December 21, 2024 • 39 mins
Vanessa is a serial business builder and technology innovator with over 25 years of experience across SAP, Trigger Media and McKinsey. The businesses she has built and relaunched are leaders in their verticals.
She is the Co-Founder and CEO of Sugarwork, an enterprise SaaS knowledge sharing platform empowering employers to own and maintain the tacit knowledge, skills, and relationships that drive their businesses using generative AI. She was most recently Vice President of SAP.iO, SAP’s early-stage venture arm, where she oversaw SAP.iO’s North American Foundries in New York and San Francisco, and recruited and accelerated 87enterprise software startups. Prior to SAP, Vanessa was Chief Operating Officer at Trigger Media Group, a $22MM digital media incubator. She co-founded and was the interim CEO of Trigger’s portfolio companies: Inside Hook (digital media company &men’s lifestyle brand; sold to private equity) and Fevo (SaaS technology for group experiences in sports and music; Series C, market leader). She began her career at McKinsey & Company and was an Associate Partner in the Firm’s Media and Entertainment Practice, based in Amsterdam, London and New York.
Sugarwork
Vanessa currently serves as a Non-Executive director of Appen Ltd. (ASX: APX), a global AI data services company; and Goodman Group (ASX: GMG), a global industrial real estate company. She serves on the Audit Committee for Appen and the Sustainability& Innovation Committee for Goodman.
Vanessa graduated magna cum laude with an AB in psychology from Harvard University and cum laude with a JD from Harvard Law School. She was a Fulbright Scholar at Universiteit Utrecht in the Netherlands where she conducted independent research on the International War Crimes Tribunal for the Former Yugoslavia and the International Court of Justice. She serves as a member of Harvard University’s Board of Overseers, and as a Past President Director of the Harvard Alumni Association (was President from July2021 - June 2022). She lives in New York City with her husband and two children.
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Episode Transcript
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(00:00):
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Pioneer in all eight services welcomes you to
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are thrilled to offer this educational program. These
design conversations
bring you people's experiences
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of knowledge management, nonprofit work, and innovation.
(01:29):
My name is Vanessa Dew. I live in
New York City.
I absolutely
love working in technology, data, and innovation. I've
worked over 25 years in this field.
And the thing I get asked a lot
is what makes someone successful?
The thing I have learned
is that growth in an industry
plus dumb luck
(01:50):
leads to success
more than any other factors combined.
Wait a minute. So part of your research
is defined by dumb luck.
That's what you're saying is the dividing rod
for success. Plus
growth of an industry.
It's true. It's so much of it isn't
about being in the right place at the
right time. If I look around me and
(02:10):
I think there have been books written about
this too. Right? I think Malcolm Gladwell
recently wrote about, oh, there's this whole slew
of these founders that were born at the
right time. You look at Bill Gates. You
look at Michael Dell. They were born in
this heyday where
computing was coming into the foray. So let's
talk about growth
of an industry. And then they happen to
(02:32):
have had the luck, like, the lucky breaks
that they had because there were many people
working at it so that they could succeed.
Of course, it's it's something I've seen again
and again. It's it's something that I've resigned
myself to accept because there are only so
many things you can't control.
And so I love talking about my mentors
because I've had the honor and privilege of
(02:53):
having some
who have been incredibly formatives and just transformational
for my personal growth and my career. I
think back to when I was 14,
and that was when I met the late
Space Shuttle commander, David Walker.
We went on a trip together as part
of a NASA student delegation
(03:14):
to what was formerly the USSR.
He was just an incredible
leader, and so he led 10 of us,
10 14 year old students,
who always then the USSR
as part of a diplomatic delegation.
You know? But what was so special was
that we kept a relationship afterwards, and fax
was one of the ways that you would
(03:34):
write one another. And I remember there was
this one time he saw me winning an
award or heard about the news, and he
faxed to my parents' fax machine to say,
I just wanna let you know I'm just
so proud of you. And it just touched
me so much. I mean, here's, like, a
a man who was, like, you know, busy
busy commanding base level missions saying, like, let
me just drop Vanessa a note.
That's amazing. It was amazing. He he sadly
(03:57):
passed in
2,001.
His widow Paige,
a few years ago sent me a photo
he found of the 2 of us. She
said, like, look at what I found, this
photo of the 2 of you when one
of his space shuttle missions was scrubbed.
And I had gone down to
watch the launch, but, unfortunately,
the space shuttle mission was scrubbed. But the
(04:17):
plus side was that all of the astronauts
came out of quarantine and said we were
able to hang out together. It's like one
of my most treasured possessions. So he's definitely
a mentor I think about very often. Well,
I'm glad you decided to bring the mentor
in because I think a lot of folks
forget what put them where they are. And
it's always good to reflect on that and
put the honor where it is and where
(04:39):
it should be to those that have helped
others. That's right. Because I think that type
of giving mentality is actually something I've been
trying to use to to pay it forward.
