Big Data is probably the most popular topic in business society nowadays. Everyone speaks of Big Data and wants to use opportunities it offers. Personally, I hear about Big Data at least 10 times a day, which is not surprising: Heinz College and job search at one time. In such a context, the topic of this very blog post seems to very relevant: indeed, Big Data is such a trend now, but for me it is not clear how it can be directly used in SCM field. So, below are some results of my research on how the Big Data can be used in managing the supply chains.
Demand forecasting
Nowadays we can see that the Big Data analysis is implemented for the demand prediction mostly by big retailers that have broad capabilities of data collection from POSes. But why do retailers need that? As we already know from the Walmart and Ikea cases discussed during previous classes, large-scale retail businesses are fully dependent on the SCM, which is a basis of their business model. That is why they are always looking for improvement in their SCM-related areas (as logistics, inventory, vendor management and so on). At the same time, retail business is always demand-driven, which means that almost everything is determined by the customer and its behavior. Analyzing the broad data on customers allows to predict this behavior and thus the demand. Knowing the demand allows to make important corrections to inventory schemes, change suppliers and so on. In this way, proper demand prediction leads to better organization of SCM, which in turn, brings reduces in costs (due to smaller inventory costs, for example) and increases in service quality.[2]
Supplier geographical locations choosing
Big Data analysis can be successfully used for the choosing the geographical location of the suppliers. Here, the historical data on severe climate effects (tornadoes, tsunamis, very low temperatures, ...), social problems (strikes, wars, ...), logistic problems (bad roads, car accidents, ..) can be analyzed while choosing the supplier location. The proper analysis in this area may allow to avoid the supply lags associated with the problems listed above.[3]
Big Data for the real flexibility of SCM
Internet of Things (IoT) is another popular term nowadays. It is "uniquely identifiable objects and their virtual representations in an Internet-like structure" (wiki). Though, we are yet far from the real IoT, we already have the technologies such as RFID which allow to track the objects in real time. The possibility of collecting the real-time data on packages, trucks, parts and so on and of analyzing it can bring huge improvements in the SCM process as all the flaws, lags and problems will be possible to catch "on the go" and thus adjust for them. This is yet the thing of the future, but it is IoT which will bring Big Data the largest importance in terms of SCM.[1, 3]
These are the three major points I found so far. However, I believe, there are much more ways of using the Big Data analysis in favor of SCM. I hope, we will touch this question during our classes, as I think it is very important as Big Data will eventually change the SCM as we know it now.
References:
1. Horn K. (2012, September 25). "Big data: driving changes in supply chain management". Europe BusinessReview.
2. Mehra G. (2013, June 27). "5 Ways Big Data Can Help Retail Supply Chains". Practical ECommerce.
3. Shacklett M. (2013, July 15). "Putting big data to use in the supply chain". TechRepublic.
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