How to encourage innovative thinking inside of your organization: Chief Innovation Officer, Engineering at NASA Shares Techniques

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A lot of people actually ask as well what will be the skills needed in the future.
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That was going to be my next question.
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It's going to be very difficult to predict.
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Well, it's going to be easy to predict in the next five years, but we're talking about maybe 15, 20 years.
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It becomes more challenging because in the next 10 years, probably the majority of the jobs don't exist today yet.
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So it will be jobs that will be created depending on what technologies, depending on what ecosystems are coming across.
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But I think that the skills that needs to be developed in everybody now is like before people used to go to college, study a degree, and then that's it.
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They never went back to college.
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They never read anything or research papers.
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I think that fact is completely gone now.
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So you need to constantly be learning, constantly be adaptive.
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You need to be able to change and get off your comfort zone and try new things.
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That's Omar Hatamle, the Chief Innovation Officer of Engineering and Executive Director of the Space Studies Program at NASA.
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He was formerly the deputy chief scientist at NASA and has been with the company for about 21 years.
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In case you haven't heard of them, NASA is a U.S. government agency that was established in 1958, and their purpose is to pioneer the future in space exploration, scientific discovery, and aeronautics research.
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In today's discussion, you will hear how Omar has seen NASA change over the last 21 years, how they plan to use technology like 3D printing and AI in the future, and his thoughts on which technologies are overhyped.
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Omar also gives us a sneak peek into how NASA works, including how they tackle problems, how they build effective teams and deal with failure, and how they focus on creative thinking.
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It is a fascinating discussion.
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One of the elements when you're doing brainstorming is we teach people how to not judge any idea beforehand.
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So for example, if people are brainstorming and somebody comes up with an idea and I say, no, I don't like this idea, this is not going to work.
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And then that person comes up with a second idea and I said, you know what, it's probably not that, that's not what I was thinking about.
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And then the third time, that person is not going to contribute to anything, he's going to shut down.
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This is Jacob Morgan, bestselling author, speaker, and futurist.
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Welcome to the Future of Work podcast, where every week I speak with C-level executives, business leaders, and authors to explore how the workplace is changing and what the future of work is going to look like.
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The goal of this show is to give you the insights, the ideas, and the inspiration to help future proof your career and your organization.
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Welcome.
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If you want to get access to more content, such as podcast transcriptions and information on working with me or having me keynote your next event, you can visit my website at thefutureorganization.com.
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If you want to take your education even further by getting access to courses that explore these themes in more depth, then check out futureofworkuniversity.com.
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Also, if you get a few seconds, please rate and review the podcast on iTunes or whatever your preferred channel is.
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It really helps the show and I personally appreciate it since the podcast does take quite a bit of effort to produce.
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In case you're interested in sponsoring the podcast or working with me, my email is jacob at thefutureorganization.com.
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Hello everyone, welcome to another episode of the Future of Work podcast.
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My guest today is Omar Hatamla.
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He's the executive director of the Space Studies program at the International Space University and he's also the chief innovation officer of engineering at NASA.
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And from what I understand you also used to be the former chief scientist at NASA, right?
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The deputy chief scientist?
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Yes, actually I was a deputy chief scientist at NASA Ames in 2014.
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And that was a very exciting position there being in the Silicon Valley and having, doing a lot of work and that's doing astronomy.
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and the CubeSats and quantum computers.
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It was very exciting times.
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Oh man, okay, so we have lots of stuff to talk about.
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But before we jump into all that, why don't you give people a little bit of background information about you, maybe some of the things that you're currently involved in, what you do as the Chief Innovation Officer, and also maybe a little bit of background about NASA.
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Yeah, no, definitely.
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First of all, thanks for having me, Jacob.
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I appreciate the time here, the opportunity.
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So I've been with NASA for about 21 years.
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I started as a structures engineer, and my last three positions was deputy chief scientist and then chief innovation officer for engineering.
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And now currently I'm the executive director for the space studies program.
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which is an international program that involves people from tens of countries to talk about the interdisciplinarity of space and how to engage from different levels.
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So after that, the chief innovation officer basically involves encouraging different divergent ways of thinking.
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using open innovation, getting people outside of the comfort zones, using design thinking.
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So there's a lot of elements.
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The basic thing is having people change their mentality, changing the culture.
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I think that's the biggest challenge that everybody faces.
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But little by little, I think you start making progress, start using some of the tools available in the market and try to
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to form alliances and collaborations, to find synergies between different industries, different governments, academia, and form an ecosystem, actually, to be able to encourage very different and diverse ways of thinking, to encourage new things to happen.
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And maybe for the few people that have not heard of NASA, I honestly don't think anybody has not heard of NASA, but just to be safe, maybe you can give us a little bit of background information about NASA, who you guys are, what you guys are doing.
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Well, NASA is a government agency.
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It's been established in 1958, and it basically leads the research for the nation in aeronautics and airspace.
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And I think we have about 10 centers, ranging from Washington, D.C., where the headquarter is, and we have several research centers, like the one in Glenn, the one in Ames Research Center, and then we have the operational centers, like the Human Space Flight Center, which the one I'm from, Johnson Space Center, that manages all the engineering
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the mission control, the astronaut training, and then we have centers like Kennedy Space Center, basically where we have the actual launch and operations to be able to put missions together and launch them into space.
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So it's a big organization, and then we do a lot of research in astronomy, in Earth observation, in planets, in aeronautics, in rocketry, in exploring deep space exploration.
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So it's a vast array of things into that.
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I'm sure a lot of people are curious, and I'm quite curious about this as well.
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Is applying for a job at NASA just like applying for a job at any company?
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I mean, job application, interviews, coming to the office.
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I mean, is it the same process to get a job at NASA as it is, for example, at IBM or Coca-Cola?
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Yeah, it's slightly different.
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It follows the federal government organization, you know, the same rules.
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So typically, most of the hires come from people have done internships or cooperative education, where they spend several semesters rotating in different departments.
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So you get to know these people, you get to know their work.
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ethics, good to know their capabilities.
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And then we have sometimes critical hires where you have to hire some people in certain disciplines that there is a need for.
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But it's the same essential guidelines that any federal agency in the government.
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It's open to the public, depending on what it is, and follows the same rules and regulations.
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And you said you've been there for 21 years.
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Yeah, exactly.
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So I'm sure you've seen the company change since your time there.
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And a lot of people are talking about the future of work and jobs and all that sort of stuff.
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How have you seen NASA change or how have you seen even just work changing during your time here?
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Well, let me tell you about the whole environment, how it's changed.
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So, for example, we just had the 50th anniversary of the Apollo program.
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And at that time, it was a competitive environment, where actually nations were competing for a race to go to the moon.
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And then it changed basically from a competitive environment into more collaborative environment, which is basically the space station.
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We have several nations came together and had this huge complex endeavor of putting the space station in orbit and being one of the most complex scientific platforms that we have ever built.
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And then actually we have a third dimension now, which is basically getting in the commercial startups, the small companies and getting a new dimension to the whole thing now.
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So what we're trying to do now is basically like SpaceX.
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And there is a lot of technologies that was developed at NASA.
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We have a lot of expertise.
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So we're passing along, we're enabling the commercial sector to be able to have an impact and creating more jobs, creating better economy, getting the technology and the knowledge and helping them.
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So combined with the amazing corporate knowledge that we have and amazing innovation and agility that the corporate sector has, I think that creates an excellent environment to create more jobs, improve the economy and so on.
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And then what we need to do is basically we can free up our resources and go explore deep space.
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Our next goal is going to be, for example, going to the moon again by 2024.
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And from there, we're going to go to Mars and hopefully soon after that, in a decade or so.
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You mentioned going from a competitive to a collaborative environment.
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And I feel like a lot of organizations are doing this as well.
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Why do you think that's the case?
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Why was it always about competition before and now it's much more about teams and working together?
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What happened?
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Well, let's look at how technology is evolving.
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So before, when you had the technology in certain sector, typically that technology only was applicable to that specific sector.
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Let me give you an example of a 3D printer or 3D manufacturing, for example.
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People thought when that technology came out, it was only done for producing components, for manufacturing.
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But in fact, it turned out to be something that spans all across various industries.
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It goes, for example, now that the food industry is using it substantially.
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And I've heard of some startups.
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You can actually program your 3D printer when you're going home and being able to print a pizza or something and you get it ready when you go home.
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It's being used in the clothing industry, so there's a lot of research, a lot of startups as well, and companies are working into creating clothing and garments using the 3D printing technologies.
