each year for the last three years and what was my profit?
• External data on sales: It’s going to rain next week — what are my forecasted sales in the region?
• Supplier price variance: Have I been paying the same price for material from my supplier for the last six months at all of my plants?
• Inventory availability: I have excess inventory in one region and stockouts in another — how do I decide what should be transferred?

Snowflake helps you answer these questions and more by providing a cloud-first data platform that is flexible, secure, easy to use, cost-effective, and accommodates all your data in one place. 

Here are five reasons to bring your ERP data to Snowflake:

Snowflake’s unique architecture is designed to handle the full volume, velocity and variety of data without making manufacturers deal with downtime for upgrades or compute changes. Its single data repository supports structured, semi-structured, and unstructured data from ERP systems (both on-premises and cloud), third-party systems and signal data, allowing users across the enterprise to access trusted business content. In addition, Snowflake is cloud-agnostic and can be moved to and from different cloud environments. Manufacturing companies can seamlessly scale their data platform across all three major cloud providers — AWS, Azure and GCP — and can switch providers without encountering operational issues. 

Snowflake’s architectural simplicity improves ease of use. Snowflake is a fully self-managed system, which means that it automatically handles storage capacity, compression, statistics and performance. Built-in automation eliminates the need for customers to build indexes or do housekeeping. Manufacturing companies no longer need specialists with proprietary programming experience to build queries because users can construct queries using familiar programming constructs. With Snowflake, you can use the languages and tools you’re already comfortable with, which results in less time spent training models. 

Snowflake’s flexible, scalable architecture allows you to attach and detach services as needed. Compute and storage are split so they can scale independently and elastically in seconds. For example, if you have a large data processing task such as the analysis of production sensor data, customer surveys or inspection reports, you can increase your compute resources without having to increase your storage. This delivers convenience, operational efficiency and cost savings. 

With Snowflake’s centralized data repository and scalability, manufacturers can easily integrate IT (CRM and ERP data) and OT (shop floor data and connected product data from IoT sensors) and achieve better visibility into operations, real-time data collection and analysis, 360-degree views of customers, and more. In addition, they can add third-party data sets through Snowflake Marketplace to enrich insights. These capabilities can increase efficiencies and security, lower costs and foster innovation. 

Built for the cloud, Snowflake leverages the most sophisticated cloud security technologies available. All data in Snowflake is always encrypted — in storage or transit — as a built-in feature of the platform. Features such as Dynamic Data Masking provide an extra layer of security. Snowflake customers retain control of their data, sharing views of data sets without moving or copying. Regardless of your current ERP environment, moving your data to Snowflake can alleviate the problems of complexity and rigidity while at the same time ensuring cloud data protection. 

Manufacturers that bring their ERP data and analytics workloads to Snowflake can say goodbye to complexity, high costs and proprietary programming, and say hello to simplicity, scalability, ease of use, security and lower costs. To dive deeper into how Snowflake unlocks advanced analytics with ERP data, download the ebook, Manufacturing Best Practices Guide: Unlocking Sap Data Analytics In Snowflake