From problem solvers to solution seekers: dismantling knowledge boundaries at NASA

Speaker A Now we're going to be, well, taking a deeper dive into two organizations with next two speakers.

Speaker B Hilalicious.

Speaker A Asaf is going to be talking about NASA and then after that we're going to have Art Hoffman from Dropbox. So turn it over to.

Speaker B Hi, I'm Milan. Good morning and I'm thrilled to be giving a talk after this broad overview of both past, present and future of organizing. And I hope that some of the things that I saw and will share.

Speaker A With you please speak into the mic.

Speaker B You meet the mic. You can't hear me. I apologize. I will show I didn't miss much. I'm Vila and I'm very honored and thankful and grateful to be here. And I hope that in my study that I will share with you today, you will see some of the emergence that you just talked about. And we will see how the coevolution of things that are in the microfarations of culture, specifically professional identity, and the design and redesign of the innovation process. I will focus specifically around that. But before I go deep, and more specifically to the context of NASA, since this is an orbit design community, I wanted to share with you my overall research motivation of studying new forms of innovation. So in case some of you have thoughts about it, questions, cool opportunities, please know that this is what I'm curious about. And then we'll dive deeply. So my overarching research motivation around these new forms of organization comes from an historical perspective about how we organize innovation. If we just take a minisecond and go back in time a little bit and think of how innovation started, right? We have the lone inventor, leonardo DA Vinci first airplane sketch and then the Industrial Revolution hit. I'm simplifying it, of course, but basically the birth of the lab. This is Thomas Edison first lab that is still today a genie. And for the next few centuries, public and private organizations are the focus and the locus of innovation. And innovation is conducted mostly within and across collaboration of public and private organizations. They've been leading that and that assumption both in the literature and across practitioners. But recently, ever since what some people call the digital revolution, the decentralization, the increased modularization, many technological changes that I will not go into have given rise to new forms of organizations. And some scholars and practitioners are claiming that today we need to go beyond, we need to transcend the organizational, the professional boundaries, we need to move into a more open, distributed, decentralized way of organizing. One of the phenomena that gave rise to this was the open source software that for the first time, thousands of thousands of individuals distributed across the globe were able to produce knowledge and innovate as well as, and sometimes even better than the incumbent organizations in their industry. And ever since, this model has been spilling over in different ways and in different shapes to different industries and organizations. Are experimenting with this in multiple ways. Right now, as we speak, many natural experimentation are taking place. The interesting thing about it is that we know more now about what's happening in the online communities. What I would like to talk to you today is more what happens in the intersection of organizations and those online open, peer to peer production communities, what happens in the intersection of these seemingly contradicting worlds or logics, as Will talked about. And I hope that by the end of the presentation, you will see the complexity, the opportunities that lies in this intersection, the cost, the change that it takes, and we can talk more about it. So now we can go deeper, now that, you know, kind of my overarching interest and the research question I would like to focus on today is how using these open architectures impacts R and D professionals and their work. So we will look at what people do, their knowledge work, their R and D work, and who they are, because this is what emerged. Just so you know. The other things that I'm also interested right now, if you have any relevant knowledge around it, is how using these open architectures actually changes the recombinant innovation process. Since if we think about a decoupling that takes place between problem formulation and problem solving, that's something that we always knew. That the way a specific R D problem or any type of problem is formulated is key for solving it, right? And innovating. Einstein wrote about it. Newton, the way you think about a problem, if I had an hour to save the world, 55 minutes, I would formulate the problem in five minutes. Solve it. That's what Einstein said. But usually it's intertwined, it's decoupled in the field. It's hard for researchers to study those because the way scientists or engineers think about problems or managers is intertwined with how they solve it. But in these new settings, these are actually decoupled. And essentially it's focused now completely on formulating the problem and then expecting someone else or many others to solve it. And I see that that's actually where a lot of the performance of these models work. It works much better when there is some work on the problem formulation side. So that's another aspect. And, of course, boundary conditions of these new models. So when does it work? When does it? It is across the different stages of the process of innovation. So we'll start with the first question, and I'll tell you why this is interesting, kind of for me, theoretically, when I first went into this, since most of what we know in the literature about R and D professionals and what they do is that they resist opening their boundaries. We know that they cross boundaries, they bring knowledge across organizations, across disciplines. But then they work on a project with very well defined boundaries. Who's in, who's out, what is in, what is out? And we know that these are important and contested area, a lot of fights. The work of Paul Carla Bospetsky and others on these boundaries of work and all the work from sociology and professionalism literature shows how experts particularly build almost fences and walls against the laymen and not willing to kind of this is what I do. So if you think I'm the Abbott's work, the heart of the theory is around the task and the problem and gaining legitimacy and jurisdiction on these problems. So opening these problems for anyone to solve, as we will see in this open innovation model, goes against the assumptions of these theories. But on the other hand, we know that the web has been challenging a lot of the assumptions around permeability on boundaries and many theories have been calling for more research. And I hope that you will see this study as the first step in understanding what is the permeability of boundaries and then how does it affect people and their work inside organization. So this is an in depth field study. This is the first paper coming out of my dissertation. There was a long, almost three years in depth longitudinal field study at NASA. These are all the cool pictures. I don't know if you can see me there standing near a lunar