1 00:00:09,840 --> 00:00:12,228 Eveline Oehrlich: Hello everybody. This is Eveline 2 00:00:12,302 --> 00:00:17,153 Oehrlich at the DevOps Institute and this is the humans of DevOps 3 00:00:17,227 --> 00:00:20,959 Podcast. Today, Is a very exciting session with a 4 00:00:21,033 --> 00:00:25,063 wonderful gentleman, Jon Clifton, CEO of the Gallup of 5 00:00:25,138 --> 00:00:29,839 Gallup, and the episode title is the Leadership Blind Spot, the 6 00:00:29,914 --> 00:00:34,540 Global Rise of Unhappiness and how Leaders Missed it. I'm very 7 00:00:34,615 --> 00:00:39,690 excited to welcome you here to our podcast. Today, Jon. hello there. 8 00:00:40,260 --> 00:00:42,030 Jon Clifton: Hi, Evelyn. thank you for having me. 9 00:00:42,480 --> 00:00:45,630 Eveline Oehrlich: Yes, excited to be here with you really 10 00:00:45,630 --> 00:00:49,770 honored to be here.Before we get into our conversation, I want to 11 00:00:49,770 --> 00:00:53,850 make sure that our listeners know who you are, and what you 12 00:00:53,850 --> 00:00:57,090 do. So I'm gonna read a little bit of that, because I could not 13 00:00:57,090 --> 00:01:01,560 remember all of this. So Jon is the CEO of Gallup, global 14 00:01:01,560 --> 00:01:04,560 analytics and advice firm. And Jon, I'll ask you a little bit 15 00:01:04,560 --> 00:01:08,220 later on, give us our listeners a little bit of an insight on to 16 00:01:08,220 --> 00:01:12,150 Gallup they might not be familiar with. So Jon's mission 17 00:01:12,180 --> 00:01:15,720 is to build the world's official statistics for everything 18 00:01:15,720 --> 00:01:20,790 related to work and life, to put people worldwide in touch with 19 00:01:20,790 --> 00:01:23,910 their strength and to help organizations great thriving 20 00:01:23,910 --> 00:01:27,780 workplaces. Jon is a non resident Senior Fellow at Baylor 21 00:01:27,780 --> 00:01:31,440 University's Institute for Studies of religion. He serves 22 00:01:31,440 --> 00:01:34,530 on the board of directors for Gallup and young professionals 23 00:01:34,560 --> 00:01:38,550 in foreign policy, and has also served on the boards of Meridian 24 00:01:38,580 --> 00:01:43,020 International Center, street wise partners, chess challenge 25 00:01:43,050 --> 00:01:47,670 in DC, and find dear, I think that's fine Dyer, I think that's 26 00:01:47,670 --> 00:01:51,540 how you say it. Because of his expertise, Jon is often called 27 00:01:51,540 --> 00:01:54,630 to speak about gallops research to international associations, 28 00:01:54,660 --> 00:01:58,290 including the United Nations International Association for 29 00:01:58,290 --> 00:02:01,620 official statistics and the World Bank. He has been 30 00:02:01,650 --> 00:02:05,760 interviewed on BBC News C spans Washington journal, and Al 31 00:02:05,760 --> 00:02:09,750 Jazeera, and has testified in front of the US Congress, who 32 00:02:09,750 --> 00:02:12,240 are the state of American small business and entrepreneurship. 33 00:02:12,750 --> 00:02:16,380 This is fantastic that you are here, Jon, take taking your time 34 00:02:16,410 --> 00:02:19,410 out of your day to be with us here at the DevOps Institute. 35 00:02:19,680 --> 00:02:22,560 Thank you very much. Again, we're honored to have you on our 36 00:02:22,560 --> 00:02:23,310 podcast. 37 00:02:24,360 --> 00:02:25,200 Jon Clifton: It's great to be here. 38 00:02:25,470 --> 00:02:28,530 Eveline Oehrlich: Yeah. So Gallup, of course, I am reached. 39 00:02:28,560 --> 00:02:31,980 I'm in research, and I have enjoyed Gallup research for 40 00:02:31,980 --> 00:02:35,520 quite a while, even as I was at Forrester not really competition 41 00:02:35,520 --> 00:02:38,280 to Gallup, because your work is very different from what we did 42 00:02:38,280 --> 00:02:42,120 at Forrester. But tell our listeners who might not be 43 00:02:42,120 --> 00:02:45,330 familiar with Gallup. What does Gallup actually do? 44 00:02:46,200 --> 00:02:48,630 Jon Clifton: At the core of everything we do is we help 45 00:02:48,630 --> 00:02:52,170 people be heard, and we help leaders listen and understand 46 00:02:52,170 --> 00:02:55,710 their constituencies. We do that at the individual level, at the 47 00:02:55,710 --> 00:03:00,510 organizational level and at the global level. And for the past 48 00:03:00,540 --> 00:03:03,900 80 years, we've been doing macro level listening, where we 49 00:03:03,900 --> 00:03:07,590 conduct surveys and ask how people feel about their lives, 50 00:03:07,620 --> 00:03:11,040 about the institutions in the countries where they live. And 51 00:03:11,040 --> 00:03:14,250 more recently, we've been helping organizations create 52 00:03:14,250 --> 00:03:19,260 thriving workplaces by listening to their colleagues and also to 53 00:03:19,260 --> 00:03:22,620 their customer bases. And the other thing is, is that we help 54 00:03:22,620 --> 00:03:25,440 build strengths based organizations, this is to 55 00:03:25,440 --> 00:03:30,150 understand how different people are, and also to help them grow 56 00:03:30,180 --> 00:03:33,810 individually, through their strengths. So those those are 57 00:03:33,810 --> 00:03:35,400 the different things that Gallup does. 58 00:03:36,540 --> 00:03:38,910 Eveline Oehrlich: So one of the things you're doing is all you 59 00:03:38,910 --> 00:03:42,780 have done is Clifton Strengths. I call it an assessment, but 60 00:03:42,780 --> 00:03:45,840 it's probably an analysis, right? Give us a couple of 61 00:03:45,840 --> 00:03:50,760 sentences on what that is. Because I have not done it yet. 62 00:03:50,940 --> 00:03:54,150 But my colleague AB has done as we just talked in our pre 63 00:03:54,180 --> 00:03:58,200 podcast, I will do it. Tell us a little bit about what that is. 64 00:03:58,800 --> 00:04:01,500 Jon Clifton: Yeah, so if you think back to ancient 65 00:04:01,560 --> 00:04:04,830 philosophy, almost every single philosopher kind of agreed that 66 00:04:04,860 --> 00:04:08,610 the key to a great life, is to do it through your strengths. 67 00:04:08,640 --> 00:04:12,450 Even modern philosophers like the business thinker Peter 68 00:04:12,450 --> 00:04:16,170 Drucker said something almost identical around the key to a 69 00:04:16,260 --> 00:04:19,830 successful career is through your strengths. And while all of 70 00:04:19,830 --> 00:04:23,130 them agreed that's what was the key to a great life, nobody 71 00:04:23,130 --> 00:04:27,510 really said where to start. And Don Clifton decades ago said he 72 00:04:27,510 --> 00:04:30,120 was going to make it his mission in the world to help people 73 00:04:30,120 --> 00:04:33,360 figure out a way to get started. And that's when he created 74 00:04:33,360 --> 00:04:36,480 StrengthsFinder, which we recently renamed to Clifton 75 00:04:36,480 --> 00:04:40,650 Strengths. He created an assessment that people could go 76 00:04:40,650 --> 00:04:42,870 through, and a lot of times people confuse it with a 77 00:04:42,870 --> 00:04:46,110 personality assessment. That's not what it is. It is a 78 00:04:46,110 --> 00:04:50,010 development accelerator so that people can understand what is it 79 00:04:50,010 --> 00:04:54,030 that makes them unique, and how can they at a very highly 80 00:04:54,030 --> 00:04:59,790 individualized type of way how can they grow because everybody 81 00:04:59,820 --> 00:05:02,160 grew Rosen develops very differently. So that's what it 82 00:05:02,160 --> 00:05:05,040 is. It's an assessment that we make available to anyone on our 83 00:05:05,040 --> 00:05:09,210 website, they go through this kind of 45 minute assessment. 84 00:05:09,210 --> 00:05:12,480 And at the end, it says, Here are the behaviors that and 85 00:05:12,480 --> 00:05:13,770 talents that make you great. 