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So in the future, for example, most of the clothing will be tailored specifically to your needs, so you'll be able to buy the file,
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or be able to design specific things and be able to print your own specific garments.
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And then we'll have obviously more electronics embedded in them and so on.
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And in the medical field, so recently we're able to print 3D printed organs based on the genetic composition of the person.
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So the risk of being rejected is almost negligible.
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and also producing casts, producing portions of bones, specifically 100% tailored to the dimensions and the contours of the specific bones.
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In construction, for example, right now, we have houses, construction equipment.
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They could construct a house with 3D printing capability in a few days at a fraction of the cost that used to cost building a conventional home.
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So that's giving access to so many people and in so many different locations
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And for us, of course, when we go to Mars, for example, it's a very far destination from Earth.
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So it is impossible for us to take all the spares or all the equipment that's needed for us to be there for substantial periods of time.
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So what we're working on right now is developing 3D printing capabilities
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And hopefully you'll be able to leverage on the in situ resources and regolith to be able to print any components that we need to use there.
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So you can see, for example, this is a technology and it's no longer applicable to one field.
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It's applicable across all different fields.
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And I can tell you so many different examples like that.
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So nowadays, it makes sense to collaborate between various industries.
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Because first of all, you have the same problem, you can actually split the cost, you can bring new resources into it, you can have different ways of thinking about it.
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So the creativity and innovation that comes because we have very diverse group of people from different industries, it creates completely different designs and different solutions that will be impossible to create in a single organization.
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Yeah.
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Very cool.
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Okay, so you mentioned all sorts of different changes that we're seeing and different technologies.
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So now I'm really curious, if you were to look, let's say 10 years in the future, what do you think the world is going to be like?
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You mentioned 3D printing of clothing, for example.
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I'm sure you have all sorts of ideas in your head around what the world would look like.
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Share your thoughts on that.
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No, absolutely.
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But before we talk about what we go on, I think that the environment, the conventional environment of the work, I think, is starting to change substantially.
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For example, there's research indicates that approximately by the year 2027 in the United States, over 50 percent of the employees will be freelancers.
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And they've done studies indicating that, for example, if you have one employee and you're paying him $100,000, the productivity that you actually get from that person is on the average of 40%.
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So you're paying for 40%, you're paying for 100% and getting 40% product or productivity from that person.
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So the freelancing is starting to become more popular.
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Employees are, you know, preferring it and employers are preferring it.
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So it's a commonality between both.
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And it seems like the conventional work environment is shifting as well.
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But let's talk about a little bit now about the future and with the technology and all that stuff.
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And I think to give you the baseline, let's start talking about the population increase.
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So if you look, for example, at the beginning of human evolution until the year 1800, the whole population of the earth was less than a billion.
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And in the span of almost 200 years,
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we went from almost less than a billion to seven and a half billion people.
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And that trends will continue increasing.
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The estimates are reaching about 10 by the year 2015.
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So we have a vast population increase and that's actually increasing that population on the earth.
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But let's look at the technologies and how the technology is going to have an impact on this and the work and the population and so on.
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If you look at artificial intelligence, which is some topic that people are starting to talk about a lot, it's becoming a very hot topic.
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And just to give you quickly, maybe I can give a few words about how the evolution, because artificial intelligence is nothing new.
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It's been in existence since the 50s.
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But recently, somehow everything became very different.
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And the reason for that is for three pillars, I believe.
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So the first one is the algorithms.
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So we have now much more advanced algorithms that go much deeper, multi-layer, compared to the basic archaic algorithms that we used to have a few decades away.
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So the basic knowledge of putting the things together that reinforce learning and so on, so becoming much more complex.
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The second thing is the computational power.
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So typical computers, you know, they go through in series.
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So you do a calculation, you solve it, you go to the next one.
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But the gaming industry actually came up, invested heavily in that and created GPUs, which could have 5,000 or 6,000 cores.
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So basically, you can run 5,000 or 6,000 operations at the same time instantaneously.
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So that creates a system that's substantially faster and can do much more complex times at a fraction of the time.
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Of course, the third element is going to be the big data.
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So none of that stuff is going to be usable without having the big data where the systems can learn from and be the feedstock and boundary conditions to go through it and being able to determine and tweak the analysis and the results.
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So between all these three now, I think we're in the phase where we call weak artificial intelligence, which is some people estimated that it's equivalent to a human five or six years old.
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You know, it's like at the beginning of the infancy.
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So, and you can see all these advances that you see is still in the weak form.
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In about seven to ten years, estimates are saying we're going to get to general artificial intelligence where you have cognitive capabilities of maybe an adult human, human brain.
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And then in about maybe 20 or 30 years, we'll get to the super artificial intelligence.
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So that's when people are actually are kind of nervous about because there's a lot of uncertainties in that field.
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But so all these things are contributing substantially to changing the landscape of the employment.
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Look, for example, I can talk to you as an engineer.
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If you're going to design something, it takes you weeks or sometimes months.
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You have to actually draft it, to design it, to build the 3D modeling, to run the finite element modeling, to do the testing, the vibration, the thermal.
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So that takes you weeks or months even.
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So with a very advanced artificial intelligence system, you can run all these things, maybe hundreds of thousands of cases or even millions of cases in a few seconds.
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And it can actually tell you which cases are the best ones for which condition and so on.
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So...
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medical doctors, for example, recently with the kind of basic algorithms that we have, in several cases, the artificial intelligence was able to outpass and surpass radiologists and dermatologists in the determination of the diagnosis.
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The same thing with Wall Street.
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I think they did comparison with the very seasoned investors, and they put them head to head with their artificial intelligence systems, which is of today's capabilities,
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And I think it was slightly ahead of the person that was there for decades with a vast amount of experience.
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Same thing with lawyers, same thing with almost any career, right?
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So the same thing is humans themselves.
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I think we're becoming much more efficient.
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We're starting to have much more electronics in us.
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One of the technologies, for example, we have at NASA, as we developed with GM,
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is a glove that enables people to be able to do repetitive tasks without being tired.
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So instead of a person doing the job for a certain amount of time and getting tired, you can do it for much, much longer.
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So all these things are telling you that you need less and less people to be able to perform the jobs and the tasks that needed to do that.
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And mission control, for example, we used to have many more people in the back rooms controlling and helping, aiding the people in the front room.
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And with the advancement of technologies, you see less and less people doing that and being able to take advantage of the amazing computational capabilities that are available.
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So all that stuff doesn't mean that people are not going to have jobs, but there's going to be a shift, obviously.
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There's going to be a big shift because initially there's going to be a phase where will be jobs for people because technologies typically create new jobs, right?
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It's just the problem is, and we had this discussion before a long time ago with the Industrial Revolution.
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People were concerned.
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that emergence of these new automation and machineries were able to displace a lot of jobs.
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And that wasn't the case.
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That was very different, obviously.
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It was actually more jobs were created and it wasn't an impact.
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I think the problem we have right now is we're competing on the intellectual level as well.
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So it's no longer on manual labor, but the intellectual capabilities.
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So that actually opens a new dimension of things that we never explored before and makes things a little bit different.
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I have so many questions for you about what you just said.
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I was trying to take notes as you were going through all that.
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All right, so the first thing that popped into mind, tell me about this glove.
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What sort of glove is it?
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What sort of routine work are we talking about here?
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And also, I'm really curious, are there other areas, and I'm sure there are, inside of NASA that you can share where you are using AI, and what are those areas, and what are you guys doing?
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Yeah, so the glove, for example, if I give you the example, if you can grab a tennis ball and squeeze a tennis ball until you get tired, probably you get tired after 10, 15, 20 times.
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So this glove, it has some actuators embedded in it.
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It enables you maybe to do it for 100, 150, 200 times without having an impact on your ligaments and your muscles and your joints.
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So you'll be able to extend the reach.
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And this is just an example of what can be done, and not only now, but in the future.
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It's beyond the imaginations of things.
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So artificial intelligence, for example, if I can give you some examples, astronomy.
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So astronomers, they have a lot of data points that actually they collect from dishes and they have to go through it manually.
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Sometimes it takes long, long periods of time.
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So with the emergence of artificial intelligence, they can go through all these kind of things and all these boring manual labor that they have to go on repetitive manual labor.
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can be done with a decent artificial intelligence.
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So the amount of work will be reduced substantially and they can concentrate on more fun things as opposed to just being doing repetitive work.
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And could be done also artificial intelligence, like I said, in designing things and finding trends and connecting dots in ways that were difficult to find before.
