| Recorded at | February 22, 2020 |
|---|---|
| Event | TEDxPurdueU |
| Duration (min:sec) | 13:50 |
| Video Type | TEDx Talk |
| Words per minute | 190.09 fast |
| Readability (FK) | 55.83 medium |
| Speaker | Karen Eber |
Official TED page for this talk
Synopsis
How do the world's best leaders and visionaries earn trust? They don't just present data -- they also tell great stories. Leadership consultant Karen Eber demystifies what makes for effective storytelling and explains how anyone can harness it to create empathy and inspire action.
| 1 | 00:13 | Maria walked into the elevator at work. | ||
| 2 | 00:16 | She went to press the button when her phone fell out of her hand. | ||
| 3 | 00:20 | It bounced on the floor and -- | ||
| 4 | 00:25 | went straight down that little opening between the elevator and the floor. | ||
| 5 | 00:29 | And she realized it wasn't just her phone, | ||
| 6 | 00:32 | it was her phone wallet that had her driver's license, | ||
| 7 | 00:35 | her credit card, her whole life. | ||
| 8 | 00:37 | She went to the front desk to talk to Ray, the security guard. | ||
| 9 | 00:41 | Ray was really happy to see her. | ||
| 10 | 00:43 | Maria is one of the few people | ||
| 11 | 00:45 | that actually stops and says hello to him each day. | ||
| 12 | 00:48 | In fact, she's one of these people that knows your birthday | ||
| 13 | 00:51 | and your favorite food, and your last vacation, | ||
| 14 | 00:54 | not because she's weird, | ||
| 15 | 00:56 | she just genuinely likes people and likes them to feel seen. | ||
| 16 | 01:00 | She tells Ray what happened, | ||
| 17 | 01:02 | and he said it's going to cost at least 500 dollars | ||
| 18 | 01:04 | to get her phone back | ||
| 19 | 01:06 | and he goes to get a quote while she goes back to her desk. | ||
| 20 | 01:10 | Twenty minutes later, he calls her and he says, "Maria, | ||
| 21 | 01:15 | I was looking at the inspection certificate in the elevator. | ||
| 22 | 01:18 | It's actually due for its annual inspection next month. | ||
| 23 | 01:22 | I'm going to go ahead and call that in today | ||
| 24 | 01:24 | and we'll be able to get your phone back and it won't cost you anything." | ||
| 25 | 01:27 | The same day this happened, | ||
| 26 | 01:30 | I read an article about the CEO of Charles Schwab, Walter Bettinger. | ||
| 27 | 01:34 | He's describing his straight-A career at university | ||
| 28 | 01:38 | going in to his last exam expecting to ace it, | ||
| 29 | 01:41 | when the professor gives one question: | ||
| 30 | 01:44 | "What is the name of the person that cleans this room?" | ||
| 31 | 01:48 | And he failed the exam. | ||
| 32 | 01:50 | He had seen her, but he had never met her before. | ||
| 33 | 01:53 | Her name was Dottie and he made a vow that day | ||
| 34 | 01:56 | to always know the Dotties in his life | ||
| 35 | 01:59 | because both Walter and Maria | ||
| 36 | 02:00 | understand this power of helping people feel seen, | ||
| 37 | 02:03 | especially as a leader. | ||
| 38 | 02:06 | I used that story back when I worked at General Electric. | ||
| 39 | 02:10 | I was responsible for shaping culture in a business of 90,000 employees | ||
| 40 | 02:15 | in 150 countries. | ||
| 41 | 02:17 | And I found that stories were such a great way | ||
| 42 | 02:19 | to connect with people | ||
| 43 | 02:21 | and have them think, | ||
| 44 | 02:23 | "What would I do in this situation? | ||
| 45 | 02:25 | Would I have known Dottie | ||
| 46 | 02:27 | or who are the Dotties I need to know in my life?" | ||
| 47 | 02:30 | I found that no matter people's gender or their generation | ||
| 48 | 02:33 | or their geography in the world, | ||
| 49 | 02:35 | the stories resonated and worked. | ||
| 50 | 02:38 | But in my work with leaders, | ||
| 51 | 02:39 | I've also found they tend to be allergic to telling stories. | ||
| 52 | 02:43 | They're not sure where to find them, | ||
