July 14, 2024 • 31 mins
In the latest episode of the Corporate Explorer series, brought to you by Wazoku, we discuss the importance of balancing personal instincts with data and evidence in business decisions. Guests, Product Marketing Manager for Electric Vehicles & Customer Experience with Cadillac, Sarah Spoto and Vincent Ducret from ChangeLogic share their experiences of implementing experimental frameworks in China for General Motors. They emphasize the critical steps of assumption analysis, prioritizing hypotheses, and iterative experimentation, while also addressing challenges in corporate environments, such as maintaining cultural buy-in and celebrating failures as learning opportunities. Sponsored by Wazoku, the episode offers deep dives into innovation management, strategic risk-taking, and the use of connected collective intelligence to drive business success.
00:00 Introduction: The Pitfalls of Instinct-Driven Decisions
00:40 The Role of Data in Corporate Exploration
01:07 Sponsor Message: Wazoku's Innovation Ecosystem
01:56 Incubation and De-risking New Business Ideas
02:19 Meet the Corporate Explorers: Sarah Spoto and Vincent Ducraix
02:50 Sarah Spoto's Journey in Corporate Innovation
04:40 Vincent Ducraix's Background and Experience
06:55 The Business Learning Life Cycle Framework
08:10 The Importance of De-risking in Corporate Ventures
13:04 Challenges and Strategies in Corporate Experimentation
14:33 The Role of Leadership and Team Buy-in
21:08 Case Study: Experimentation in China
30:28 Final Thoughts and Contact Information
Find Sarah here: https://sarahspoto.com
Find Vincent here: https://changelogic.com/team/vincent-ducret/
https://www.linkedin.com/in/vducret/
Key Takeaways
This conversation explores business experimentation using a framework outlined in the Corporate Explorer book. Here are the key takeaways:
Challenges of Corporate Innovation:
- Reliance on past experience can lead to failure in new ventures due to high uncertainties.
- Traditional methods like surveys might not capture the right data for untested ideas.
The Business Experiments Framework:
- Identify Key Assumptions: List all critical assumptions about your new venture (customer value proposition,problem addressed, etc.).
- Prioritize Assumptions: Focus on the riskiest assumptions that could derail the project.
- Design Experiments: Create creative experiments to test these assumptions with real customer data (not just surveys).
- Collect Learnings: Analyze experiment results to validate or disprove assumptions.
- Iterate: Use learnings to refine your approach and potentially conduct new experiments on remaining assumptions.
Benefits of Business Experiments:
- Reduces risk by validating assumptions before significant resource investment.
- Provides data-driven decision making for building the right product for the right customer.
Challenges of Implementing Business Experiments:
- Balancing Speed and De-risking: There's a tension between demonstrating progress and taking the time to properly de-risk the project.
- Cultural Shift: Organizations need to embrace experimentation and see failures as learning opportunities.
- Team Buy-in: Both leadership and working-level teams need to understand the value of experimentation.
Success Factors:
- Strong Leadership Support: Having advocates who understand and champion the approach is crucial.
- Cultural Investment: Educate teams on the process and celebrate failures as learning opportunities.
- Focus on Learning: Value the insights gained from experiments, even if they disprove assumptions.
Example Implementation:
- Sarah Spoto's experience in China highlights the importance of setting the right incentives and building a cross-functional team for experimentation.
- Assumptions analysis is a valuable starting point, even if full experimentation isn't implemented.
Overall, business experimentation offers a structured approach for de-risking new ventures and making data-driven decisions in the face of uncertainty.
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Aidan McCullen (00:00):
There are many examples of how even the most successful
(00:03):
entrepreneurs and business managerscan fail , they put personal
conviction and opinion ahead of data.
Andy grove intel's legendaryceo committed, The business to
video conferencing equipmentin the late nineteen nineties.
Jeff emmelt another storied ceo betGE's future on the internet of things.
(00:24):
The browser company mozilla reportedlyspent four hundred million dollars on
a new phone operating system these aredecisions made on instinct that failed.
So how does a corporate explorerreplace or at least supplement
instincts and opinions with data andevidence to demonstrate whether an
(00:47):
idea is worth pursuing , or if itrequires a pivot or even a shutdown?
How does a corporate exploreranswer questions that have a
major potential to jeopardize
the projects progress and ultimately it'sfuture success if not addressed up front.
Big questions to get through on today'sepisode of the corporate explorer.
(01:11):
Just a reminder that the corporateexplorer series is brought to you by
Wazoku Was oku helps large organizationscreate effective sustainable innovation
ecosystems that accelerate efficiencygains and new value growth and it
does this through intelligence.
Enterprise software that connectsand harnesses the power of employees,
suppliers, startups, universities,and the unique Wazoku crowd of over
(01:35):
700, 000 plus global problem solvers.
Wazoku calls this connectedcollective intelligence, and you can
find our friends at Wazoku at www.
wazoku.
com.
So today's episode describes howincubation tests on proven assumptions
of an idea for a new business by derisking each element before committing
(01:59):
scarce resource to the project.
Is a great pleasure to welcome thecoauthors of the corporate explorer feel
book, i'm a chapter entitled businessexperiments the risking execution spend
through experiments, sarah spoto andvincent Ducret welcome to the show
Sarah Spoto (02:18):
thank you.
Thanks so much for having me
Vincent Ducret (02:21):
Thank you.
Aidan McCullen (02:22):
it's great to have you guys sarah maybe.
You start by introducing yourself andhow you got involved in this chapter
and then we'll come to the van song andthen we'll get stuck into the chapter.
Sarah Spoto (02:34):
Thanks again for having me here.
I'm Sarah Spoto.
at the time when this chapter waswritten, I was working in China, in
With General Motors, I was the directorof strategy innovation as well as
brand strategy for the organization.
And it was really anincredible opportunity for me.
I had been working at the headquartersin Detroit for GM for a number of years.
(02:58):
And to go to a region to reallybuild a startup within this large
multinational corporation washonestly a dream come true for me.
I consider myself an entrepreneur.
But of course, being in corporatesometimes you don't always
get those opportunities to dosomething truly, entrepreneurial.
(03:19):
And in this case, I did.
And so I'm really proud to say that wehad leadership who very much supported
our efforts in taking an experimentationapproach to how we developed the
offerings for this new business modeland doing it in conjunction with more
(03:40):
traditional methods like market research.
Right?
And I think those complementeach other very well.
So my role there, I was actuallyemployee number 4 on the team.
So, while I have this fancy soundingtitle, I wear a lot of hats.
And it was really helping to driveinnovation an agile methodology and
bring this experimentation approachto the business while at the same time
(04:02):
also building our brand there as well.
