WEBVTT 1 00:00:00.000 --> 00:00:03.500 (lively electronic music) 2 00:00:06.510 --> 00:00:11.510 We all know that a beautiful BMW i4 M50, like this one, 3 00:00:11.520 --> 00:00:13.522 is made out of thousands of components. 4 00:00:13.522 --> 00:00:15.900 (machines whirring) 5 00:00:15.900 --> 00:00:18.570 And procuring those components to the right price, 6 00:00:18.570 --> 00:00:22.413 right quality in the right time is hugely complex. 7 00:00:23.400 --> 00:00:26.790 I'm now heading to BMW's Research and Innovation Center 8 00:00:26.790 --> 00:00:30.086 to discuss how GenAI has changed the game here. 9 00:00:30.086 --> 00:00:35.086 (lively music continues) (car engine purring) 10 00:00:39.997 --> 00:00:42.660 (lively electronic music continues) 11 00:00:42.660 --> 00:00:45.283 If you think of GenAI, GenAI is so strong 12 00:00:45.283 --> 00:00:48.450 on unstructured data and managing complexity. 13 00:00:48.450 --> 00:00:50.400 How do you describe the complexity challenge 14 00:00:50.400 --> 00:00:52.165 when it comes to procurement at BMW? 15 00:00:52.165 --> 00:00:54.420 The good thing is you can start with procurement 16 00:00:54.420 --> 00:00:57.006 because there's a lot of unstructured data: contracts, 17 00:00:57.006 --> 00:00:59.724 tender assist. And the cool thing is you start 18 00:00:59.724 --> 00:01:02.520 and gain trust with unstructured data 19 00:01:02.520 --> 00:01:03.930 and you gain trust in your organization. 20 00:01:03.930 --> 00:01:05.310 You learn to build the blueprint, 21 00:01:05.310 --> 00:01:07.290 and then you transform the next level 22 00:01:07.290 --> 00:01:10.260 to get into structured data and combine the two. 23 00:01:10.260 --> 00:01:12.927 If you just think in one division with GenAI, 24 00:01:12.927 --> 00:01:16.050 I would say you missed the point. 25 00:01:16.050 --> 00:01:20.340 If you think about, if you have a GenAI-driven organization, 26 00:01:20.340 --> 00:01:22.770 that really brings the entire business units 27 00:01:22.770 --> 00:01:24.270 completely in a different alignment. 28 00:01:24.270 --> 00:01:26.880 It's not optimizing just one process; 29 00:01:26.880 --> 00:01:29.370 it's optimizing an entire workflow. 30 00:01:29.370 --> 00:01:32.220 And GenAI is not just the tip of the iceberg at the end, 31 00:01:32.220 --> 00:01:35.610 it's, hey, what of the process can I rethink 32 00:01:35.610 --> 00:01:37.530 and GenAI do for me in a better way, 33 00:01:37.530 --> 00:01:40.715 and I as a human resource can focus on what really matters? 34 00:01:40.715 --> 00:01:43.500 You were one of the very first movers in the company. 35 00:01:43.500 --> 00:01:45.570 What is the difference from a concept 36 00:01:45.570 --> 00:01:47.100 to bringing it to scale? 37 00:01:47.100 --> 00:01:50.830 Never give up, because you'll face a lot of obstacles 38 00:01:50.830 --> 00:01:53.910 and roadblocks, but for scalability, really, 39 00:01:53.910 --> 00:01:56.340 the only thing that matters is you have to have 40 00:01:56.340 --> 00:01:59.100 the leap of faith that you will be able to tackle it. 41 00:01:59.100 --> 00:02:01.920 Don't give up. It is an iterative process, 42 00:02:01.920 --> 00:02:03.221 like with any other programs, 43 00:02:03.221 --> 00:02:05.550 IT programs or vehicle programs, 44 00:02:05.550 --> 00:02:07.470 and you have to have a little bit of vision 45 00:02:07.470 --> 00:02:10.440 and mindset that all the things they've thrown at you 46 00:02:10.440 --> 00:02:13.414 that does not work, somehow you can get it done. 47 00:02:13.414 --> 00:02:16.470 Thinking of the mindset needed to pull off GenAI, 48 00:02:16.470 --> 00:02:18.240 to bring it really to value, 49 00:02:18.240 --> 00:02:20.370 what is the learning of combining the best team, 50 00:02:20.370 --> 00:02:22.260 the dream team, to make this all happen? 51 00:02:22.260 --> 00:02:24.810 Tech got everybody excited. 52 00:02:24.810 --> 00:02:29.100 However, I think, to create value, we need a 180. 53 00:02:29.100 --> 00:02:31.558 You have to bring in the product vision. 54 00:02:31.558 --> 00:02:34.440 What does this really mean for my organization, 55 00:02:34.440 --> 00:02:37.260 and how can I make a difference as a USP in a product 56 00:02:37.260 --> 00:02:38.835 like a car or how can I make a difference 57 00:02:38.835 --> 00:02:40.949 with my business partners in a value chain? 58 00:02:40.949 --> 00:02:43.290 Thinking of external partners, 59 00:02:43.290 --> 00:02:45.660 how can external partners, like BCG, 60 00:02:45.660 --> 00:02:48.540 what is it that the external world can bring to the table? 61 00:02:48.540 --> 00:02:50.580 I think, at the beginning, what we really lacked 62 00:02:50.580 --> 00:02:54.300 was the talent and the gift to execute. 63 00:02:54.300 --> 00:02:56.640 Where we looked for external partners was specifically 64 00:02:56.640 --> 00:03:01.044 in the fields of governance, platform, and execution. 65 00:03:01.044 --> 00:03:04.320 We at BCG, BCG X, and Platinion are excited 66 00:03:04.320 --> 00:03:07.260 to work with all the adopters, like the BMW Group, 67 00:03:07.260 --> 00:03:10.494 to unlock the trend of GenAI, not only conceptualizing it, 68 00:03:10.494 --> 00:03:13.219 not only scaling it, but really bringing it to value. 69 00:03:13.219 --> 00:03:15.157 We're excited to see where BMW's heading 70 00:03:15.157 --> 00:03:17.518 and where the trend will bring all of us. 71 00:03:17.518 --> 00:03:21.851 (lively electronic music continues)