WEBVTT 00:00:00.000 --> 00:00:02.240 Okay, let's jump right in. Today we're doing 00:00:02.240 --> 00:00:04.400 a deep dive into something pretty fundamental 00:00:04.400 --> 00:00:06.860 if you're interested in how change happens. We're 00:00:06.860 --> 00:00:09.619 talking about Everett Rogers' really influential 00:00:09.619 --> 00:00:12.679 work from 2003 on the diffusion of innovations. 00:00:13.320 --> 00:00:15.560 This is basically the framework that helps explain, 00:00:16.000 --> 00:00:18.760 pretty predictably actually, how new ideas or 00:00:18.760 --> 00:00:21.489 new tools spread through a group. Exactly. And 00:00:21.489 --> 00:00:23.329 it's fascinating because the material we're drawing 00:00:23.329 --> 00:00:25.989 on today actually frames this for leaders. It 00:00:25.989 --> 00:00:28.149 comes from an excerpt from the book, Efficacious 00:00:28.149 --> 00:00:30.769 Technology Management, which is often used with, 00:00:30.769 --> 00:00:33.390 say, education leaders or heads of organizations. 00:00:33.469 --> 00:00:36.149 So this isn't just theory. It helps explain things 00:00:36.149 --> 00:00:38.750 we see all the time, like why some new software 00:00:38.750 --> 00:00:41.600 takes off in a company and another just... disappears. 00:00:41.859 --> 00:00:43.280 Right. And that's kind of our mission for you 00:00:43.280 --> 00:00:46.259 today. We want you to walk away with maybe a 00:00:46.259 --> 00:00:48.200 more structured way of looking at how people 00:00:48.200 --> 00:00:51.200 adopt new things, stop seeing it as just random 00:00:51.200 --> 00:00:53.560 chaos, and start seeing these patterns. You'll 00:00:53.560 --> 00:00:56.460 learn about five specific stages, who's in them, 00:00:56.500 --> 00:00:59.320 and kind of what makes them tick. And predictability 00:00:59.320 --> 00:01:02.710 is the key word there. The source material really 00:01:02.710 --> 00:01:05.390 hammers this home. Once an innovation gets into 00:01:05.390 --> 00:01:08.170 a community, its spread isn't random. It follows, 00:01:08.349 --> 00:01:11.170 well, almost statistical patterns across these 00:01:11.170 --> 00:01:13.769 five groups. And there are ways to actually measure 00:01:13.769 --> 00:01:16.069 this, which is what makes it so useful, right? 00:01:16.609 --> 00:01:19.030 Yeah. Rogers and others use these two main visual 00:01:19.030 --> 00:01:21.209 tools, these curves. Let's start with the famous 00:01:21.209 --> 00:01:24.109 one, the bell curve. Ah, yes, the bell curve. 00:01:24.290 --> 00:01:27.969 So what that shows you is the number of people 00:01:27.969 --> 00:01:31.120 at the actual count who fall into of those five 00:01:31.120 --> 00:01:33.280 adoption stages at any given time. It's like 00:01:33.280 --> 00:01:35.620 a snapshot. If you're rolling out a new system, 00:01:35.700 --> 00:01:37.519 this tells you who you're dealing with now. OK, 00:01:37.599 --> 00:01:39.200 so it maps the population across the stages. 00:01:39.219 --> 00:01:42.180 You see who's an innovator, who's early majority, 00:01:42.260 --> 00:01:44.000 and so on. But then there's the other curve, 00:01:44.079 --> 00:01:46.659 the S -curve. That's different. Completely different 00:01:46.659 --> 00:01:49.239 focus, yeah. The S -curve tracks the cumulative 00:01:49.239 --> 00:01:51.920 number of adopters over time. It shows the total 00:01:51.920 --> 00:01:53.719 percentage of the population that has adopted 00:01:53.719 --> 00:01:55.760 the innovation up to that point. So it starts 00:01:55.760 --> 00:01:58.420 slow. Then there's the steep acceleration phase. 00:01:58.459 --> 00:02:00.900 And finally, it levels off as you approach saturation. 