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So I think it's pervasive technology that's gonna be embedded in every single industry, every single aspect of our life substantially.
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The other thing that you mentioned, which I thought was interesting, and actually I've given a couple of talks on AI, so I've spent some time looking at the history of AI, but a lot of people don't know this.
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And you mentioned this, that AI is not new and it has been around since the 50s.
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So can you talk a little bit about that?
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Because I feel like a lot of people assume that this is a new concept, new idea.
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It came out of nowhere and everyone's talking about it, but it's been decades.
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Yeah.
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Yeah, no, definitely.
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Well, first of all, in the 50s, the basic assumptions on the algorithms, the mathematical assumptions that go into these complex mathematical models were very basic.
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And if you're gonna try to emulate
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is some of the human brain, it's extremely complex way of doing things.
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So first of all, the basic models were very simple and they were completely erroneous.
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They weren't even remotely close to what they were supposed to do.
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And then the computational power that we had was very, very basic as well.
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So it took forever.
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So for a long time, people actually gave up on these kinds of things.
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They said this is not working properly.
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And until recently, a bunch of researchers came in and started putting a lot of research, a lot of funding into it.
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And in the last decade or even a little bit more, I've seen amazing transformations in these mathematical models and algorithms that were able to do much, much better job than what we had before.
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And like I said, that combined with the three elements now, with that amazing computational power.
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So the cool thing about the gaming industry is it's not only developed these kind of things, but they developed it in a way
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for the gaming industry that actually it's very cheap.
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So a lot of labs around the world can use it now.
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So you don't have to be a lab with a lot of funding, with a lot of resources, because these things are available at decent prices.
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So it opens the doors for so many universities, for so many labs and researchers around the world to be able to be engaged in that field.
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And the more people get engaged into that area, then the better results, the better accuracy, the better progress you try to make in this field.
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And then the big data.
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tremendous amount of data being created.
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So if you wanna teach, for example, an algorithm how to identify a cat, then you have to show that algorithms, it has to go through thousands or hundreds of thousands of pictures, right?
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In order for that algorithm to be able to recognize the cats, that this is a cat, this is so on.
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So the big data is a third dimension that we definitely need to be able to make the progress.
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And all these three things were not available in the 50s.
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And that's why the synergy and that center of gravity is improving substantially.
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Okay.
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And so when you look at the world of AI, do you think there's a lot of hype in it?
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Or is a lot of the concern and discussion around it real?
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So, for example, the elimination of jobs, being able to create a kind of a human intelligence by 2030 or 2040.
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We talk about driverless car.
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I mean, is all that sort of stuff actually going to happen?
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Or do you think it's maybe a little bit overblown and everything will just be fine in the future?
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Yeah, well there is actually both.
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I think in my opinion, it could be both happening.
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So first of all, I mean, the work week.
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The work week right now, the standard is 40 hours, you know, five days a week.
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And in my opinion, this is almost like a random number because right now, eventually you can do so many things and you don't need to do the job in so many days or so many hours per day.
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So I think the transition will be essentially is to having less amount of days, you know, working less hours.
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and being able, hopefully, people spend more time doing the things that they enjoy, and being able to capitalize on the technological transformation and advances to be able to improve their lives, the quality of their lives.
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I think that would be the best one.
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But the more we keep moving forward, and like we said, with the big population increase and getting advanced technologies beyond the imagination,
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I think that's where the biggest impact will be.
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And even the current economic models, I think they won't be sustainable anymore.
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When you have huge population increases, we have a lot of billions of people, potentially, if that is the case, potentially without having jobs, then the current economic models might be breaking down.
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So we need to look into what is going to be the future economical models.
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And people to be able psychologically to be satisfied, they need to feel that they're having self-worth, they're contributing, they're producing something.
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So that's all these things.
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So it's gonna be from the psychological, from the technological, from the economical.
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It's gonna be something that policy makers, CEOs, needs to be working substantially on that and be able to predict what's gonna happen the next five, 10, 20, 30 years, according to what advances are we trying to see.
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Another thing, Jacob, I think we need to definitely build the bridge between industry, academia, and government, because all of us need to be working together.
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If technology is improving so fast, if somebody is studying a technical degree in five years, potentially some of the things you study in the first year might be a little bit slightly different by the time you graduate.
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So we need to be constant rejuvenation, constant update and cycle.
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and the loop between all these people, the academia industry and government, to be able to produce the better workforce in the future.
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And a lot of people actually ask as well, what will be the skills needed in the future?
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That was gonna be my next question.
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Yeah.
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It's going to be very difficult to predict.
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Well, it's going to be easy to predict in the next five years, but we're talking about maybe 15, 20 years.
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It becomes more challenging because in the next 10 years, probably the majority of the jobs don't exist today yet.
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So it will be jobs that will be created depending on what technologies, depending on what ecosystems are coming across.
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But I think that the skills that need to be developed in everybody now is –
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is like before people used to go to college, study a degree, and then that's it.
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They never went back to college, they never read anything or research papers.
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I think that fact is completely gone now.
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So you need to constantly be learning, constantly be adaptive.
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You need to be able to change and get out of your comfort zone and try new things.
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So you need to develop also jobs, the jobs that will be more difficult to impact is jobs that necessitates or needs to be creative.
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have emotional intelligence probably, having decision-making capabilities.
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So any job in that field might be a little bit more difficult to penetrate initially.
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We don't know what's gonna happen in the long future.
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But traits like that will be needed.
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Just adaptability, learning constantly, and being able to adapt to the new environments.
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Because if you look at the work environment now, people that have been working for 15, 20 years, it's very difficult to change the ways of their, the way they do their job.
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It's very, very difficult to do that.
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So I think this mindset will need to change and people need to be more adaptable, more flexible in order to be able to be sustainable and maintain these technological changes that we're having.
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I have one more technology question for you, and then maybe we can switch into some of the non-technology stuff, like ways of thinking.
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I mean, you mentioned design thinking.
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And the last technology question is more around which technologies are you paying attention to that you think are going to have the greatest impact?
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So you mentioned quantum computing.
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We talked about AI.
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You mentioned 3D printing.
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Which areas are you paying attention to the most and why?
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And which ones do you think are maybe a little bit overhyped?
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Okay, well, I can give you five technologies and I think definitely gonna be big, big impacts.
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And the thing I'm looking into right now, look at the internet, for example, it was a basic technology, but out of that technology, we have almost $7.5 trillion in economy.
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And look how many millions and millions of jobs were created because of that technology.
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So now we have artificial intelligence, we have drones, we have autonomous systems, we have quantum computers, for example, we have 3D printing.
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So these are basic technologies, but I'm interested in knowing what are gonna be the ecosystems that are gonna be developed across around all these basic technologies, because all of these will need support systems, support technologies, support startups, support industries.
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Let me give you an example of driverless cars.
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So a driverless car is going to have substantial impacts on the positive and on the negative as well.
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It's going to create jobs, it's going to take a lot of jobs from different places.
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For example, the driverless cars, when you talk about manufacturing, car manufacturing,
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So on average, people in the United States have two cars or three cars per family.
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But if you have a car that's autonomous, it can go from one place to another by itself, then obviously you don't need three cars.
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You only need one car, and the car will take the members of the family and be able to pick them up and be coming.
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Because right now, we only drive to the work destination.
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Right.
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and we leave the car in the parking lot for the most of the day.
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So you can have one car that takes care of the whole family and drives by itself and immediately you reduce the amount of cars between 50 to 70%.
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And then the discussions are actually around the,
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the neighborhoods having fleets of cars for neighborhoods or so on.
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So we're talking about substantial reduction in the amount of cars, um, and that needs to be produced.
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So the question is, what's going to be the impact on these car manufacturing people insurance.
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For example, if these cars will never get into an accident, they're 100% safe eventually.
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And that will never be stolen.
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So what is the role of insurance companies in these kind of things?
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And most of the insurance companies, it's a big source of income from them is insuring these automobiles and cars and vehicles.
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So if you only need to ensure a fraction and then eventually maybe reduced, so what's going to impact on the jobs from these fields?
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Hotels, for example, if you right now you can drive, for example, from San Francisco to Los Angeles.
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It's about maybe a six-hour drive or so.
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So instead of sleeping and staying at Los Angeles, if you have to have a meeting and come back, you can have your meeting and come back in your car.
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You can sleep while your car is driving you back.
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And so what's the impact on the hotel industry and the garages?
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But at the same time, these technologies are going to be creating new jobs.
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because they're going to be servicing companies that will need to be adapted and work to be able to help these technologies.
