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

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

A Game Changing Year for IT Industry led by Cloud, Big Data, Social and Mobile Platforms

Posted by sangeetha reddy on Oct 23, 2016 8:21:26 PM

It has been almost 15 years since Silicon Valley in california has seen the current high momentum in innovation, technology and investments, last since during the dot com days in 1999.  The successes of social media companies and its impact on business and geo political landscape has made us only imagine further on the impact to the IT industry.

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Topics: Big Data

How to become a Data Driven Organization?

Posted by sangeetha reddy on Oct 23, 2016 8:18:46 PM

Organizations have always relied on data. The difference between mid-1990’s and today as an example is that the cost to find the right data has dramatically gone down. We know the costs of a microprocessor and memory chip in the last 20 years have gone down exponentially. With that the data storage volumes and the algorithms capabilities to find the right information fast have gone up exponentially as well. While all of this were happening, companies have adapted to these changes and evolved and some companies like Amazon and Google and many more have grown during these 20 years. What is common between Amazon and Google is that they help you search through volumes of data and provide you the most relevant information for you in the least amount of time to make a purchasing decision or any other form of life impacting decision.

Now, finding faster and better data for actionable decisions is becoming a need in every organization. When thinking of transforming a company to be data driven, start with thinking broadly on how do People, Process and Machines in your company interact with each other? Understand how the organization is generating, searching, consuming data and making decision to take actions. Companies do function like a living organisms with data acting as the blood in the body. The more efficiently and effectively the blood flows, the body remains health, so is the effect the data causes to the organization. All of this is not as complicated as it appears. Executive and management need to look at this as a structured exercise and a journey to get to the better state in data usage than the current state. There is no destination in this journey of becoming more data driven; instead there is more of becoming a company in a more evolved state than the current state.

In Summary, to transform a company to become data driven, three key steps are needed

1. Know your Data,

2. Formalize your Outcome and

3. Be ready to change the fundamental of the business supported by data evidences.

Above all, be ready to foster a culture of exploration of data and raising the questions and finding the relevant answers. Interested to learn further, listen to a live customer at the webinar on How to become a Data Driven Organization ?

 

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Topics: Big Data, Analytics