Will the Cloud help in the Supply Chain resiliency...?

Since our lives and work started to evolve with the new normal, preserving many lessons the pandemic has taught us and reflecting on how we can build a more resilient supply chains.

This is my first blog and it is based on an article published in Forbes magazine. A recent telephonic conference with more than 50-C level executives from France and Italy consisting of people from retail, fashion, and automotive industries, and their specialty is supply chain which got staggered in the past few months due to pandemic.

For many years, they followed supply chain practices that have the lowest price method and the minimum viable inventories. But the introduction of Covid-19 has changed the entire situation.

Factories were closed down and panic customers hoarded basic goods. Even the health care system couldn’t even secure essential personal protective equipment due to supply chain destruction.

 As a result, there was two prolonged dilemmas: one was the supply chain breakdown and the second was the traditional data that the businesses used to manage the supply chain no longer reflected customer demand. So, we need a more sophisticated method which uses real-time data to estimate customer demand.

The Power of Digital Supply Chain Twins for Better Decision Making

The pandemic shows that large-scale destruction or a disaster scenario can change the entire consumer behavior which ultimately destroys the supply chain.

This results in the concept of creating a digital supply chain twin. A digital twin is a digital representation of the physical asset, process, or systems that can be redesigned if the failure arises and is modeled in the cloud using a diverse array of data. This eventually increases the reliability and performance of the entire supply chain system.

Cloud-based supply chain management and modeling are often used for real-time decision making and reliability assessment. Within one cloud data center, we also integrated critical data, allowing for better business decisions based on real-time data and risk assessment. The data analytics along with the decision making by artificial intelligence will help us solve our toughest problems.

Modernizing data warehouse

The first step is often to build a data warehouse in the cloud. This unites all of your data sources while maintaining the security and the semantic richness of your information.

Built-in machine learning and analytics can produce better consumer-behavior models, anticipating spikes, and shortages while avoiding overstocking. Tools such as the AutoML from Google Cloud and BigQuery ML can train high-quality, custom machine-learning models with minimal effort and experience in machine-learning.

Access to Real-Time Consumer Behaviour Data Is the Key for Strong Supply-Chain.

The Home-Depot uses Google's data warehousing service to keep more than 50,000 items stocked at 2,000 locations. Such a setup allows us to quickly react to new consumer needs, tracking what items are sold, as well as when and where they are sold.

Industrial Internet of Things accesses distributed data in real-time via sensors and forwards it to the cloud. It reveals new tastes in products, how people want them delivered, and how they want to consume them.

We are at the beginning of a long road to rethinking and rebuilding our supply chain models. Now is the time to create resilient systems that offer deeper user understanding, more flexible management, and better stability in the face of unpredictable disruptions.

THANK YOU!