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we're here today with Wharton professors
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Laura Huang and anoop menon to talk
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about their new paper which looks at
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entrepreneurial activity and the impact
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of watershed moments anoop and Laura
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thanks for being here with us today
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thanks for having us so first of all
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could you please give us a quick summary
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of the problem that you were looking at
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that you're studying in this paper
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absolutely ah so this is a question
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that's near and dear to both our hearts
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we're big aerospace buffs and so the
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question we were starting with is we
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look at the aerospace industry and even
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the past five years or so there's been a
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huge amount of buds right so there's
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Elon Musk there's Mars colonization
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these days you know space travel but on
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the other hand this aerospace is an
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industry which is a classic example of a
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hard to break into industry this is a
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really entrenched industry very high
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entry costs because of capital
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requirements skills that are required
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the top engineers that you read
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regulatory connections that you need to
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have so just like if you were to ask me
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a classic example of a high entry
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barrier industry this would be it many
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people had tried to enter it to do
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private space and had failed but all of
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a sudden in the past a decade or so big
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change so that's what kind of got us
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started like okay what happened here why
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what drove this changing can we
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understand something about industry
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evolution and entrepreneurial entry by
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studying this particular case so yeah we
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were kind of we were interested in this
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sort of aspect that there's these new
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private firms that are entering this
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industry right so um so I was really
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interested in looking at these private
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firms anup was really interested in
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their cognitive models and and their
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mental models and our third co-author
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Tiana's Azul who's at London Business
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School was also interested in this
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aspect of entrepreneurial entry and so
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we have this industry where in the past
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it's been so difficult to actually enter
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but yet we see that this progress has
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been made in the past sort of decades so
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we really wanted to investigate why that
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was and how did that happen great now
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total tell me a little bit about how did
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you do that
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then what did you find once you did that
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because it seemed to me that that's a
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pretty amorphous thing to try and study
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so I mean how did you go about looking
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at it absolutely so we basically we
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recognize that this has been this is an
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industry that has a lot of history
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obviously so we went back back to the
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1950s and even earlier than that we've
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been looking at conference proceedings
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so we have 21,000 articles conference
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proceedings documents dating back to
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that time period all the way to the
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present day and so we looked at sort of
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what was happening what are these the
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changes where do these changes come from
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and we also supplemented it with lots of
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interviews with regulators engineers
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people at all these different sort of
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all of the different touch points that
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that that would be in this industry in
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fact one of the fun things to really fun
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things about this project was I got to
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talk to an astronaut I got to talk to a
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colonel in the Pentagon I got to talk to
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NASA people's was spent at sometimes on
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this very dangerous right sometimes all
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in the same day sometimes you write and
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and there they've been incredibly
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willing to kind of share their own
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thoughts on this industry and so we've
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used that and and looked at the both the
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the conference proceedings and all these
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documents we had and kind of tailored it
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and and thought about all of these
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different angles that we could look at
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it now was there a particular watershed
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moment cuz like when you say a watershed
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moment is it always one specific
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discreet thing or can that be a little
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more like is that it can be a little
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broader than that like when you say that
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was there one one moment for this
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industry or was that one moment sort of
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a bunch of different things that
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happened or right in fact it might be
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helpful to just build up a little bit to
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that right so the literature if you are
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the academic literature on change art
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and like how do industries change where
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the opportunities come from they tend to
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look at either like big breaks in
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technology so technological
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discontinuities or big regulatory shocks
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that happen or some sort of like social
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movement collective action gonna these
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are like three big buckets that have
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been talked about and there are aspects
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of that here too but here what was
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interesting is the
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cognitive element as well and that's
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where this watershed moment comes in and
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what what we mean by that is if you
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think about any industry especially
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these kind of stable long-standing
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industries you have the major players in
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the space who all have beliefs about who
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does what how things work the rules of
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the game if you will almost tacit rules
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of the game and if anybody tries to
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deviate just by themselves they get
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kicked out or like they get pulled back
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into it right so these are relatively
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resilient mental structures or
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collective mental models that kind of
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define the rules of the game for the
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industry and what we're trying to say is