86 00:05:14,550 --> 00:05:17,070 Eveline Oehrlich: Fantastic, I will do it, I have it on my 87 00:05:17,070 --> 00:05:19,650 plan, I've had it on my bucket list for actually quite a long 88 00:05:19,650 --> 00:05:23,460 time. I just have not done it. While I was at Hewlett Packard 89 00:05:23,460 --> 00:05:25,800 many, many years ago, we did the Myers Briggs, I'm sure you 90 00:05:25,800 --> 00:05:29,280 familiar with that, of course, it's very, very different. So 91 00:05:29,280 --> 00:05:32,520 I'm very curious to do it. Anyway. That's not why we're 92 00:05:32,520 --> 00:05:36,660 here. We're actually here because of this wonderful book 93 00:05:36,690 --> 00:05:40,710 called blind spot. I actually have read this book during my 94 00:05:40,710 --> 00:05:43,920 vacation here in South France. And I have to tell you, it was 95 00:05:43,920 --> 00:05:48,030 fascinating. It was stunning. It was daunting, it was thought 96 00:05:48,030 --> 00:05:52,830 provoking. And it was actually for me, a little bit scary, 97 00:05:52,830 --> 00:05:57,420 because I love my job. I love what I do. I've always loved 98 00:05:57,420 --> 00:05:59,880 what I do. I'm extremely engaged, and those who were 99 00:05:59,880 --> 00:06:04,710 working with me, are very engaged. And I'm just amazed at 100 00:06:04,740 --> 00:06:07,590 all the data in the book and all the details you have gathered. 101 00:06:07,620 --> 00:06:12,900 So the most serious finding, of course, is that almost every 102 00:06:12,900 --> 00:06:17,280 leader in the world has missed that there are huge challenges 103 00:06:17,280 --> 00:06:20,040 in that there are a lot of unhappy. There's a lot of 104 00:06:20,040 --> 00:06:24,480 unhappy people, right. So first of all, congratulations to the 105 00:06:24,480 --> 00:06:29,520 book, it launched September 13. This year, fantastic, great 106 00:06:29,520 --> 00:06:33,300 book, lots of success. I wish you lots of success, I know it 107 00:06:33,300 --> 00:06:38,490 will have lots of success. Tell me about what led you to this 108 00:06:38,490 --> 00:06:40,410 research and write the book. 109 00:06:41,220 --> 00:06:43,590 Jon Clifton: Well, public and private sector leaders still 110 00:06:43,590 --> 00:06:48,720 today are focused on rational indicators, things like whether 111 00:06:48,720 --> 00:06:52,050 or not people have jobs through unemployment indicators, GDP per 112 00:06:52,050 --> 00:06:55,530 capita, whether or not companies are making more profit. But what 113 00:06:55,530 --> 00:06:58,560 they don't focus on are indicators about how people 114 00:06:58,560 --> 00:07:01,680 feel. And that's a problem. Because what we've learned 115 00:07:01,680 --> 00:07:05,940 through behavioral economics now is that decision making for 116 00:07:05,940 --> 00:07:10,170 humans is not necessarily rational. In fact, most of it is 117 00:07:10,170 --> 00:07:14,340 actually emotional yet, we don't really follow indicators about 118 00:07:14,340 --> 00:07:16,980 how people feel. And we think that's a problem. So a little 119 00:07:16,980 --> 00:07:19,500 over 15 years ago, we said we're gonna create the world's 120 00:07:19,500 --> 00:07:22,290 official statistics for how people feel. And we started to 121 00:07:22,290 --> 00:07:24,330 ask people, do you have a lot of stress? Do you have a lot of 122 00:07:24,330 --> 00:07:28,110 anger? Do you have a lot of sadness, because just like today 123 00:07:28,110 --> 00:07:31,110 that we can quantify whether or not an economy is growing or 124 00:07:31,110 --> 00:07:34,680 contracting, we also want to know, if we could pick up if 125 00:07:34,710 --> 00:07:37,560 stress was increasing, or if the world was getting sad, or if it 126 00:07:37,560 --> 00:07:41,550 was getting angrier. And in our first about five to six years of 127 00:07:41,550 --> 00:07:46,290 tracking this, we effectively saw no change. We saw kind of 128 00:07:46,320 --> 00:07:48,960 what we thought in terms of conventional wisdom, which was 129 00:07:48,960 --> 00:07:52,860 that in places that were affected by war, or an economic 130 00:07:52,860 --> 00:07:57,330 crisis, people felt a lot more misery. But about 10 years ago, 131 00:07:57,330 --> 00:07:59,670 we started to see a trend that really started to concern us, 132 00:07:59,670 --> 00:08:03,840 which was the fact that anger, stress, sadness, physical pain, 133 00:08:03,840 --> 00:08:09,120 and worry began increasing all over the world. And it was 134 00:08:09,120 --> 00:08:11,610 happening in places like India, it was happening in places like 135 00:08:11,610 --> 00:08:16,890 China, Brazil, Mexico, almost at exactly the same rate. So we 136 00:08:16,890 --> 00:08:20,220 felt like it was a good time to alert the world about this very 137 00:08:20,220 --> 00:08:22,950 concerning trend and release a book on it. And that's what 138 00:08:22,950 --> 00:08:23,550 we're doing now. 139 00:08:24,990 --> 00:08:28,470 Eveline Oehrlich: So, the type of research you do as a 140 00:08:28,470 --> 00:08:31,590 researcher myself, of course, I'm curious. And in the book it 141 00:08:31,590 --> 00:08:35,010 describes I want you to share with our listeners, how do you 142 00:08:35,010 --> 00:08:39,420 actually go about researching this whole unhappiness or 143 00:08:39,420 --> 00:08:41,730 happiness? I know there's a whole bunch of things, and I 144 00:08:41,730 --> 00:08:45,270 don't want you to give away too much. But first question, how do 145 00:08:45,270 --> 00:08:49,440 you actually do your research? And second question, once you 146 00:08:49,470 --> 00:08:52,710 have done this research, where are you? And how are you 147 00:08:52,710 --> 00:08:56,340 actually sharing that and going forward with besides the book? 148 00:08:57,060 --> 00:09:01,050 Unknown: Well, so the way that we do this research is conducted 149 00:09:01,050 --> 00:09:03,720 through surveys. And for some reason, a lot of people get 150 00:09:03,750 --> 00:09:06,450 uncomfortable when we talk about surveys, I think they think that 151 00:09:06,450 --> 00:09:10,290 individuals may not know how to accurately reflect how their 152 00:09:10,290 --> 00:09:12,390 lives are going. But interestingly enough, most of 153 00:09:12,390 --> 00:09:15,210 the data that we actually consume, at least in terms of 154 00:09:15,450 --> 00:09:18,210 macro level indicators are actually conducted by surveys, 155 00:09:18,210 --> 00:09:21,690 for example, unemployment is one of the most relied upon 156 00:09:21,690 --> 00:09:25,830 statistics internationally. And oftentimes, people think that 157 00:09:25,830 --> 00:09:28,230 that's some sort of headcount or that companies submit their 158 00:09:28,230 --> 00:09:31,890 payroll. It's not the case. Unemployment is measured by a 159 00:09:31,890 --> 00:09:35,310 massive survey in the United States. 60,000 people per month 160 00:09:35,310 --> 00:09:38,460 are interviewed. And after about an hour there, they're asked, Do 161 00:09:38,460 --> 00:09:41,250 you have a job? We effectively did the same thing. But instead 162 00:09:41,250 --> 00:09:44,520 of saying, Do you have a job, we just ask people, How much stress 163 00:09:44,520 --> 00:09:47,700 do you have how much anger and there are a lot of people to 164 00:09:47,700 --> 00:09:50,640 that goal? Is it accurate? Do people know how much stress they 165 00:09:50,640 --> 00:09:54,660 have? They do. And you can actually test this through 166 00:09:54,660 --> 00:09:57,360 things like brain scans, you can actually ask their friends and 167 00:09:57,360 --> 00:09:59,520 if you say to him, is your friend experiencing a lot of 168 00:09:59,520 --> 00:10:02,880 stress and In a lot of times, they are more times than not, 169 00:10:02,880 --> 00:10:07,020 they're very accurate. So people are in touch with how they feel, 170 00:10:07,020 --> 00:10:11,580 and they can accurately report it to a total stranger. And 171 00:10:11,580 --> 00:10:14,160 speaking of its total strangers, so the way that we capture this 172 00:10:14,310 --> 00:10:17,250 in roughly 140 countries every single year is that in 40 173 00:10:17,250 --> 00:10:20,310 countries, we do phone calls, we call people's mobile phones, we 174 00:10:20,310 --> 00:10:22,860 call their landlines, and then we have a conversation with 175 00:10:22,860 --> 00:10:25,440 them. But for the other 100 countries, because not everyone 176 00:10:25,440 --> 00:10:28,650 in the world has a phone, we do face to face interviewing. And 177 00:10:28,650 --> 00:10:32,100 this is not just in capital cities or major economic hubs. 178 00:10:32,310 --> 00:10:34,890 These are truly nationally representative samples, meaning 179 00:10:34,920 --> 00:10:38,040 oftentimes the interviewers that we work with, will have to even 180 00:10:38,040 --> 00:10:41,820 drive eight to nine hours in order to conduct just a handful 181 00:10:41,820 --> 00:10:45,630 of interviews, to ask people how their lives are going. So this 182 00:10:45,630 --> 00:10:48,750 is a really extensive process that we undertake in order to 183 00:10:48,750 --> 00:10:52,380 make sure that we're capturing the right kind of information. 