While heading out of the drive-way to get groceries, a probable thought going through your mind could be, ‘When will someone do my groceries for me?’. Two options that come to mind are either, getting very rich very soon, or when the days of flying cars and hover boards are no longer a fiction, and your bidding gets done by near real-life humanoids. The latter will require life extensions though.
Then one other option comes to mind. Online shopping. Some people have good stories and others don’t. The idea of shopping online isn’t a new one, and it doesn’t take much to get onto a website that offers online shopping.
So you pick your goods, add them to the cart, and finish your purchase. Now you arrive at the inevitable question.
How will it be shipped? You might have fragile goods, or large items. What shipment mode? Will the cost be added in to the overall price or otherwise. When will it reach your home? Valuable or sensitive goods will need a more personal receipt. Or even sensitivity in delivery. Who will need to accept delivery in terms of authorisation?
Accept for a few well known logistical companies, your options are limited. Modes of transportation and different stages you will need to go through such as filling out forms and accepting routes or delivery modes are more than tedious, so taking that drive down to the grocery shop is the best option.
The best option, that is, until Swedish company Shipwallet emerged.
A company that’s using big data analytics to harness the power of logistics and give the user personalised suggestions on best delivery based on algorithms and machine learning to arrive at the best suitable option.
What does this mean in real world terms?
It would be like driving to the grocery store, ordering your items, then as you are paying for your items at the cashier, they suggest which type of delivery would best fit your delivery needs. The data that facilitates this option is gathered from google, shippers and past behaviours of your neighbours.
Piotr Zaleski, CEO of Shipwallet describes it. “Consumers can configure their shopping with much more granularity, but we also have a predictive analytics platform on top of it, which calculates the best shipping options. So a new consumer comes to the checkout and we say “you should basically have this shipping option.” Using all the data we have from the shippers—from Google and also from the past behaviour of your neighbours—we can say “this is the best shipping option for your particular address.”
Woe’s begone? Well not just yet. The denominating factor to this whole system and its success, is data. Data from shoppers. Data from shippers. Data from vendors. The challenge then is in retrieval. Getting companies to share their data.
That brings us the another dilemma. One that’s being faced by Shipwallet. Getting companies to share their company data, route information, customer knowledge to the world. Literally. The pros and cons in business terms and pros and cons to the customer and where the line is drawn.
Here is the question that big data users keep coming back to. The question of security.
Laws and systems currently in place to mitigate and safeguard personal and sensitive data are juvenile at best, save corporations who delve into those areas as a business. Big data analytics users are moving at a much quicker pace incorporating ideas into company offerings, faster than companies with the solutions are willing to, or even able to keep up and deliver. Cost factor comes into play. Operational downtime needs to be factored in too.
Also, machine learning, without massive amounts of data is pretty much a waste of resource. The idea is in its infancy and though many corporations promise the eventuality of it, it won’t be part of mankind’s immediate world.
However, in terms of where getting convenience delivered to your door-step is, I’d like to say, it is impressive. We are flying into uncharted territory of innovation and imagination at break-neck speeds. Exciting times are in the cards. The future is here now and knocking at our door.
- June 2017(79)
- May 2017(105)
- April 2017(113)
- March 2017(108)
- February 2017(112)
- January 2017(109)
- December 2016(110)
- November 2016(122)
- October 2016(111)
- September 2016(123)
- August 2016(170)
- July 2016(142)
- June 2016(153)
- May 2016(118)
- April 2016(60)
- March 2016(86)
- February 2016(154)
- January 2016(3)
- December 2015(150)