WEBVTT 1 00:00:00.476 --> 00:00:02.893 (soft music) 2 00:00:10.618 --> 00:00:13.597 We've been talking a lot about the bionic company, 3 00:00:13.597 --> 00:00:17.496 and today we're going to dive in to the drivers of change. 4 00:00:17.496 --> 00:00:22.340 What makes the company of the future, the bionic company, 5 00:00:22.340 --> 00:00:24.667 so different from the company of today? 6 00:00:24.667 --> 00:00:27.851 And there are three things we're going to explore. 7 00:00:27.851 --> 00:00:31.833 The first is that in the bionic company, 8 00:00:31.833 --> 00:00:35.497 processes are operated by humans and technology. 9 00:00:35.497 --> 00:00:38.578 Today, processes are operated by humans. 10 00:00:38.578 --> 00:00:41.993 And the truth is that the economics of humans 11 00:00:41.993 --> 00:00:44.620 and the economics of humans plus technology 12 00:00:44.620 --> 00:00:45.570 are very different. 13 00:00:46.530 --> 00:00:49.406 Humans are flexible, 14 00:00:49.406 --> 00:00:51.418 but not replicable. 15 00:00:51.418 --> 00:00:56.323 Technology is very replicable, but not nearly as flexible. 16 00:00:57.973 --> 00:00:59.540 And so, what does that mean? 17 00:00:59.540 --> 00:01:01.550 Why does it change the organizational structure? 18 00:01:01.550 --> 00:01:03.630 Well if you think about humans, 19 00:01:03.630 --> 00:01:05.571 the organizational structure of today, 20 00:01:05.571 --> 00:01:09.630 with leaders who cascade their ideas to middle managers 21 00:01:09.630 --> 00:01:12.160 and then move them down into the frontline 22 00:01:12.160 --> 00:01:13.400 makes a lot of sense. 23 00:01:13.400 --> 00:01:17.016 You put smart people near the customer, near the operation, 24 00:01:17.016 --> 00:01:20.230 and they coach the people in that organization. 25 00:01:20.230 --> 00:01:22.730 And that's actually what's driven the BU 26 00:01:22.730 --> 00:01:24.300 and the organizational structures 27 00:01:24.300 --> 00:01:25.970 that you see in many organizations; 28 00:01:25.970 --> 00:01:29.080 lots of BU's geographically located, 29 00:01:29.080 --> 00:01:31.226 whether those are sales territories 30 00:01:31.226 --> 00:01:35.109 or full operating units or operational units. 31 00:01:35.109 --> 00:01:36.870 But think about it for a second. 32 00:01:36.870 --> 00:01:38.800 When we move to the bionic company 33 00:01:38.800 --> 00:01:40.200 and you start to say, 34 00:01:40.200 --> 00:01:43.580 now processes are a mix of technology and people, 35 00:01:43.580 --> 00:01:46.255 would you want your CRM process 36 00:01:46.255 --> 00:01:48.380 to be designed and implemented 37 00:01:48.380 --> 00:01:50.488 in 20 different geographic units? 38 00:01:50.488 --> 00:01:51.516 You wouldn't. 39 00:01:51.516 --> 00:01:52.770 And why wouldn't you? 40 00:01:52.770 --> 00:01:55.180 Well, first, because it's too expensive. 41 00:01:55.180 --> 00:01:58.220 Having 20 different systems is just really expensive 42 00:01:58.220 --> 00:01:59.650 from the technology point of view. 43 00:01:59.650 --> 00:02:03.226 But the second piece is actually also really important; 44 00:02:03.226 --> 00:02:06.017 and that is, in order to make AI work, 45 00:02:06.017 --> 00:02:08.325 you need data at scale to train, 46 00:02:08.325 --> 00:02:11.900 and you can't train AI on just the data 47 00:02:11.900 --> 00:02:15.124 that you get from your CRM system in Central Florida. 