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For example, if you're going to stay in your car for prolonged periods of time, you probably need to eat.
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So maybe there's some way of maybe printing food or being able to produce food during the long drives.
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Yeah, maybe mobile office, better communication and mobile office environments.
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and maybe entertainment systems that are beyond what we have right now, security obviously.
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So cybersecurity will be essential, will be completely paramount for the success of the driverless cars.
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So we'll be creating more jobs in that field.
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So you can say, this is the technology, for example, single one, and it's creating jobs, but at the same time, it's displacing so many different jobs at the same time.
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So the question is, where's the balance gonna fit eventually?
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Is it gonna be more in the losing jobs or more in creating jobs?
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And that's the questions we'll have to see, actually, as we go along.
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Yeah, that's that's a very good question.
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I feel like a lot of people today are focused on the elimination of jobs and they never talk about the creation of jobs.
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And and I think that's why there's so much negativity around it, because we're very obsessed with the jobs that will be removed, but not with all the jobs that are going to be created.
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So I'm really glad that you brought that up.
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I wanted to switch gears a little bit and talk a little bit around how you encourage different types of thinking.
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Because in your LinkedIn profile, which I thought you had a very interesting way that you described your role.
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And you said, empower the organization to create creative thinking to tackle moonshot challenges and develop capacity to innovate.
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So let's start with the first part of that, which is to empower the organization to develop creative thinking.
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How do you develop creative thinking?
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Are there exercises or trainings that you guys do internally?
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Sure.
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Okay, so one of the things that I do is I teach something called Design Thinking Workshop.
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And so what I try to instill in people is completely think outside of the box.
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Don't take the normal assumptions.
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And I've done an investigation actually in teaching the class so many times.
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So one of the elements that I ask people to design is one of them is designing a wallet.
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And then I put a picture of the wallet and I tell them to come up with an idea how to design the wallet.
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And then 100% of the times people design a conventional wallet like the one you were showing them.
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So they were sickly, it was anchoring the thinking process because they were seeing that wallet and that was everything they were concentrating on.
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And then I, for the last few classes I did, I didn't put the picture, I said design a wallet and a wallet could be anything.
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And the ideas were completely, completely creative, completely out of the box.
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That was the most creative classes I've taught is the last few ones.
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When I took that picture and the conditioning of the image by encouraging people to think completely in divergent ways and not condition themselves about what's going on in front of them.
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And this is a Stanford exercise, right?
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Exactly.
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Yep, exactly.
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So there's multiple ones.
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The wallet is a good one because it applies to everybody.
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Everybody knows the same.
389
00:35:35.404 --> 00:35:37.165
Everybody has a wallet of some sense, right?
390
00:35:37.185 --> 00:35:37.385
Right.
391
00:35:37.785 --> 00:35:43.688
And you can do the same thing to create, you know, talk about cities, how to design cities, how to design products.
392
00:35:44.228 --> 00:35:52.972
It's just a way basically of involving the customer in the loop because a lot of times people do designs from one area and they don't involve the customer in the loop.
393
00:35:53.132 --> 00:35:54.873
And that's when you start failing to things.
394
00:35:57.650 --> 00:36:03.715
And for people that want to see this, I think they can go into the Stanford website, right, to see the wallet design challenge.
395
00:36:03.735 --> 00:36:06.898
I think it's like a public template that somebody can download.
396
00:36:07.258 --> 00:36:07.879
Yes, exactly.
397
00:36:08.159 --> 00:36:08.480
Okay.
398
00:36:08.500 --> 00:36:10.301
Like I said, the wallet is one of them.
399
00:36:10.641 --> 00:36:13.764
The methodology is being developed between Harvard and Stanford.
400
00:36:13.784 --> 00:36:15.666
They have amazing, you know, literature.
401
00:36:16.386 --> 00:36:18.468
But the examples, there's tens of examples.
402
00:36:18.488 --> 00:36:22.992
And one of the ones I like to use sometimes is the wallet because, like I said, it's something common between everybody.
403
00:36:23.012 --> 00:36:23.933
Everybody, you have your wallet.
404
00:36:24.428 --> 00:36:28.693
And it's simple to pass the message and teach the class and the workshop to gain the idea.
405
00:36:29.493 --> 00:36:39.397
Okay, so it sounds like you teach employees this concept, but how does it become applicable into sort of real world how they're doing their jobs?
406
00:36:39.537 --> 00:36:48.200
Because it's one thing obviously to do something in a class, it's another thing to actually take those concepts and apply them in the real world when they're doing work for NASA.
407
00:36:48.220 --> 00:36:49.320
So how do you translate that?
408
00:36:50.021 --> 00:36:56.123
Okay, well it's something very important and I think it's an impediment to a lot of organization is something called groupthink.
409
00:36:56.665 --> 00:37:08.329
So when you have, for example, five engineers, or you have five business people, you have five medical doctors, then it's like having one person, because all of these people are going to have the same mentality, the same way of thinking.
410
00:37:08.829 --> 00:37:15.472
So one of the ways I encourage people to do is actually diversify the group as much as possible, and that's when you start having creative...
411
00:37:15.961 --> 00:37:18.824
ideas completely creative.
412
00:37:19.184 --> 00:37:27.992
So imagine if you have an engineer, you have a scientist, you have a business person, you have a lawyer, you even have an accountant, I mean an artist.
413
00:37:28.352 --> 00:37:31.095
So the ideas you'll be able to get will be 100% different.
414
00:37:31.195 --> 00:37:33.277
And then if you have people from different generations as well,
415
00:37:34.818 --> 00:37:37.321
people from different cultural backgrounds.
416
00:37:37.702 --> 00:37:40.265
It's completely diverse, the ideas we'll be able to get.
417
00:37:40.645 --> 00:37:45.231
So that's something very essential, very important, is diversifying your group as much as possible.
418
00:37:45.311 --> 00:37:47.774
That's when you start getting ideas outside of the box.
419
00:37:48.795 --> 00:37:55.924
I'm glad that you mentioned that because I have a new book that's coming out in January of next year on the future leader.
420
00:37:56.604 --> 00:38:03.392
And I talk a lot about this idea of diverse teams, which I don't think we pay enough attention to in the business world today.
421
00:38:04.033 --> 00:38:08.274
But for for a leader, I guess, how do you how do you ensure that diverse team?
422
00:38:08.294 --> 00:38:10.715
Are there certain criteria that you look at?
423
00:38:11.475 --> 00:38:18.156
If you're not a part of a diverse team, do you encourage employees at NASA to speak up and say, hey, you know, everybody on this team is the same and looks the same.
424
00:38:18.176 --> 00:38:19.637
Maybe we should get some other people in here.
425
00:38:20.257 --> 00:38:25.178
Or how do you encourage that so that people don't get in trouble so they're not scared to speak up?
426
00:38:25.851 --> 00:38:27.752
Yeah, no, it's a trial and error.
427
00:38:27.812 --> 00:38:30.514
And hopefully you keep trying until you get something that works out.
428
00:38:30.855 --> 00:38:33.316
But talking about speaking out, for example.
429
00:38:33.376 --> 00:38:41.082
So one of the elements when you're doing brainstorming is we teach people how to not judge any idea beforehand.
430
00:38:41.442 --> 00:38:46.366
So, for example, if people are brainstorming and somebody comes up with an idea and I say, no, I don't like this idea.
431
00:38:46.386 --> 00:38:47.106
This is not going to work.
432
00:38:47.266 --> 00:38:49.248
And then that person comes up with a second idea.
433
00:38:49.853 --> 00:38:53.374
And I said, you know what, it's probably not that, that's not what I was thinking about.
434
00:38:53.814 --> 00:38:57.516
And then the third time, that person is not gonna contribute anything, he's gonna shut down.
435
00:38:57.996 --> 00:39:02.178
So what we do is we try to encourage everybody to come up with ideas and we don't judge anything.
436
00:39:02.198 --> 00:39:05.279
We said, yeah, I like your idea and actually I can combine it with that person.
437
00:39:05.679 --> 00:39:08.660
I can combine it, this idea combined to a third concept.
438
00:39:09.040 --> 00:39:14.702
So it's even the way you run these kind of things and the way you deal with people, I think it has a lot of difference.
439
00:39:14.782 --> 00:39:17.023
It makes a big difference in the way you harvest things.
440
00:39:18.003 --> 00:39:21.345
There's a lot of psychological elements that go into creativity and innovation as well.
441
00:39:22.286 --> 00:39:24.607
How do you guys structure your teams?