Aidan McCullen (04:04):
Brilliant sarah and so great to have you and it's great to
have somebody who's done the work andhas all the scar tissue and all the
arrows in the back for doing that workas well which really makes it real.
And Vincent, maybe you introduceyourself as well and then will
describe the chapter but also theframeworks that exist in the chapter.
Vincent Ducret (04:24):
With great pleasure and thanks again for the invitations
and so nice to see you again, Sarah.
So in fact I have a computerengineer background, okay?
And by the way, I'm just calling you todayfrom the place where I graduated more
than 20 years ago EPFL in, in Lausanne.
So I started really my career as asoftware developer, so I was exposed very
(04:45):
early to all those extreme programming,agile way of thinking, of working.
And I work several yearsfor Sun Microsystems.
Probably some of you mightremember this company.
And then I moved to the other side ofthe mirror, I used to say, because I
spent 15 years in corporate environment.
So when I joined SARA on thisproject, I was used, I will
(05:07):
say, to the corporate world.
So I know what might be the challenge.
What might be, I will saythe problems they may face.
So I spent 15 years in corporateenvironments, having worked for different
departments and the last six, sevenyears, I was part of the transformation
organization, moving a very famous companyfrom business centric to Customer centric.
(05:28):
So really adopting a much more customercentric approach for this company.
And I have also the opportunity todayto teach business transformation and
innovation principles in differentuniversity in St Gallens or in Geneva.
And I joined ChangeLogic twoyears and a half ago as as a
(05:48):
consultant to help company togrow beyond their core business.
So really more or less, I willsay helping company like Sarah was
working for to explore, test andscale new venture and new business.
And this is how I was, I will say workingwith with Sarah on this very interesting
and passionate project for, GMPI in China.
Aidan McCullen (06:12):
Brilliant we have the perfect people in the room to get
it both sides of the story as welland i thought we start by that so
Vincent., you've taught other people,the frameworks, but also you've used
those frameworks in organizations,which is a totally different thing
than just teaching them the whole time.
So we're going to tee us up for oneof the great diagrams that's in this
(06:34):
chapter, the business learning life cycle.
And I'll show that on the screenin a moment, but just to tee you
up you say the first impulse formany corporates is to trust their
employees, experienced knowledge andskills to address uncertainties.
They have earned this trust by deliveringhigh performance results in the past from
the existing businesses for many years.
(06:56):
However, the reality is.
That rarely an idea survives itsfirst contact with a customer.
The uncertainties of an emerging businessmake your first ideas susceptible to
bias, meaning that there is a strongcorrelation between the trust approach
and the failure of corporate Innovationand then you outline steps to perform
(07:18):
iterative, experimentation from assumptionidentification through experiment design
and execution to data driven decisionmaking, and you use an approach that Sarah
used in China with General Motors chinapremium import and we'll talk about that
in a moment but first i'd love if you'dintroduce us and i'll show on the screen
(07:42):
this great diagram
Vincent Ducret (07:44):
Thank you, Aiden.
So, in fact, one of the challenge ofcorporates where they are launching new
ventures is that they are most of thetime entering a world of uncertainties
something that they never explored before.
And the higher risk they can take isjust to rely on the past experience
to take decisions for somethingwhich is completely new for them, and
(08:07):
this is the big difference betweenexplorations and explotations.
Explotations, you have probablydecades of success where you have fine
tuned everything to work perfectly.
But usually you can notuse this experience, this
knowledge to explore new world.
And this is why you need to adoptthis de risking approach that
(08:27):
we have illustrated through thisloop called business experiments.
And for this, you usually start by statingall the key assumptions hypothesis you
are making about your new ventures.
Those might be related to thecustomers you think you will
deliver a value proposition.
It might be related to the problemyou think you are addressing, as well
(08:48):
as to the value proposition itself.
And maybe the ecosystems youthink you need to put in place
to deliver the value proposition.
So you start first by listing,establishing all those key hypotheses
you are making, usually you can say,what must be true for my idea to work?
Okay?
Because if this is not true, Imight be, I would say, doing the
(09:10):
wrong stuff for the wrong people.
Okay.
So once you have done this one, youcan move to a step two, which is
about prioritizing those assumptions,hypotheses, because you cannot
address everything at the same time.
Will you be able to de riskat 100 percent of business?
No.
Okay, if you do this in six years, youare still de risking, I will say, an idea.
(09:33):
But they are very burning risks thatyou have to tackle as soon as possible,
because you know that if you are wrong,you might probably, I will say, to
move back a few weeks, if not monthsin the past, to correct something.
So this is why you need to prioritizeyour hypothesis and look, looking
usually at what I call rats.
(09:54):
Your riskiest assumption to test.
Okay.
This is I would say the one that are themost dangerous for your project this is
where usually sometimes you put the dustbelow the carpet expecting that the dust
will never pop up again Don't do this.
Okay.
Look at those one Even if this one isputting in danger the project you are
working on Then, once you have identifiedthose riskiest assumptions to test,
(10:19):
this is where the most interesting partstarts for me, and probably the most
creative one, is designing experiments.
How can you invalidate yourassumptions by getting real data
evidence from your target customers.
And this is also applicable for B2C andB2B model from your partner as well.
(10:40):
Okay.
In the B2B models.
And when I means this is where youneed highly creative because most
of the time You don't have anythingtangible to show to your customers.
You are still at a very early stage.
So how can you test with your customers,typical willingness to pay, willingness
to acquire your solutions, okay?
(11:02):
When this solution still does not exist.
And when I mean you need to becreative, because you need to go
beyond the traditional way of testingwith your customers, which are
asking them or making a survey, okay?
Which is the easiest way, I willsay, to get data from your customers,
but maybe the easiest way aswell to get buyer's data, okay?
(11:22):
And to not get any proof of what youare really, I will say, doing, if it
is right or wrong for your customers.
Once you have done your experiments, ofcourse, you will collect learnings, okay?
Aidan.
And those learnings might be takentelling you that you are right or wrong.
At the end, it doesn't matter.
It just gives you, I would say, thedata you need to take decisions.
(11:45):
And based on this learning, thenyou can decide to go for the next
iteration, for the next loop, whereyou will look maybe at the second
riskiest assumptions you have to test.
Okay.
And maybe sometimes you willhave collected enough evidence
after a few loops that you canmove forward with your project.
Okay.
That for example, it's time for younow to start building really your first
(12:07):
version of your product, like your MVP.
Okay.
To test it further with your customers.
But this loop is to remind to thepeople that the most important in
incubation is not about, I will say,prototyping is about de risking.