rover, but these are the cool innovations that took place while I was there and just taking field notes. But this is what happened in three years. And just to give you a sense of the type of data, I collected a wealth of qualitative and quantitative. So they'll focus on the qualitative data observation. They were very open and nice to let me join the lab, shadow people, observe people working meetings. This was crucial for me to see the change that I will soon describe for you and to be in all the work meetings, specifically the Space Life Science Division and the 14 labs audits interviews. I interviewed more than 100 people in different periods of time, especially multiple times. It was important to keep track of the change, and the internal document surveys were crucial. So it was important for me to see what they talk about in meetings, what they do, what they talk to me. But I could not analyze the change in their work if I didn't have those project documents across time. So I could actually see if something has changed after this experimentation with open innovation in their project work documents and their internal work. So we will focus today on the Space Life Science engineers and scientists, a very kind of typical life science organization, but doing that in space and look at their perspective and how did they experience this open innovation so briefly to describe what is this open innovation in this case that took place? So space life science division did a brave thing. I realized now, compared to other organizations that they said, we hear all this talk about open innovation, we don't know exactly what it is. How about we just try posting, opening our strategic problems? We had a strategy plan for this year. How about we keep on working on it in the same time in the way we do? We have collaboration contractors and in the same time we'll try to put it online in all these open innovation platforms and see what happens basically for a year. So it's kind of this parallel simultaneous effort to try and solve this problem. This is space life science division. That's their structure guideline. And I'm trying to show you the type of scientific and technological problems. So these are strategic and that's what I mean to rephrase because many organizations just open kind of a side problem to the crowd, but not really their strategy problems. So these were their strategic problems ranging from different disciplines. You can see scientific and technological and they posted it on three of the most leading global innovation platforms. If you know InnoCentive, a lot of scientists and engineers and different professions on this platform. Around 400,000 members yet to come, more technological focus, also between 200 and 300,000 members and yet tope coder in the end, which is mostly software and programmers and type of kind of computer science professionals. So they did that. It took them not a lot of time and it felt like a different process. And since this is an.org design conference, I just wanted to give you a glimpse of the design of the process and how different it was and how it was experienced. So they kept on repeating oh, this is a whole different way. I can never do Texas accent. I don't know even what my accent is. But imagine that in a Texan accent of doing business. And I was trying to keep the dimensions of how is that different, what is exactly different, where is the tension, et cetera. So speaking about boundaries, talking about the standard R and D process, we know how it works here. It was undefined. They didn't know who's going to come and solve it. Sometimes they're asking is it open to anyone? It is completely anonymous. People can choose all these platforms. You don't know where this person comes from geographically, what are their level of education? Nothing so unlike the expert driven model that we know in R and D. That's the dominant model here. Anyone, the relationship, the nature of them is very different. On the open online, it's this minimal consent, 2 seconds. You don't have the negotiation, the depth, the knowledge of each other, which you have in R and D projects. The hierarchy of the process is different. The level of control is you don't know how they're developing their answers, what they're doing. You can check up on their back and you can test it as they're doing their work. And of course, the nature of the process is very different temporarily and spatially. R and D processes are usually long here, this was chunked into three to six months problems. And the spatial geographic distribution, of course, is very different as well. So to give you a sense, what happened after three months, only of these 14 strategic r and d problems. So over 3000 people from 30 countries participated in trying to solve these 14 problems. The interesting thing that came back is not just the amount of people. And granted, they said it's NASA, so I'm sure it attracts more people than usual, but usually that's the case if you have a small amount of people inside your organization versus a huge crowd that is interested in solving, but they just think they were the solutions. So four out of the 14 challenging problems that they were still working on, as I told you, this was a year long experience, and only three months have passed. And they were bringing experts from outside doing workshops, but four were solved, basically. Specifically, I'll tell you about one that is known, and you can google about it. It's known as the home run of this experiment. It's around predicting solar flares. I don't know if you know, this is a picture from may this year. So solar flares are a big risk. And we're basically now in predicting solar flares where we used to be a century ago, in predicting kind of earth storms. So people sit in their control rooms, they see gamma, beta. In 24 hours, they just start shouting, okay, shut down, shut down, let's cancel the mission. Cancel this. It's regularly risky radiation burst on humans, on equipment. And of course, it can go all the way to satellites. And then we're all done basically here. If we don't have satellites, we can't go into it. But it's obvious specifications both society and the military. So it's a big problem. Okay, it's a problem estimated around $800 billion a year. People work around it in the whole heliophysics community beyond NASA. This guy, if you can see him there, that gave me the permission to show the picture that he shared. Bruce craig, a semi retired radio engineer from rural new hampshire, solved that in less than three months. He's a radio engineer. He's not ideal physics. He brought a different model from radio engineer field in japan and triangulated it and made a discovery. So before they had a 50%, which is like tossing a coin type of prediction model in 24 hours, he brought a model that worked in 75%. The NASA folks tested it 80% to 85% variance. So this was a huge storm. This is the picture that he presented when he got an award in the white house of office of science, technology policy. I won't get into the details, but this has made things go on fire, of course, and literally, and people were excited, and the managers got attention, and all of a sudden, obama writes something about it in his memo. But what happens to the people inside