184 00:10:53,400 --> 00:10:55,800 Eveline Oehrlich: So we can envision, and I was seeing, I 185 00:10:55,800 --> 00:10:58,440 can see the the picture in the book, a gentleman in Indonesia, 186 00:10:58,470 --> 00:11:01,650 who is going actually into one of the heads in Indonesia, I've 187 00:11:01,650 --> 00:11:05,910 actually traveled there myself, and has a conversation with a 188 00:11:05,910 --> 00:11:08,760 lady, I think asking her the variety of questions. And so you 189 00:11:08,760 --> 00:11:11,430 travel across, you have folks who travel across and they are 190 00:11:11,430 --> 00:11:13,830 local, and they speak the language to actually do that. 191 00:11:13,830 --> 00:11:17,130 Wow, very different from the we do a lot of surveys also at the 192 00:11:17,130 --> 00:11:20,790 DevOps Institute. But of course, you're absolutely right survey, 193 00:11:20,790 --> 00:11:24,720 sometimes we see some biases, and we see some challenges. Of 194 00:11:24,720 --> 00:11:28,440 course, our sample size is nearly not nearly as as large as 195 00:11:28,440 --> 00:11:32,400 your as your sample size. Fantastic. Okay, let's, let's 196 00:11:32,400 --> 00:11:36,000 get into the let's get into the, as we call it, the depth of the 197 00:11:36,000 --> 00:11:42,300 book. And one thing, which really was was important to me, 198 00:11:42,360 --> 00:11:46,050 and what I what I realized, because I believe I'm the only 199 00:11:47,460 --> 00:11:50,760 optimist, German optimist, I think, because Germans are not 200 00:11:50,760 --> 00:11:53,490 very optimistic. And if my German colleagues are out there 201 00:11:53,490 --> 00:11:56,700 who want to get some, get some love on optimism, reach out to 202 00:11:56,700 --> 00:12:01,200 me, but the book discusses this topic of negative emotion index. 203 00:12:02,520 --> 00:12:05,250 across and you mentioned it already, you asked about anger, 204 00:12:05,250 --> 00:12:08,970 stress, sadness, worry, physical pain and sadness, which has been 205 00:12:08,970 --> 00:12:14,190 rising over the past decade. So a couple of things to discuss. 206 00:12:14,520 --> 00:12:18,450 First of all, what does that mean that negative emotion index 207 00:12:18,480 --> 00:12:21,300 elaborate a little bit on that? What what are you asking those 208 00:12:21,300 --> 00:12:24,720 folks? Are you saying, Are you? Are you sad? So yes, no 209 00:12:24,840 --> 00:12:29,220 question, right? Help us understand that negative emotion 210 00:12:29,220 --> 00:12:32,340 index, and then there is a positive emotion index as well. 211 00:12:32,340 --> 00:12:35,760 So if you can elaborate on that, that would be also wonderful. 212 00:12:36,060 --> 00:12:39,300 Jon Clifton: Absolutely. So before I say this, I should also 213 00:12:39,300 --> 00:12:43,410 note that what we are measuring is very difficult. And we are 214 00:12:43,410 --> 00:12:47,400 only 15 years into this work. Where as you take indicators 215 00:12:47,400 --> 00:12:50,790 like GDP are a lot of people feel that the birth of GDP took 216 00:12:50,790 --> 00:12:53,760 place in the late 1930s, when Simon Kuznets approached 217 00:12:53,760 --> 00:12:58,650 Congress and said, Hey, we have an indicator to basically figure 218 00:12:58,650 --> 00:13:02,490 out, is the economy growing? Or is it getting smaller? We're 219 00:13:02,490 --> 00:13:05,430 doing the same in terms of how people's lives are going. So you 220 00:13:05,430 --> 00:13:09,330 know, GDP still almost 100 years in has its imperfections. So 221 00:13:09,330 --> 00:13:12,810 it's not to say that this work that we are doing is yet 222 00:13:12,810 --> 00:13:15,690 perfect. So there may be imperfections, but we're doing 223 00:13:15,690 --> 00:13:18,900 our best. And so the way that we've determined this is based 224 00:13:18,930 --> 00:13:23,670 on extensive research by academics like Ed Diener and 225 00:13:23,730 --> 00:13:28,350 Nobel laureate Danny Kahneman, where we said like, what is it 226 00:13:28,380 --> 00:13:31,440 that makes a great life? Or how do you define well being, and we 227 00:13:31,440 --> 00:13:34,650 did it with two constructs. One is how people see their lives. 228 00:13:34,890 --> 00:13:38,160 And the other is how people live their lives. So how people see 229 00:13:38,160 --> 00:13:41,820 their lives is kind of an overall reflection of everything 230 00:13:41,820 --> 00:13:44,790 that's taken place in their life. And it taps in to what 231 00:13:44,790 --> 00:13:48,180 Danny Kahneman who say, is the remembering mind. And the way 232 00:13:48,180 --> 00:13:51,090 that we capture that is to ask people rate your life on a scale 233 00:13:51,090 --> 00:13:54,540 of zero to 10, where 10 is the best possible life. And zero is 234 00:13:54,540 --> 00:13:57,990 the worst imaginable life. Where do you stand today, the results 235 00:13:57,990 --> 00:14:00,840 of that have been made famous people call it happiness, it's 236 00:14:00,840 --> 00:14:04,620 probably more of a measure of contentment. But the people who 237 00:14:04,620 --> 00:14:07,680 on average rate their lives the best are people that live in the 238 00:14:07,680 --> 00:14:10,230 Nordic countries. It's why you hear that Denmark or Finland, 239 00:14:10,500 --> 00:14:13,260 are oftentimes the happiest countries in the world. Again, 240 00:14:13,260 --> 00:14:16,290 the brand is happiness. But it's probably more accurate to say 241 00:14:16,290 --> 00:14:18,870 that the most content the people who rate their lives the worst 242 00:14:18,870 --> 00:14:22,320 are places like Afghanistan. In our last survey in Afghanistan 243 00:14:22,320 --> 00:14:25,860 and 2021. We did face to face interviews, women were 244 00:14:25,860 --> 00:14:29,280 interviewing women, the Taliban allowed it. And we saw some of 245 00:14:29,280 --> 00:14:31,740 the worst life ratings not just that we've ever seen in the 246 00:14:31,740 --> 00:14:34,290 history of our tracking of Afghanistan, but also in the 247 00:14:34,290 --> 00:14:37,770 history of our tracking of our entire global database. So you 248 00:14:37,770 --> 00:14:40,950 can also see there that it does confirm some of conventional 249 00:14:40,950 --> 00:14:43,650 wisdom that we know things aren't great in Afghanistan. And 250 00:14:43,650 --> 00:14:47,340 we know probably even based on external indicators like GDP per 251 00:14:47,340 --> 00:14:50,010 capita, that people who live in the Nordic countries are doing 252 00:14:50,010 --> 00:14:52,740 quite well. But on the other side of the ledger, is how 253 00:14:52,740 --> 00:14:56,610 people live their lives. And this is more in the moment on 254 00:14:56,610 --> 00:14:59,310 whether or not someone is feeling stress. Whether or not 255 00:14:59,310 --> 00:15:02,760 somebody is laughing and smiling a lot. Now, ideally, we would 256 00:15:02,760 --> 00:15:05,550 have some sort of buzzer that attached to everyone in 257 00:15:05,550 --> 00:15:08,820 humanity. And we could sort of ask them right at that moment, 258 00:15:08,820 --> 00:15:12,690 say, How do you feel, or that we would be able to get to do some 259 00:15:12,690 --> 00:15:16,050 sort of cortisol test so we can actually see their levels of 260 00:15:16,050 --> 00:15:19,500 stress. Unfortunately, we just don't have the ability to do 261 00:15:19,500 --> 00:15:23,340 that. And so the next best thing we can do is say, please tell me 262 00:15:23,340 --> 00:15:27,750 about all day yesterday, did you feel a lot of the following? How 263 00:15:27,750 --> 00:15:30,480 about anger, stress, sadness, physical pain, or worry, those 264 00:15:30,480 --> 00:15:33,000 are the negative emotions. And then we also asked about 265 00:15:33,000 --> 00:15:35,550 positive emotions, whether or not people felt well rested, 266 00:15:35,550 --> 00:15:38,160 whether or not they were treated with respect, laughed and 267 00:15:38,160 --> 00:15:42,330 smiled, experienced enjoyment, or learned or did something 268 00:15:42,330 --> 00:15:45,300 interesting. So those 10 indicators, five, negative five 269 00:15:45,300 --> 00:15:48,810 positive are how people are experiencing life each day. And 270 00:15:48,810 --> 00:15:51,120 the reason