You need to de risk as much aspossible to bring all the data, the
confidence that you are doing theright thing for the right customer
(12:31):
to address the right problems.
So this is why as long as youdon't have enough data evidence
to tell you that you are right.
You need to keep, I will say, looping.
Aidan McCullen (12:39):
it's so difficult to Vincent and sarah when so sarah for
example you're going to china you have a.
A bias for action you really want to getstuck in you want to show progress and
then you have to take a step back andyou have to use a diagram like this and
i just want to get i just want to getstarted and when you have to go through
(13:03):
that loop first of all the disciplineto go through that loop and then.
Discipline to perhaps do it a secondtime it's really hard for a corporate
explore cause you cause of this timeyou know you feel like the, sounds of
time are slipping away all the time andi'd love to hear how you manage that.
(13:24):
When you're talking back to HQ and say,look, I got to go through this process.
Otherwise I'm going to besquandering money for the company
or how did you position that
Sarah Spoto (13:33):
Yeah, it's such a good question.
And it's a totally valid concernthat I think all of your listeners
who work in corporate willunderstand and sympathize with.
They're always trying to balance.
De risking to have that confidenceespecially if you're building a new
organization, you're a leader in thatorganization as well as showing that
you're making progress and moving quickly.
(13:55):
And sometimes you really have tomove quickly to build that momentum
in the broader organization, right?
And get that buy in.
So I think there's a few differenttactics we use to accomplish this.
I think making sure that you havestrong leadership support is really key.
Making sure that you have advocatesin your organization who can support
(14:17):
you and your different or innovativeapproach to doing business because
it is very different, right?
And the already the business modelthat you're working on, right?
Is going to be different in itself.
And then you add a layer of, okay, ourmethodology is totally different as well.
So make sure that you have theright voices in the right forums
to support what you're doing, which
(14:38):
I'm saying it very simply,but it's not simple.
Right?
So we actually took a very strategicapproach to thinking about who we
needed to bring on board along with us.
And thankfully, we were able todo that within our organization
and the broader organization.
But that's just 1 level, becausethe experiments are going to get
done, by your working level team.
(14:58):
And in a lot of cases,your team is really lean.
You might be under resource.
Everybody is doing a lot of thingsoutside of their typical scope and that
can be hard to motivate folks to say.
Okay, we're going to take an approachthat you are not familiar with at
all, outside of your normal work.
(15:18):
But we think it's the right thing to do.
So there's also, I think the buy inthat has to happen at the working
level as well, like the culturalpiece of it and giving folks that
that psychological safety to seefailure as part of this process.
And that, takes a lot of effort andI really I think that's something
I definitely want to emphasize.
(15:39):
And this podcast in particular,because maybe you read it in a book
and okay, great, the framework,let's follow the framework.
But there's that other element of thatcultural piece that's so important and
making sure as a leader, as a corporateexplorer in your own organization, that
you're taking the time to get by andwith your working level team as well.
(16:00):
So spend and dedicate that timeto educate them on the process.
They're the ones that are going to make ithappen bring them along for it, make sure
they understand the impact that they'rehaving the power of the frameworks that
you are using and then make sure also thatyou're celebrating the failures as well.
And I remember the first moment aresult of one of our experiments.
(16:24):
Came back working with Vincent andteam and it was a failed experiment
and it was a very celebratory momentfor us because we got information.
It was like, Oh, thisis not what we thought.
And that's great.
It was actually clear,really clear, right.
The experiment allowed us to havethat clarity even in our failure,
and it allowed us to pivot.
(16:45):
So making sure that you'retaking time to pay attention
to the cultural aspect as well.
Aidan McCullen (16:49):
great point?
And that, failure piece so manypeople would try to cover up that
failure, but how you positionthat and go, we saved ourselves.
Millions by not actually goinghere because we proved it wrong
for you this is one of the keyroles of the consultant here.
Vincent Ducret (17:09):
Exactly.
And I would like just to emphasizewhat you just say, Aidan.
This is sometimes very important toshow to the management that by not doing
something, how much money you are saving.
Because this is where sometimesyou may have the spark in their
eyes and say, Oh no, I got you.
Okay.
We have spent maybe three weeks to do thisexperiments, but we are saving six months
(17:31):
of doing something that nobody needs.
And by the way, you saved me half amillion because that was the plan we had.
Okay.
Because usually when you startexperimenting, people have the feeling
that you are slowing down everything.
You say, Oh, but why are we experimenting?
Let's just build it.
Okay.
And I say, yeah, that's fine.
Because if you are measuredjust on delivering something,
(17:52):
perfect, build it, deliver it.
But then if nobody's using it and youare also measuring about the customer
adoptions, you might be in trouble.
Okay.
So that's why, yes, you mighthave to invest a little bit of
time at the beginning to startunderstanding how to experiment.
But as soon as you start doing thisone, you are saving a lots of time,
money, and resources that you can useon stuff which are demonstrating real
(18:15):
progress, real data, and evidence.
Okay.
But this is hard at the beginning foryour leaders to understand this one
because they have been so used to go tosome leadership meetings where you just
show the I'm sorry to be brutal, but theway you are burning the money you got
for your project, here you are much moreadopting a small step approach where you
(18:35):
show progress and you are not measuringthe progress in the same way that you
are measuring an exploitation project,because here you have lots of unknown.
So you have to also measure differently.
I will say your progress, but showing theway you are wasting, you are saving money.
It's a nice way for somepeople to get it very quickly.
Aidan McCullen (18:56):
are the conversations that don't happen early like that this doesn't
happen and it's great to hear you say.
That the culture allowed youto even engage with advance on
the change team to actually go.
We're gonna do this slowly we're gonnago through the steps so that we don't
squander money and waste resource andwaste our time as well and ultimately
(19:18):
get to a failure but if we find thosefailures are those cracks early.
That's actually a huge win that's avery tough chasm cross for corporate
explorers and i've been guilty of thisas have so many of our audience where
we're going to go if i build somethingeven if it's not successful at least
i've built it and i can point to it.
(19:40):
But that's not what you want to point to.
So there's a lot in there, but Iwanted to bring it back a step.
So you, so Sarah, I'm justthinking about you as a template
for many corporate explorers.
So been given this huge opportunity.
The first step is then you go,okay, I need to map this out.
(20:01):
You had an existing relationshipwith change logic vans on becomes
your account manager and then do youguys map it together and you can go
this is how we're gonna approach it.
And then you go for it because there's adiagram that i have from the book that i
thought it looks like this was the nextstep then i just want to help our audience
go because there's lots of little bits inbetween that we skip when we have these
(20:24):
conversations but i really wanna helpother corporate explorers so they get it.