| 53 | 02:44 | or they're not sure how to tell them, | ||
| 54 | 02:47 | or they think they have to present data | ||
| 55 | 02:49 | and that there's just not room to tell a story. | ||
| 56 | 02:52 | And that's where I want to focus today. | ||
| 57 | 02:55 | Because storytelling and data is actually not this either-or. | ||
| 58 | 02:58 | It's an "and," they actually create this power ballad | ||
| 59 | 03:01 | that connects you to information differently. | ||
| 60 | 03:04 | To understand how, | ||
| 61 | 03:06 | we have to first understand what happens neurologically | ||
| 62 | 03:08 | when you're listening to a story and data. | ||
| 63 | 03:12 | So as you're in a lecture or you're in a meeting, | ||
| 64 | 03:14 | two small parts of your brain are activated, | ||
| 65 | 03:17 | Wernicke and Broca's area. | ||
| 66 | 03:19 | This is where you're processing information, | ||
| 67 | 03:21 | and it's also why you tend to forget 50 percent of it | ||
| 68 | 03:24 | right after you hear it. | ||
| 69 | 03:26 | When you listen to a story, | ||
| 70 | 03:28 | your entire brain starts to light up. | ||
| 71 | 03:32 | Each of your lobes will light up | ||
| 72 | 03:34 | as your senses and your emotions are engaged. | ||
| 73 | 03:37 | As I talk about a phone falling and hitting the ground with a thud | ||
| 74 | 03:41 | your occipital and your temporal lobes are lighting up | ||
| 75 | 03:44 | as though you are actually seeing that falling phone | ||
| 76 | 03:47 | and hearing it hit with a thud. | ||
| 77 | 03:50 | There's this term, neural coupling, | ||
| 78 | 03:52 | which says, as the listener, | ||
| 79 | 03:54 | your brain will light up exactly as mine | ||
| 80 | 03:58 | as the storyteller. | ||
| 81 | 04:00 | It mirrors this activity | ||
| 82 | 04:01 | as though you are actually experiencing these things. | ||
| 83 | 04:06 | Storytelling gives you this artificial reality. | ||
| 84 | 04:09 | If I talked to you about, like, walking through the snow | ||
| 85 | 04:12 | and with each step, | ||
| 86 | 04:13 | the snow is crunching under my shoes, | ||
| 87 | 04:16 | and big, wet flakes are falling on my cheeks, | ||
| 88 | 04:20 | your brains are now lighting up | ||
| 89 | 04:21 | as though you are walking through the snow and experiencing these things. | ||
| 90 | 04:26 | It's why you can sit in an action movie | ||
| 91 | 04:28 | and not be moving, | ||
| 92 | 04:29 | but your heart is racing as though you're the star on-screen | ||
| 93 | 04:32 | because this neural coupling has your brain lighting up | ||
| 94 | 04:35 | as though you are having that activity. | ||
| 95 | 04:39 | As you listen to stories, | ||
| 96 | 04:41 | you automatically gain empathy for the storyteller. | ||
| 97 | 04:44 | The more empathy you experience, | ||
| 98 | 04:47 | the more oxytocin is released in your brain. | ||
| 99 | 04:50 | Oxytocin is the feel-good chemical | ||
| 100 | 04:52 | and the more oxytocin you have, | ||
| 101 | 04:55 | the more trustworthy you actually view the speaker. | ||
| 102 | 04:58 | This is why storytelling is such a critical skill for a leader | ||
| 103 | 05:02 | because the very act of telling a story | ||
| 104 | 05:04 | makes people trust you more. | ||
| 105 | 05:07 | As you begin to listen to data, some different things happen. | ||
| 106 | 05:10 | There are some misconceptions to understand. | ||
| 107 | 05:13 | And the first is that data doesn't change our behavior, | ||
| 108 | 05:17 | emotions do. | ||
| 109 | 05:19 | If data changed our behavior, | ||
| 110 | 05:21 | we would all sleep eight hours and exercise and floss daily | ||
| 111 | 05:24 | and drink eight glasses of water. | ||
| 112 | 05:26 | But that's not how we actually decide. | ||
| 113 | 05:29 | Neuroscientists have studied decision-making, | ||
| 114 | 05:32 | and it starts in our amygdala. | ||