okay, so managers get attention, resources. This we can talk about on a different day. I want to see what happens with the people inside. And they were first just surprised completely. This is the head of this unit and he said this has spun up so fast here and it's caught everyone of Bars turnaround time for solution like this could take years. And then an interesting process started, kind of unveiling. So the manager said, okay, this is great, this is working, it's fast, it's cheap. We get more research, more attention from the headquarters. Let's do a year as fast. Let's do our next strategy meeting and decide what to open. And on that day, on that workshop, I can describe to you the tensions and fears and crazy things that people started telling to each other in this meeting. And it started around budgets and stuff like that. And then it started getting really emotional and deep. And people were saying, what value am I? These things? Every time I have a problem, wanting me to put it out there, it's like slap on the face. We were trained this goes against what we were trained and modeled to do. The history is the scientific method goes against it. People talk in our training, I'm supposed to solve problems. I take this. We work together. So every time I have a problem, just post it out there. It's like cheating. What am I here for? I came to innovate. I want to go. Some people say I want to be open, I want to be out there. I don't want to be employed by anyone. I want to sit at home and solve problems all day. So the more people started talking about why they came, I started going into this. I won't go too deep into the artifact, but I could this narrative analysis and of course it's known and also the data shows here that there is a very clear hero figure of the problem solver of the innovator. The thing is, with this open innovation model, there was no clear hero figure and people could interpret it in different ways. And that's what took place. That's the emergence part that started taking place. Some people said, okay, I'm protecting myself from it. This is why I'm here. This goes against and we'll see how it obviously made them resist this model or adopt it, but only on the surface. On the other hand, some people said, wait a minute, this is about the big agenda. This really works. This can help us solve. So how about instead of thinking ourselves as problem solvers, let's change the way we think about ourselves. And this all happened in arguments, in the labs, in meetings. And one pivotal moment took place when a senior scientist said who cares? Enough with this argument. The solution may come from you, from your lab, from a collaborator, from an open innovation platform. You should not care. You are the solution seeker. So let's think of ourselves differently. Let's build ourselves differently. And in the paper I go deep into this transition from problem solvers to solution seekers. And I show that people that protected their identity also protected their knowledge and boundary work. And they did not bring in this knowledge that was found unfortunately, outside all the solutions. They did not put them in the R and D process and the knowledge that they have inside that did not openly share. And on the other hand, those people that started this emergent profession or refocusing work on being a solution seeker really dismantled their knowledge boundaries and made a deep change in their R and D design and structure. And to give you a quick quote, the people that did dismantling talk about it as a shift from thinking about the lab of my world, when the world is my lab. Some of them even left their level. Just quickly show you what do I mean by dismantling? So they started thinking of what it is in their knowledge production that they can open from within and outside. So I look at knowledge closed from internal knowledge out and external in. So an example about the data, they started thinking, okay, we only set the problem. Maybe we should open it from data that we have. And this is sensitive data. Some of it are regarding astronauts health. They found ways to quantify it and open and share it in the process. Quickly, I'll just show you. If we talk about artifacts, some people left their R D units and asked to open a new unit that you can Google it now it's called Opennessa. They don't have any research inside NASA anymore. So those are the people that talk about the world is now my lab. All they do is outside of NASA. So I looked at the external knowledge and as this mentoring work took place, it was integrated and how the internal knowledge goes out and the resulting locus and focus of innovation that went outside of the boundaries. And I basically mapped those different behaviors and I showed the connection between how the professional identity work took place, the knowledge boundaries, and in the end, where the locus of innovation resides. So that's the gist of the process that took place. I apologize. It was very fast to try to summarize three years of these people's life, but some theoretical interesting issues that come out of it. I think that we see that organizational members do no longer function only as knowledge of kambernators or kind of gatekeepers. They also change the boundaries of the organization. They prefer it, they dismantle them. It has decomplication on this professional versus layman and how do they think of themselves? Of course, having the identity as something that explains a challenge was even a surprise for me, as I was kind of in the field. Understanding that actually how people think about themselves is crucial for what they do and the structure of their work and processes. So this relationship I think, is just very interesting and it's to be explored even further. And I hope this gives you a sense of this complexity of what is the next way, what are those new forms of organizing and how do they imply there are many implications that I will not go into it. But what does it mean about that tradition, the incentive system? Many organizations are now trying to change it and make this so that also the people that if they bring something from outside in, the people inside get some kudos and credit for it. There are now co authored scientists that co author things with Crowds with Crowds. And even about the training. It goes deep to the training of the scientists and engineers. There's now one course that is starting to pick up place in Harvard Engineering that is basically teaching engineers not to code everything by themselves. They have to have part of it open source with the system. So it goes deep to are we training people just to work by themselves and be the problem solvers or constantly work in this more open way and can go deep into it? And of course we have some new cases and some other people that are studying here in the room that look beyond R and D professionals and even about ourselves. I know some colleagues are doing some stuff about our role as professors and with open education. So this is for the future, but basically this is it. So the transition. This is Gene Crant. I don't know if everyone remembers the Follow 13 movie. So this transition from Houston we have a problem, to NASA posting the problems and the world is saying, Houston, we have a solution.