48 00:02:15.124 --> 00:02:18.064 And so, technology plus human processes 49 00:02:18.064 --> 00:02:20.170 are the fundamental driver 50 00:02:20.170 --> 00:02:22.740 of why platform organizational structures 51 00:02:22.740 --> 00:02:24.190 emerge in the bionic company. 52 00:02:25.909 --> 00:02:28.550 The second major driver of change 53 00:02:28.550 --> 00:02:30.209 and why bionic companies are different 54 00:02:30.209 --> 00:02:32.210 has to do with advances 55 00:02:32.210 --> 00:02:36.080 in how technology platforms and stacks are constructed, 56 00:02:36.080 --> 00:02:37.830 and in particular, 57 00:02:37.830 --> 00:02:40.616 it has to do with a concept called APIs. 58 00:02:40.616 --> 00:02:42.730 APIs are the interfaces 59 00:02:42.730 --> 00:02:46.256 that allow technology to talk to each other, 60 00:02:46.256 --> 00:02:48.883 and they allow technology to be modular. 61 00:02:48.883 --> 00:02:52.454 But the important part to understand is that with APIs, 62 00:02:52.454 --> 00:02:54.662 the transaction costs 63 00:02:54.662 --> 00:02:58.546 of interacting, one group of human beings to another, 64 00:02:58.546 --> 00:03:00.857 go down dramatically. 65 00:03:00.857 --> 00:03:02.950 Let me give you an example of this. 66 00:03:02.950 --> 00:03:04.459 You all know about Uber. 67 00:03:04.459 --> 00:03:07.220 In the old days, think about the transaction costs 68 00:03:07.220 --> 00:03:09.304 or how hard it was to actually order a cab. 69 00:03:09.304 --> 00:03:11.661 You had to find something in the yellow pages, 70 00:03:11.661 --> 00:03:14.035 pick up a phone, call someone; 71 00:03:14.035 --> 00:03:16.680 they had to call the driver, give them their address, 72 00:03:16.680 --> 00:03:18.640 maybe they got it right, maybe they got it wrong; 73 00:03:18.640 --> 00:03:20.250 and eventually, the driver came to you, 74 00:03:20.250 --> 00:03:22.211 but if they got lost along the way, 75 00:03:22.211 --> 00:03:26.030 well, all of that meant they called back to their dispatcher 76 00:03:26.030 --> 00:03:26.958 who called you; 77 00:03:26.958 --> 00:03:29.948 and eventually, finally, they reached you at the address. 78 00:03:29.948 --> 00:03:31.570 But that took a lot of work. 79 00:03:31.570 --> 00:03:33.907 There were a lot of human transaction costs 80 00:03:33.907 --> 00:03:36.403 in making that interaction happen. 81 00:03:36.403 --> 00:03:39.393 Today, with a platform of Uber or Lyft, 82 00:03:39.393 --> 00:03:42.430 those transaction costs are almost zero. 83 00:03:42.430 --> 00:03:43.940 And so, the fact that technology 84 00:03:43.940 --> 00:03:47.055 allows transaction costs to drop radically, 85 00:03:47.055 --> 00:03:48.548 means many things. 86 00:03:48.548 --> 00:03:51.713 It means that organizational structures can become modular. 87 00:03:51.713 --> 00:03:53.920 You can design small groups of people 88 00:03:53.920 --> 00:03:55.920 who interact with other small groups of people 89 00:03:55.920 --> 00:03:58.629 around your organization in a very fluid way. 90 00:03:58.629 --> 00:04:01.531 It means that ecosystems can be created 91 00:04:01.531 --> 00:04:04.513 so that you can actually interact with other companies. 92 00:04:04.513 --> 00:04:07.450 Think Salesforce as your CRM platform, 93 00:04:07.450 --> 00:04:10.258 or AWS as your cloud platform. 