AI Summit San Francisco 2019
September 25 2019, San Francisco, CA, United States
AI Summit San Francisco 2019
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Experts in AI: Improving sustainability and profitability in retail
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About speakers

  • Michael Feindt
    Professor / Founder & Chief Scientist at KIT / Blue Yonder
  • Amy Turner
    Head of Digital Content at Informa Tech

About the talk

Artificial intelligence is one of those rare technologies that can help organizations boost their environmental credentials, while also improving the bottom line.

A good example of an industry where AI is creating positive change is retail.

“Food waste is a really big problem nowadays, and it is actually one of the sustainability goals of the United Nations, to halve food waste in the next five years,” Dr Michael Feindt, founder and chief scientific advisor at Blue Yonder, told AI Business.

Feindt gave a presentation on the topic at the AI Summit in San Francisco, in which he outlined how AI algorithms can be designed to help decrease food waste, helping improve both sustainability and profitability. Blue Yonder and its parent company JDA are working with 75 of the top 100 retailers, and all six of the largest grocery wholesalers.

Keep up-to-date with all the latest AI news and insight at http://www.aibusiness.com

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Welcome to AI business TV coming to you from the AI Summit San Francisco by and chief Scientific Advisor at 00:04 jda and pots of blue. Yonder welcome. How are you? 00:14 Thank 00:17 you very much. Very good 00:29 today and everywhere and seen here and 00:36 many many people interested in Ai and 00:45 tomorrow. I'm using living a key notes on sustainability and 00:50 profitability already for especially for you to 01:00 set 01:09 the world right now. 01:20 NFL in the food food, like sushi or 01:30 ground beef is very important Pet Supply Chains It's really up to her as you're not allowed to have too much. And 01:40

actually it's one of the things of the 01:47 United Nations to have to place in the next 5 years and by the Lord as one 01:55 of the companies who does it and I am glad I think that is exactly like profitability which is necessary for Enterprises really 02:05 important role and what we see now is how can we design that post? Carpal tunnel 02:15 and sustainable to really have enzymes function 02:25 to minimize food away 02:28 at the same time do to be to be profitable and also the service fee to those as a 02:38

customer service in his heart by any chance 02:48 that sings always come 02:51 if the reality does not perform as expected as much as you want to 03:01 avoid. The other very important thing is that you really have to use AI in automation because as you can reach the to go somewhere 03:11 only if you optimize it for every single item Every single store every day if it's very different from 03:20 Individual 03:29 to individual that is what modern day I can be. Being an 03:40 enabling Avery industry imaginable and see you tomorrow. 03:50

Yes. So what we're doing is always a 03:56 decision support or this is an automation the team many many decisions that have to be done in the retail business everyday. So that is Pacifica 04:06 supermarket chain in about 15 to 20 million replenishment decisions. Play 04:15 some everyday hits everybody who has to reorder and how many and 04:20 so 20 million by human or false the same as all the time 04:30 do not think about all the influencer and we forgot to use also weather for weather forecast in our projection. 04:39

What's the decision 04:49 and 04:51 don'ts Rising price at the fittings? All right price is right before every item. The right time is very important thing especially 05:00 again for the news. I got you something that is true for plane ticket set 05:09 to Four Seasons 05:19 fresh food to 05:28 write pricing policy. And I'm going to try to have value is a 05:36 02 expected. Low profit or 05:45 retail 05:53 pricing strategy and that for every single item 05:56 if they wanted everything in store and online and venison done completely or did Neji this message though. 06:06

They're very very powerful. 06:15 A little bit more on the supply chain 06:26 results of trusting. It's 06:30 this method always look very good if there's lots of data and lots of the 06:39 one we have. Millions update and 06:44 production manufacturing 06:53 at the very beginning 07:03 customers 07:05 want to head to predict as good as possible and then I'll probably have to process information at once. 07:15 Ed Wilson NC Distribution Center 07:26 as 07:28 much information as possible so we can also predict the order that we 07:39

have the same 07:42 video production what raw materials do we need? 07:50 What resources do we need at? What nmn power do we need horses at any of our kind of tea should be released yet by the customer 08:00 to our vision is that we have all of them in one big platform, where are all the states of resides and we have to trust in complete 08:10 visibility of everything and second predictability and something is on the Prescriptive automatic decision-making, 08:20 which is a complicated thing and of course Automation and so I love this 08:30

pic 08:39 already. What where long do we have to act all ready before something goes wrong to make the whole system more stable 08:50 friends. So what you see is being of the big things to shake up the industry 09:00 retail specifically in the next one to two years. What are we going to be best? If I bring 09:10 this what I told you or you will go out into real life for many many has to make a complete change of the 09:20 way they are working and doing the different departments purchasing and 09:30

pretty horizontal and optimization 09:34 also means openness of a time someone and supply chain and of course also, and I'm quite a bit of change in 09:43 Organizational 09:52 really 09:54 mainstream before the majority of it and Trust building already 10:06 about Elizabeth majority. Not yet. Then I think that the next big big thing in AI research side 10:16 is everything which has caused a lychee. So it's not enough that we learned only things from historic theater. Is it, Nations and make predictions, 10:26

but if we want to post our aim if we want to design a better excuse policy then we also have to Edwin forward or to understand 10:36 all the extra point is that was done in the history and if you have to really understand what is it called the effect of this decision 10:46 that we have tomorrow in order to ultimately come to a better attitude. 10:53 Solutions starting from something with smallest copies. What companies 11:02 do right now and in general automatically improve story, that's why you need to understand 11:12

the concept of causality that has one branch of mathematics and AI machine learning and 11:21 it's the only stops to make your connection to research areas that are not one and in my prediction is that this will be the next 11:31 big thing as Greenwich to together. This will enable after we need to take a decision for the next week which pusher. 11:41 Thank you. So if I can find thank you for joining us yet. 11:56

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