00:02:01.040 --> 00:02:04.400 That's the S -sheep. So bill curve is who's adopting 00:02:04.400 --> 00:02:07.200 now. S -curve is how many have adopted in total 00:02:07.200 --> 00:02:10.919 so far. And crucially, Not everything makes it 00:02:10.919 --> 00:02:13.259 through these curves successfully, right? Absolutely 00:02:13.259 --> 00:02:15.919 not. The sources are clear. The innovation itself 00:02:15.919 --> 00:02:19.060 has to work. It needs to be efficacious, effective, 00:02:19.259 --> 00:02:21.300 efficient. It has to actually be better than 00:02:21.300 --> 00:02:23.520 what people were doing before. That's the filter. 00:02:23.699 --> 00:02:26.620 Makes sense. OK, let's get into those five stages, 00:02:26.759 --> 00:02:28.240 starting at the very beginning of the curve. 00:02:28.759 --> 00:02:31.379 The first wave. These are the highest risk takers, 00:02:31.560 --> 00:02:34.620 right? The innovators. Only 2 .5 % of the population. 00:02:34.719 --> 00:02:37.419 Tiny group, yeah. And their defining trait is 00:02:37.419 --> 00:02:39.599 being connected outside their immediate group 00:02:39.599 --> 00:02:42.400 or organization. They're the ones reading obscure 00:02:42.400 --> 00:02:45.240 journals, going to niche conferences, maybe beta 00:02:45.240 --> 00:02:47.979 testing things, months before anyone else. They 00:02:47.979 --> 00:02:50.060 bring stuff in from the outside. They're okay 00:02:50.060 --> 00:02:52.860 with risk too, I gather. They put time, maybe 00:02:52.860 --> 00:02:54.840 even their own money, into trying new things. 00:02:55.159 --> 00:02:57.280 Even things that might not work out or ever get 00:02:57.280 --> 00:03:00.199 adopted widely. That's exactly it. They're experimenting. 00:03:00.500 --> 00:03:02.800 And in today's world, you know, they might be 00:03:02.800 --> 00:03:04.939 scattered geographically but connected digitally 00:03:04.939 --> 00:03:07.620 through networks. But once they bring that idea 00:03:07.620 --> 00:03:10.280 in, the really critical group becomes the next 00:03:10.280 --> 00:03:14.659 one. Ah, the early adopters. The next 13 .5%. 00:03:14.659 --> 00:03:17.599 Yes. And here's a contrast. Innovators bring 00:03:17.599 --> 00:03:20.259 it in, but early adopters are deeply respected 00:03:20.259 --> 00:03:22.680 within the organization or community. They're 00:03:22.680 --> 00:03:25.340 the opinion leaders, the ones people look to. 00:03:25.479 --> 00:03:28.039 So the innovators might find the cool new thing, 00:03:28.400 --> 00:03:30.699 but they need the early adopters to make it legitimate 00:03:30.699 --> 00:03:33.979 internally. Precisely. Innovators often actively 00:03:33.979 --> 00:03:36.500 seek out early adopters. Because if this group 00:03:36.500 --> 00:03:38.599 gets on board, the chances of wider adoption 00:03:38.599 --> 00:03:41.020 shoot way up. They provide that social proof. 00:03:41.180 --> 00:03:43.699 They vet the innovation, show others how it applies, 00:03:44.060 --> 00:03:45.979 and basically become the role models. They are 00:03:45.979 --> 00:03:48.039 critical change agents. OK, so that's the first 00:03:48.039 --> 00:03:51.000 16 % combined, the risk takers and the internal 00:03:51.000 --> 00:03:54.389 champions. But getting past 16 %? That's often 00:03:54.389 --> 00:03:56.490 the hard part, isn't it? Crossing that gap to 00:03:56.490 --> 00:03:58.770 the mainstream. It's famously called crossing 00:03:58.770 --> 00:04:01.629 the chasm in some contexts because you're shifting 00:04:01.629 --> 00:04:04.490 your focus entirely. You move from people excited 00:04:04.490 --> 00:04:07.090 by novelty, the innovators and early adopters, 00:04:07.469 --> 00:04:10.610 to people who need practicality and proof. If 00:04:10.610 --> 00:04:12.530 the early adopters can't show clear benefits 00:04:12.530 --> 00:04:16.050 and success, the innovation often stalls right 00:04:16.050 --> 00:04:18.610 there. Which brings us to the biggest chunk of 00:04:18.610 --> 00:04:21.899 the population, the majority. Okay. That's a 00:04:21.899 --> 00:04:25.839 huge 68 % split in two. Let's start with the 00:04:25.839 --> 00:04:29.139 first half, the early majority, 34%. Right. These 00:04:29.139 --> 00:04:31.040 are the first ones we'd really call followers. 