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that these watershed moments are big
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shocking events which caused actors in a
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space to like really sit back and wonder
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hey should things really be this way
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always and so to your question we had
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least from our chats it resonated very
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very much with what the articles were
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saying as well two sets of watershed
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moments one ok there's the initial big
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watershed moment which is the Sputnik
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moment and it is a term by itself right
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so Sputnik gets launched and all of a
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sudden over here we freak out like oh my
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god and that causes NASA to be found at
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DARPA to be founded big changes all of a
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sudden space goes from being a backwater
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to being top of you know this is the
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Cold War being played out in space so
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that gels the collective mental model
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around the belief that Oh space is for
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big governments big firms failures not
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an option a lot of money is required
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only the top talent can be here so
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that's the set of beliefs that gels
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around this goes through the Apollo
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program through the 80s as well the
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shuttle program but the first set of
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shocking watershed moments happen at the
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end of the 80s so you get the Challenger
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disaster which very shockingly very
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vividly demonstrates to the public that
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you know what maybe the government
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doesn't always get it right maybe you
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know things can go really badly wrong
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the same time you get the Cold War
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ending the berlin wall falling like
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literally
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and that causes many people to question
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like okay why are we spending so much on
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space it's amazing Russia we're not
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great there is no USSR in there's no
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Soviet so so and then committees get
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formed like how do we rethink space so
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that causes what we call like the
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initial shake-up of the model and then
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there's the service so that's so what
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your new biz kind of referring to is
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this dislodging of this mental model
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that was there right so we see that as
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he's mentioning that a lot of this entry
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that a lot of this disruption that we've
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seen in the past was happening through
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technological discontinuities the
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regulatory discontinuities through
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collective action but what we're finding
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in our in our data in our analysis of
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this context is that it's these these
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cognitive discontinuities that are from
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that are catalyzed from these watershed
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moments so watershed moments here are
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these very emotionally resident very
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publicly sort of recalled moments that
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we're seeing like Challenger right like
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the fall of the Berlin Wall and those
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dislodged and then we find three other
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ones that kind of Risa Lydda fide that
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that brought about this new mental model
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right so we had in 86 right challenger
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in 89 we had the Berlin Wall and then we
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have um then we have Columbia the
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Columbia disaster right again something
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that we all vividly remember right i can
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remember watching this and and and can
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recall where i was when when columbia
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happened and then we also have you know
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the awarding of the COTS contract and
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Ansari X PRIZE Ansari X PRIZE actually
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came first right so we have we're seeing
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that there's this public this new
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entrant this relatively unknown company
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that's getting awarded this contract
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that prior to that was going to people
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that were connected to the government
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that were connected to NASA right and so
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we're seeing this sort of shift that's
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Risa Lydda fying into something that's
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that's we believe now that it's not just
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the entity it's not just the government
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it's not just a National endeavour now
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there's this public these public firms
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sorry these private firms that are kind
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of
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coming in and so the story at least the
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way we said in the paper so we had that
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initial model which is called the old
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space of the big space model gets really
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shaken at the end of the 80s and then
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the government actually tries pretty
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hard to encourage private sector
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engagement they try different programs
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through the 90s but there isn't much
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success in fact there is a Texan banker
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billionaire call Andrew bill he's like
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Elon version 0 point 0 like you know
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before he alone who put in like hundreds
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of millions of his own dollars into
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Beale aerospace his private space
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venture but he shot sharp in two
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thousand or so and there's a very public
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letter that he put out where he blames
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NASA basically says hey you say you want
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private space to be involved but you're
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still making your sweet deals you give
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you sweet deals to Boeing and Lockheed
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zuv the world a big the the cost plus
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contractors the primes as they're called
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we small guys we just can't compete and
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so he shut shop right so this is
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transition period where we're trying to
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bring in private space but we don't know
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how to do it there is no consensus or a
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collective mental model on how this
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should be done but then once after
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Columbia happens and then the Ansari
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XPrize everybody to the T keeps talking
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about how the ansari x prize was such a
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big moment all of a sudden you go oh my
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god a private company with private money
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was able to build a plane which went to
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space came back turned around did that
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again people private people can actually
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do this that's like a big shock to
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everybody now they actually believe it
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as possible once they believe it is