we have to measure them differently, is because 271 00:15:51,120 --> 00:15:53,400 they have different drivers. And we can see that they have 272 00:15:53,400 --> 00:15:56,880 different outcomes. For example, the people who say that they 273 00:15:56,880 --> 00:16:00,270 laugh and smile a lot, and also experienced the most enjoyment 274 00:16:00,300 --> 00:16:03,030 or people in Latin America, people in Latin America know how 275 00:16:03,030 --> 00:16:06,270 to have fun, arguably, more than anyone else in the world. And we 276 00:16:06,270 --> 00:16:09,450 can see it in our data. On the other hand, in terms of negative 277 00:16:09,450 --> 00:16:13,320 emotions, this has been true for 15 straight years, the region of 278 00:16:13,320 --> 00:16:15,960 the world that expresses the most anger, the most sadness, 279 00:16:15,960 --> 00:16:19,200 the most physical pain is the Middle East, Iraq and Iran are 280 00:16:19,200 --> 00:16:24,090 oftentimes at the very top. And also places like Afghanistan. So 281 00:16:24,090 --> 00:16:27,810 also in Afghanistan, we saw the highest negative emotions, on 282 00:16:27,840 --> 00:16:30,180 all those indicators that we've ever seen in the history of our 283 00:16:30,180 --> 00:16:33,210 database, not just for Afghanistan, but also for 284 00:16:33,780 --> 00:16:37,110 negative emotions. So those are the two different constructs 285 00:16:37,110 --> 00:16:39,750 that we measure. One is how people see their lives. And the 286 00:16:39,750 --> 00:16:42,360 other is how they live their lives, which we also break up 287 00:16:42,360 --> 00:16:45,150 into two different constructs positive emotions and negative 288 00:16:45,150 --> 00:16:45,870 emotions. 289 00:16:46,560 --> 00:16:50,310 Eveline Oehrlich: Fascinating. So when I think of Finland, I 290 00:16:50,340 --> 00:16:53,940 actually don't remember them smiling a lot. So how can they 291 00:16:53,940 --> 00:16:58,050 be the happiest people in the world? Right? I think you go 292 00:16:58,050 --> 00:17:02,160 into that in more detail in the book. Are they are they're not 293 00:17:02,160 --> 00:17:04,350 really happy to content? Right? 294 00:17:04,650 --> 00:17:07,980 Jon Clifton: Yeah, there's a really cool kind of study that I 295 00:17:07,980 --> 00:17:10,860 think a journalist did. And they went and asked people on the 296 00:17:10,860 --> 00:17:14,490 streets in Finland, they said, Hey, Finland, was just announced 297 00:17:14,490 --> 00:17:16,740 that they are the happiest country in the world. What do 298 00:17:16,740 --> 00:17:19,530 you think about that? And people on the street, were saying, I'm 299 00:17:19,530 --> 00:17:22,710 not very happy. Those results don't make sense to me. In fact, 300 00:17:22,710 --> 00:17:25,980 one minister actually said, Well, if we're the happiest 301 00:17:25,980 --> 00:17:28,740 country in the world, I feel sorry for all the other 302 00:17:28,740 --> 00:17:33,870 countries. And I think that's because of the brand happiness. 303 00:17:34,110 --> 00:17:36,600 And if you read the World Happiness Report that actually 304 00:17:36,600 --> 00:17:39,090 launches this and they use Gallup data. So the data I'm 305 00:17:39,090 --> 00:17:42,750 referring to are the data that they use, are the life rating 306 00:17:42,780 --> 00:17:46,470 data. And they say that while this might not be happiness that 307 00:17:46,470 --> 00:17:49,410 we're capturing, it might actually be subjective well 308 00:17:49,410 --> 00:17:52,860 being or contentment, they said, the reason that we use the word 309 00:17:52,860 --> 00:17:56,370 happiness is because it's what gets the most attention. Sure. 310 00:17:56,370 --> 00:17:59,670 And if they said, we have the world contentment report, people 311 00:17:59,670 --> 00:18:02,550 probably wouldn't read it. And I agree with him. The reason I 312 00:18:02,550 --> 00:18:07,710 agree with him is because I did report myself on Gallup dot coms 313 00:18:07,710 --> 00:18:12,210 website, or gallops website and actually found exactly what they 314 00:18:12,210 --> 00:18:15,120 found, which is I wrote an article use words like well 315 00:18:15,120 --> 00:18:19,800 being thriving, contentment, and people don't read it. And when 316 00:18:19,800 --> 00:18:22,440 you switch the word to happiness, all of a sudden, 317 00:18:22,440 --> 00:18:25,800 people are much more likely to pick it up. So even if you 318 00:18:26,010 --> 00:18:29,190 remind people in the methodology that we're actually may not be 319 00:18:29,190 --> 00:18:32,130 capturing happiness, we're kind of getting more of contentment. 320 00:18:33,060 --> 00:18:36,480 They're just a lot more likely to read it. So I think it is 321 00:18:36,480 --> 00:18:38,640 important that you have to get the branding, right, if you want 322 00:18:38,640 --> 00:18:41,190 to make sure that the information is consumed, because 323 00:18:41,190 --> 00:18:44,070 unfortunately, people do judge a book by its cover. 324 00:18:44,880 --> 00:18:47,580 Eveline Oehrlich: Absolutely. And we are the DevOps Institute 325 00:18:47,580 --> 00:18:51,210 sometimes have that same challenge. Because when people 326 00:18:51,210 --> 00:18:54,000 think about the DevOps Institute in the word DevOps, they all 327 00:18:54,000 --> 00:18:58,800 think we're geeks, and we all we do is write code. And IT folks 328 00:18:58,800 --> 00:19:02,250 Well, some of us are, and our community is very large. We have 329 00:19:02,250 --> 00:19:06,480 over 90,000 members and followers. Not all of them are 330 00:19:06,480 --> 00:19:09,750 geeks. There's a lot of people out there White, who who have I 331 00:19:09,750 --> 00:19:12,810 don't think so. And then the word Institute is another one of 332 00:19:12,810 --> 00:19:16,470 those words. So we're trying to think about some changes in 333 00:19:16,470 --> 00:19:23,940 words as well. All right, so your most surprising finding for 334 00:19:23,940 --> 00:19:27,870 yourself on the report when when you step back, and you look at 335 00:19:27,870 --> 00:19:32,400 the book, and you go, Jon, this this, this really blew, this 336 00:19:32,400 --> 00:19:34,350 really blew me away. What was it? 337 00:19:34,680 --> 00:19:37,260 Jon Clifton: Well, there were four of them. And there's an 338 00:19:37,260 --> 00:19:41,700 entire section dedicated to four of the most surprising findings 339 00:19:41,700 --> 00:19:45,990 because we at Gallup can't fully make sense of what they mean. 340 00:19:46,380 --> 00:19:49,380 And I'll start with the first one, which is when we started 341 00:19:49,380 --> 00:19:53,940 tracking emotions, we knew based on previous research that you 342 00:19:53,940 --> 00:19:56,790 have to measure positive and negative emotions separately. 343 00:19:57,030 --> 00:20:02,070 Why because they measure very different things. For example, 344 00:20:02,070 --> 00:20:05,580 if somebody attends a funeral, they may experience especially 345 00:20:05,580 --> 00:20:08,730 of, you know, potentially a grandparent that died of old 346 00:20:08,730 --> 00:20:11,550 age, they may experience a lot of sadness and a lot of 347 00:20:11,550 --> 00:20:14,520 loneliness, but they actually might laugh a lot too. Because 348 00:20:14,670 --> 00:20:17,700 as the family gets together and remembers the good times that 349 00:20:17,700 --> 00:20:21,390 they had with them, they can experience positive emotions as 350 00:20:21,390 --> 00:20:25,740 well. So it's really important to measure both constructs, 351 00:20:25,740 --> 00:20:29,850 because we, as humans, process them differently. So we started 352 00:20:29,850 --> 00:20:33,690 doing that. And interesting, the results at a national level were 353 00:20:33,930 --> 00:20:36,990 looked very similar to what the previous research said, Why? 354 00:20:37,290 --> 00:20:41,010 Because I was on my way to Singapore. And I started looking 355 00:20:41,010 --> 00:20:43,350 at our data, and I wanted to look at the positive and 356 00:20:43,350 --> 00:20:45,840 negative emotions that we're tracking. And interestingly 357 00:20:45,840 --> 00:20:48,720 enough, I pulled up the positive emotions data and saw that 358 00:20:48,720 --> 00:20:52,590 positive emotions were dropping. And in fact, Singapore was 359 00:20:52,590 --> 00:20:55,440 reporting the least amount of positive emotions in the world. 