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June 27, 2022 | Divya Khare

One Platform to Supercharge your Supply Chain: Glassbox Methodology

How near are we to having self-running supply chains? Is it possible for production, warehousing, and transportation to become “lights-out” processes where no human intervention is required? Much of the supply chain can already be automated with artificial intelligence. It can also create a self-learning and adapting supply chain. Today’s AI technology is advanced enough to allow supply chain activities to run unattended for extended periods of time. Perhaps indefinitely. 

New technology can often be a solution in time of a problem. If AI is to be effective and profitable in the supply chain, it must be motivated by current operational concerns. Of course, it has the potential to provide new opportunities in the future. The first question, however, should be this one in order to gain management support as quickly as possible. “What in the supply chains needs to be improved right now?” Here are some instances.

  • Hard to plan for demand – What does this mean?
  • Excessive safety stocks and bullwhip effect – What does this mean?
  • Supplier unreliability
  • Transport network unpredictability
  • Demand by customers and partners – Isnt this the same as the first point? 
  • Seeing the real bottom line impact of supply chain decisions What is seeing? Change wording

One Platform to make Supply Chain Decisions simple and faster

Advanced analytics and artificial intelligence are the keys to addressing relevance, resilience, and responsibility at the same time. Our research reveals that leaders are rapidly adopting these powerful technologies, helping them stay ahead of their competition and extracting the advantages generated by technologies like artificial intelligence and machine learning

Supply chain analytics and AI have a plethora of applications, and the list keeps growing. However, not all use cases are made equal. Some use cases are more difficult to scale than others, and the influence on critical business priorities varies. This is why businesses intending to increase their spending on and use of these technologies should concentrate their first efforts on maximizing their return on investment.

End to End planning on a single platform

Pluto7’s Glass-box approach is built on transparent solutions that you can tweak to deliver optimal performance to your supply chain. Unlike a closed box, you can see through it and control your Data Integration, ML models, Analytics Interface, and everything else.

– Cloud Platform

The value of data is determined by its accessibility and applicability. Only on the cloud can data achieve size, agility, and the potential to drive reinvention, allowing businesses to fly. Migration is only the beginning. Companies are upgrading their data infrastructure so that their employees can work with data and cloud innovation with ease.

Across all cloud models and delivery methods, the cloud migration framework combines industrialized capabilities with distinctive pre-configured industry-specific tools, processes, and automation.

– Data Foundation

Any AI solution must start with a solid data foundation. Finding and integrating data from hybrid and multi-cloud settings, evaluating and processing the data to extract the most usable information, and managing and administering enterprise data is a difficult and time-consuming tasks.

To produce speedy, actionable insights, connect and blend internal and external data. From procurement to sales, an integrated end-to-end data unification approach may handle the opportunities and limits of all business areas.

– ML modules

Drive enterprise-wide visibility into all aspects of the supply chain with a granularity that humans can’t match on a large scale. Deliver sophisticated optimization features to enhance forecasting accuracy, efficiency, and cost savings while satisfying your consumers. 

Machine learning is a strong analytical approach that may help supply chain companies deal with massive amounts of data. Because of telematics, IoT devices, intelligent transportation systems, and other powerful technologies, ML in the supply chain ensures that large volumes of data are processed with the greatest variety and unpredictability. This enables supply chain companies to learn a lot more and generate more accurate forecasts.

– AI solutions

Despite the fact that 90% of today’s firms have implemented cloud, just a third are seeing the expected ROI. While the cloud provides you with next-generation computing capacity and access to new types of data in the proper quantity and quality, the most advanced businesses recognize that AI is the bridge that allows you to turn that data into business value. 

We help you build flexible AI-powered solutions that you can tweak, integrate and extend. Predict demand 25% better while reducing inventory carryover cost by 30% and saving $10M annually.

– Decisions Platform

A rising number of supply chain organizations are employing machine learning techniques to trigger automatic reactions and control demand-supply mismatches, cutting costs and improving customer experience. With  Planning in a Box, build a resilient and agile supply chain. Smarter and faster supply chain decision-making to respond quickly and cost-effectively to rapid changes in market conditions. 

– Support and Maintenance

We believe our team works best when we can act as an extension of yours. Get continuous support and maintenance from Pluto7. We aim to ensure that our platform is highly reliable and relevant to your constantly evolving supply chain needs.

Conclusion

Essentially Planning in a Box 2.0 is your Supply Chain Twin that is scalable throughout operations with a precise blend of internal, external, and even IoT data to drive higher intelligence throughout the supply chain. 

In a nutshell, Pluto7’s Planning in a Box is a single platform that supports a complete end-to-end Supply Chain process and is fully integrated.

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Write to us at contact@pluto7.com

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