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possible things start to get into motion
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right so then we have the precursor of
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the COTS contract like people put
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together commissions and oh we should
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really treat this like a like almost
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like a venture capital like NASA should
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become more like a venture capital firm
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rather than this cost plus regulator
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who's controlling everything it's a big
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mindset shift that happens and then you
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start converging towards the new model
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that we see today that's the story
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and now with this research so first of
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all what can the space industry take
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from this but then also what can other
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industries take from this yeah I think
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that's a it's a great question because
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we we are relatively contextualized
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right we're looking at this one industry
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and so something that we'd love to do is
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to look at other industries as well but
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I think in general right we tend to
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think that disruption and we tend to
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think that new industry emergence
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entrepreneur emergence happens from
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these big technological shocks write
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something big happens and that paves the
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way for other new entrants to come in or
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there's a big regulation that kind of
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changes things that changes the
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incentive structure that allows other
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people to come in and what what I think
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industries can take from this is that
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it's more complicated than that there's
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lots of things that are that are
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happening there are these emotionally
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resonant events that are happening all
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the time we don't know what form it's
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going to take necessarily but they are
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affecting the mental models and things
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are happening so even if there are
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technological shifts it's co-evolving
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alongside these other changes in our
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ways of thinking and our mental models
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are mental schemas and prototypes and
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all these sorts of things these
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collective ways of these collective
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beliefs and so keeping that in mind as
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industries are involved evolving and how
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as companies are trying to play within
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these these sort of rules is really
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important I think to adjust quickly
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build on that may be another way
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paraphrasing that would be you know in
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the strategy courses entrepreneurship
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courses we say oh where are
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opportunities let's analyze the industry
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landscape let's analyze the
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technological landscape and regulatory
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landscape to find where the
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opportunities are we're saying is that
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maybe we can also analyze the mental
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landscapes the cognitive landscapes of
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the agents what they believes are and
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how they're changing as another avenue
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to think about where opportunities might
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be and where change might come from well
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cuz it definitely seems like with the
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state with the case of space that I mean
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the technology was there for a long time
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but people didn't believe that it could
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happen privately and so it does seem to
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be kind of a I don't know cautionary
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tale almost to other industries that I
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mean you may have the technology to be
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able to do it but if people don't
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believe you can do it or don't believe
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it's your place to do it
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then they're not gonna buy into it
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anyway perfectly silly yeah the
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technologies absolutely it's an enabler
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right so even in in new space in the
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aerospace industry what we're seeing you
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know we tend to think of it as a very
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technologically heavy sort of industry
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and there are advancements right and
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those are enablers without the internet
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this wouldn't have happened without
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other sorts of things but those were not
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responsible for the disruption they were
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not responsible for this this entry in
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fact you know a noob has had people say
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to him you know I could go to home depot
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and I could pick up some parts and still
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make this this sort of habit and that's
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not to say this is not very
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technological right so um but but these
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are we're seeing lots of incremental
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advancements we're seeing lots of other
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things it's not one big technology shift
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that or one big technology disruption
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that was causing this and the other
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thing is exactly as you said it's the
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tech that catches the attention right
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everybody like oh the tech change it or
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maybe even some regulatory change but
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the cognitive things a bit subtle and
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and to understand that even if you have
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the best in class tech like so I've had
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rocket scientists who are like the best
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in the business like we know how to do
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this we've done we've had the capability
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for decades but nobody would believe me
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nobody would fund me so what can I do
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right great there you go now how it's
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interesting to me like because one of
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the things that this research seem to
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rely a lot on was actually person to
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person interviews I mean data as well
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but also really sit down and talking to
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people and these days we hear a lot from
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companies about I have to analyze my
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data I have to analyze my data so when
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you're looking companies that want to
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analyze mental models I mean is this
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what they need to do to they need to go
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out and talk to people I mean and how
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would they go about doing that like it
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seems like that's almost like the
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opposite of what we almost seem to be
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encouraging companies to do today like
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you need to look at data but this looks
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at people well there's such a big put
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with me we talk so much about big data
