The number of.people working in warehouses was decreasing every year while the number of distribution centers to support blooming e-commerce trade kept on increasing. While picking was being automated for sometime but now even packing is being done by machines. The trucks will already start self.driving in a few years. Winder where all the money saved through this effort is going to land up. Will corporates further improve their profits without profiting.the societies in which they thrive. What's the point of that wealth !!
Tuesday, May 14, 2019
Sunday, April 28, 2019
Today's Distribution Center: You Say You Want an Evolution?
A very informative article which lists the evolution of Distribution Centers from Warehouses.
The explosion of item variety, repacking, automations, processing
Today's Distribution Center: You Say You Want an Evolution? - Inbound Logistics
The explosion of item variety, repacking, automations, processing
Today's Distribution Center: You Say You Want an Evolution? - Inbound Logistics
Monday, April 22, 2019
Artificial Intelligence in Logistics
The IT industry thrives on creating an Hype which is well documented by the Gartner Hype cycle.
The potential benefits of these new age technologies are bull horned by the Industry experts all the time in various forum to drive new purchases, to attract investments and to fill out seats in coaching classes. While I do not discount them all, the actual benefit and maturity of any of such technologies does take a lot of time to reach a level which deserves such attention.
I am not sure if such 'game changing' 'end user configurable' 'out of the box' technologies with '70 - 140% proven improvements' are already out there then why am I struggling for so many small things all the time. What gives.
AI for Logistics, brings some resemblance of feasibility to it by focusing AI usage to 'enabling predictions and proactive exception management'
Though there too I see challenges in various areas which might stop AI and ML Machine learning solutions from being fully successful and effective any time soon
- comprehensive expertise: systems grow organically in bits and pieces with hardly there being a single of group of people who know it all
- purity of data: quite a bit of effort are spent on resolving issues which are lead due to mismatch of master data setup across the myriad systems in the landscape
While I am sure one day all these will be surmounted, with potentially loss of jobs, but i don't think threatened any time soon
The potential benefits of these new age technologies are bull horned by the Industry experts all the time in various forum to drive new purchases, to attract investments and to fill out seats in coaching classes. While I do not discount them all, the actual benefit and maturity of any of such technologies does take a lot of time to reach a level which deserves such attention.
I am not sure if such 'game changing' 'end user configurable' 'out of the box' technologies with '70 - 140% proven improvements' are already out there then why am I struggling for so many small things all the time. What gives.
AI for Logistics, brings some resemblance of feasibility to it by focusing AI usage to 'enabling predictions and proactive exception management'
Though there too I see challenges in various areas which might stop AI and ML Machine learning solutions from being fully successful and effective any time soon
- comprehensive expertise: systems grow organically in bits and pieces with hardly there being a single of group of people who know it all
- purity of data: quite a bit of effort are spent on resolving issues which are lead due to mismatch of master data setup across the myriad systems in the landscape
While I am sure one day all these will be surmounted, with potentially loss of jobs, but i don't think threatened any time soon
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