360 00:20:55,620 --> 00:20:57,960 So instinctively, I thought, well, if positive emotions are 361 00:20:57,960 --> 00:21:01,590 going down, negative emotions must be going up. And so I 362 00:21:01,620 --> 00:21:04,230 looked at the negative emotions data, and it wasn't the case 363 00:21:04,230 --> 00:21:08,550 negative emotions were also going down. And again, this is 364 00:21:08,550 --> 00:21:11,730 because both of these constructs have to be measured differently, 365 00:21:11,730 --> 00:21:15,540 because they don't necessarily move together. And so we 366 00:21:15,540 --> 00:21:18,630 actually started reporting the data very differently. And we 367 00:21:18,630 --> 00:21:22,500 said, let's look at collective emotions, who reports the most 368 00:21:22,500 --> 00:21:26,220 across the board and who reports the least. And what we found is, 369 00:21:26,220 --> 00:21:28,350 is that the country that reported the most at the time 370 00:21:28,350 --> 00:21:31,710 was the Philippines, followed by almost every country in Latin 371 00:21:31,710 --> 00:21:35,190 America. And the country that reported almost no emotions at 372 00:21:35,190 --> 00:21:39,810 all was Singapore. And it actually caused kind of this 373 00:21:39,810 --> 00:21:43,290 article to go viral. Because then people started referring to 374 00:21:44,130 --> 00:21:46,860 Singapore as the emotionless society, which I don't think was 375 00:21:46,860 --> 00:21:50,400 necessarily fair to brand the country as because so much of 376 00:21:50,400 --> 00:21:54,330 what Singapore has done, is helped put together I think, one 377 00:21:54,330 --> 00:21:58,140 of the best run societies in the world. They excel at GDP per 378 00:21:58,140 --> 00:22:01,020 capita, they sell at having one of the lowest unemployment in 379 00:22:01,020 --> 00:22:04,800 the world. They excel at virtually everything, except on 380 00:22:04,800 --> 00:22:08,970 this particular indicator. But after the story went viral, and 381 00:22:08,970 --> 00:22:11,430 it was on the cover of the Straits Times three days in a 382 00:22:11,430 --> 00:22:15,990 row. And the minister actually wrote a scathing piece about it 383 00:22:15,990 --> 00:22:21,330 as well. But we noticed that in our following surveys, that all 384 00:22:21,330 --> 00:22:24,300 the indicators went up, people started feeling a lot more 385 00:22:24,300 --> 00:22:28,590 positive in life. And we don't know why. And so in fact, 386 00:22:28,620 --> 00:22:31,830 Singapore started becoming one of the higher ranked countries 387 00:22:31,890 --> 00:22:35,430 in the world for positive emotions. And so it's one of the 388 00:22:35,430 --> 00:22:38,190 questions that remains is why did this take place? And could 389 00:22:38,190 --> 00:22:40,860 it have been some sort of flaw in gallops methodology? We could 390 00:22:40,860 --> 00:22:44,430 certainly be open to that when somebody says, you know, we can 391 00:22:44,430 --> 00:22:48,450 tell you with 95% confidence about the results of our survey, 392 00:22:48,450 --> 00:22:51,210 what they mean is that one out of 20 times, they could fall 393 00:22:51,210 --> 00:22:54,390 outside of that confidence interval. So was that the case? 394 00:22:54,930 --> 00:22:58,590 We're not entirely sure. But what we are interested in is 395 00:22:58,590 --> 00:23:01,800 what can we learn? What can the world learn from Singapore in 396 00:23:01,800 --> 00:23:04,680 terms of how those data changed overnight, because if it was 397 00:23:04,680 --> 00:23:08,190 something meaningful, then the world would have a lot to learn 398 00:23:08,190 --> 00:23:11,040 from on how we can all live better lives. So that was one of 399 00:23:11,040 --> 00:23:13,980 the top four things that was most surprising to us. 400 00:23:16,140 --> 00:23:18,330 Eveline Oehrlich: Anything else? Any other things? 401 00:23:18,450 --> 00:23:21,150 Jon Clifton: Well, I think, I think another one has to do with 402 00:23:21,150 --> 00:23:25,560 how women raised their lives around the world. Because when 403 00:23:25,560 --> 00:23:27,960 you look at two of the single biggest drivers of a great life, 404 00:23:27,960 --> 00:23:30,930 one is whether or not you physically feel safe. And in our 405 00:23:30,930 --> 00:23:33,660 database. When we asked men and women do you feel safe walking 406 00:23:33,660 --> 00:23:36,870 alone, at night, and you're in the city or area where you live, 407 00:23:36,900 --> 00:23:40,470 one of the widest gaps with respect to gender is that women 408 00:23:40,470 --> 00:23:43,410 are just less likely to feel safe walking alone at night in 409 00:23:43,410 --> 00:23:45,960 their communities. And the second one is economic 410 00:23:45,960 --> 00:23:50,220 opportunities. We can see when we replicate employment surveys 411 00:23:50,220 --> 00:23:53,220 globally that women have fewer economic opportunities than men. 412 00:23:53,220 --> 00:23:56,910 So if you just look at labor force participation, about 75% 413 00:23:56,910 --> 00:24:00,000 of men globally, participate in the global workforce, and it's 414 00:24:00,030 --> 00:24:03,510 50% of women culturally, sometimes culture plays a role 415 00:24:03,510 --> 00:24:07,410 in that take India, for example, where it's 75% of men and 25% of 416 00:24:07,410 --> 00:24:13,980 women. So there are economic and physical safety issues that are 417 00:24:14,280 --> 00:24:18,330 a challenge with respect to women globally. So here's the 418 00:24:18,330 --> 00:24:20,520 interesting thing. When we say to women rate your life on a 419 00:24:20,520 --> 00:24:25,740 scale of zero to 10. Where do you stand today, what we find is 420 00:24:25,740 --> 00:24:30,000 that women rate their lives exactly the same as men, if 421 00:24:30,000 --> 00:24:33,660 anything, they rate their lives slightly higher than men. And 422 00:24:33,660 --> 00:24:37,500 this pattern is true. Globally, every year since we've been 423 00:24:37,500 --> 00:24:40,410 doing this tracking. It's true in every region. And it's true 424 00:24:40,410 --> 00:24:43,770 in every single country in the world and has been true since 425 00:24:43,770 --> 00:24:47,370 we've been tracking. So why is this happening? We're not 426 00:24:47,370 --> 00:24:51,510 entirely sure. In fact, one of our colleagues, Carol Graham at 427 00:24:51,510 --> 00:24:55,320 Brookings, she's one of the top 400 most cited female economists 428 00:24:55,320 --> 00:24:57,570 in the world and also wrote a white paper about this. I 429 00:24:57,570 --> 00:25:00,240 believe the title is something like are women happy? are the 430 00:25:00,240 --> 00:25:05,400 men and she to can't quite put her finger on exactly why this 431 00:25:05,400 --> 00:25:08,550 phenomenon is happening. But the book goes through and I 432 00:25:08,550 --> 00:25:12,810 interview for leading women like Carol Graham, who focused on 433 00:25:12,810 --> 00:25:15,750 this to say, Why do you think this might be the case? And what 434 00:25:15,750 --> 00:25:18,810 can the world learn from this so that we can ultimately help 435 00:25:18,810 --> 00:25:20,460 people see their lives better everywhere? 436 00:25:20,880 --> 00:25:22,920 Eveline Oehrlich: Great research, if you need help on 437 00:25:22,920 --> 00:25:27,600 that one happy to call on the IT women in the in our journey? 438 00:25:28,470 --> 00:25:31,260 Because I think they have something to say on this topic. 439 00:25:31,290 --> 00:25:35,820 Great. Okay, another question. We talk a lot about well being 440 00:25:35,910 --> 00:25:41,010 and you have a lot of topics in your book around wellbeing, and 441 00:25:41,010 --> 00:25:45,180 you discuss five elements. Can you talk a bit more about them? 442 00:25:45,480 --> 00:25:47,970 The Careers, social, financial, physical well being and 443 00:25:47,970 --> 00:25:50,430 community well being just elaborate a little bit, and then 444 00:25:50,460 --> 00:25:53,970 I'll have a follow up question, particularly towards career. But 445 00:25:53,970 --> 00:25:56,340 if you wanted to elaborate on those five elements a little 446 00:25:56,340 --> 00:25:57,420 bit, that would be wonderful. 