KloudData

SNOWFLAKE FOR RETAIL AND CONSUMER PACKAGED GOODS

Retailers, consumer packaged goods (CPG) manufacturers, and eCommerce companies are under immense pressure to

adapt and meet evolving consumer needs while ensuring speed, convenience, and quality. But gaining insight into customer

preferences, operating costs, performance trends, and supply chain networks is often complicated by legacy systems and data

silos that hinder advanced analytics, jeopardize data security, and make sharing live data impossible.

More retail organizations are turning to the cloud to transform and scale their analytics capabilities and unlock data-driven

insights to optimize every area of their business, from driving supply chain efficiency to optimizing inventory management and

fulfillment. With Snowflake Cloud Data Platform, all retail organizations can glean insights across the value chain and use data to drive robust revenue growth and deliver personalized multi-channel experiences that consumers expect.

✅ Unify all of your data:

Bring together your structured and semi-structured data from different sources and channels to gain a universal view of your business and customers.

✅ Reduce costs and maintenance:

Save time and resources with a near-zero maintenance solution that’s simple to use and cost-efficient.

✅ Gain deeper, faster insights:

Eliminate bottlenecks and support different reporting and analytics needs by empowering all users and workloads with live data access and consistent performance.

✅ Share data securely:

Share data efficiently and securely with internal data consumers and external partners while remaining compliant with built-in security that supports SOC 1 and 2 Type 2 and PCI DSS requirements.

❄️ SNOWFLAKE FOR RETAIL AND CONSUMER PACKAGED GOODS

Retailers, consumer packaged goods (CPG) manufacturers, and eCommerce companies are under immense pressure to
adapt and meet evolving consumer needs while ensuring speed, convenience, and quality. But gaining insight into customer
preferences, operating costs, performance trends, and supply chain networks is often complicated by legacy systems and data
silos that hinder advanced analytics, jeopardize data security, and make sharing live data impossible.

More retail organizations are turning to the cloud to transform and scale their analytics capabilities and unlock data-driven
insights to optimize every area of their business, from driving supply chain efficiency to optimizing inventory management and
fulfillment. With Snowflake Cloud Data Platform, all retail organizations can glean insights across the value chain and use data to drive robust revenue growth and deliver personalized multi-channel experiences that consumers expect.

✅ Unify all of your data:
Bring together your structured and semi-structured data from different sources and channels to gain a universal view of your business and customers.

✅ Reduce costs and maintenance:
Save time and resources with a near-zero maintenance solution that’s simple to use and cost-efficient.

✅ Gain deeper, faster insights:
Eliminate bottlenecks and support different reporting and analytics needs by empowering all users and workloads with live data access and consistent performance.

✅ Share data securely:
Share data efficiently and securely with internal data consumers and external partners while remaining compliant with built-in security that supports SOC 1 and 2 Type 2 and PCI DSS requirements.

DIGITAL MANUFACTURING USE CASE #2: PREDICTIVE ASSET MAINTENANCE

> 10-20% increase in overall equipment effectiveness!
> 5-10% reduction in maintenance costs (labor, spare parts)!
> Up to 20% reduced waste due to machinerary start up and stopping

Predictive asset maintenance allows operators and plant management to anticipate machine downtime or tool failures, and schedule maintenance proactively. Performing maintenance only when required, as opposed to traditional time-based maintenance practices, limits machine downtime and encourages effective use of labor.

Implementing predictive asset maintenance allows supervisors to schedule maintenance as needed, based on the true condition of machines, and to effectively coordinate production around planned machine downtime. Effective planning of maintenance reduces machine downtime and limits cycle starts and stops. By limiting these factors, manufacturers see increases in throughput and asset utilization, and a reduction in material waste and scrap.

Data from manufacturing ex*****on systems (MES), ERP systems, maintenance systems, operational historians, and sensors are used to train ML models and drive analytics. Implementation of predictive asset maintenance allows for real-time analytics and alerting capabilities to inform plant workers of machine activity.

To create a digital factory, manufacturers are applying new cloud technologies to address their business challenges with a variety of use cases. To know more, reach us at https://lnkd.in/dvZ69Rg