So maybe i'll share on the screen.
This diagram and maybe you'll talkto us cause this maps to very much
to the framework and this is howyou actually, stepped into china
Sarah Spoto (20:43):
Well, it's a great question, because I think the context is really
important when I think it's worth actuallytaking a step back on it because I
was fortunate enough to join the team,as I mentioned, as employee number 4.
And so we were really lean, and then wecould all really take a strong leadership
position and kind of building thestrategic vision for the organization.
(21:06):
And for us, I think thatwas really important.
Was why we were successful withimplementing experimentation, because
even before we knew who change logicwas, we are the managing director
and the rest of the leadershipteam, we spent a lot of time.
Being really clear on what our objectiveswere as an organization, and I think
(21:31):
what helped us be more open to acceptingthis process of experimentation is
that our objectives weren't as moretypically focused on get X, Y, Z
done, but really more focused onthe learnings we wanted to generate.
and so I, to simplify it, itwas really making sure that we.
(21:52):
Had organized the team around the rightincentives that then made it possible
to even explore something like what wedid with change logic and with Vincent.
And so we didn't explicitly have thatrelationship or that process in mind.
I was not familiar with experimentation.
At all not not since takingscience classes in school, right?
(22:16):
I was very familiar with, like, at abroad, a broad level, obviously, the
importance of getting data and we're verydata centric business and the importance
of market research and getting in frontof your consumers and that kind of stuff,
but not experimentation explicitly, but Ithink taking the time to build the right
incentives and the right vision early on,then let us down this path of Thinking
(22:38):
about how can we really be successful andit became clear that de risking was really
important and that we needed or that as aleadership team, we wanted to look beyond
the typical approaches to doing that.
And that's where changelogic became involved.
One of our leadership team members, hehad a relationship with change logic.
(23:01):
And so we brought them in.
But honestly, it was, Midstream.
And so that's why I think I mentionedthat cultural piece, because even by
the time that Vincent came involved,the team was growing really quickly.
And we had people running wehad experts doing sales, right?
We had experts doing marketing and theywere running and down the path of the
(23:22):
tasks that they needed to get done.
And so we introduced this midstreamand had to really get everybody.
At that working level on boardwith us with experimentation.
So that's kind of how how it happened.
Truthfully, it took it did take sometime for us to to educate the team
(23:43):
to get them on board to build theright group of folks who are going
to focus on the experimentation.
We wanted it to sitvery cross functionally.
We didn't want this to be siloed withmarket research experts or marketing
experts or commercial experts.
We wanted everybody from, or atleast a representative from every
discipline as a part of the process.
(24:03):
So obviously that requiressome education as well.
But once we had lined up those rightteams, then we were able to work.
Effectively with Vincent and teamto start generating experiments,
it took it always takes a bit toget the 1st few off the ground.
Lots of questions and trial and error.
And then I think once we did that, andwe got some in market, then we were
(24:25):
able to build momentum and really startto get the data and results and to
Vincent's points earlier demonstrate toour leadership the value of this process.
As a compliment to thetraditional methods we were also
using to de risk our business.
So tell us about, , so , the firstexperiment, say, for example, or
maybe it was the one that , youproved was wrong, the wrong approach.
(24:47):
So , what actually happens and maybe we'lluse this diagram on the screen to, to map
that steps, those steps that you took.
The first piece was reallythe assumptions analysis.
And I think this is so critical.
It's important not toskip this piece of it.
(25:07):
And honestly, even as a corporateexplorer, if you are not fully on board
with experimentation as a process, juststart with the assumptions analysis,
because that alone is going to reveal somuch about your biases as an organization.
And.
Help frame your thinkingfrom the very beginning.
It's still a tactic that I use even inmy own work as a marketing professional.
(25:29):
Even if I don't go into experimentation.
But anyway, so we started withthe assumptions analysis and
really saying what must betrue for this business to work.
And then, of course, appliedthat to different offerings
that we were exploring.
And that was not a shortprocess necessarily because
again, it was cross functional.
We wanted to have inputfrom the right teams.
We wanted to be robust enough from there.
(25:52):
We prioritized the assumptionsbased on some assumptions.
We could really quickly.
Answer either with existing data ordata that already existed publicly
third party data or results from recentmarket research or things like that
or some were just simply questionswe could get answered within the
(26:12):
organization and then some were true.
Unknowns and that's where wefocused the experimentation.
Even building this framework during theprocess was What happened right so we
had what on the screen here is this niceneat framework, but it looked different.
The first time we were using itinvolved to, to fit what I think
(26:35):
you make it most effective for ouruse but yeah, so then we were able
to use it to define the experiments,
Vincent Ducret (26:40):
and I think if I can add on this Aidan and Sarah, thank you.
What on the screen is a great exampleof one of the experimentation among,
I will say, I don't remember how manywere run over the last probably one
year and a half of this project, butthat was an experimentation where,
Probably most of the time people wouldhave just, I will say, ask customers
(27:02):
to get a response to the questions.
In that case, we really use like communityin China to test, I will say people's
behaviors and figuring out without, I willsay, asking them if they will rather opt
for solution a rather than solution B.
But they were not knowing that we werereally testing them it was made in a
(27:23):
way that it was natural for them toget, I will say this offer in front
of them and select a or B, but we werehere testing really customer behaviors
and this is where experimentationis very challenging for most of the
corporate is how can I cross the borderbetween people saying and people doing.
And this is a good examples wherewe were testing this idea about
(27:46):
vehicle subscription services tosee if the model we had in mind
where we have multi branded.
Would get preference to a model whereyou have only cars for the same from
the same brand Okay and again You canhave just I will say question a few
people around and say do you preferto rent always car from this brand?
Or you would like to have a portfolioof brands and maybe they will have
(28:08):
tell you yes But the problem is thatthey tell you yes and the day where
the offer exists they don't use it.
Okay.
Because what they say is not what they do.
So here we found a way using communitythat was existing in China to really
test their behaviors and to see towhich level they are ready to even
subscribe for service, which wasnot yet existing at this stage.
(28:29):
Okay.
So this framework is helping youstructuring your assumptions and
turning it into something that youcan test, measure, and you can take
decision and decision may be Just acceptthat you are wrong and that's okay.
That's a learning.
You are not failing You are justlearning that you are right or you
are wrong or you have enough datatelling you that you are right
(28:53):
, Aidan McCullen: Sarah did you want to add anything
Sarah Spoto (28:55):
just in terms of like the application of the experiments,
because we, we were in a, in themiddle of the pandemic when we.
Executed our first set of experiments.