442
00:39:25.067 --> 00:39:32.211
Is it, I know, for example, Amazon, they have their famous like two pizza rule where no team should be bigger than two large pizzas can feed.
443
00:39:33.091 --> 00:39:35.713
Do you structure your teams in any particular way?
444
00:39:36.832 --> 00:39:37.473
It depends.
445
00:39:37.553 --> 00:39:39.355
It's a big organization, right?
446
00:39:39.575 --> 00:39:44.180
And every director, every organization does it in a different way.
447
00:39:45.101 --> 00:39:47.904
Some people try to leverage a lot on open innovation.
448
00:39:48.505 --> 00:39:50.267
Open innovation, by the way, has been incredible.
449
00:39:50.687 --> 00:39:51.828
So right now, for example...
450
00:39:53.550 --> 00:40:05.274
If you have a challenge, if you have a problem, not only you can leverage of the employees that you have in-house, but you can put a challenge and actually have hundreds of thousands of people looking at it and producing solutions that are, you know, it would be something incredible.
451
00:40:06.035 --> 00:40:13.137
One of the actually cases I read recently is a potato chip manufacturing company was having an issue with the extra grease.
452
00:40:15.428 --> 00:40:19.771
They were struggling because to remove the grease from the chips, you need to shake the potato.
453
00:40:20.112 --> 00:40:23.114
And that results in the potatoes broken into pieces.
454
00:40:23.154 --> 00:40:26.396
And it's not attractive when you open a bag of chips with broken pieces, right?
455
00:40:26.977 --> 00:40:31.240
So they put an open challenge on one of these open innovation platforms.
456
00:40:31.861 --> 00:40:32.041
And...
457
00:40:32.929 --> 00:40:35.410
The results actually, the best solution came from a violinist.
458
00:40:35.950 --> 00:40:46.676
So the violinist actually came up with the tone that actually was hitting the natural frequency of the grease and was being removed from the chip without impacting the potato chip itself.
459
00:40:47.336 --> 00:40:51.158
And so you can see it's like, you can come up with amazing solutions.
460
00:40:51.298 --> 00:40:55.700
You don't have to have as many employees working on things because you can leverage on the huge amount of vast
461
00:40:56.273 --> 00:41:03.017
resources that you have outside of your organization with the emergence of these new open innovation platforms Do you guys do that internally at NASA as well?
462
00:41:03.518 --> 00:41:04.198
Yeah, exactly.
463
00:41:04.218 --> 00:41:05.779
We do some internally.
464
00:41:05.839 --> 00:41:07.820
We use some of them externally.
465
00:41:08.221 --> 00:41:13.224
So that's like I said, the power of crowdsourcing has been incredible in every single thing that we do.
466
00:41:14.164 --> 00:41:18.167
Not only in companies like Uber, like Facebook, like everything.
467
00:41:18.807 --> 00:41:24.391
And open innovation, I think, has been incredible in bringing crowdsources to help with solutions and technologies.
468
00:41:24.411 --> 00:41:24.531
Yeah.
469
00:41:25.191 --> 00:41:31.255
Okay, so it sounds like part of your job, as you said, you encourage this kind of unique way of thinking.
470
00:41:31.335 --> 00:41:40.642
And the main way you do that is through these workshops, these programs that you teach around thinking out of the box, and also through diversity.
471
00:41:40.702 --> 00:41:42.984
Are those the two kind of main pillars you use?
472
00:41:44.164 --> 00:41:45.726
Also, there's other ones.
473
00:41:46.306 --> 00:41:50.389
For example, the more you read about articles, recent articles, read books.
474
00:41:50.449 --> 00:41:51.970
So we do also a series of topics
475
00:41:52.805 --> 00:41:58.410
Once a week, we have brown bag lunches where we talk about maybe an article that has to do with innovation, with creativity.
476
00:41:59.591 --> 00:42:08.139
So, you know, for example, there is so many cases, I can tell you, that don't involve spending a penny in solving big problems.
477
00:42:08.760 --> 00:42:12.423
There is, for example, a bike company, an electric bike company in the Netherlands.
478
00:42:13.095 --> 00:42:20.340
And they were having about a rate of 60 to 70 percent return because it's a very sensitive equipment with a lot of electronics.
479
00:42:20.920 --> 00:42:26.864
And people in the shipping companies, when they were seeing that they were shipping bicycles, they were being rough and transporting them from one place to another.
480
00:42:27.425 --> 00:42:33.489
And that's actually the company almost ran out of business because most of these components and bicycles were coming back to them damaged.
481
00:42:34.029 --> 00:42:36.672
So one of the employees came up with a brilliant idea.
482
00:42:36.832 --> 00:42:42.459
Okay, said, why don't you actually print a picture of a TV, an LCD TV on the box of the bicycle?
483
00:42:42.879 --> 00:42:46.504
And that gives the impression to the shipping people that they're transporting a TV.
484
00:42:47.044 --> 00:42:50.228
So by doing that, it's a simple idea and almost...
485
00:42:51.556 --> 00:42:53.398
eliminated completely the problem that they had.
486
00:42:53.658 --> 00:42:54.319
That's awesome.
487
00:42:54.999 --> 00:42:56.080
I love that idea.
488
00:42:56.741 --> 00:43:01.386
Another example is there's also a small town in one of the European countries.
489
00:43:01.886 --> 00:43:04.469
They were having problems with speeding cars.
490
00:43:05.089 --> 00:43:10.274
And they put a lot of fines, big fines, and it wasn't having an impact on reducing the speeding cars.
491
00:43:10.314 --> 00:43:13.698
And there was a lot of kids playing, so they were concerned about potential accidents.
492
00:43:14.783 --> 00:43:28.835
So one of the people in the city council came up with an idea and said, instead of punishing people for speeding, why don't we actually have, we actually encourage people that don't do this damage or don't do speeding, we encourage them by positive reinforcement.
493
00:43:29.295 --> 00:43:32.498
So they started recording all the plates of the cars,
494
00:43:33.087 --> 00:43:35.308
And the ones that were not speeding, they put them into a pool.
495
00:43:35.688 --> 00:43:42.331
And at the end of the month, they got a check from the people that were speeding for the collections of the money that they collected from people were speeding.
496
00:43:42.811 --> 00:43:52.255
So by doing reinforced learn, reinforced actually behavior, as opposed to, to, to, to take the money from the people that also solve the problem substantially.
497
00:43:53.297 --> 00:43:54.877
We can talk for a long time.
498
00:43:54.897 --> 00:43:56.158
I have so many examples about that.
499
00:43:56.198 --> 00:43:59.458
But sometimes innovation doesn't require you to spend so much money.
500
00:43:59.478 --> 00:44:04.279
It just could be a simple idea that could have a big impact on solving a big problem that you've been having for years.
501
00:44:04.819 --> 00:44:06.420
Yeah, no, those are great stories.
502
00:44:07.240 --> 00:44:21.863
So I guess for people listening, maybe for leaders or even for individuals, if they want to encourage this kind of innovative thinking, you recommend those two things, kind of teaching design thinking in new ways of approaching problems and also focusing on building diverse teams.
503
00:44:22.831 --> 00:44:30.657
Yes, and also reading as much as possible cases, innovation cases, creativity cases from different magazines, innovation magazines.
504
00:44:31.117 --> 00:44:34.200
And also I noticed it's very essential who you surround yourself with.
505
00:44:34.760 --> 00:44:42.626
If you have creative people in your organization and these people are talking and showing what they're doing, it's a contagious thing.
506
00:44:42.666 --> 00:44:44.928
So people will definitely start thinking differently.
507
00:44:44.948 --> 00:44:46.890
So the more examples, for example, you show to people.
508
00:44:47.891 --> 00:44:52.456
they start rewiring the way of thinking and they start thinking about things in a different way completely.
509
00:44:52.836 --> 00:44:58.082
So it's who do you engage with, who you surround yourself with, what literature do you read,
510
00:44:58.815 --> 00:45:03.657
how diverse your team is, how do you capitalize on the tools that we have today in open innovation.
511
00:45:04.097 --> 00:45:07.379
And at the end, it has to do with leadership as well.
512
00:45:07.539 --> 00:45:12.721
So a lot of organizations, for example, say I wanna be innovative.
513
00:45:12.981 --> 00:45:14.882
I wanna create so many innovative products.
514
00:45:15.502 --> 00:45:20.044
And a lot of employees come out and they come up with these concepts, but everything stops in the middle.
515
00:45:20.344 --> 00:45:22.405
Typically middle management is what stops everything.
