Amazon Files Patent for Speculative Shipping – Probable game changer
“Here is the basic idea: Amazon would forecast demand for a given geographic region, whether that is a state, a metro area – or maybe even an apartment building, on something like a daily basis.
It would then pre-ship items towards that geographic area at the same level of granularity (meaning possibly, for example, based on a 5-digit zip code, maybe a 3-digit code, or maybe a street address with no name/unit), using common carriers. Each package would be uniquely identified.
If an order is received for that item, then the delivery address would be communicated to the carrier, which would somehow update the shipping information for that parcel.”
I think Amazon’s Speculative Shipping is one step towards winning the battle in ‘Last Mile advantage’. Today in the increasing competition in the e-commerce space, delivery has become an essential factor after pricing and assortment. This strategy from Amazon, if succesfully implemented would help in same day delivery with an premium charge. Proper forecasting would actually allow Amazon to distribute the products at relevant geographic regions,reduce the delivery time significatly and increasing the customer satisfaction.
This would require a paradigm shift in thinking about delivery which typically waits for the order to come from customer. Algorithms need to be built to cater this kind of delivery model.
I think new SAP application on HANA can cater to this speculative shipping process. This would require data crunching of all previous orders, category spread, geographical spread and predict the next shipping.
Regards,
Ambarish Modak,
Product Owner @SAP
The increasing number of business method patents makes these e-commerce sites more and more powerful. The new methods of doing business brought a revolution in market. Each of the companies now wants to implement the different business strategies of other companies to be successful. I guess it is one of the big reasons why one needs to patent the business methods