WEBVTT 1 00:00:00.240 --> 00:00:02.100 To succeed in the next decade, 2 00:00:02.100 --> 00:00:05.340 companies will have to build high performing teams, 3 00:00:05.340 --> 00:00:07.240 but how exactly do you measure 4 00:00:07.240 --> 00:00:09.600 the quality of those relationships? 5 00:00:09.600 --> 00:00:11.120 Are team members happy, 6 00:00:11.120 --> 00:00:13.970 or are they just smiling through clenched teeth? 7 00:00:13.970 --> 00:00:17.000 What if you could measure these kinds of social interactions 8 00:00:17.000 --> 00:00:21.190 and power dynamics just as you would a balance sheet, 9 00:00:21.190 --> 00:00:24.171 and how might data analytics and AI help? 10 00:00:24.171 --> 00:00:27.250 11 00:00:27.250 --> 00:00:30.820 Human AI is built on the idea of social physics. 12 00:00:30.820 --> 00:00:35.630 line:15% It's the idea that you can look at human organizations 13 00:00:35.630 --> 00:00:37.620 line:15% and characterize what's working 14 00:00:37.620 --> 00:00:40.410 line:15% and what's not working using statistics. 15 00:00:40.410 --> 00:00:41.930 With organizations you want 16 00:00:41.930 --> 00:00:45.196 to do that more or less continuously. 17 00:00:45.196 --> 00:00:48.310 As you might expect, silos are bad. 18 00:00:48.310 --> 00:00:52.710 People working together across organizations, good, 19 00:00:52.710 --> 00:00:55.650 and you can actually watch the patterns of communication 20 00:00:55.650 --> 00:00:58.470 through phone, through face to face, 21 00:00:58.470 --> 00:01:01.550 e-mail's not so important because people tend to ignore it, 22 00:01:01.550 --> 00:01:03.230 but those are the things that show you 23 00:01:03.230 --> 00:01:06.290 the flow of ideas in your organization, 24 00:01:06.290 --> 00:01:08.510 and most organizations don't pay any attention to them. 25 00:01:08.510 --> 00:01:11.290 Somebody else does the phone which is crazy. 26 00:01:11.290 --> 00:01:13.430 There's your most valuable resource, 27 00:01:13.430 --> 00:01:16.063 and you don't even know what's happening with it. 28 00:01:16.063 --> 00:01:18.780 29 00:01:18.780 --> 00:01:20.750 So the sorts of data that you need 30 00:01:20.750 --> 00:01:24.260 to measure of course is how are you talking to yourselves. 31 00:01:24.260 --> 00:01:27.380 Are you actually built into little silos 32 00:01:27.380 --> 00:01:30.880 by district, by country, by goals? 33 00:01:30.880 --> 00:01:33.770 Or are you actually trading ideas 34 00:01:33.770 --> 00:01:35.733 about best practice and what works? 35 00:01:37.680 --> 00:01:40.640 There's really too much data to pay attention to everything, 36 00:01:40.640 --> 00:01:42.250 and how are you going to do it? 37 00:01:42.250 --> 00:01:44.610 That's where some of these AI tools come in. 38 00:01:44.610 --> 00:01:47.280 So for instance, we have ways of having 39 00:01:47.280 --> 00:01:50.670 a computer listen to the conversations in real time, 40 00:01:50.670 --> 00:01:53.370 and measure engagement about the topic. 41 00:01:53.370 --> 00:01:55.790 You can also do other things like that, 42 00:01:55.790 --> 00:01:57.200 like for instance, the patterns 43 00:01:57.200 --> 00:01:59.860 of calls within your organization. 44 00:01:59.860 --> 00:02:01.800 You don't have to look at the content, 45 00:02:01.800 --> 00:02:05.010 just the, you know, does this group talk to that? 46 00:02:05.010 --> 00:02:07.120 And that's something that we do 47 00:02:07.120 --> 00:02:09.513 to be able to sort of diagnose, 48 00:02:10.470 --> 00:02:14.090 essentially, sclerosis within organizations. 