516
00:45:22.985 --> 00:45:28.147
And the reason is because they're afraid that if they actually take risk, that their jobs will be at risk.
517
00:45:28.693 --> 00:45:40.764
And I found out that the best way to tackle these kind of things is by actually the executives having in the performance evaluation mandatory actions that this is something you need to do, but at the same time have their backup, right?
518
00:45:40.884 --> 00:45:41.384
Have their back.
519
00:45:41.905 --> 00:45:45.308
So if something happens, they need to understand it's not going to impact their job.
520
00:45:45.408 --> 00:45:47.690
It's encouraged to take risks.
521
00:45:48.312 --> 00:45:51.814
And if something happens, your job is not gonna be at risk.
522
00:45:51.894 --> 00:45:58.377
And when people feel comfortable then, then you have a whole cycle happening from the top to the bottom, and we have things happening in organizations.
523
00:45:58.857 --> 00:46:01.979
Otherwise, the whole system will break through.
524
00:46:02.019 --> 00:46:05.761
So it's the leadership, the organization, the way you think about things.
525
00:46:06.341 --> 00:46:08.042
It's a puzzle, it's like a Lego.
526
00:46:08.062 --> 00:46:11.784
It's like different pieces that have to come together to be able to come up with the best results.
527
00:46:12.244 --> 00:46:15.972
The other thing that you're talking about is this idea of moonshots.
528
00:46:16.693 --> 00:46:20.320
So can you talk about what those are and how you encourage people to reach for those?
529
00:46:21.395 --> 00:46:25.779
So yeah, moonshots, essentially it came from going to the moon.
530
00:46:25.819 --> 00:46:31.424
So at that time it was seemingly like an impossible task to go to the moon with the technology we had.
531
00:46:32.085 --> 00:46:43.095
And with the amount of determination and work and the technology development and funding, we're able to do something that seems completely impossible.
532
00:46:43.355 --> 00:46:45.237
So that's where the term moonshot came.
533
00:46:45.777 --> 00:46:52.645
And Moonshot is something where you create multiple orders of value compared to, or they call sometimes 10x.
534
00:46:52.866 --> 00:47:00.395
It's like compared instead of having maybe 10%, 20%, or 30% improvement, you create something that's actually 10 times better than what you have right now.
535
00:47:01.035 --> 00:47:05.177
And that's why to do that you have to think completely different.
536
00:47:05.377 --> 00:47:10.240
You have to go back to the basic, to the drawing board and start coming up with completely new things.
537
00:47:11.160 --> 00:47:14.502
Look at, for example, at the smartphones when it first came out.
538
00:47:14.662 --> 00:47:18.364
That was completely a moonshot almost because people used to have simple phones.
539
00:47:18.824 --> 00:47:24.747
So the smartphones, the creation of the smartphones actually, that was, in my opinion, one of the moonshots that changed completely.
540
00:47:25.587 --> 00:47:29.889
These industries are creating this revolution in communication that we have today.
541
00:47:30.329 --> 00:47:33.271
Same thing in medicine, same thing in any field as well.
542
00:47:33.751 --> 00:47:38.974
But yeah, so unfortunately, these moonshots are very much, much, much more difficult.
543
00:47:39.454 --> 00:47:41.115
And the majority of it will fail.
544
00:47:41.615 --> 00:47:46.097
But if you have some of them that succeed, that will change completely, 100% your industry.
545
00:47:47.160 --> 00:47:49.240
How do you deal with failure at NASA?
546
00:47:49.720 --> 00:47:53.861
Yeah, well, failure, and the thing is, I see failures in two different ways.
547
00:47:54.061 --> 00:48:00.902
I mean, obviously, when you have people, or astronauts on a rocket going to launch, if you fail, now that's absolutely not acceptable.
548
00:48:01.703 --> 00:48:08.004
But there's a lot of times, a lot of way you can fail before you get there, and you learn a lot from it, actually.
549
00:48:08.344 --> 00:48:15.345
And just to give you an example about failure, and about errors, and from nature, so you know, like the monarch butterflies, for example,
550
00:48:15.945 --> 00:48:26.074
So there was a genetic error in one from one generation to another and that thing enabled the larva to eat some milkweed which is a poisonous plant.
551
00:48:26.474 --> 00:48:34.981
So because of that, when the larva ate that one, because of the genetic composition, genetic error that happens, allowed them to do that without poisoning them.
552
00:48:35.462 --> 00:48:41.447
So when it transformed into monarch butterflies, then the predators learned over time
553
00:48:41.827 --> 00:48:45.971
that these butterflies are poisonous and they just left them alone.
554
00:48:46.391 --> 00:48:51.556
So from something, from mistake, it created something that actually, essentially saved the whole species.
555
00:48:52.016 --> 00:48:56.400
So there is a lot of things and benefits from failing and from making mistakes.
556
00:48:56.620 --> 00:49:01.904
And as long as you learn from them and you don't repeat them again, I think it's not a bad thing.
557
00:49:02.525 --> 00:49:09.331
It's just the problem is at the end, collectively, if you keep making mistakes at the end, then that's absolutely not acceptable luck.
558
00:49:09.771 --> 00:49:14.212
like when it comes to sending people and humans into different places.
559
00:49:14.732 --> 00:49:25.035
When employees at NASA fail, and of course, we're not talking about sending a human into space, but maybe during the course of, you know, regular projects or things like they're working on here on Earth.
560
00:49:25.635 --> 00:49:29.035
If an employee fails, how do you deal with it?
561
00:49:30.176 --> 00:49:31.756
You know, they made a big mistake.
562
00:49:32.296 --> 00:49:33.556
What happens to that employee?
563
00:49:33.576 --> 00:49:35.577
How do you then treat it or address it?
564
00:49:36.200 --> 00:49:44.660
Yeah, that's like any other organization, depends who's the employee, who's their manager, is he a leader, is he a manager, what kind of mistake did he make,
565
00:49:45.159 --> 00:49:48.341
Did he make mistakes multiple times?
566
00:49:48.681 --> 00:49:50.122
So it's very dynamic, right?
567
00:49:50.202 --> 00:49:51.302
It's multiple dimensional.
568
00:49:51.462 --> 00:49:52.543
It's very difficult.
569
00:49:52.563 --> 00:49:56.805
But I can tell you about my personal experience dealing with people.
570
00:49:57.666 --> 00:50:01.047
If they make a mistake, it's okay.
571
00:50:01.068 --> 00:50:01.968
We can learn from it.
572
00:50:02.088 --> 00:50:06.550
And we try to actually have corrective action and make sure that never happens again.
573
00:50:06.610 --> 00:50:09.332
And we share these mistakes with other groups.
574
00:50:10.128 --> 00:50:12.130
So actually people can learn from each other.
575
00:50:12.651 --> 00:50:24.402
And I don't see it as a bad thing initially because, you know, if you're actually going to be punishing people making mistakes, then you're going to be able to restrict people from doing a lot because you're going to be actually afraid to take any risk.
576
00:50:24.902 --> 00:50:26.404
And without taking risk, you can't do much.
577
00:50:26.584 --> 00:50:30.347
You have to take risk in order to be pushing the envelope and doing something that's going to be different.
578
00:50:30.367 --> 00:50:30.467
Yeah.
579
00:50:31.188 --> 00:50:38.256
Do you guys have a certain risk framework that you use to help you decide where to make your investments or which decisions to make?
580
00:50:38.376 --> 00:50:39.797
Or how do you approach that?
581
00:50:40.378 --> 00:50:41.459
Yeah, there is definitely.
582
00:50:41.860 --> 00:50:44.362
NASA has a huge corporate knowledge in these kind of things.
583
00:50:44.422 --> 00:50:46.184
And there's tons and tons of people.
584
00:50:46.224 --> 00:50:47.205
That's what they do for a living.
585
00:50:47.726 --> 00:50:51.850
And sometimes, you know, they buy risk by investing more in certain areas or not.
586
00:50:51.870 --> 00:50:53.292
So it's a big field, obviously.
587
00:50:53.852 --> 00:50:54.793
We deal with it every day.
588
00:50:55.013 --> 00:50:57.134
And because the space business is very risky business.
589
00:50:57.194 --> 00:51:01.497
And no matter what you do at the end, you have to accept a certain element of risk.
590
00:51:01.617 --> 00:51:04.339
Otherwise, you're in the wrong business.
591
00:51:05.380 --> 00:51:07.041
Yeah, there's always going to be risk.
592
00:51:07.461 --> 00:51:12.104
Are you able to share any of that framework, like some of the steps that go into it or some of the things that you think about?