| 115 | 05:35 | This is our emotional epicenter | ||
| 116 | 05:37 | where we have the ability to experience emotions | ||
| 117 | 05:40 | and it's here at a subconscious level where we begin to decide. | ||
| 118 | 05:44 | We make choices to pursue pleasure | ||
| 119 | 05:47 | or to avoid risk, | ||
| 120 | 05:48 | all before we become aware of it. | ||
| 121 | 05:51 | At the point we become aware, | ||
| 122 | 05:54 | where it comes to the conscious level, | ||
| 123 | 05:56 | we start to apply rationalization and logic, | ||
| 124 | 05:59 | which is why we think we're making these rationally-based decisions, | ||
| 125 | 06:02 | not realizing that they were already decided in our subconscious. | ||
| 126 | 06:07 | Antonio Damasio is a neuroscientist | ||
| 127 | 06:10 | that started to study patients that had damage to their amygdala. | ||
| 128 | 06:14 | Fully functioning in every way, | ||
| 129 | 06:16 | except they could not experience emotions. | ||
| 130 | 06:20 | And as a result, they could not make decisions. | ||
| 131 | 06:23 | Something as simple as "do I go this way or this way" | ||
| 132 | 06:27 | they were incapable of doing, | ||
| 133 | 06:29 | because they could not experience emotions. | ||
| 134 | 06:32 | These were people that were wildly successful | ||
| 135 | 06:35 | before they had the damage to their amygdala | ||
| 136 | 06:37 | and now they couldn't complete any of their projects | ||
| 137 | 06:40 | and their careers took big hits, | ||
| 138 | 06:41 | all because they couldn't experience emotions where we decide. | ||
| 139 | 06:47 | Another data misconception. | ||
| 140 | 06:50 | Data never speaks for itself. | ||
| 141 | 06:54 | Our brains love to anticipate | ||
| 142 | 06:56 | and as we anticipate, | ||
| 143 | 06:57 | we fill in the gaps on what we're seeing or hearing | ||
| 144 | 06:59 | with our own knowledge and experience | ||
| 145 | 07:02 | and our own bias. | ||
| 146 | 07:03 | Which means my understanding of data is going to differ from yours, | ||
| 147 | 07:07 | and it's going to differ from yours, | ||
| 148 | 07:09 | because we're all going to have our own interpretation | ||
| 149 | 07:12 | if there isn't a way to guide us through. | ||
| 150 | 07:15 | Now I'm not suggesting that data is bad and story is good. | ||
| 151 | 07:19 | They both play a key role. | ||
| 152 | 07:21 | And to understand how, | ||
| 153 | 07:22 | you have to see what makes a great story. | ||
| 154 | 07:25 | It's going to answer three questions. | ||
| 155 | 07:28 | The first is: | ||
| 156 | 07:29 | What is the context? | ||
| 157 | 07:31 | Meaning, what's the setting, who is involved, | ||
| 158 | 07:34 | why should I even care? | ||
| 159 | 07:36 | What is the conflict, | ||
| 160 | 07:38 | where is that moment where everything changes? | ||
| 161 | 07:42 | And what is the outcome? | ||
| 162 | 07:44 | Where is it different, what is the takeaway? | ||
| 163 | 07:47 | A good story also has three attributes, | ||
| 164 | 07:51 | the first being it is going to build and release tension. | ||
| 165 | 07:54 | So because our brains love to anticipate, | ||
| 166 | 07:57 | a great story builds tension by making you wonder: | ||
| 167 | 08:00 | "Where is she going with this?" | ||
| 168 | 08:03 | "What's happening next," right? | ||
| 169 | 08:05 | A good story keeps you, keeps your attention going. | ||
| 170 | 08:09 | And it releases it by sharing something unexpected | ||
| 171 | 08:12 | and it does this over and over throughout the story. | ||
| 172 | 08:15 | A great story also builds an idea. | ||
| 173 | 08:18 | It helps you see something that you can no longer unsee, | ||
| 174 | 08:22 | leaving you changed, | ||
| 175 | 08:23 | because stories actually do leave you changed. | ||
| 176 | 08:27 | And a great story communicates value. | ||
| 177 | 08:30 | Stanford has done research on one of the best ways | ||