Speaker A Like a lot of companies the last handful of years, we focused a lot on change management. We talk about design, but it's on paper until you actually put it into practice. Part of that is dealing with resistance to change. And we'll talk about sometimes the folks that have achieved the most in the current system are the most resistant to finding a new system. I love a couple of comments you said about or some quotes about where does this lead me, what value do I have? It's like I'm cheating. Did you see any commonalities between those that maybe had a harder time with the change versus those that were open and excited about the opportunity for sort of advanced innovation?

Speaker B This is a great question. So I was looking for these changes because in our world we think that maybe things can be explained. What people do by their gender, status, power, incentive, many things. And none of them in this case and I try to test each of them and none of them in this case really showed a difference, I think, in this specific case. But what I hear many managers take from this is the way it is framed, the way it is even narrated. So in this specific case, the open innovation thing was not it was not thoughtful in the sense that the manager didn't come and say this is X or this is Y. They had this experimental mindset so it left room for interpretation bottom up. And also, to be honest, what happened with the manager. They were so scared by all these fears and tensions and fragmentation, so they backed off for a while. So that's why it left actually room for this to emerge, for those that want to pick it up and for those because they were just this is too much for me. It's a political price I'm paying for this change and I'm not sure it's worth it. So they went to headquarters and now headquarters has a whole new thing. But you have it. And that's what I see in many organizations. They say, okay, let's create it, let's do it somewhere else. It's too hard for the people from inside. But basically I know that many managers are trying to think of how to make it so that it comes much more bottom up and that there is room in the way you narrate and frame the change plan, whatever it is. And you don't say kind of where does it leave the professionals? Are they still the hero? Can they re narrate themselves to be the heroes of whatever their work is? I think that's something I hope people can do because in the end of the day, we need a sense of meaning in our work, regardless of which profession it is.