I've read recently
what gets you up out of bed every
day, and it has something to do with
artificial intelligence. Could you tell me something about
why that exists? In in terms of why
(05:00):
artificial intelligence
exists, or why does it get me out
of bed? Why? Why? Exactly. You know,
Some people, it's about food or coffee or
something, but you're like, oh, artificial food. Been
thinking I guess, like, my whole entire career
has been about solving problems, solving problems that
I see around me, or maybe I should
(05:21):
say it's like resolving pain points.
I think so much about wisdom. I think
so much about what people have known. I
guess maybe when I was younger,
and I remember when I was learning physics,
physics was actually one of my favorite subjects
because, basically, we would adjust things that I
would be thinking about when I was younger.
Like, why is it that when you're on
a trade and you drop a ball, that
(05:42):
ball is not, like, far behind you? Why
is it, like, with you? Either things with
us or would just keep me up at
night. Maybe I was just a
total total nerd,
throwing me out. But I, you know, I
just think about the wisdom that people have
had for centuries.
And so you think about the big philosophers
and
how they were able
(06:03):
to do the work that they did with
very little resources around them, and how did
they know how to do things, and how
can we tap into that and build upon
it? Why is it that, like, as humans,
we seem to be making the same mistakes
over and over again.
And so
Yeah. So wait a minute now. So what
I hear you say is
(06:23):
you like puzzles. Yes. You like to figure
out things. That's right. So there's inquisitiveness.
Some of it is physics. I understand because
you wanna understand
why. Why does this do this? Why doesn't
it not do that? You pose different questions,
and then you try to figure out the
answer. But in the world of artificial intelligence,
(06:44):
you're expanding that concept. That's right. Because now
it is beyond your little circle of knowledge.
It is global knowledge on call. That's right.
It's global knowledge on call. It's also the
ability to build upon that knowledge. And I
think about the work that I've done in
the past. I spent a decade at McKinsey,
the consulting firm. And I remember what I
(07:05):
loved most about it besides the people, of
course, just in terms of the day to
day work was the fact that you would
build upon what other people had done in
similar situations.
And I just remember thinking like, wow. This
is saving so much time. This is turbocharging
the thinking.
And to be able to do that, it
(07:25):
just pushes you in a different dimension. And
what if you can rely on technology to
help you to do a lot of that
work? It democratizes it for many people. It
also allows you to make these leaps that
would have just been that much harder to
bring things together just that much more quickly
when it would have taken maybe days or
(07:46):
weeks to crunch through analyses.
For me, I get up in the beginning
of the day just thinking like, oh, you
know, what types of problems can we solve
using this type of technology?
And as we have gone from the thinking
machine, the idea that a mechanism
can produce results the human cannot
or at least in a way the human
(08:08):
cannot.
There's a couple things here. So we're we've
advanced beyond the binary yes, no, such a
simplistic model
to something so sophisticated.
Does it also produce AI philosophy? Is there
a philosophical
stance of just the AI itself?
Itself is based on the rules and parameters
(08:30):
that humans give it. That's where the topic
of ethics, the topic
of what inputs are going in is so
important. I mean, I'm thinking
a lot about how do you make sure
that what is being built is free from
bias, free from discrimination
when humans, unfortunately,
have those tendencies.
(08:50):
Mhmm. I think that's one of the biggest
questions to date. When you have this type
of technology that could democratize, it could also,
at the same time, make problems even more
persistent
and dangerous,
frankly. Or twist it. Yeah. Twist it and
make it even weaponized weaponizable AI. I mean,
I'm sure that exists.
People like to spend
(09:10):
energy on destruction
as much as creation.
Just for those that are just catching up
now, let's go look at a definition of
artificial intelligence. I'm surprised they start with the
theory.
It's a theory? Is is it a theory?
I thought it was an actual product. It
says the theory and development of computer systems
able to perform tasks that normally require
(09:32):
human intelligence. Mhmm. So facial recognition,
visual perception, speech recognition, decision making,
translation
on the spot.
There's a lot of productivity
bonuses to this. So where does this sit
for you? Let's talk about SugarWorks. Let's talk
about where you're parking your wagon in this
(09:52):
domain of artificial intelligence
and what does it do? In terms of
what I'm doing in artificial intelligence,
I am using AI to help and enable
organizations or companies
to capture tacit institutional knowledge. So if you
think about what makes a company tick, what
makes a company really distinctive,
(10:14):
it's, of course, like, about the people the
people who are there, but also the people
who have been there before, building upon that
knowledge. But if you think about how much
of that knowledge is captured,
maybe 15%,
20%
is documented.
The rest of it is in people's heads.
And so the whole notion of how do
you get that out
(10:35):
so that the whole organization can benefit is
something I'm incredibly
obsessed with because I think that that could
make organizations go faster. And not just that.
When we are in this phase now where
baby boomers are retiring in droves,
Attrition is at an all time high in
companies.
