Big Data Discovery/Real-time Data in Supply Chain

As we have learned, demand prediction is a critical aspect for successful and efficient supply chain management. Traditional prediction uses historical numbers, the general trend of economy and the life cycle of the industry, in which the assumption is that history could be reproduced in a way. However, only using these data could not accurately predict the future. The technology of collecting large amount of data in real-time sense is the cutting-edge trend of the demand prediction in supply chain. The real-time data is especially useful for retailers because they have no orders ahead of time. Two articles in reference are regarding to this technology.

The first article talks about four cases of application of real-time data in retail industry, among which the first one is the most interesting. It is a case for a fuel retailer to collect real-time data of fuel product mix and consumption rates from sensor in service station or convenience store. The data make it faster to market with offers, and better to position revenue and agility because offers can be instantaneously changed to respond to customer demand shifts.

The second article talks a single case of combined real-time identification and visualization. Retail businesses want to know customer needs and feedback in order to respond more targeting, real-time collecting systems use powerful data mining infrastructure to collect real-time data on social media, such as Tweets. For example, a clothing retailer wants to find out differences in customer reaction from different states to a certain defects, they could use real-time data from social media to see the negative and positive comments on its brand. After a spatial visualization, the retailer could readily find out the most intense complaints on the map and adopt methods such as extra discounts to dispose the defected items in that area. The following picture is the demonstration of a collected and visualized data.

What applications of real time do you think there are in other industries other than retail?

References:
http://www.techrepublic.com/article/putting-big-data-to-use-in-the-supply-chain/
http://www.esri.com/esri-news/arcnews/winter1314articles/gis-accelerates-big-data-discovery