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Supply Chain Analytics

1724 Words7 Pages

Supply chain is an indispensable part of any modern day manufacturing firm. With the demand for any product being acutely variable it is highly imperative for any firm to optimize its supply chain – a chain of intermediaries, right from the sourcing of the raw materials to the managing of returns. Business Analytics tools with its real time application helps in combining technology with human effort to identify trend and highlight opportunities, all in real time and with live data. Supply chain practices are in vogues now which utilize the business analytics framework for improving the performance of the supply chain. In order to synchronize it with the ever changing economic landscape, we believe that it is important to implement strong strategies …show more content…

There are many ways to deliver it with supply chain analytics solutions. First dimension can be in the form of Executive Information Systems (EIS): Executive dashboards with drill down analysis that support decision making at an executive level. Second dimension could be Standard reports that are designed and built centrally and then published for general use. There are generally two types one being parameterized one wherein fixed layout reports that allows users to specify which data are to be included and other one being interactive reports that gives users the flexibility to manipulate the structure, layout and content of a generic report via buttons, drop downs, etc. Third dimension of SC analytics can be OLAP tools (Online Analytical Processing) which lays stress on relatively simple techniques like pattern recognition, deduction to data in order to extract new insights. Ad-hoc reports as a one off exercise and advanced analytics in the form of regression, sensitivity analysis and hypothesis testing could be other popular dimensions for the SCM in the …show more content…

A terabyte-sized data mart cost $6 million few years ago and would fetch much more today. On a positive note, today there are inexpensive open source software as well as proprietary software and hardware that are less costly than in the past. Although Analytics tools are easier to use, companies still need a technically savvy team to deploy the data warehouse that integrates all their information into one place. The team also must create applications to access the information and decide which data sets within the warehouse will be most useful.BI tools might not be able to make informed decisions based on the information but can present users with organized, analyzed

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