Pluto7 Blog

Value Chain Planning moves local with machine learning

Posted by Salil Amonkar on Feb 16, 2017 9:28:23 AM

Technology leads the path for change, but success is dependent upon the ecosystem to adopt the change.

Industries will either move away from or gravitate toward a specific geography based on economics, geopolitical situations or basic demand and supply.  US manufacturing has gone through an interesting journey of starting local (e.g., automotive companies like Ford) and then expanding globally for both distribution as well and manufacturing. These companies are beginning to show that the path can also come full circle to boost manufacturing locally. Part of the need for all of this is driven by US political interests as well as the strong public sentiment and grass roots efforts to "buy local" which are fair expectations, given other countries are doing the same.

At the same time, there are some interesting shifts happening in technology as well, which are shaping the manufacturing industry in new was, powered by Data.  Cloud, when combined with the power of machine learning, now challenges the fundamental notion of the need for human resources at various stages in the value chain. When data is combined with advanced analytics and workflow automation, conducting various checks and balances in the end to end value chain (e.g. status or quality inspection ) are now in threat of being replaced. Will the political campaigns that promise manufacturing jobs really address this analytics problem? In my opinion, only partly. There is an extent to which governments can compel manufaturing companies regarding when, where and how they run their business before experiencing pushback and workarounds. The journey that will persist, no matter what incremental improvements are made in any given supply chain organization, the industry will efficiently explore new ways and means to drive human productivity and better customer experience.  

With the evolution of Cloud solving the new asks of supply chain planning is now becoming lot more critical and the expectations with Lead Time, Inventory Turns and Forecast Accuracy KPI managements have also changed. This is not only for the large enterprises but also for mid size and smaller customers. At Pluto7, we leverage the power of cloud, mobile and big data combined with machine leanrning to solve the very basic problems of demand and supply and drive above KPI improvements. Over decades of experience with Value chain we now have formed solutions to solve the same with Planning in a Box. 

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Topics: Machine Learning, Big Data, Google Cloud Platform

Planning In A Box - My thoughts On scalability

Posted by sangeetha reddy on Dec 20, 2016 12:38:50 PM

As this week draws to a close, and I continue to work with beta customers, I thought I'd share a bit of my own thoughts on our Planning in A Box SaaS solution and the relevance to Supply Chain.

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Topics: Tableau, Google Cloud Platform

Planning in a Box showcased by Tableau at their Largest user conference as an innovative Supply Chain solution with embedded analytics

Posted by sangeetha reddy on Nov 9, 2016 8:11:49 AM

Planning in a Box - SaaS supply chain collaborative platform built on GCP recognized by Tableau at the user conference as innovative with embedded analytics .     Click Here to Request a Trial Licence

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Topics: Machine Learning, Tableau, Google Cloud Platform, Artificial Intelligence, Paxata

Better Supply Chain Management with Machine learning and Embedded Tableau Analytics

Posted by sangeetha reddy on Nov 1, 2016 3:31:02 PM

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Topics: Machine Learning, Big Data, Analytics, Tableau, Google Cloud Platform, Artificial Intelligence, Paxata