94 00:04:10.258 --> 00:04:12.210 You can interact with those companies 95 00:04:12.210 --> 00:04:13.770 in a much lower-cost way, 96 00:04:13.770 --> 00:04:16.120 or your customers can interact with you 97 00:04:16.120 --> 00:04:17.311 in a much lower-cost way. 98 00:04:17.311 --> 00:04:20.237 It changes the fundamental organizational structure, 99 00:04:20.237 --> 00:04:22.860 from one with high transaction costs, 100 00:04:22.860 --> 00:04:24.230 and thus a rigid structure, 101 00:04:24.230 --> 00:04:27.423 to a much more modular one where ecosystems are embedded. 102 00:04:28.533 --> 00:04:30.435 And then the final piece 103 00:04:30.435 --> 00:04:34.363 has to do with how data and technology 104 00:04:34.363 --> 00:04:36.767 learn differently than humans. 105 00:04:36.767 --> 00:04:39.925 So, as humans, and you can probably all relate to this, 106 00:04:39.925 --> 00:04:44.541 we learn pretty quickly, but we forget just as fast. 107 00:04:44.541 --> 00:04:46.930 And it's hard, as I was talking about before, 108 00:04:46.930 --> 00:04:49.699 for humans to replicate their knowledge to other humans. 109 00:04:49.699 --> 00:04:51.936 Technology is actually different. 110 00:04:51.936 --> 00:04:54.120 Technology isn't quite as flexible 111 00:04:54.120 --> 00:04:55.505 in how it thinks over time, 112 00:04:55.505 --> 00:04:57.872 but if you think about how AI learns, 113 00:04:57.872 --> 00:05:02.020 it builds and builds and builds its knowledge over time. 114 00:05:02.020 --> 00:05:03.050 And the best companies, 115 00:05:03.050 --> 00:05:06.400 the Alibabas, the Amazons of this world, 116 00:05:06.400 --> 00:05:10.800 actually put defined experimentation into their algorithms 117 00:05:10.800 --> 00:05:12.594 so that they're continuously learning. 118 00:05:12.594 --> 00:05:15.101 And every day, they get a little bit better. 119 00:05:15.101 --> 00:05:16.730 And so what that means 120 00:05:16.730 --> 00:05:19.953 is, learning becomes a profound advantage, 121 00:05:19.953 --> 00:05:23.250 a competitive advantage, for the companies of the future: 122 00:05:23.250 --> 00:05:24.768 the bionic companies. 123 00:05:24.768 --> 00:05:27.580 And it's actually a first-mover advantage. 124 00:05:27.580 --> 00:05:29.157 Sometimes people think, 125 00:05:29.157 --> 00:05:30.857 "Okay, we should just be a fast follower. 126 00:05:30.857 --> 00:05:32.687 We'll figure out where other companies are going 127 00:05:32.687 --> 00:05:33.607 on data and AI, 128 00:05:33.607 --> 00:05:34.970 and then we'll catch up." 129 00:05:34.970 --> 00:05:38.919 But the truth is, because of the way machines learn, 130 00:05:38.919 --> 00:05:40.710 you want to get there first, 131 00:05:40.710 --> 00:05:42.570 you want to build that knowledge quickly, 132 00:05:42.570 --> 00:05:43.403 and it will become 133 00:05:43.403 --> 00:05:45.189 a greater and greater advantage over time. 134 00:05:45.189 --> 00:05:47.286 I hope this gives you some food for thought 135 00:05:47.286 --> 00:05:49.140 about the fundamental reasons 136 00:05:49.140 --> 00:05:51.904 as to why the bionic company of tomorrow 137 00:05:51.904 --> 00:05:52.743 is going to be so different 138 00:05:52.743 --> 00:05:55.884 from many of the traditional companies today. 139 00:05:55.884 --> 00:05:57.862 And if you take those into account 140 00:05:57.862 --> 00:06:00.500 and build your own bionic company, 141 00:06:00.500 --> 00:06:04.126 you'll be well on your way to competitive advantage. 142 00:06:04.126 --> 00:06:06.543 (soft music)