| 178 | 08:32 | to shape organizational culture, | ||
| 179 | 08:34 | and it is storytelling, | ||
| 180 | 08:36 | because it's going to demonstrate what you value and encourage | ||
| 181 | 08:39 | or what you don't value and what you discourage. | ||
| 182 | 08:43 | As you start to write your power ballad, | ||
| 183 | 08:46 | most people want to start with the data. | ||
| 184 | 08:49 | They want to dig in, | ||
| 185 | 08:50 | because we often have piles of data. | ||
| 186 | 08:53 | But there's a common mistake we make when we do that. | ||
| 187 | 08:57 | I was working with a CEO. | ||
| 188 | 08:59 | She came to me to prepare for her annual company-wide meeting | ||
| 189 | 09:02 | and she had 45 slides of data | ||
| 190 | 09:05 | for a 45-minute presentation. | ||
| 191 | 09:08 | A recipe for a boring, unmemorable talk. | ||
| 192 | 09:11 | And this is what most people do, | ||
| 193 | 09:13 | they come armed with all of this data | ||
| 194 | 09:15 | and they try to sort their way through | ||
| 195 | 09:18 | without a big picture | ||
| 196 | 09:19 | and then they lose their way. | ||
| 197 | 09:22 | We actually put the data aside and I asked her, | ||
| 198 | 09:25 | "What's the problem you're trying to solve? | ||
| 199 | 09:27 | What do you want people to think and feel different | ||
| 200 | 09:30 | and what do you want people to do different at the end of this?" | ||
| 201 | 09:33 | That is where you start with data and storytelling. | ||
| 202 | 09:35 | You come up with this framework to guide the way through | ||
| 203 | 09:39 | both the story and the data. | ||
| 204 | 09:41 | In her case, | ||
| 205 | 09:42 | she wants her company to be able to break into new markets, | ||
| 206 | 09:45 | to remain competitive. | ||
| 207 | 09:47 | She ended up telling a story about her daughter, | ||
| 208 | 09:49 | who's a gymnast who's competing for a scholarship, | ||
| 209 | 09:52 | and she had to learn new routines with increasing difficulty | ||
| 210 | 09:55 | to be competitive. | ||
| 211 | 09:57 | This is one of your choices. | ||
| 212 | 09:59 | Do you tell a story about the data itself | ||
| 213 | 10:02 | or do you tell a parallel story, | ||
| 214 | 10:04 | where you pull out points from the story to reinforce the data? | ||
| 215 | 10:09 | As you begin this ballad, | ||
| 216 | 10:11 | this melody and harmony of data and storytelling come together | ||
| 217 | 10:15 | in a way that will stay with you long after. | ||
| 218 | 10:19 | Briana was a college adviser. | ||
| 219 | 10:24 | And she was asked to present to her university leadership | ||
| 220 | 10:27 | when she realized that a large population of their students with autism | ||
| 221 | 10:31 | were not graduating. | ||
| 222 | 10:33 | She came to me because her leaders kept saying, | ||
| 223 | 10:35 | "Present the data, focus on the data," | ||
| 224 | 10:37 | but she felt like university officials already had the data. | ||
| 225 | 10:41 | She was trying to figure out how to help them connect with it. | ||
| 226 | 10:44 | So we worked together to help her tell the story about Michelle. | ||
| 227 | 10:49 | Michelle was a straight-A student in high school | ||
| 228 | 10:51 | who had these dreams of going to university. | ||
| 229 | 10:54 | Michelle was also a student with autism | ||
| 230 | 10:57 | who was terrified about how she would be able to navigate | ||
| 231 | 11:00 | the changes of university. | ||
| 232 | 11:02 | Her worst fears came true on her first phone call | ||
| 233 | 11:05 | with her adviser, | ||
| 234 | 11:06 | when he asked her questions like, | ||
| 235 | 11:09 | "Where do you see yourself in five years?" | ||
| 236 | 11:11 | and "What are your career aspirations?" | ||
| 237 | 11:14 | Questions that are hard for anybody. | ||
| 238 | 11:18 | But for a person with autism | ||