593
00:51:13.217 --> 00:51:18.021
Yeah, there is a lot of analysis, failure modes and effect analysis, hazard analysis.
594
00:51:18.081 --> 00:51:28.170
So depending what component you design, you can see, for example, what are the failure modes for that kind of thing, how critical they are, how many redundancies do you have.
595
00:51:28.551 --> 00:51:34.436
So it's a big framework that people can do, and it's big specialists that work on these fields and areas.
596
00:51:34.456 --> 00:51:34.636
Yeah.
597
00:51:34.871 --> 00:51:35.591
Okay, okay.
598
00:51:36.552 --> 00:51:40.194
The other thing I know that you spend a lot of time thinking about is innovation.
599
00:51:40.974 --> 00:51:43.115
So how do you define innovation?
600
00:51:43.135 --> 00:51:44.016
So what is it?
601
00:51:44.176 --> 00:51:48.798
And how do you encourage your team, your employees to be innovative?
602
00:51:49.398 --> 00:51:49.539
Yeah.
603
00:51:50.019 --> 00:51:56.242
So innovation in my opinion is basically using the resources that you have to create new value.
604
00:51:57.534 --> 00:52:04.304
So not necessarily – sometimes people refer to innovation when you create something that you spend maybe tens of millions to develop a new technology.
605
00:52:04.745 --> 00:52:06.607
Yeah, obviously, that is an element of innovation.
606
00:52:06.647 --> 00:52:11.595
But innovation could be just using some of the resources that you have right now and create something completely different.
607
00:52:12.175 --> 00:52:14.056
that creates better value than what you had before.
608
00:52:14.517 --> 00:52:20.880
Or could be thinking of an idea that actually can solve a problem like the one we alluded to earlier before.
609
00:52:21.401 --> 00:52:29.625
So innovation has a lot of segments and all collectively is how do you make better value into the organization?
610
00:52:29.665 --> 00:52:37.090
How do you make things better, cheaper, create something that is much, much better than what it used to be before?
611
00:52:37.650 --> 00:52:40.812
I think all that stuff collectively is an element of innovation.
612
00:52:42.088 --> 00:52:42.308
Okay.
613
00:52:42.888 --> 00:52:46.470
And yeah, I mean, I think innovation is a huge topic.
614
00:52:46.510 --> 00:52:49.792
And sometimes I think people confuse sort of invention with innovation.
615
00:52:50.812 --> 00:52:51.613
Yeah, no, exactly.
616
00:52:52.493 --> 00:52:57.096
An invention could be an element of that, but it's, yeah.
617
00:52:57.176 --> 00:52:58.276
Not necessarily the same thing.
618
00:52:58.817 --> 00:52:59.397
No, definitely.
619
00:52:59.757 --> 00:53:00.277
Okay.
620
00:53:00.517 --> 00:53:06.020
Yeah, innovation could be, you know, something is not an invention, but an invention could be part of an innovation.
621
00:53:06.060 --> 00:53:07.181
So it's intertwined.
622
00:53:08.180 --> 00:53:09.521
What is it like to work at NASA?
623
00:53:09.901 --> 00:53:13.182
So is it free food, open spaces, gym memberships?
624
00:53:13.663 --> 00:53:15.223
Or what's the environment like there?
625
00:53:15.484 --> 00:53:16.784
No, it's very exciting.
626
00:53:16.824 --> 00:53:24.788
Obviously, you're working on the leading edge technology to sending people into different planets or to study the latest sciences in different fields.
627
00:53:24.848 --> 00:53:26.429
So it's very exciting from that perspective.
628
00:53:27.169 --> 00:53:28.890
But essentially, it's a government agency, right?
629
00:53:28.910 --> 00:53:35.033
So it's not like, well, sometimes when I go visit Google or visit Facebook and some of these high tech companies,
630
00:53:35.639 --> 00:53:36.760
And you get the free food.
631
00:53:36.800 --> 00:53:38.141
The environment is very different.
632
00:53:38.281 --> 00:53:40.583
Obviously, we cannot do that in government organizations, right?
633
00:53:41.284 --> 00:53:43.626
But each one has advantages and disadvantages.
634
00:53:43.666 --> 00:53:46.469
But it's a very exciting job, very exciting organization.
635
00:53:46.509 --> 00:53:52.314
I think it's one of the ones with the highest job satisfaction across the federal agencies.
636
00:53:52.454 --> 00:53:54.496
And it's incredible.
637
00:53:54.976 --> 00:53:56.978
Everybody there is very motivated, very hard worker.
638
00:53:57.701 --> 00:54:01.224
And together, I think it's amazing things are happening.
639
00:54:02.365 --> 00:54:15.035
What do you think people listening to this who are not working for engineering organizations or space companies like NASA, what can they learn from some of the approaches or the ways of thinking that you guys have internally?
640
00:54:15.135 --> 00:54:24.963
So, you know, for, for people out there who are, you know, traditional business environment, business jobs, what advice would you give to them based on what you've learned at NASA?
641
00:54:26.787 --> 00:54:35.772
I think it goes both ways, actually, because one of the things I like to do every month is go to a completely different company that's outside of my industry.
642
00:54:36.193 --> 00:54:40.575
And I see how they run their business, what governance models they have, and I try to learn from them.
643
00:54:41.015 --> 00:54:44.958
So I think it's something that's both directional.
644
00:54:45.358 --> 00:54:46.859
We learn because we don't do everything.
645
00:54:47.639 --> 00:54:49.060
We're not the best at everything, obviously.
646
00:54:49.880 --> 00:54:54.604
But a lot of the things are being done much better in different industries and different organizations.
647
00:54:55.065 --> 00:54:59.808
So I think the best way to do is try to have benchmarking.
648
00:55:00.189 --> 00:55:10.357
So collectively, people from different industries, maybe from different government organizations, start having benchmarking and try to learn from each other and see what –
649
00:55:11.260 --> 00:55:12.301
How do you guys deal with failures?
650
00:55:12.341 --> 00:55:14.483
How do you deal with creating new value?
651
00:55:14.563 --> 00:55:15.604
How do we learn from each other?
652
00:55:15.644 --> 00:55:17.705
Can we learn from your mistakes?
653
00:55:17.765 --> 00:55:19.447
Can we learn from your successes?
654
00:55:19.487 --> 00:55:21.548
Can we work together to solve some of these kind of things?
655
00:55:21.949 --> 00:55:28.714
So I think that is the most essential element is kind of actually do it in a big scale and benchmark and learn from each other.
656
00:55:29.775 --> 00:55:41.325
Do you think there are any practices that you guys use at NASA that other companies don't, whether it's decision making, whether it is an approach that you have to problem solving?
657
00:55:41.345 --> 00:55:44.988
Maybe it's even a way that you approach leadership or a perk that you have.
658
00:55:45.548 --> 00:55:50.832
Is there anything that you think is unique to NASA that no other company out there has or does?
659
00:55:52.335 --> 00:55:53.356
That's a very good question.
660
00:55:54.117 --> 00:55:57.180
So, yeah, obviously we're very good at systems engineering.
661
00:55:57.320 --> 00:56:07.770
I think we're at JSC, for example, Johnson Space Center is one of the best in the world at systems engineering, how to put different systems and components together to produce some big vehicle or big thing.
662
00:56:08.871 --> 00:56:16.218
We're very good, for example, at risk analysis, at safety and mission assurance, because we have to deal with that every single day.
663
00:56:16.935 --> 00:56:19.756
And also, but it depends on the organization.
664
00:56:19.796 --> 00:56:27.039
For example, if you're talking about the flight director, then the governance model is very different than a person, for example, in a design organization.
665
00:56:27.459 --> 00:56:33.961
So depending on which organization you are, it's going to be very different, the governance models and the way you deal with the management and so on.
666
00:56:34.881 --> 00:56:39.263
But yeah, if I had to choose two, I would say definitely systems engineering
667
00:56:39.960 --> 00:56:45.466
and safety analysis, risk analysis, and all these kind of things, since this is at the core of what we do.
668
00:56:46.026 --> 00:56:51.412
And at least at Johnson Space Center, but in other places they do more research and science and stuff like that.
669
00:56:52.455 --> 00:56:56.776
Earlier you talked about changing mentality and you talked about culture.
670
00:56:57.317 --> 00:56:59.857
And I know this is also a struggle for a lot of organizations.
671
00:57:00.458 --> 00:57:03.979
So what do you do to change someone's mentality or way of thinking?