447 00:25:57,900 --> 00:26:00,930 Jon Clifton: Yeah. So when we noticed that this trend of 448 00:26:00,930 --> 00:26:03,780 negative emotions was increasing, what we wanted to do 449 00:26:03,780 --> 00:26:08,700 is understand why. And so what we did is we looked at the 450 00:26:08,700 --> 00:26:11,580 pattern of people who rate their lives the best, and people who 451 00:26:11,580 --> 00:26:13,770 rate their lives the worst, and then looked at their negative 452 00:26:13,770 --> 00:26:18,090 emotions. And what we found is that 15 years ago, about three 453 00:26:18,090 --> 00:26:21,570 and a half percent of people said, my life is a perfect 10. 454 00:26:22,020 --> 00:26:26,640 And we found that about 1.5% said, my life is a zero, my life 455 00:26:26,640 --> 00:26:30,480 actually cannot get any worse. Fast forward to 15 years later. 456 00:26:30,510 --> 00:26:33,120 And what we found is that the people who said their life is a 457 00:26:33,120 --> 00:26:37,020 perfect 10, more than doubled, it's almost 8% today, and the 458 00:26:37,020 --> 00:26:39,750 people who said my life cannot get any worse more than 459 00:26:39,750 --> 00:26:43,920 quadrupled it to is almost 8% today. And if you isolate the 460 00:26:43,920 --> 00:26:47,760 top quintile, and the lower quintile, you can see a pattern 461 00:26:47,790 --> 00:26:50,640 emerge, where the people who are writing their lives, the best, 462 00:26:50,910 --> 00:26:54,870 are continuing to get higher life ratings. And the people who 463 00:26:54,870 --> 00:26:58,860 rate their lives the worst, are rating in the lives even worse. 464 00:26:59,070 --> 00:27:01,170 And then when we look at the people who are rating their 465 00:27:01,170 --> 00:27:03,630 lives the best and the rating lives, the worse and isolate 466 00:27:03,630 --> 00:27:07,020 their negative emotions, we can see those in the bottom quintile 467 00:27:07,020 --> 00:27:09,630 who keeps saying my life is worse and worse and worse, that 468 00:27:09,630 --> 00:27:13,140 they are seeing the biggest increase in negative emotions in 469 00:27:13,140 --> 00:27:16,980 our whole database. That said, what we want to do is isolate of 470 00:27:16,980 --> 00:27:20,370 the people who say my life's at 10, or my life is zero, what do 471 00:27:20,370 --> 00:27:22,800 they have in common, we found that those people who say my 472 00:27:22,800 --> 00:27:26,490 life is at 10, they oftentimes have five things in common. And 473 00:27:26,490 --> 00:27:29,730 this is true across the entire world, which is they have great 474 00:27:29,730 --> 00:27:32,760 relationships, socially, they have high social wellbeing, they 475 00:27:32,760 --> 00:27:35,760 live in great communities, which we call community well being. 476 00:27:36,300 --> 00:27:39,540 Their physical well being is high, their financial well being 477 00:27:39,540 --> 00:27:42,990 is strong, and they also have strong work well being. And the 478 00:27:42,990 --> 00:27:45,540 people who are raising their lives, the worst appear to be 479 00:27:45,540 --> 00:27:49,800 getting less of these five things over the past 15 years. 480 00:27:49,950 --> 00:27:52,620 So those are the five drivers that we identified, and that we 481 00:27:52,620 --> 00:27:56,700 believe are the common source of this global rise of misery. 482 00:27:57,390 --> 00:28:02,520 Eveline Oehrlich: Wow, those numbers are blowing me away. 8% 483 00:28:03,030 --> 00:28:07,650 on the on the left hand side, say whoever miserable life to 484 00:28:07,650 --> 00:28:12,990 get to that point. Wow, unbelievable that I had to just 485 00:28:12,990 --> 00:28:16,950 sit in in awe and listen to that. That's just unbelievable 486 00:28:16,980 --> 00:28:21,690 and scary to where we are. So on the pandemic, did you? I mean, 487 00:28:21,900 --> 00:28:25,260 we are just out of it. Right? We've had horrible to the whole 488 00:28:25,260 --> 00:28:29,010 world and a horrible two years. Did that have any impact on it 489 00:28:29,010 --> 00:28:29,940 at all? Do you think? 490 00:28:30,870 --> 00:28:33,270 Jon Clifton: So this is why we did the book. Because when we 491 00:28:33,270 --> 00:28:36,360 first announced these results, we did so in what we call our 492 00:28:36,360 --> 00:28:39,990 Gallup global emotions report. And we launched it about midway 493 00:28:39,990 --> 00:28:43,380 through 2020. And when we came out, we said in our global 494 00:28:43,380 --> 00:28:46,410 database, we have found that there's a global rise of anger, 495 00:28:46,410 --> 00:28:49,320 stress, sadness, physical pain, and worry, and everyone that we 496 00:28:49,320 --> 00:28:52,620 send the message to, they said, Gee, why is that a surprise? Why 497 00:28:52,620 --> 00:28:55,410 would we be surprised that misery has reached a new high 498 00:28:55,590 --> 00:28:58,350 when we are all collectively suffering from a global 499 00:28:58,350 --> 00:29:01,800 pandemic? And we said, You're not listening, because the trend 500 00:29:01,800 --> 00:29:05,430 started before the pandemic. And that's what's got us concerned. 501 00:29:05,760 --> 00:29:08,910 And after two years of trying to reinforce this message, and also 502 00:29:08,910 --> 00:29:12,630 seeing that the pandemic probably exacerbated this 503 00:29:12,660 --> 00:29:16,230 already increasing negative emotions because of course, the 504 00:29:16,230 --> 00:29:20,100 global pandemic made people's lives collectively worse. People 505 00:29:20,100 --> 00:29:22,230 still weren't listening. And this is why we had a rather 506 00:29:22,230 --> 00:29:25,950 forceful title on the book, which is blind spot, because we 507 00:29:25,950 --> 00:29:29,100 believe that this global rise of negative emotions has been 508 00:29:29,130 --> 00:29:31,290 hiding in the blind spot of leaders everywhere. 509 00:29:31,740 --> 00:29:35,190 Eveline Oehrlich: So no excuse. Because we hear that a lot when 510 00:29:35,190 --> 00:29:39,420 I speak to leaders, about their employees, we just think about a 511 00:29:39,420 --> 00:29:43,380 year. Yeah, well, you know, we understand we're just coming out 512 00:29:43,380 --> 00:29:46,560 of a pandemic. So I will refer to the book and say no, not 513 00:29:46,560 --> 00:29:49,830 true. This is not something which just started because of 514 00:29:49,830 --> 00:29:52,560 the pandemic. There was a whole bunch of things already 515 00:29:52,560 --> 00:29:57,420 lingering and alright. We could of course go hours and hours on 516 00:29:57,420 --> 00:30:00,000 it, but I don't want to take away all the findings into the 517 00:30:00,000 --> 00:30:03,150 Just from the book, but there's one thing I want to hone into, 518 00:30:03,180 --> 00:30:06,180 which of course for us at the DevOps Institute, we are an 519 00:30:06,180 --> 00:30:08,640 institution with learning. We want to bring our community 520 00:30:08,640 --> 00:30:11,640 members together and advance their career, right? Well, we 521 00:30:11,640 --> 00:30:14,340 want to have fun. We also want to be their friends and they 522 00:30:14,340 --> 00:30:18,780 want we're many of us are friends. But one of the things I 523 00:30:18,780 --> 00:30:22,170 read in the book and these numbers again, I hope you don't 524 00:30:22,170 --> 00:30:27,270 mind if I quote them on the career that there is, you know, 525 00:30:27,270 --> 00:30:31,350 there's 7.7 billion people on the planet, right? 5.4 billion 526 00:30:31,740 --> 00:30:37,890 adults 3.3 billion adults want a great job. 1.5 billion have a 527 00:30:37,890 --> 00:30:44,520 good job. And only 300 million have a great job. Maybe you and 528 00:30:44,520 --> 00:30:47,880 I are the two who belong to the 300 million because we have a 529 00:30:47,880 --> 00:30:52,380 great job. And for the listeners ABS hour in the background, 530 00:30:52,590 --> 00:30:58,500 master of podcasts, so shout out to a be amazing, only 300 531 00:30:58,500 --> 00:31:02,850 million have a great job. Why is it that what, what? What's going 532 00:31:02,850 --> 00:31:03,810 on in the world? 533 00:31:04,500 --> 00:31:06,030 Jon Clifton: Well, we have a problem right now when we're 534 00:31:06,030 --> 00:31:09,750 trying to understand the global jobs picture. Because right now, 535 00:31:09,750 --> 00:31:13,410 the way that unemployment is captured does a great disservice 536 00:31:13,560 --> 00:31:16,860 to the misery that exists in the global workplace. For example, 537 00:31:16,860 --> 00:31:21,480 right before the pandemic, the ILO said that 5.5% of people 538 00:31:21,540 --> 00:31:25,020 were unemployed, if you use that as just an overall estimate to 539 00:31:25,020 --> 00:31:28,350 understand the global jobs picture. Again, we know that the 540 00:31:28,350 --> 00:31:31,560 amount of people that are living in poverty, that does not 541 00:31:31,830 --> 00:31:36,510 accurately represent the global jobs picture. 