And so, we started out with moredigital focused experiments and think
in China, they have, of course, and,incredible ecosystem of digital tools.
(29:15):
We chat being a great example of that.
And to Vincent's point that wecould really leverage that for
understanding community behavior.
But eventually we were able to pivotinto experiments in in real life.
And I think that's really importantbecause it's so easy to stay within
(29:36):
your corporate environment, say, withinyour your building and something that
change logic really challenge us todo is to get out of the building.
To get in front of customers, becausea secondary benefit to doing these
experiments is you give your team exposureto customers in a way that they might
not typically get in their normal roles.
(29:59):
And I think those learnings go even beyondthe results of the experiment as well.
Aidan McCullen (30:02):
Fantastic guys for people who want to reach out and find
you where is the best place are you firstwhere is the best place to find you.
Sarah Spoto (30:09):
You can find me Sarah's photo at LinkedIn.
Vincent Ducret (30:12):
Same for me LinkedIn, Vincent Ducret
Vincent Ducre.
You will find me
Aidan McCullen (30:18):
multiple ways of saying Vincent, but it's Vincent
Ducre, which is the best way.
And it's been a pleasurehaving you authors of the
corporate explorer field book.
And before I finish infour, I thank our guests.
I want to thank our sponsor Wazokuwho helps large organizations create
effective, sustainable innovationecosystems that accelerate efficiency
(30:38):
gains and new value growth.
And does so through intelligent enterprisesoftware that connects and harnesses
the powers of employees, suppliers,startups, universities, and the unique
Wazoku crowd of problem solvers of700, 000 plus what Wazoku calls
connected collective intelligence.
(30:59):
And you can find Wazoku at www.
Wazoku.
com for now authors of.
The corporate explorer field book andsarah spoto thank you for joining us
Vincent Ducret (31:11):
Thank you for inviting us
There are many examples of how even the most successful
(00:03):
entrepreneurs and business managerscan fail , they put personal
conviction and opinion ahead of data.
Andy grove intel's legendaryceo committed, The business to
video conferencing equipmentin the late nineteen nineties.
Jeff emmelt another storied ceo betGE's future on the internet of things.
(00:24):
The browser company mozilla reportedlyspent four hundred million dollars on
a new phone operating system these aredecisions made on instinct that failed.
So how does a corporate explorerreplace or at least supplement
instincts and opinions with data andevidence to demonstrate whether an
(00:47):
idea is worth pursuing , or if itrequires a pivot or even a shutdown?
How does a corporate exploreranswer questions that have a
major potential to jeopardize
the projects progress and ultimately it'sfuture success if not addressed up front.
Big questions to get through on today'sepisode of the corporate explorer.
(01:11):
Just a reminder that the corporateexplorer series is brought to you by
Wazoku Was oku helps large organizationscreate effective sustainable innovation
ecosystems that accelerate efficiencygains and new value growth and it
does this through intelligence.
Enterprise software that connectsand harnesses the power of employees,
suppliers, startups, universities,and the unique Wazoku crowd of over
(01:35):
700, 000 plus global problem solvers.
Wazoku calls this connectedcollective intelligence, and you can
find our friends at Wazoku at www.
wazoku.
com.
So today's episode describes howincubation tests on proven assumptions
of an idea for a new business by derisking each element before committing
(01:59):
scarce resource to the project.
Is a great pleasure to welcome thecoauthors of the corporate explorer feel
book, i'm a chapter entitled businessexperiments the risking execution spend
through experiments, sarah spoto andvincent Ducret welcome to the show
Sarah Spoto (02:18):
thank you.
Thanks so much for having me
Vincent Ducret (02:21):
Thank you.
Aidan McCullen (02:22):
it's great to have you guys sarah maybe.
You start by introducing yourself andhow you got involved in this chapter
and then we'll come to the van song andthen we'll get stuck into the chapter.
Sarah Spoto (02:34):
Thanks again for having me here.
I'm Sarah Spoto.
at the time when this chapter waswritten, I was working in China, in
With General Motors, I was the directorof strategy innovation as well as
brand strategy for the organization.
And it was really anincredible opportunity for me.
I had been working at the headquartersin Detroit for GM for a number of years.
(02:58):
And to go to a region to reallybuild a startup within this large
multinational corporation washonestly a dream come true for me.
I consider myself an entrepreneur.
But of course, being in corporatesometimes you don't always
get those opportunities to dosomething truly, entrepreneurial.
(03:19):
And in this case, I did.
And so I'm really proud to say that wehad leadership who very much supported
our efforts in taking an experimentationapproach to how we developed the
offerings for this new business modeland doing it in conjunction with more
(03:40):
traditional methods like market research.
Right?
And I think those complementeach other very well.
So my role there, I was actuallyemployee number 4 on the team.
So, while I have this fancy soundingtitle, I wear a lot of hats.
And it was really helping to driveinnovation an agile methodology and
bring this experimentation approachto the business while at the same time
(04:02):
also building our brand there as well.
Aidan McCullen (04:04):
Brilliant sarah and so great to have you and it's great to
have somebody who's done the work andhas all the scar tissue and all the
arrows in the back for doing that workas well which really makes it real.
And Vincent, maybe you introduceyourself as well and then will
describe the chapter but also theframeworks that exist in the chapter.
Vincent Ducret (04:24):
With great pleasure and thanks again for the invitations
and so nice to see you again, Sarah.
So in fact I have a computerengineer background, okay?
And by the way, I'm just calling you todayfrom the place where I graduated more
than 20 years ago EPFL in, in Lausanne.
So I started really my career as asoftware developer, so I was exposed very
(04:45):
early to all those extreme programming,agile way of thinking, of working.
And I work several yearsfor Sun Microsystems.
Probably some of you mightremember this company.
And then I moved to the other side ofthe mirror, I used to say, because I
spent 15 years in corporate environment.
So when I joined SARA on thisproject, I was used, I will
(05:07):
say, to the corporate world.
So I know what might be the challenge.
What might be, I will saythe problems they may face.
So I spent 15 years in corporateenvironments, having worked for different
departments and the last six, sevenyears, I was part of the transformation
organization, moving a very famous companyfrom business centric to Customer centric.
(05:28):
So really adopting a much more customercentric approach for this company.
And I have also the opportunity todayto teach business transformation and
innovation principles in differentuniversity in St Gallens or in Geneva.
And I joined ChangeLogic twoyears and a half ago as as a
(05:48):
consultant to help company togrow beyond their core business.
So really more or less, I willsay helping company like Sarah was
working for to explore, test andscale new venture and new business.
And this is how I was, I will say workingwith with Sarah on this very interesting
and passionate project for, GMPI in China.