00:04:31.399 --> 00:04:33.259 They watch the early adopters. They need to see 00:04:33.259 --> 00:04:35.800 it working, see the bugs ironed out, get confirmation 00:04:35.800 --> 00:04:38.120 from people they trust inside the system. They're 00:04:38.120 --> 00:04:40.399 more deliberate. Maybe a bit skeptical. I remember 00:04:40.399 --> 00:04:42.680 that old quote Rogers used. Oh, the Alexander 00:04:42.680 --> 00:04:45.379 Pope one. Be not the first by whom the new is 00:04:45.379 --> 00:04:48.220 tried, nor the last to lay the old aside. That 00:04:48.220 --> 00:04:50.589 perfectly captures them. They wait for credible 00:04:50.589 --> 00:04:52.870 evidence from those early adopters. Then they 00:04:52.870 --> 00:04:54.870 tend to make the decision to adopt. They don't 00:04:54.870 --> 00:04:56.589 want to be first, but they also don't want to 00:04:56.589 --> 00:04:58.629 be left behind. So if you're trying to spread 00:04:58.629 --> 00:05:01.370 an idea, your messaging has to change here. Less 00:05:01.370 --> 00:05:04.949 cutting edge, more proven results. Exactly. You 00:05:04.949 --> 00:05:08.149 need case studies, testimonials from peers, solid 00:05:08.149 --> 00:05:10.870 data showing it works, and the risk is low. Okay, 00:05:10.910 --> 00:05:13.009 that makes sense. Now for the second half of 00:05:13.009 --> 00:05:16.430 that main group, the other 34%, the late majority. 00:05:16.750 --> 00:05:19.480 This group adopts... Only when it feels like 00:05:19.480 --> 00:05:22.560 almost everyone else already has. When the innovation 00:05:22.560 --> 00:05:25.579 is becoming the standard, their motivation shifts 00:05:25.579 --> 00:05:28.459 again. It's less about advantage and more about, 00:05:28.459 --> 00:05:31.500 well, pressure. Pressure. Like social pressure 00:05:31.500 --> 00:05:34.180 or practical pressure? Both, really. There are 00:05:34.180 --> 00:05:37.069 growing expectations to use the new thing. Maybe 00:05:37.069 --> 00:05:39.329 the old tools are becoming harder to use or aren't 00:05:39.329 --> 00:05:41.490 supported anymore. Think about economic reasons, 00:05:41.790 --> 00:05:44.149 too. Or just the sheer inconvenience of sticking 00:05:44.149 --> 00:05:46.009 with the old way when everyone else has moved 00:05:46.009 --> 00:05:48.529 on. They adopt when pretty much all the uncertainty 00:05:48.529 --> 00:05:50.910 is gone. It feels safer to switch than to stay 00:05:50.910 --> 00:05:54.310 put. Hmm. So they're responding more to necessity 00:05:54.310 --> 00:05:57.189 and the established norm. Yeah. The tipping point 00:05:57.189 --> 00:05:59.129 has well and truly passed by the time they come 00:05:59.129 --> 00:06:01.269 on board. Which leads us to the final group. 00:06:01.689 --> 00:06:06.600 The last 16%. The later adopters, Rogers and 00:06:06.600 --> 00:06:08.699 others sometimes use the term laggards historically, 00:06:08.920 --> 00:06:11.019 right? They did, though Rogers himself became 00:06:11.019 --> 00:06:13.180 critical of the blame often associated with that 00:06:13.180 --> 00:06:16.399 term. But yes, this group, the later adopters, 00:06:16.600 --> 00:06:18.860 they tend to hold onto the traditional ways the 00:06:18.860 --> 00:06:21.579 longest. They often adopt only when the old way 00:06:21.579 --> 00:06:23.660 is simply no longer an option. And they tend 00:06:23.660 --> 00:06:26.079 to stick together socially. communicating mostly 00:06:26.079 --> 00:06:28.319 with others who are also late to adopt. That's 00:06:28.319 --> 00:06:30.639 often the case, yes. They can form a sort of 00:06:30.639 --> 00:06:33.480 closed social circle, reinforcing their existing 00:06:33.480 --> 00:06:35.899 views and practices. But here's where Rogers 00:06:35.899 --> 00:06:37.740 adds that really important layer of insight. 00:06:37.839 --> 00:06:41.100 OK. He saw how organizations often blame these 00:06:41.100 --> 00:06:43.759 individuals, call them resistant, stubborn, you 00:06:43.759 --> 00:06:47.660 know, laggards. But he argued against that. He 00:06:47.660 --> 00:06:49.779 said, wait a minute. Don't just blame the person. 