5% is even what 542 00:31:36,510 --> 00:31:40,170 many economists consider the natural rate of unemployment. So 543 00:31:40,170 --> 00:31:43,590 it means that there's no slack in the in the global jobs 544 00:31:43,590 --> 00:31:46,500 market. And it's just not the case, even after the pandemic, 545 00:31:46,650 --> 00:31:53,610 unemployment, only rised to 6.5%. How could that be? And so 546 00:31:53,670 --> 00:31:57,660 the challenge with it is how its measured. And in many developing 547 00:31:57,660 --> 00:32:01,140 countries take a place like Nigeria, for example, right now, 548 00:32:01,170 --> 00:32:04,200 in a place a no excuse me, Burundi, I believe their 549 00:32:04,200 --> 00:32:07,230 unemployment rate is less than a percent. But think about that 550 00:32:07,260 --> 00:32:09,990 this is one of the poorest countries in the world. And 551 00:32:10,020 --> 00:32:12,540 apparently, they have kind of the most optimal job market, 552 00:32:12,540 --> 00:32:15,360 it's not the case. And the reason for it is that we kind of 553 00:32:15,360 --> 00:32:18,420 blur the lines between this concept of self employment in 554 00:32:18,420 --> 00:32:21,120 the West, when we hear self employment, we think someone is 555 00:32:21,120 --> 00:32:23,970 self employed because of freedom, or because they want to 556 00:32:23,970 --> 00:32:27,030 be the next great entrepreneur that creates a multi billion 557 00:32:27,030 --> 00:32:31,170 dollar company. And it's seen as a source of pride, either one 558 00:32:31,290 --> 00:32:35,940 for which you determined to become become self employed. But 559 00:32:35,940 --> 00:32:40,320 in poor countries, it's not the case. Because people don't. And 560 00:32:40,350 --> 00:32:42,570 again, other economists have said this. So I'm quoting their 561 00:32:42,570 --> 00:32:46,140 work. They don't have the luxury to be unemployed. What does that 562 00:32:46,140 --> 00:32:49,890 mean, in many poor countries, they don't have unemployment 563 00:32:49,890 --> 00:32:52,650 benefits offered by the government. So people are forced 564 00:32:52,650 --> 00:32:55,980 to do anything they can. And so when somebody is conducting a 565 00:32:55,980 --> 00:32:59,370 survey, and they say, Did you work an hour in the past week? 566 00:32:59,940 --> 00:33:02,520 Or did you work 30 hours in the past week, someone who is 567 00:33:02,550 --> 00:33:06,090 potentially selling trinkets on the street or begging, they'll 568 00:33:06,090 --> 00:33:08,280 say, of course, I worked. Now, they didn't have meaningful 569 00:33:08,280 --> 00:33:12,840 work. And that is a very large percent of people currently in 570 00:33:12,840 --> 00:33:15,390 the workforce. In fact, I believe it's 30%, or self 571 00:33:15,390 --> 00:33:20,190 employed, yet half live or live under less than $2 a day. So 572 00:33:20,190 --> 00:33:24,090 again, this masks over the real global jobs crisis that we have. 573 00:33:24,090 --> 00:33:27,060 But the other piece is the misery of people who are 574 00:33:27,060 --> 00:33:31,590 currently working full time for a paycheck. And when somebody is 575 00:33:31,590 --> 00:33:34,050 totally emotionally detached from work, and they're 576 00:33:34,050 --> 00:33:37,830 miserable, and it's usually caused by their manager. They'll 577 00:33:37,830 --> 00:33:40,350 take this misery to places like tick tock so when you hear about 578 00:33:40,350 --> 00:33:44,670 people who are quiet, quitting, quiet quitting is not a new 579 00:33:44,670 --> 00:33:49,290 concept. It is a new term for an old concept. But people who are 580 00:33:49,290 --> 00:33:52,020 quietly quitting or you know, pronouncing their misery on Tik 581 00:33:52,020 --> 00:33:55,020 Tok are actually doing so overtly and not so quietly at 582 00:33:55,020 --> 00:33:59,820 all. And their frustration is real. And this frustration is 583 00:33:59,820 --> 00:34:02,790 what we've referred to historically as active 584 00:34:02,790 --> 00:34:05,220 disengagement. And if you look at somebody who's actively 585 00:34:05,220 --> 00:34:08,760 disengaged in their job, we find that they have the same amount 586 00:34:08,760 --> 00:34:11,820 if not more stress, sadness, pain, worry and anger. As 587 00:34:11,820 --> 00:34:14,280 someone who has no work whatsoever. This is a 588 00:34:14,280 --> 00:34:18,090 statistical fact. So the misery that's currently happening even 589 00:34:18,090 --> 00:34:23,430 with people who are full time, employees is causing a major 590 00:34:23,430 --> 00:34:26,640 problem for us globally and contributing to the global rise 591 00:34:26,640 --> 00:34:30,780 of unhappiness. So to help curb the global rise of unhappiness, 592 00:34:31,020 --> 00:34:34,860 this isn't just about sorting out issues like poverty, which 593 00:34:34,860 --> 00:34:38,580 it is also about helping curb the global rise of hunger. It's 594 00:34:38,580 --> 00:34:43,110 also about making better workplaces because it's causing 595 00:34:43,140 --> 00:34:46,650 just so much misery to people in the workplace today. 596 00:34:47,730 --> 00:34:50,040 Eveline Oehrlich: Interesting. I just read some research from 597 00:34:50,040 --> 00:34:56,790 Gartner. They published the top five priorities for HR leaders 598 00:34:56,850 --> 00:35:01,650 in in organizations I think it is I think they interviewed 800 599 00:35:02,670 --> 00:35:09,150 HR leaders globally, and work place happiness didn't show up. 600 00:35:09,990 --> 00:35:14,850 Number one, they, the number one thing they that is good for HR 601 00:35:14,850 --> 00:35:17,400 leaders is to focus on their leaders and how to develop their 602 00:35:17,400 --> 00:35:20,430 leaders, which is good, right? Because if we have good leaders, 603 00:35:20,790 --> 00:35:25,470 hopefully, depending on what we mean by good leaders, but if we 604 00:35:25,470 --> 00:35:29,460 have good leaders, hopefully they will be able to create a 605 00:35:29,460 --> 00:35:33,720 workforce an environment where happiness is there and where 606 00:35:33,720 --> 00:35:35,970 people can thrive and where people can actually feel 607 00:35:36,210 --> 00:35:39,570 engaged. And that, again, brings us back to whatever else we want 608 00:35:39,570 --> 00:35:46,560 to do. But I found that interesting I can see you have 609 00:35:46,560 --> 00:35:48,270 something to say to that? 610 00:35:48,900 --> 00:35:51,090 Jon Clifton: Well, I think one of the problems right now is the 611 00:35:51,090 --> 00:35:53,610 word happiness, because there are a lot of executives that 612 00:35:53,610 --> 00:35:57,690 hear that word. And it completely turns them off. Why? 613 00:35:57,690 --> 00:36:02,580 Because they believe that happiness at work is created by 614 00:36:02,670 --> 00:36:06,780 ping pong tables, right? Whose ball tables whatever. And, 615 00:36:06,930 --> 00:36:10,560 again, I think it has to do with the word happiness. And that's a 616 00:36:10,560 --> 00:36:14,310 problem that that I am participating in. But it's 617 00:36:14,310 --> 00:36:17,820 because it gets more attention, unfortunately. And the reality 618 00:36:17,820 --> 00:36:22,110 is, is what I think the best executives are trying to do is 619 00:36:22,140 --> 00:36:26,400 it's not necessarily this sort of ephemeral, ephemeral, 620 00:36:26,400 --> 00:36:30,000 fleeting, or transitory feeling of happiness, what they are 621 00:36:30,000 --> 00:36:32,700 trying to do is create thriving workplaces, and thriving 622 00:36:32,700 --> 00:36:36,330 workplaces are not necessarily about foosball tables. You know, 623 00:36:36,360 --> 00:36:39,240 I think workplaces mean that somebody cares about your 624 00:36:39,240 --> 00:36:41,670 development, that you have the opportunity to do what you do 625 00:36:41,670 --> 00:36:44,580 best, and you have the things you need in order to do your job 626 00:36:44,610 --> 00:36:49,770 effectively. Those are the basic needs of people at work. And 627 00:36:49,770 --> 00:36:54,570 when those are met, only then can someone truly be thriving at 628 00:36:54,570 --> 00:36:57,720 work. And so I think that's the distinction when we use this 629 00:36:57,720 --> 00:37:00,630 word happiness, if we can get an address that is more of an 630 00:37:00,630 --> 00:37:03,960 emotional attachment at work and just getting someone's basic 631 00:37:03,960 --> 00:37:07,380 needs met, then I think, then you see the presence of thriving 632 00:37:07,380 --> 00:37:09,570 in a workplace. So 633 00:37:09,630 --> 00:37:12,840 Eveline Oehrlich: it is, you know, I love what you said, but 634 00:37:12,840 --> 00:37:17,700 as an individual, if I'm in a organization, where a leader 635 00:37:17,700 --> 00:37:21,570 does not see that and are as many as we know, as when we know 636 00:37:21,570 --> 00:37:24,090 there's only 300 million of us what really happy out there. 