Aidan McCullen (06:12):
Brilliant we have the perfect people in the room to get
it both sides of the story as welland i thought we start by that so
Vincent., you've taught other people,the frameworks, but also you've used
those frameworks in organizations,which is a totally different thing
than just teaching them the whole time.
So we're going to tee us up for oneof the great diagrams that's in this
(06:34):
chapter, the business learning life cycle.
And I'll show that on the screenin a moment, but just to tee you
up you say the first impulse formany corporates is to trust their
employees, experienced knowledge andskills to address uncertainties.
They have earned this trust by deliveringhigh performance results in the past from
the existing businesses for many years.
(06:56):
However, the reality is.
That rarely an idea survives itsfirst contact with a customer.
The uncertainties of an emerging businessmake your first ideas susceptible to
bias, meaning that there is a strongcorrelation between the trust approach
and the failure of corporate Innovationand then you outline steps to perform
(07:18):
iterative, experimentation from assumptionidentification through experiment design
and execution to data driven decisionmaking, and you use an approach that Sarah
used in China with General Motors chinapremium import and we'll talk about that
in a moment but first i'd love if you'dintroduce us and i'll show on the screen
(07:42):
this great diagram
Vincent Ducret (07:44):
Thank you, Aiden.
So, in fact, one of the challenge ofcorporates where they are launching new
ventures is that they are most of thetime entering a world of uncertainties
something that they never explored before.
And the higher risk they can take isjust to rely on the past experience
to take decisions for somethingwhich is completely new for them, and
(08:07):
this is the big difference betweenexplorations and explotations.
Explotations, you have probablydecades of success where you have fine
tuned everything to work perfectly.
But usually you can notuse this experience, this
knowledge to explore new world.
And this is why you need to adoptthis de risking approach that
(08:27):
we have illustrated through thisloop called business experiments.
And for this, you usually start by statingall the key assumptions hypothesis you
are making about your new ventures.
Those might be related to thecustomers you think you will
deliver a value proposition.
It might be related to the problemyou think you are addressing, as well
(08:48):
as to the value proposition itself.
And maybe the ecosystems youthink you need to put in place
to deliver the value proposition.
So you start first by listing,establishing all those key hypotheses
you are making, usually you can say,what must be true for my idea to work?
Okay?
Because if this is not true, Imight be, I would say, doing the
(09:10):
wrong stuff for the wrong people.
Okay.
So once you have done this one, youcan move to a step two, which is
about prioritizing those assumptions,hypotheses, because you cannot
address everything at the same time.
Will you be able to de riskat 100 percent of business?
No.
Okay, if you do this in six years, youare still de risking, I will say, an idea.
(09:33):
But they are very burning risks thatyou have to tackle as soon as possible,
because you know that if you are wrong,you might probably, I will say, to
move back a few weeks, if not monthsin the past, to correct something.
So this is why you need to prioritizeyour hypothesis and look, looking
usually at what I call rats.
(09:54):
Your riskiest assumption to test.
Okay.
This is I would say the one that are themost dangerous for your project this is
where usually sometimes you put the dustbelow the carpet expecting that the dust
will never pop up again Don't do this.
Okay.
Look at those one Even if this one isputting in danger the project you are
working on Then, once you have identifiedthose riskiest assumptions to test,
(10:19):
this is where the most interesting partstarts for me, and probably the most
creative one, is designing experiments.
How can you invalidate yourassumptions by getting real data
evidence from your target customers.
And this is also applicable for B2C andB2B model from your partner as well.
(10:40):
Okay.
In the B2B models.
And when I means this is where youneed highly creative because most
of the time You don't have anythingtangible to show to your customers.
You are still at a very early stage.
So how can you test with your customers,typical willingness to pay, willingness
to acquire your solutions, okay?
(11:02):
When this solution still does not exist.
And when I mean you need to becreative, because you need to go
beyond the traditional way of testingwith your customers, which are
asking them or making a survey, okay?
Which is the easiest way, I willsay, to get data from your customers,
but maybe the easiest way aswell to get buyer's data, okay?
(11:22):
And to not get any proof of what youare really, I will say, doing, if it
is right or wrong for your customers.
Once you have done your experiments, ofcourse, you will collect learnings, okay?
Aidan.
And those learnings might be takentelling you that you are right or wrong.
At the end, it doesn't matter.
It just gives you, I would say, thedata you need to take decisions.
(11:45):
And based on this learning, thenyou can decide to go for the next
iteration, for the next loop, whereyou will look maybe at the second
riskiest assumptions you have to test.
Okay.
And maybe sometimes you willhave collected enough evidence
after a few loops that you canmove forward with your project.
Okay.
That for example, it's time for younow to start building really your first
(12:07):
version of your product, like your MVP.
Okay.
To test it further with your customers.
But this loop is to remind to thepeople that the most important in
incubation is not about, I will say,prototyping is about de risking.
You need to de risk as much aspossible to bring all the data, the
confidence that you are doing theright thing for the right customer
(12:31):
to address the right problems.
So this is why as long as youdon't have enough data evidence
to tell you that you are right.
You need to keep, I will say, looping.
Aidan McCullen (12:39):
it's so difficult to Vincent and sarah when so sarah for
example you're going to china you have a.
A bias for action you really want to getstuck in you want to show progress and
then you have to take a step back andyou have to use a diagram like this and
i just want to get i just want to getstarted and when you have to go through
(13:03):
that loop first of all the disciplineto go through that loop and then.
Discipline to perhaps do it a secondtime it's really hard for a corporate
explore cause you cause of this timeyou know you feel like the, sounds of
time are slipping away all the time andi'd love to hear how you manage that.
(13:24):
When you're talking back to HQ and say,look, I got to go through this process.
Otherwise I'm going to besquandering money for the company
or how did you position that
Sarah Spoto (13:33):
Yeah, it's such a good question.
And it's a totally valid concernthat I think all of your listeners
who work in corporate willunderstand and sympathize with.
They're always trying to balance.
De risking to have that confidenceespecially if you're building a new
organization, you're a leader in thatorganization as well as showing that
you're making progress and moving quickly.
(13:55):
And sometimes you really have tomove quickly to build that momentum
in the broader organization, right?
And get that buy in.
So I think there's a few differenttactics we use to accomplish this.
I think making sure that you havestrong leadership support is really key.
Making sure that you have advocatesin your organization who can support
(14:17):
you and your different or innovativeapproach to doing business because
it is very different, right?
And the already the business modelthat you're working on, right?
Is going to be different in itself.
And then you add a layer of, okay, ourmethodology is totally different as well.
