Can Numbers manage the Supply chain better?
Let’s see. You are home after a long tiresome flight and now discovered that you got the wrong baggage from Airport. How do you feel? ; Or ever seen a situation during guest lecture, when the anchor has already welcomed the guest and the presenter is searching for the bouquet to greet him? ; Target of Supply chain management is reaching the right consumer at right time with right quality and addressing both Demand side & Supply side uncertainties. One best example of supply uncertainty is Reliance backing down on establishing its power plant due to sudden rise in Indonesian Coal prices – problem caused due to “Single sourcing”. Demand Side Uncertainty may cause “Bull-Whip effect”. Can analytics solve these issues?
HAU LEE’S SUPPLY CHAIN UNCERTAINTY FRAMEWORK
Low (Functional Products)
High (Innovative Products)
Low (Stable process)
High (Evolving process)
Risk- Hedging SC
Ex: Hydro-Electric power
Business analytics & Big Data have a wide range of application and are ubiquitous. This type of descriptive analysis is used to assess current market position of the company & effectiveness of past decisions. It also can be used for Predictive analysis (Predicting the trends based on past performances) and Prescriptive analysis (for formulating optimization techniques & best outcomes including the effects of variability)
In the aftermath of 2011 Fukushima tsunami, Intel sent teams to Japan to help their suppliers. It’s the big data which gave them those early warning signals about the capabilities of their dependency on Japan’s suppliers which prompted them to do what they did. Supply chains, in a traditional way, respond to various factors but analytics is the tool which can sense & quantify responsiveness in the market. Using analytics tools like Supplier selection support & Suppliers...
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