637 00:37:24,330 --> 00:37:27,810 What can I do as an individual, I walk up to my manager and say, 638 00:37:27,870 --> 00:37:29,190 Hey, I'm unhappy. 639 00:37:31,200 --> 00:37:33,180 Jon Clifton: I think this is where leadership emerges. 640 00:37:33,990 --> 00:37:38,220 Because engagement and a thriving workplace is not 641 00:37:38,220 --> 00:37:42,990 necessarily dictated by the leaders in an organization. Now 642 00:37:42,990 --> 00:37:45,270 we do see some of the strongest correlations. Again, as I 643 00:37:45,270 --> 00:37:48,930 mentioned, 70% of the variance does depend on who you named 644 00:37:48,930 --> 00:37:53,040 manager. But let's be clear, concepts like recognition, which 645 00:37:53,040 --> 00:37:57,270 matter in workplaces, sometimes are best not when they come from 646 00:37:57,270 --> 00:38:00,390 your boss, not when they come from a senior executive. But 647 00:38:00,390 --> 00:38:04,050 when they come from one of your peers, and when they're random 648 00:38:04,080 --> 00:38:08,340 and when they are sincere. And when that takes place, 649 00:38:08,370 --> 00:38:10,770 engagement increases and workplaces are just 650 00:38:10,770 --> 00:38:15,540 fundamentally better. The other thing is, is the inner the 651 00:38:15,540 --> 00:38:19,320 personal relationships that exist at workplaces, one of the 652 00:38:19,320 --> 00:38:23,670 single things that keeps people to work place, even in some 653 00:38:23,670 --> 00:38:26,940 global studies more than pay is whether or not they have close 654 00:38:26,940 --> 00:38:30,060 relationships with their colleagues at work. This idea 655 00:38:30,240 --> 00:38:32,520 that, you know, we shouldn't be friends with our colleagues at 656 00:38:32,520 --> 00:38:37,080 work is something that we need to end forever, because it's 657 00:38:37,080 --> 00:38:39,900 just not true. We're basically fighting human nature when we 658 00:38:39,900 --> 00:38:44,040 come in with that kind of belief. And we also know that, 659 00:38:44,100 --> 00:38:47,040 you know, when you ask adults in a place like the United States, 660 00:38:47,160 --> 00:38:49,410 where is it that you're most likely to meet friends, they 661 00:38:49,410 --> 00:38:51,960 don't say that it's through a religious institution, they 662 00:38:51,960 --> 00:38:54,960 don't say that it's through the friends have their children's 663 00:38:54,960 --> 00:38:59,580 friends, they say it's at work. And these types of bonds not 664 00:38:59,610 --> 00:39:03,030 only keep people in their jobs, it also makes them more 665 00:39:03,030 --> 00:39:06,270 productive. It also creates an environment where they give more 666 00:39:06,270 --> 00:39:09,180 direct feedback, where they have somebody where they can have an 667 00:39:09,180 --> 00:39:11,880 outlet to talk about things that are frustrating them. And it 668 00:39:11,880 --> 00:39:14,820 also causes people to work the extra hour because they're not 669 00:39:14,820 --> 00:39:17,700 necessarily doing it for the leaders of the organization. 670 00:39:17,700 --> 00:39:22,110 They're doing it for each other. There's kind of a famous study 671 00:39:22,110 --> 00:39:25,500 when they say that, within the military, that people in the 672 00:39:25,500 --> 00:39:28,950 military, they do join, to fight for their country to fight for 673 00:39:28,950 --> 00:39:32,430 their loved ones. But when they fight, they do it for their 674 00:39:32,430 --> 00:39:35,550 brothers, they do it for the other individuals within the 675 00:39:35,550 --> 00:39:39,540 military. There are parallels to that in the workplace, that the 676 00:39:39,540 --> 00:39:42,840 reason that we stay the extra hour is because we have a close 677 00:39:42,840 --> 00:39:47,130 relationship with those that are that we're working with. So I do 678 00:39:47,130 --> 00:39:51,540 think that creating thriving workplaces is not necessarily a 679 00:39:51,540 --> 00:39:55,320 role of the leadership, the manager, there is a huge role 680 00:39:55,320 --> 00:39:58,230 the individual contributors can make 681 00:39:58,890 --> 00:40:01,440 Eveline Oehrlich: Beautiful, just one more thing and then I 682 00:40:01,440 --> 00:40:06,720 know we need to go. This reminds me of my first position. I just 683 00:40:06,720 --> 00:40:09,480 finished business school in Germany. And I started you at 684 00:40:09,480 --> 00:40:13,080 Hewlett Packard. And this was a time where Dave and Bill were 685 00:40:13,080 --> 00:40:17,670 still there. The founders of HP. They came around to us in the 686 00:40:17,670 --> 00:40:23,070 town in Germany, and the culture at the company was fantastic. We 687 00:40:23,190 --> 00:40:27,240 love each other. We, we care for each other. And this might not 688 00:40:27,240 --> 00:40:30,120 be politically correct, but I'm going to say it anyway. Hewlett 689 00:40:30,120 --> 00:40:35,490 Packard at the time was known as the best marriage advice 690 00:40:35,490 --> 00:40:39,180 company, you found your partner there? I did. I found my 691 00:40:39,180 --> 00:40:43,290 husband, I moved with him to the United States in 1986. It was 692 00:40:43,290 --> 00:40:47,280 just a wonderful place. And because of that, we worked hard. 693 00:40:47,310 --> 00:40:49,680 We were engaged. And when you were just saying that that's 694 00:40:49,680 --> 00:40:53,700 exactly what made me think of, I stayed there forever, until I 695 00:40:53,700 --> 00:40:58,920 left in 2006. Imagine 1983 until 2006. I worked at one company at 696 00:40:58,920 --> 00:41:03,060 multiple jobs, but I loved it. It changed in the in the latter 697 00:41:03,060 --> 00:41:05,280 years because they had some challenges. We won't go into 698 00:41:05,280 --> 00:41:08,730 that right now. But exactly that feeling I had when you were 699 00:41:08,730 --> 00:41:13,590 describing that super. Okay, we have taken so much time of yours 700 00:41:14,340 --> 00:41:17,850 have one more question for you. That has nothing to do with your 701 00:41:17,850 --> 00:41:20,490 research. What do you like to do on the weekend? 702 00:41:22,110 --> 00:41:25,020 Jon Clifton: I read a lot on the weekends. And I also spend time 703 00:41:25,020 --> 00:41:30,630 with my wife. And so it's a great boost for work well being 704 00:41:30,720 --> 00:41:34,020 and also for social well being so yeah, 705 00:41:34,650 --> 00:41:37,740 Eveline Oehrlich: Super Jon, this was wonderful. Thank you so 706 00:41:37,740 --> 00:41:41,010 much. This was a really, really great conversation. I hope our 707 00:41:41,010 --> 00:41:45,150 listeners out there enjoyed. To learn more about Gallup, it's 708 00:41:45,150 --> 00:41:49,740 easy to find, go look at www gallup.com. The book, the blind 709 00:41:49,740 --> 00:41:53,850 spot is out can be bought can be read. There's many, many other 710 00:41:53,850 --> 00:41:57,870 resources blogs, there's lots of research coming up. This was 711 00:41:57,870 --> 00:42:02,820 fantastic. Have a great rest of the day everybody listening and 712 00:42:02,820 --> 00:42:06,570 Jon, wonderful to have you if you ever need anything on 713 00:42:06,570 --> 00:42:10,860 DevOps, reach out to us. We're happy to hear. We're happy to 714 00:42:10,920 --> 00:42:14,580 help you on on it or if you want to do some joint research, happy 715 00:42:14,580 --> 00:42:16,620 to work together. Thank you again. 716 00:42:17,040 --> 00:42:19,770 Jon Clifton: Awesome. Thank you everyone and thank you AB for 717 00:42:19,860 --> 00:42:21,180 having an interest in what we do.