So make sure that you have theright voices in the right forums
to support what you're doing, which
(14:38):
I'm saying it very simply,but it's not simple.
Right?
So we actually took a very strategicapproach to thinking about who we
needed to bring on board along with us.
And thankfully, we were able todo that within our organization
and the broader organization.
But that's just 1 level, becausethe experiments are going to get
done, by your working level team.
(14:58):
And in a lot of cases,your team is really lean.
You might be under resource.
Everybody is doing a lot of thingsoutside of their typical scope and that
can be hard to motivate folks to say.
Okay, we're going to take an approachthat you are not familiar with at
all, outside of your normal work.
(15:18):
But we think it's the right thing to do.
So there's also, I think the buy inthat has to happen at the working
level as well, like the culturalpiece of it and giving folks that
that psychological safety to seefailure as part of this process.
And that, takes a lot of effort andI really I think that's something
I definitely want to emphasize.
(15:39):
And this podcast in particular,because maybe you read it in a book
and okay, great, the framework,let's follow the framework.
But there's that other element of thatcultural piece that's so important and
making sure as a leader, as a corporateexplorer in your own organization, that
you're taking the time to get by andwith your working level team as well.
(16:00):
So spend and dedicate that timeto educate them on the process.
They're the ones that are going to make ithappen bring them along for it, make sure
they understand the impact that they'rehaving the power of the frameworks that
you are using and then make sure also thatyou're celebrating the failures as well.
And I remember the first moment aresult of one of our experiments.
(16:24):
Came back working with Vincent andteam and it was a failed experiment
and it was a very celebratory momentfor us because we got information.
It was like, Oh, thisis not what we thought.
And that's great.
It was actually clear,really clear, right.
The experiment allowed us to havethat clarity even in our failure,
and it allowed us to pivot.
(16:45):
So making sure that you'retaking time to pay attention
to the cultural aspect as well.
Aidan McCullen (16:49):
great point?
And that, failure piece so manypeople would try to cover up that
failure, but how you positionthat and go, we saved ourselves.
Millions by not actually goinghere because we proved it wrong
for you this is one of the keyroles of the consultant here.
Vincent Ducret (17:09):
Exactly.
And I would like just to emphasizewhat you just say, Aidan.
This is sometimes very important toshow to the management that by not doing
something, how much money you are saving.
Because this is where sometimesyou may have the spark in their
eyes and say, Oh no, I got you.
Okay.
We have spent maybe three weeks to do thisexperiments, but we are saving six months
(17:31):
of doing something that nobody needs.
And by the way, you saved me half amillion because that was the plan we had.
Okay.
Because usually when you startexperimenting, people have the feeling
that you are slowing down everything.
You say, Oh, but why are we experimenting?
Let's just build it.
Okay.
And I say, yeah, that's fine.
Because if you are measuredjust on delivering something,
(17:52):
perfect, build it, deliver it.
But then if nobody's using it and youare also measuring about the customer
adoptions, you might be in trouble.
Okay.
So that's why, yes, you mighthave to invest a little bit of
time at the beginning to startunderstanding how to experiment.
But as soon as you start doing thisone, you are saving a lots of time,
money, and resources that you can useon stuff which are demonstrating real
(18:15):
progress, real data, and evidence.
Okay.
But this is hard at the beginning foryour leaders to understand this one
because they have been so used to go tosome leadership meetings where you just
show the I'm sorry to be brutal, but theway you are burning the money you got
for your project, here you are much moreadopting a small step approach where you
(18:35):
show progress and you are not measuringthe progress in the same way that you
are measuring an exploitation project,because here you have lots of unknown.
So you have to also measure differently.
I will say your progress, but showing theway you are wasting, you are saving money.
It's a nice way for somepeople to get it very quickly.
Aidan McCullen (18:56):
are the conversations that don't happen early like that this doesn't
happen and it's great to hear you say.
That the culture allowed youto even engage with advance on
the change team to actually go.
We're gonna do this slowly we're gonnago through the steps so that we don't
squander money and waste resource andwaste our time as well and ultimately
(19:18):
get to a failure but if we find thosefailures are those cracks early.
That's actually a huge win that's avery tough chasm cross for corporate
explorers and i've been guilty of thisas have so many of our audience where
we're going to go if i build somethingeven if it's not successful at least
i've built it and i can point to it.
(19:40):
But that's not what you want to point to.
So there's a lot in there, but Iwanted to bring it back a step.
So you, so Sarah, I'm justthinking about you as a template
for many corporate explorers.
So been given this huge opportunity.
The first step is then you go,okay, I need to map this out.
(20:01):
You had an existing relationshipwith change logic vans on becomes
your account manager and then do youguys map it together and you can go
this is how we're gonna approach it.
And then you go for it because there's adiagram that i have from the book that i
thought it looks like this was the nextstep then i just want to help our audience
go because there's lots of little bits inbetween that we skip when we have these
(20:24):
conversations but i really wanna helpother corporate explorers so they get it.
So maybe i'll share on the screen.
This diagram and maybe you'll talkto us cause this maps to very much
to the framework and this is howyou actually, stepped into china
Sarah Spoto (20:43):
Well, it's a great question, because I think the context is really
important when I think it's worth actuallytaking a step back on it because I
was fortunate enough to join the team,as I mentioned, as employee number 4.
And so we were really lean, and then wecould all really take a strong leadership
position and kind of building thestrategic vision for the organization.
(21:06):
And for us, I think thatwas really important.
Was why we were successful withimplementing experimentation, because
even before we knew who change logicwas, we are the managing director
and the rest of the leadershipteam, we spent a lot of time.
Being really clear on what our objectiveswere as an organization, and I think
(21:31):
what helped us be more open to acceptingthis process of experimentation is
that our objectives weren't as moretypically focused on get X, Y, Z
done, but really more focused onthe learnings we wanted to generate.
and so I, to simplify it, itwas really making sure that we.
(21:52):
Had organized the team around the rightincentives that then made it possible
to even explore something like what wedid with change logic and with Vincent.
And so we didn't explicitly have thatrelationship or that process in mind.
I was not familiar with experimentation.
At all not not since takingscience classes in school, right?
(22:16):
I was very familiar with, like, at abroad, a broad level, obviously, the
importance of getting data and we're verydata centric business and the importance
of market research and getting in frontof your consumers and that kind of stuff,
but not experimentation explicitly, but Ithink taking the time to build the right
incentives and the right vision early on,then let us down this path of Thinking
(22:38):
about how can we really be successful andit became clear that de risking was really
important and that we needed or that as aleadership team, we wanted to look beyond
the typical approaches to doing that.
And that's where changelogic became involved.
One of our leadership team members, hehad a relationship with change logic.