00:06:50.100 --> 00:06:52.459 Right. He suggested that if you actually study 00:06:52.459 --> 00:06:55.240 why this group is delaying adoption, you often 00:06:55.240 --> 00:06:57.199 learn something critical about the organization 00:06:57.199 --> 00:07:00.389 itself. Their reasons for delaying might point 00:07:00.389 --> 00:07:04.009 to real problems, maybe lack of resources, poor 00:07:04.009 --> 00:07:06.189 training, maybe the innovation doesn't actually 00:07:06.189 --> 00:07:08.589 work well for their specific role or context. 00:07:09.170 --> 00:07:11.050 Things that the earlier adopters who might have 00:07:11.050 --> 00:07:13.670 had more resources or flexibility could overcome, 00:07:14.069 --> 00:07:16.670 but that represent genuine barriers for this 00:07:16.670 --> 00:07:19.509 last group. Wow, okay. That flips the perspective 00:07:19.509 --> 00:07:21.920 completely. Their resistance isn't just stubbornness, 00:07:22.000 --> 00:07:23.920 it could be a signal about systemic issues. It 00:07:23.920 --> 00:07:26.240 could be valuable feedback, exactly, a diagnostic 00:07:26.240 --> 00:07:28.699 tool for the organization hidden in the reasons 00:07:28.699 --> 00:07:31.560 for delay. That's powerful. Okay, let's quickly 00:07:31.560 --> 00:07:33.879 recap the five groups then. We have innovators, 00:07:34.060 --> 00:07:36.500 2 .5%, the external connectors, risk -takers. 00:07:36.939 --> 00:07:40.279 Then early adopters, 13 .5%, the respected internal 00:07:40.279 --> 00:07:42.959 opinion leaders. They bridge the gap. Then the 00:07:42.959 --> 00:07:46.540 bulk. the early majority, 34%, the deliberate 00:07:46.540 --> 00:07:48.980 followers who need proof from early adopters, 00:07:49.300 --> 00:07:52.240 followed by the late majority, another 34%, who 00:07:52.240 --> 00:07:54.560 adopt due to pressure and necessity once it's 00:07:54.560 --> 00:07:57.459 the norm. And finally, the later adopters, the 00:07:57.459 --> 00:08:00.399 last 16%, who hold out the longest, and whose 00:08:00.399 --> 00:08:02.899 reasons for delay Roger says we should really 00:08:02.899 --> 00:08:05.639 pay attention to. Exactly. And knowing these 00:08:05.639 --> 00:08:08.569 predictable stages, these percentages, It gives 00:08:08.569 --> 00:08:11.610 you a map. You can look at any new tool or practice 00:08:11.610 --> 00:08:13.850 spreading in your workplace or even in society 00:08:13.850 --> 00:08:16.089 and get a quick sense of where it is in that 00:08:16.089 --> 00:08:18.370 life cycle. Are you still in the early adopter 00:08:18.370 --> 00:08:20.449 phase or are you trying to convince the late 00:08:20.449 --> 00:08:23.730 majority? It changes everything about how you 00:08:23.730 --> 00:08:26.050 approach it. Which brings us to our final thought 00:08:26.050 --> 00:08:29.069 for you the listener to kind of chew on. It comes 00:08:29.069 --> 00:08:31.569 directly from that insight about the later adopters. 00:08:32.049 --> 00:08:34.629 If Rogers is right, And this framework generally 00:08:34.629 --> 00:08:37.850 holds true, meaning about 16 % of any group will 00:08:37.850 --> 00:08:40.809 likely be the last to adopt. And if he specifically 00:08:40.809 --> 00:08:42.889 warns against blaming them individually, then 00:08:42.889 --> 00:08:45.710 the challenge becomes listen to them, understand 00:08:45.710 --> 00:08:47.809 their rationale. So here's the question for you. 00:08:48.070 --> 00:08:49.990 In your own organization, when you think about 00:08:49.990 --> 00:08:52.610 the people who seem slowest to adopt a new change, 00:08:53.210 --> 00:08:55.769 what might you be missing? What organizational 00:08:55.769 --> 00:08:58.450 barrier, what resource issue, what perspective 00:08:58.450 --> 00:09:00.610 that's only visible from their position might 00:09:00.610 --> 00:09:01.389 you be overlooking?