672
00:57:04.039 --> 00:57:05.959
And I suppose this comes in a lot of different ways.
673
00:57:05.999 --> 00:57:11.241
It could be for leaders who have a very hard time adapting to new ways of working.
674
00:57:11.781 --> 00:57:15.483
So for example, I think you mentioned 21 years ago, it used to be very competitive.
675
00:57:15.503 --> 00:57:16.263
Now it's collaborative.
676
00:57:16.883 --> 00:57:21.126
I'm sure there are some leaders who just had a very hard time changing that way of thinking.
677
00:57:21.686 --> 00:57:25.169
Or maybe it's an employee who's having a hard time changing their way of thinking.
678
00:57:26.009 --> 00:57:26.830
What do you do?
679
00:57:26.970 --> 00:57:31.993
How do you get people to see things differently and sort of make that mental switch?
680
00:57:32.574 --> 00:57:32.734
Yeah.
681
00:57:33.134 --> 00:57:37.417
Yeah, I think that's one of the most difficult cultural elements that people struggle with.
682
00:57:38.017 --> 00:57:44.942
And one of the things that you people typically, if you are in innovation field, when people tell you, hey, it's not broken, why should I fix it?
683
00:57:45.502 --> 00:57:47.883
So, it's very, very difficult to deal with kind of things.
684
00:57:47.923 --> 00:57:51.725
So, in my opinion, I see it two approaches you can do for that.
685
00:57:52.325 --> 00:58:09.112
The first one is try to incrementally, try to push little changes to what they're trying to do and show the people that you're dealing with that by doing this little incremental change compared to what was used to happen, look at how much value and how much benefit and how much advances you were able to do.
686
00:58:10.372 --> 00:58:14.635
Another one is actually to do it more drastically, where you actually have bigger measures and bigger changes.
687
00:58:15.136 --> 00:58:22.161
And then when things, they see the value at the end result of it, people start embracing more and more the change.
688
00:58:22.461 --> 00:58:24.883
But it has to do with so many different elements.
689
00:58:24.923 --> 00:58:30.447
Younger generations, obviously, is more susceptible to being more creative and doing things and changing things.
690
00:58:30.827 --> 00:58:33.369
If somebody's been doing the same job for 20, 30 years or 40 years,
691
00:58:34.590 --> 00:58:38.815
it becomes much more challenging to be able to change the mentality or the way they do things.
692
00:58:39.235 --> 00:58:47.244
But in these cases, you have to do it incrementally at very small steps and eventually show the value from being able to embrace new ways of doing business.
693
00:58:47.744 --> 00:58:50.347
Well, you've been at NASA for 21 years, you said.
694
00:58:50.387 --> 00:58:55.633
How do you keep yourself excited about the job and keep yourself engaged in the work that you're doing?
695
00:58:57.277 --> 00:59:11.148
Well, the thing is every few years you need to look for a new challenge, obviously, because every time, for example, you get an assignment, you're very excited, you have so much energy, you're actually questioning things.
696
00:59:11.529 --> 00:59:19.035
And actually, these questions might bring so much value because as an outsider, you're coming in with different perspectives.
697
00:59:19.055 --> 00:59:24.199
So people there have been immersed into that environment that are difficult sometimes for them to see what's happening.
698
00:59:24.599 --> 00:59:39.626
So when you come in with this energy and everything is exciting and you learn, but then I think people need to switch jobs maybe after every three or four years to keep the momentum going, to keep you excited, to keep you challenged, right?
699
00:59:39.806 --> 00:59:41.447
And being able to keep things interesting.
700
00:59:41.487 --> 00:59:46.669
Otherwise, eventually you reach a point where it becomes stagnant and there's not much progress being made.
701
00:59:47.389 --> 00:59:53.572
So I think, in my opinion, it needs to change every three to four years to be able to keep the momentum going.
702
00:59:54.648 --> 00:59:57.211
Well, I know we are just about out of time.
703
00:59:58.272 --> 01:00:06.963
Is there anything else that you want listeners to know or any last parting words of wisdom that you have for people who are tuning in?
704
01:00:08.202 --> 01:00:12.445
No, I think eventually we have a very exciting future.
705
01:00:12.865 --> 01:00:19.350
It's going to be incredible the amount of advances we've had in technology, how much benefits it's having to society.
706
01:00:20.311 --> 01:00:24.674
And I think overall, all these technologies will be for the better.
707
01:00:24.714 --> 01:00:26.315
There's going to be some challenges, some risks.
708
01:00:26.855 --> 01:00:30.518
But I think all these elements will be able to have good benefits.
709
01:00:30.838 --> 01:00:39.121
make people maybe live longer, have better economic lives, better incomes, more comfortable societies.
710
01:00:39.622 --> 01:00:42.863
So I think overall it will be a benefit.
711
01:00:42.943 --> 01:00:46.544
And it's incredible to see how much advances we've done in the last 100 years.
712
01:00:47.105 --> 01:00:54.307
When the main transportation was horses, now we're going to the moon and we're talking about driverless cars or even driverless flying cars.
713
01:00:55.368 --> 01:00:59.129
So imagine what the future will hold in 20 or 25 years from now.
714
01:00:59.149 --> 01:01:00.470
I think it's going to be something very interesting.
715
01:01:01.338 --> 01:01:08.813
Well, where can people go to learn more about you or some of the work that you're doing or some of the projects that NASA has going on?
716
01:01:08.853 --> 01:01:11.879
I mean, anything that you want to mention for people to check out, please feel free to do so.
717
01:01:13.070 --> 01:01:23.939
Yeah, so NASA has an amazing website, outlines all the missions that we're doing in terms of going missions to Mars or new satellites missions or new science, new technologies.
718
01:01:24.800 --> 01:01:34.288
We also have a spin-off book that we produce every single year that shows you the technologies that were developed for space actually could be applicable to create economies and jobs on Earth.
719
01:01:34.828 --> 01:01:37.471
And that tells you what the value from space.
720
01:01:37.491 --> 01:01:41.375
So sometimes people ask, why are you spending so much money in space?
721
01:01:41.395 --> 01:01:43.397
You know, we're actually we need it for the economy.
722
01:01:43.817 --> 01:01:54.328
But most of the research has indicated that for every dollar you spend on space, the return is from three to six dollars in terms of creating value, creating jobs and creating new technologies that creates new businesses.
723
01:01:54.348 --> 01:01:54.428
And.
724
01:01:55.126 --> 01:01:58.968
So you have to look into all these kind of elements as well.
725
01:02:00.309 --> 01:02:05.072
Well, Omar, thank you so much for taking time out of your day to join me.
726
01:02:05.452 --> 01:02:08.254
I found the conversation fascinating and I hope people enjoyed it as well.
727
01:02:08.314 --> 01:02:09.455
So thank you very much.
728
01:02:10.295 --> 01:02:11.115
Thank you very much, Jacob.
729
01:02:11.615 --> 01:02:12.876
And thanks, everyone, for tuning in.
730
01:02:12.916 --> 01:02:15.417
Again, my guest has been Omar Hatamle.
731
01:02:15.457 --> 01:02:19.958
He's the executive director of the Space Studies Program at the International Space University.
732
01:02:20.398 --> 01:02:23.579
And he's also the chief innovation officer of engineering at NASA.
733
01:02:23.639 --> 01:02:24.519
He's on LinkedIn.
734
01:02:24.539 --> 01:02:25.340
You can find him there.
735
01:02:25.360 --> 01:02:28.041
And also make sure to check out the NASA website.
736
01:02:28.101 --> 01:02:29.441
I will see all of you next week.
737
01:02:33.200 --> 01:02:35.682
Thanks for tuning into the Future of Work podcast.
738
01:02:35.782 --> 01:02:36.783
I hope you enjoyed the show.
739
01:02:37.284 --> 01:02:42.989
Please do me a favor and rate and review the show on iTunes or whatever your preferred podcast platform is.
740
01:02:43.630 --> 01:02:55.782
And remember, if you want to take your education even further by getting access to courses based on some of the themes that I explore in this show, then check out futureofworkuniversity.com.
741
01:02:56.462 --> 01:03:04.245
If you're interested in being added to my newsletter, you can do that by visiting thefutureorganization.com forward slash newsletter.
742
01:03:04.785 --> 01:03:12.327
And you can also get in touch with me directly if you have any inquiries for podcast sponsorships, working with me, or having me keynote your next event.
743
01:03:12.827 --> 01:03:16.308
My email is jacob at thefutureorganization.com.
744
01:03:16.328 --> 01:03:18.209
I will see you next week.