(23:01):
And so we brought them in.
But honestly, it was, Midstream.
And so that's why I think I mentionedthat cultural piece, because even by
the time that Vincent came involved,the team was growing really quickly.
And we had people running wehad experts doing sales, right?
We had experts doing marketing and theywere running and down the path of the
(23:22):
tasks that they needed to get done.
And so we introduced this midstreamand had to really get everybody.
At that working level on boardwith us with experimentation.
So that's kind of how how it happened.
Truthfully, it took it did take sometime for us to to educate the team
(23:43):
to get them on board to build theright group of folks who are going
to focus on the experimentation.
We wanted it to sitvery cross functionally.
We didn't want this to be siloed withmarket research experts or marketing
experts or commercial experts.
We wanted everybody from, or atleast a representative from every
discipline as a part of the process.
(24:03):
So obviously that requiressome education as well.
But once we had lined up those rightteams, then we were able to work.
Effectively with Vincent and teamto start generating experiments,
it took it always takes a bit toget the 1st few off the ground.
Lots of questions and trial and error.
And then I think once we did that, andwe got some in market, then we were
(24:25):
able to build momentum and really startto get the data and results and to
Vincent's points earlier demonstrate toour leadership the value of this process.
As a compliment to thetraditional methods we were also
using to de risk our business.
So tell us about, , so , the firstexperiment, say, for example, or
maybe it was the one that , youproved was wrong, the wrong approach.
(24:47):
So , what actually happens and maybe we'lluse this diagram on the screen to, to map
that steps, those steps that you took.
The first piece was reallythe assumptions analysis.
And I think this is so critical.
It's important not toskip this piece of it.
(25:07):
And honestly, even as a corporateexplorer, if you are not fully on board
with experimentation as a process, juststart with the assumptions analysis,
because that alone is going to reveal somuch about your biases as an organization.
And.
Help frame your thinkingfrom the very beginning.
It's still a tactic that I use even inmy own work as a marketing professional.
(25:29):
Even if I don't go into experimentation.
But anyway, so we started withthe assumptions analysis and
really saying what must betrue for this business to work.
And then, of course, appliedthat to different offerings
that we were exploring.
And that was not a shortprocess necessarily because
again, it was cross functional.
We wanted to have inputfrom the right teams.
We wanted to be robust enough from there.
(25:52):
We prioritized the assumptionsbased on some assumptions.
We could really quickly.
Answer either with existing data ordata that already existed publicly
third party data or results from recentmarket research or things like that
or some were just simply questionswe could get answered within the
(26:12):
organization and then some were true.
Unknowns and that's where wefocused the experimentation.
Even building this framework during theprocess was What happened right so we
had what on the screen here is this niceneat framework, but it looked different.
The first time we were using itinvolved to, to fit what I think
(26:35):
you make it most effective for ouruse but yeah, so then we were able
to use it to define the experiments,
Vincent Ducret (26:40):
and I think if I can add on this Aidan and Sarah, thank you.
What on the screen is a great exampleof one of the experimentation among,
I will say, I don't remember how manywere run over the last probably one
year and a half of this project, butthat was an experimentation where,
Probably most of the time people wouldhave just, I will say, ask customers
(27:02):
to get a response to the questions.
In that case, we really use like communityin China to test, I will say people's
behaviors and figuring out without, I willsay, asking them if they will rather opt
for solution a rather than solution B.
But they were not knowing that we werereally testing them it was made in a
(27:23):
way that it was natural for them toget, I will say this offer in front
of them and select a or B, but we werehere testing really customer behaviors
and this is where experimentationis very challenging for most of the
corporate is how can I cross the borderbetween people saying and people doing.
And this is a good examples wherewe were testing this idea about
(27:46):
vehicle subscription services tosee if the model we had in mind
where we have multi branded.
Would get preference to a model whereyou have only cars for the same from
the same brand Okay and again You canhave just I will say question a few
people around and say do you preferto rent always car from this brand?
Or you would like to have a portfolioof brands and maybe they will have
(28:08):
tell you yes But the problem is thatthey tell you yes and the day where
the offer exists they don't use it.
Okay.
Because what they say is not what they do.
So here we found a way using communitythat was existing in China to really
test their behaviors and to see towhich level they are ready to even
subscribe for service, which wasnot yet existing at this stage.
(28:29):
Okay.
So this framework is helping youstructuring your assumptions and
turning it into something that youcan test, measure, and you can take
decision and decision may be Just acceptthat you are wrong and that's okay.
That's a learning.
You are not failing You are justlearning that you are right or you
are wrong or you have enough datatelling you that you are right
(28:53):
, Aidan McCullen: Sarah did you want to add anything
Sarah Spoto (28:55):
just in terms of like the application of the experiments,
because we, we were in a, in themiddle of the pandemic when we.
Executed our first set of experiments.
And so, we started out with moredigital focused experiments and think
in China, they have, of course, and,incredible ecosystem of digital tools.
(29:15):
We chat being a great example of that.
And to Vincent's point that wecould really leverage that for
understanding community behavior.
But eventually we were able to pivotinto experiments in in real life.
And I think that's really importantbecause it's so easy to stay within
(29:36):
your corporate environment, say, withinyour your building and something that
change logic really challenge us todo is to get out of the building.
To get in front of customers, becausea secondary benefit to doing these
experiments is you give your team exposureto customers in a way that they might
not typically get in their normal roles.
(29:59):
And I think those learnings go even beyondthe results of the experiment as well.
Aidan McCullen (30:02):
Fantastic guys for people who want to reach out and find
you where is the best place are you firstwhere is the best place to find you.
Sarah Spoto (30:09):
You can find me Sarah's photo at LinkedIn.
Vincent Ducret (30:12):
Same for me LinkedIn, Vincent Ducret
Vincent Ducre.
You will find me
Aidan McCullen (30:18):
multiple ways of saying Vincent, but it's Vincent
Ducre, which is the best way.
And it's been a pleasurehaving you authors of the
corporate explorer field book.
And before I finish infour, I thank our guests.
I want to thank our sponsor Wazokuwho helps large organizations create
effective, sustainable innovationecosystems that accelerate efficiency
(30:38):
gains and new value growth.
And does so through intelligent enterprisesoftware that connects and harnesses
the powers of employees, suppliers,startups, universities, and the unique
Wazoku crowd of problem solvers of700, 000 plus what Wazoku calls
connected collective intelligence.
(30:59):
And you can find Wazoku at www.
Wazoku.
com for now authors of.
The corporate explorer field book andsarah spoto thank you for joining us
Vincent Ducret (31:11):
Thank you for inviting us
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