Speaker A Thank you. I was wondering, from an organization design point of view, could you talk about how the people inside NASA who were engaging with the outside sort of structured themselves and set themselves up so they could accommodate all of this stuff and prioritize what actually looked like was going to be valuable?

Speaker B Anything specific you are interested about? Just almost.

Speaker A If you've got a part of the organization that's doing open engagement, you're getting 3000 people contributing ideas. How does it set itself up to actually work through those ideas, decide which ones to progress, et cetera.

Speaker B So as I mentioned in the beginning, there are new capabilities such as how do I formulate the problems now? How do I make it efficient? Right? I don't want to be flooded by the crowd in that sense. So bear in mind 3000 for 14 problems. So most people had and these are short solutions. So one of the things that they are now building, these capabilities and new skill sets. So this being a solution seeker is different. It adds a layer of knowing how to formulate the problem, how to search. So they build this model of degrees of openness. They think these open systems are constantly changing. So it doesn't have to necessarily be an open innovation platform. One of the beautiful stories that took place in the end of this study is that someone on the weekend actually Googled and at the end through YouTube found a medical device, an engineer that was not even in part of this experiment in the first phase. But she was in all these workshops and she know instead of developing this medical device that we need for a strategic problem that took place all of a sudden she said how about I just search for it a little bit before? Didn't even posted it. And she found this physician who developed it for going remotely to his patients and actually it's now in the International Space Station. It was tested. So it kind of changed their mindset about starting outside first before they go in and develop something. But it's a new mindset in that sense.

Speaker A Very much for this interesting presentation.

Speaker B Who owns the intellectual property rights of the solution? Who owns the intellectual property rights of the cartilage? Bowling is here. She can tell you much more about the It impact of this whole new way of organizing in these specific platforms. It's relatively simple in the sense that they found a way to basically once you decide to accept the reward, you give it to the company. I can tell you that the legal folks in any of the organizations I'm studying are having a really hard time with all these open systems. In my past I was a lawyer, so I have little empathy, but not really because they really ruined innovation in the end of the day. But there are few now legal scholars and practitioners that really understand that there are shortcuts today and so far there hasn't been any mega lawsuits or anything to deter people. So once there is one kind of more advanced person in the legal department, usually it goes through, but in the beginning that's what the managers were working. How do we get legal on board? How do we get procurement? They were not thinking about standards and the engineers in that sense because they were so worried. But it's new in that sense, a.

