"Will Giving Away My Best Stuff Kill My Business?" — Transcript

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1. 0:00Give away good stuff for free that other
2. 0:03people charge for before asking for
3. 0:05money in order to ask for more money
4. 0:08later.
5. 0:09You will make more net money over a
6. 0:11longer period of time by giving stuff
7. 0:12away for free first.
8. 0:14Period.
9. 0:15And again, it's counterintuitive cuz the
10. 0:17intuitive thought is, well, if I give
11. 0:18away free stuff, they're already going
12. 0:19to get the value, they're not going to
13. 0:20want to pay me.
14. 0:22Uh, if I give away my free stuff,
15. 0:24um,
16. 0:24they're going to steal it, or my
17. 0:25competitors will steal it. There's, you
18. 0:27know, a hundred reasons that people come
19. 0:28up with why they shouldn't give away or
20. 0:30they I don't want to take the time to
21. 0:31give away free stuff. Um, for all of
22. 0:33those reasons, they intuitively, they
23. 0:36they make rational sense. And one of the
24. 0:37things that you have to be careful of
25. 0:38when you're an entrepreneur is is buying
26. 0:40your own right? Getting high
27. 0:41on your own supply. Like, you might
28. 0:43convince your team that what you just
29. 0:45said is true. Like, each of those
30. 0:46explanations I just gave would be
31. 0:47reasonable to believe. They just also
32. 0:49are false.
33. 0:50And so, just because something makes
34. 0:51rational sense doesn't make it true. And
35. 0:53that is one of the biggest lessons that
36. 0:54I've learned in entrepreneurship is that
37. 0:59where you get stuck is where the logical
38. 1:01solution is not correct.
39. 1:04I'll say that again. Where you get stuck
40. 1:07is where the logical solution is not
41. 1:08correct. And so,
42. 1:10um,
43. 1:11who am I I'm I'm blanking. Uh, Rory
44. 1:12Sutherland uh, has a couple good
45. 1:14examples of this. I'll tell you both of
46. 1:15them cuz I like them a lot. But, in in
47. 1:18uh, in the UK, they're getting a lot of
48. 1:20complaints around, um, you know,
49. 1:22elevators being slow. And so, this is
50. 1:24kind of like the dog example I gave at
51. 1:25the beginning of this. Um, if the
52. 1:27elevator is being slow, it's like you
53. 1:28could try and make the elevators fast.
54. 1:30you have to take out more insurance, and
55. 1:31then the cables have to be strengthened
56. 1:32to a certain degree, blah, blah, blah,
57. 1:34blah, blah, blah, right? Those are all
58. 1:35the very expensive logical people
59. 1:37complaining about being slow. Let's make
60. 1:38it faster. The thing is, people always
61. 1:40want it to be faster. And even then,
62. 1:41they'll complain that it's not fast
63. 1:42enough when it's faster than it was
64. 1:44before, right? People just always want
65. 1:45it to be instant. And so, they will
66. 1:46never be satisfied from a speed
67. 1:47perspective.
68. 1:49But, what is the counterintuitive
69. 1:50solution? The counterintuitive solution
70. 1:52Counterintuitive solution would be, how
71. 1:54can we
72. 1:55make them not realize that the time is
73. 1:57going by. And so the counterintuitive
74. 1:59solution is just put some mirrors in
75. 2:00there and then people are sit sit there
76. 2:02try to pick their teeth, right? Trying
77. 2:04to look at themselves in the mirror,
78. 2:05trying to get a get an angle, get a
79. 2:06little tricep flex going.
80. 2:08And all of a sudden the complaints go
81. 2:10down. They go away. And so there there
82. 2:13are these these different ways of
83. 2:14framing the problem that that are
84. 2:17typically the correct solution but not
85. 2:18the logical one.
86. 2:20Right?