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now and I think data is absolutely it's
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critical we need data in order to make
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our decisions but we also need to
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remember and some of both of our other
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work looks at this very aspect of you
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know data you need to also have a lens
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with which to analyze
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this data with which to understand this
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data and that's where i think these sort
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of personal interactions bringing
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together what your mental model might be
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looking at different contacts that's
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really necessary in order to make sense
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of the data because even though you have
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all this data you still need to find a
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way to slice and dice the data pick out
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which things you're going to to focus on
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try and analyze it in a way that's it's
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cohesive and make sense so all of this
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sort of goes together and just add
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that's kind of funny that you ask that
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because one of the other research
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streams that i have is actually working
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on big data and machine learning and one
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of the things that I'm trying to do with
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that is to extract people's mental
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models from what they say and what they
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do using big data techniques so while
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talking to people is still what I like
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to do and that's like really the you
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know that's one very good way to get at
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this I don't think it rules out data
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either there's a lot that you can say
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about how people are thinking that you
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can do from doing machine learning on
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that as well so kind of speaks to the
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idea that people need to sort of do both
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or use one as a lens to look at the
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other and corroborate even like it
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complements each other's in fact it's
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funny because one of the reasons why we
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started working on this paper together
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is because we were both interested in in
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these this kind of cognition that's
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happening but also these emotional sort
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of resident events and anoop looks at it
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from one angle where he's looking at the
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big data on how you can actually I'm
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looking at it from intuition and gut
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feel and so a lot of our you should see
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some of our conversations where we're
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going back and forth Pinchbeck and then
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we kind of meet in the middle and think
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about the ways that both of those things
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are important and impact what it is
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we're looking at so it's been kind of a
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fun journey just in that in the
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different angles that we've both come at
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understanding cognition emotions and all
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these different things that that were
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capturing here now what would you say
00:17:25
sets this research in particular apart
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from other research that's been
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conducted on similar topics or on this
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topic yeah you won't want me to take
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this oh yes so I think that um what we
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mentioned a little bit before is that
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you know there are different ways of
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understanding and
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urgence and entrepreneurial entry and
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we've seen lots of these different ways
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that that definitely resonate in in a
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lot of different context and this
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context as well right but what we're
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finding here is that there's another
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route that perhaps could co-evolve with
00:17:55
these things so it could co-evolve it
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could potentially supplant it could be
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so you do have these these different
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ways that emergence is happening we also
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find that through these emotionally
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resonant events through these watershed
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moments that there are drivers there are
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catalysts that are changing the way that
00:18:12
proceeds and so I think it's important
00:18:14
to get this holistic you know how are we
00:18:17
actually understanding this in all of
00:18:19
its complications in all the different
00:18:21
forms that it could that it could hash
00:18:23
out and the ways that it could come
00:18:24
about and so I think that's something
00:18:26
that we were a little bit surprised
00:18:28
about that it could both there are
00:18:30
instances where it co-evolved zor
00:18:31
instances where this might be driving
00:18:33
the effect and that it's important to
00:18:35
understand all these different factors
00:18:37
no can you only with a watershed moment
00:18:40
I mean can you actually identify a
00:18:41
watershed moment while it's happening or
00:18:43
is it only possible to do that looking
00:18:45
back it's a very good question yeah
00:18:48
right now it's all historical right so
00:18:51
it's what people are saying and what we
00:18:53
can see in the text can we do it live
00:18:57
something we need to think about I'm
00:19:00
sure psychologists can like Laura can
00:19:03
quickly develop metrics to see like the
00:19:06
emotional resonance that certain events
00:19:08
are having what long-term impact that it
00:19:11
could have on the industry good question
00:19:14
yeah I think I mean in order to
00:19:16
understand the mental models right so a
00:19:18
lot of this is because there's this
00:19:20
solidifying sort of process we could
00:19:22
perhaps identify this is an important
00:19:24
emotionally resonant event but to
00:19:26
actually understand the effect of that
00:19:28
right there is some more sort of things
00:19:30
that that need to go into this but also
00:19:33
you know something that anoop and I have
00:19:34
talked about is that it's really
00:19:35
important to understand how this
00:19:37
continues to evolve right so anup just
00:19:39
this morning was talking to me about you
00:19:41
know there's also these negative these
00:19:43
negative events that we're seeing right
00:19:45
something goes wrong and some things
00:19:47
blowing up we see this all over the news
00:19:49
all right and so it's important to
00:19:51
continue to to track this
00:19:53
you want to say more about that because
00:19:54
you actually this was something we
00:19:56
talked about just this morning yeah I
00:19:57
mean recently SpaceX is the rocket
00:20:01
exploded on the launchpad and I can't
00:20:04
get big like it literally blows up right
00:20:06
and this people have said this is a very
00:20:09
touchy industry exactly because how
00:20:12
visible and explosive everything is and
00:20:15
people are worried that one big failure
00:20:17
is enough to go back to where we were so
00:20:20
to your question what determines the
00:20:23
impact that any one event is going to
00:20:25
have I think that's a great question for
00:20:27
future research and that brings us to my
00:20:29
last question is there anything else you
00:20:30
guys plan to look at in the future where
00:20:32
how to continue this research yeah I
00:20:34
mean there's a number of different
00:20:36
things right so we want one thing is we
00:20:38
want to understand a little bit more of
00:20:39
the micro drivers of this right so right
00:20:42
now we're looking at what's happening
00:20:44
we're looking at these changes in mental
00:20:45
models but one thing that we've talked a
00:20:46
lot about and with our co-author teona
00:20:48
as well it's kind of understanding a
00:20:50
little bit more of the the granular
00:20:52
mechanisms behind this and what's
00:20:55
actually happening on this more
00:20:57
individual level and the other thing
00:20:59
that we mentioned a lot is just you know
00:21:01
the context right this is an in-depth
00:21:03
look into one particular industry one
00:21:08
particular context we believe there's
00:21:11
other context where these emotionally
00:21:12
resonant these watershed moments are
00:21:14
going to have this big effect on mental
00:21:17
models but they may operate in different
00:21:19
ways in some industries it could be
00:21:21
technology that's driving in and these
00:21:22
watershed moments are taking more of an
00:21:25
ancillary role or it could be the
00:21:27
opposite there's lots of different
00:21:28
iterations of how of how this could come
00:21:31
about so I think those are all different
00:21:33
things that we that both we as well as
00:21:36
other scholars will continue to look at
00:21:38
so that we can really understand this
00:21:41
phenomenon of entry and disruption and
00:21:43
yeah I knew pollera thanks so much for
00:21:45
being with us thank you thanks for
00:21:47
having us
00:22:05
you