Speaker A Clarification if you could give it to us. I'm a little unsure of the difference between sharing your knowledge with other people and the idea of as an organization sort of sharing the problem. And this came to my mind when you talked about the person who solved the whole problem of solar flares. That was because the organization shared the problem. I didn't hear that there was shared knowledge that enabled this person to solve the problem. So again, how do these two ideas, these two concepts work together and how is it reflected in this one person who solved the whole problem, apparently by themselves without knowledge from other members of NASA?

Speaker B When you said not knowledge sharing, what just exactly do you mean? What type of knowledge sharing? The fact that he didn't see the previous R and D work on this problem, for instance.

Speaker A That would. Be an example.

Speaker B Yes.

Speaker A There was nothing that you said that indicated that he had seen knowledge from other people.

Speaker B Yes.

Speaker A So he was the recipient in the organization with the beneficiary of problem sharing, but not knowledge sharing.

Speaker B And in the internal knowledge opening, I would say I look at these different I think of it as kind of across the R and D process. So I think you start usually with some data and from there you either research it in a lab or depending on what type of work they do. And I would say sharing the problem, sometimes it's very hard, but it's definitely not the whole process. So it's almost the end sometimes of the process. When you have a defined problem and even when you share it, there is a level of how much do you share of the prior history and prior attempts and failures that were there. And I see a variation across that. So some groups really tried to say don't try that, this has failed, we don't want that. And they try to kind of summarize sometimes five, nine years of R and D work into a two page problem formulation. Those that went deeper, that's the full dismantling try to open and share the knowledge from the moment it's created from the data and the analysis, and keep on going through wiki kind of platforms that every person, even when they know or learn about a new medical device, they post it. So the intra organizational platforms are no longer only from intra organizational members. They work on Wikipedia platforms to make it open to anyone. So if that scientist again wants to solve another problem, he will not only see now the end of it, he can actually see the knowledge as it's progressed, but that's only in the extreme version of full dismantling. In those that do what I call perforation only kind of hybrid, they only share that part. They still make sure that they have control on what they share. It's really scary in that sense for them to share their ongoing day to day.

Speaker A Thank you. One more question.

Speaker C I'm Ken Shepard. Thank you very much. From an organization design, from an HR manager working together, it occurs to me that you need to do this model, perhaps fewer people, different talents at a higher level of complexity. So it's an.org design, it's a role definition problem, a recruiting socialization problem, and it is an organization design problem. So if I were one of the people who was used to working in the lab, I would feel very threatened because I would see the implications, fewer of me are needed of a different type than me, maybe a higher level of complexity. Do you have any comments on that?

Speaker B I sometimes have this funny sometimes when I finish to executives or even with friends, I say what would you do? And kind of people split in the audience. And I can see that some people are like even now, when we're talking about open education, many people say, oh, people will take my courses and then they will stop coming, and it makes me obsolete. So in the data, not speaking about what I think, but what people thought and did, that's the thing about living. You have room for interpretation. So some people disinterpret it. You need less people now. You can do less. And some people actually thought, I can do more with the same thing. And I have new so my role has changed. It doesn't mean they do not need me anymore. Actually. I can build new capabilities that are important and needed. So I think there is a lot in this role, crafting and reframing that people it's not a clear cut. So I wouldn't say some organizations really sometimes decide to lay off some people if they want to change their R and D. So I hear why? I mean, it's a scary thing. It is to say. But still, those people that decided to embrace it decided because they think it can empower them, it can enhance their capabilities and not only diminish and disrupt.

Speaker C So in the Age of the Smart Machine by Susanna, when it changed, fewer people, different times, that's what occurs to me. So I don't know, maybe we need to look at what happens a couple of years down.

Speaker B Yes, this is ongoing. That's why I say it's, like in the field right now.

Speaker A Thank you very much.