49 00:02:14.090 --> 00:02:16.240 Are you talking to yourself, 50 00:02:16.240 --> 00:02:18.763 or are you just in these little echo chambers? 51 00:02:20.290 --> 00:02:23.660 52 00:02:23.660 --> 00:02:25.610 Ideally you're measuring enough 53 00:02:25.610 --> 00:02:30.300 about how things come out in an organization 54 00:02:30.300 --> 00:02:32.080 as a function of these conversations 55 00:02:32.080 --> 00:02:35.300 that you can capture things like power dynamics. 56 00:02:35.300 --> 00:02:38.840 We know that people at the same level 57 00:02:38.840 --> 00:02:41.790 in the organization tend to trade innovations 58 00:02:41.790 --> 00:02:45.100 much more than they trade up, or down, 59 00:02:45.100 --> 00:02:48.030 and obviously that's a problem. 60 00:02:48.030 --> 00:02:49.670 It has to do with power dynamics. 61 00:02:49.670 --> 00:02:51.380 It has to do with reputation, 62 00:02:51.380 --> 00:02:53.463 strategic gaming of the system. 63 00:02:54.760 --> 00:02:57.100 I think you need to set up situations 64 00:02:57.100 --> 00:03:01.090 where that sort of up and down is valued, 65 00:03:01.090 --> 00:03:04.880 things for instance where status is not so obvious, 66 00:03:04.880 --> 00:03:08.080 but you also need to ask how does 67 00:03:08.080 --> 00:03:12.140 the organization of work groups or teams of teams, 68 00:03:12.140 --> 00:03:15.200 how is that working for the things you're trying to do, 69 00:03:15.200 --> 00:03:17.630 and it needs to be very high frequency there. 70 00:03:17.630 --> 00:03:20.260 It needs to be, you know daily, 71 00:03:20.260 --> 00:03:21.830 and I think it's one of the big things 72 00:03:21.830 --> 00:03:25.650 that every organization should be doing aggressively, 73 00:03:25.650 --> 00:03:28.520 is making all of their management structure 74 00:03:28.520 --> 00:03:31.760 really literate in how you use data, 75 00:03:31.760 --> 00:03:35.530 collect data, use it to make decisions, 76 00:03:35.530 --> 00:03:36.950 because if they don't know how to do it, 77 00:03:36.950 --> 00:03:38.878 you're never going to be data driven. 78 00:03:38.878 --> 00:03:40.680 79 00:03:40.680 --> 00:03:44.000 So a few key takeaways are clear. 80 00:03:44.000 --> 00:03:47.000 Break down silos, make sure your team members 81 00:03:47.000 --> 00:03:50.940 are communicating up and down as well as side to side, 82 00:03:50.940 --> 00:03:54.410 and use AI to track trends, measure progress, 83 00:03:54.410 --> 00:03:57.513 and make changes to build better team relationships. 84 00:03:58.570 --> 00:04:01.840 But doing this in practice is tricky. 85 00:04:01.840 --> 00:04:03.910 How do you manage AI to get the most 86 00:04:03.910 --> 00:04:05.700 out of the human beings on your team, 87 00:04:05.700 --> 00:04:08.640 plus the digital technology at hand? 88 00:04:08.640 --> 00:04:11.583 Who should review the data your AI is gathering? 89 00:04:12.550 --> 00:04:16.520 Who'll make decisions about what you're seeing in the data, 90 00:04:16.520 --> 00:04:18.480 and how do you make sure that AI 91 00:04:18.480 --> 00:04:22.580 is working properly versus going off the rails? 92 00:04:22.580 --> 00:04:25.280 In the next video, Sandy shares his insights 93 00:04:25.280 --> 00:04:28.083 on this subject of leading in the age of AI.