87. 2:21And I'll give you a a final one um
88. 2:24which is you want to
89. 2:26you you think when you start well this
90. 2:28isn't scalable, right? I hear this all
91. 2:30the time from people who are trying to
92. 2:31pick their their first business or first
93. 2:33thing to sell. But this also applies to
94. 2:35business owners who are starting a new
95. 2:36revenue line or new business unit for
96. 2:38larger companies is that we think well
97. 2:40that's not scalable, right?
98. 2:42But in order to do something and make it
99. 2:45scalable, you need to do something
100. 2:46unscalable first. Elon talks about this
101. 2:48in the algorithm, right? Uh which is
102. 2:50actually not him but the book is by his
103. 2:51president but it it details the process
104. 2:53of optimizing any any any um
105. 2:56uh manufacturing process or any
106. 2:57input-output process. And so
107. 3:00there are first what why are we doing
108. 3:02this? We question the requirement.
109. 3:03Second
110. 3:04we uh delete the stupid steps. Then we
111. 3:07optimize, simplify. How do we make it as
112. 3:09simple as humanly possible, get the most
113. 3:10for the least? Then how do we accelerate
114. 3:11it? How do we make it faster? And then
115. 3:13and only then
116. 3:14do we automate? Do we make it scalable?
117. 3:17And so the the problem for the problem
118. 3:19with trying to make everything scalable
119. 3:21is that you end up making many things
120. 3:22that should not have been scaled to
121. 3:23begin with which is actually less
122. 3:24efficient than deciding not to do it at
123. 3:26all.
124. 3:27And so you you actually miss out on the
125. 3:29optimization steps that create scalable
126. 3:31solutions is by doing things that are
127. 3:33unscalable first. And if I can really
128. 3:35drive that one home, like for the love
129. 3:37of God, like this is one that this is
130. 3:39one that I'm like I'm I'm presently in
131. 3:42this in this right now. Like this is
132. 3:44something that I think about on a
133. 3:45regular basis which is like because we
134. 3:47have a lot of scale, right? We have we
135. 3:48have a large brand, we have a lot we We
136. 3:50a very large team, we have a lot of
137. 3:51companies. Like, there's a lot There's a
138. 3:53lot going on, right? And so, it makes
139. 3:55sense to automatically want to start
140. 3:57with, let's only build something that's
141. 3:58scalable.
142. 3:59But,
143. 4:00I have to fight that intuitive solution
144. 4:04with the counterintuitive thinking
145. 4:05process of, "No, we're going to go slow
146. 4:07to go fast. We're going to do these
147. 4:09things the right way, the manual way,
148. 4:12and then try and strip away as much from
149. 4:13these processes as humanly possible,
150. 4:15optimize as much as we can, then see can
151. 4:17we compress timelines, and then and only
152. 4:20then we say, 'Okay, now let's see if
153. 4:21there's a scalable version of this um
154. 4:24that works.' Now, one of the interesting
155. 4:26things that you'll also find is that
156. 4:27people think about scalability, and they
157. 4:29think that just because it requires a
158. 4:30human, it doesn't make it scalable.
159. 4:32It's a cost and return question. It's
160. 4:34not whether it like humans are scalable.
161. 4:36I mean, for the love of God, they're
162. 4:37Like, the the OpenAIs and the
163. 4:39Anthropic's have 5,000 employees, all
164. 4:41right? And so, like, if if employees or
165. 4:43humans added or conferred no additional
166. 4:44value, they wouldn't have them there,
167. 4:46right?
168. 4:47And so, um it's just that it is more
169. 4:50difficult to scale, not that it is
170. 4:52unscalable. And in order if there is an
171. 4:55increase in difficulty or complexity, we
172. 4:57just have to ask the question, is is it
173. 4:58worth it? Right? Like, if hiring 100
174. 5:01people makes you a billion dollars, then
175. 5:03it's probably worth doing rather than
176. 5:04trying to automate it, right? Especially
177. 5:06if you can get there faster. And so,
178. 5:08this is the This is the tradeoff. And
179. 5:11so, each of the the the solutions that I
180. 5:12just went
181. 5:13>> If you like this video and you're a
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193. 5:32enjoy.