| 239 | 11:20 | to have to respond to verbally? | ||
| 240 | 11:23 | Paralyzing. | ||
| 241 | 11:25 | She got off the phone, was ready to drop out, | ||
| 242 | 11:27 | until her parents sat down with her | ||
| 243 | 11:29 | and helped her write an email to her adviser. | ||
| 244 | 11:32 | She told him that she was a student with autism, | ||
| 245 | 11:35 | which was really hard for her to share | ||
| 246 | 11:37 | because she felt like there was a stigma associated just by sharing that. | ||
| 247 | 11:42 | She told him that she preferred to communicate in writing, | ||
| 248 | 11:44 | if he could send her questions in advance, | ||
| 249 | 11:47 | she would be able to send replies back to him | ||
| 250 | 11:49 | before they got on the phone to have a different conversation. | ||
| 251 | 11:53 | He followed her lead | ||
| 252 | 11:55 | and within a few weeks, | ||
| 253 | 11:56 | they found all of these things they have in common, | ||
| 254 | 11:58 | like a love for Japanese anime. | ||
| 255 | 12:01 | After three semesters, | ||
| 256 | 12:03 | Michelle is a straight-A student thriving in the university. | ||
| 257 | 12:08 | At this point, Briana starts to share some of the data | ||
| 258 | 12:11 | that less than 20 percent of the students with autism | ||
| 259 | 12:14 | are graduating. | ||
| 260 | 12:16 | And it's not because they can't handle the coursework. | ||
| 261 | 12:19 | It's because they can't figure out | ||
| 262 | 12:20 | how to navigate the university, | ||
| 263 | 12:22 | the very thing an adviser is supposed to be able to help you do. | ||
| 264 | 12:27 | That over the course of a lifetime | ||
| 265 | 12:29 | the earning potential of someone with a college degree | ||
| 266 | 12:32 | over a high school degree | ||
| 267 | 12:34 | is a million dollars. | ||
| 268 | 12:35 | Which is a big amount. | ||
| 269 | 12:37 | But for a person with autism | ||
| 270 | 12:38 | that wants to be able to live independent from their family | ||
| 271 | 12:41 | it's life changing. | ||
| 272 | 12:44 | She closed with, | ||
| 273 | 12:45 | "We say our whole passion and purpose | ||
| 274 | 12:48 | is to help people be their best, | ||
| 275 | 12:50 | to help them be successful. | ||
| 276 | 12:52 | But we're hardly giving our best service | ||
| 277 | 12:54 | by applying this one-size-fits-all approach | ||
| 278 | 12:56 | and just letting people fall through the cracks. | ||
| 279 | 12:59 | We can and we should do better. | ||
| 280 | 13:01 | There are more Michelles out there, | ||
| 281 | 13:02 | and I know because Michelle is my daughter." | ||
| 282 | 13:06 | And in that moment, the jaws in the room went -- | ||
| 283 | 13:10 | And someone even wiped away tears, | ||
| 284 | 13:12 | because she had done it, | ||
| 285 | 13:13 | she had connected them to information differently, | ||
| 286 | 13:16 | she helped them see something they couldn't unsee. | ||
| 287 | 13:19 | Could she have done that with data alone? | ||
| 288 | 13:22 | Maybe, but the things is, they already had the data. | ||
| 289 | 13:25 | They didn't have a reason not to overlook the data this time. | ||
| 290 | 13:30 | That is the power of storytelling and data. | ||
| 291 | 13:34 | That together, they come together in this way | ||
| 292 | 13:36 | to help build ideas, | ||
| 293 | 13:38 | to help you see things you can't unsee. | ||
| 294 | 13:40 | To help communicate what's valued | ||
| 295 | 13:42 | and to help tap into that emotional way that we all decide. | ||
| 296 | 13:46 | As you all move forward, | ||
| 297 | 13:48 | shaping the passion and purpose of others as leaders, | ||
| 298 | 13:51 | don't just use data. | ||
| 299 | 13:53 | Use stories. | ||
| 300 | 13:55 | And don't wait for the perfect story. | ||
| 301 | 13:57 | Take your story and make it perfect. | ||
| 302 | 13:59 | Thank you. | ||
| 303 | 14:00 | (Applause) |