You also have, of course, remote and hybrid
(10:56):
work
making it very difficult for people to share
information. And then there's also the rise of
independent contractors.
That makes it just that much tougher to
share knowledge. What I'm trying to do is
to essentially create a way so that you
can capture this knowledge and then summarize it
and create outputs using AI. You know, I
(11:17):
understand I understand about the tacit and the
expressed knowledge, 2 different things.
But in the process of combining artificial intelligence
as a game changer for organization,
you're depending
on all users to be inquisitive
and to find answers
in a different way than what they're normally
(11:38):
ever did. Right? I mean, you're gonna change
behaviors. Behaviors
are changing already. I think that if that
if if there's, like of course, like everybody
says, there's one constant there is change. Right?
That it it is change and in terms
of how people do things. I think how
people are doing things now post pandemic,
if you just think about it in organizations,
it's just that much harder. Like, where do
(11:58):
I go to to find x, y, and
z? How do I find that? Are there
better tools out there for me to do
it? Or, you know, the people who are
most resourceful know that the quickest way is
to find the experts in an organization and
to try to get out that information. The
ones who are not as resourceful don't know.
Let's back this down to prehistoric
(12:19):
digital age of what that behavior used to
be. Mhmm. And in an organization, either you
had a formal mentorship,
apprenticeship
kind of thing where knowledge was built and
shared and
developed, and that was usually down a track
of a skill, right, or or something of
a specialized nature.
Now, we are in this century and now
(12:40):
we are not so much, in my view,
particularly,
building people with deep knowledge around one skill.
We're fostering a an ability to adapt, overcome,
and connect.
So the idea that
not long ago in an organization, you would
have 1 person or a few people that
were your go to for answers,
(13:01):
either they had institutional knowledge or experience
and they had all the data. You know,
if you're the new person and somebody said,
where do I oh, call Joe. Call Sally.
She she knows everything.
That tacit knowledge was, like, in a straw,
and now you've got tacit knowledge in an
idea that is more flat and more available.
(13:23):
We're trying to get it so that it's
not just about
knowing that it's Sally or Joe that you
have to go after. That maybe that there
are also these other folks who have this
knowledge, but they just never had a chance
to share it is also something that you
can tap into. That's essentially part of what
we're trying to do is to say that
there are subject matter experts throughout an organization.
(13:45):
Some of them are very well known to
the org. Actually, some others, their immediate teams
might know, but the rest of the organization
might not know that.
And
personality wise, not everybody wants the phone to
ring to ask them all kinds of questions.
Right? They're introverts, and they're like, hey. Go
figure it out yourself. I don't have time
for you. And I think we've all encountered
those folks who just know so much.
(14:09):
And and you're just like, wait a second.
What else do you know? And then I
think when you find those people, you're just
like, wait. Wait. I could
ask you basically 50 questions and be here
all day and just learn so much from
what is spewing out. Yes. And that's that's
that's, like, the the gold that we're trying
to mine for organizations.
SugarWorks in and of itself is
(14:31):
a platform.
Yes. It is. It's a software as a
service platform.
And it is one that I presume
would combine with whatever you're using. If you're
using Google or if you're using
Microsoft, you know, whatever that is, it ponies
up to whatever you've got because you've gotta
be able to touch all the documentation, all
(14:51):
the resources. So we're actually not touching the
resources per se. We're touching the people. So
we basically
get the folks to go in a video
meeting just like the one we're having right
now. We send in an AI notetaker, which
records, transcribes, summarizes the meeting. But if I'm
in this type of knowledge sharing session and
I'm referring to documents,
(15:13):
that is something that we do pull out
to say this document
is being referenced,
so you should be able to go to
that document. But we are integrating into these
solutions so that you can drive and get
to that document. Okay. So the deeper knowledge
and interconnectedness
with the historical perspective
(15:33):
is not the first thing you guys are
doing. Your first thing you're doing is conversations.
Conversations,
but elicited
conversations. It's not just about saying we're going
to be a fly on the wall in
every conversation. These are very structured.
Right. Right. Structured. Got it. Alright. So let's
talk about that. I guess it would be
mission dependent on the customer. I mean, who
(15:55):
you talk to and why.
Right? Because you gotta set all these things
up. Or does the customer that's their job.
They they figure all that. Yeah. So the
customers then they come to us to say
this is the type of information we're trying
to elicit, and then we help them create
those structured discussion guides. Like, what we find
is that a lot of people don't even
know what questions to ask so that you're
(16:17):
driving towards the insights. And it's almost like
an an art form to be able to
ask the big questions like, what would you
change if you can wave a magic wand,
walk me through the problems you typically see?
Who do you go to when x, y,
and z happens?
What does great look like? That's what we're
trying to bring out. So how do you
manufacture the questions?
(16:38):
Because you're not gonna know every industry. No.
We don't. We definitely don't know every industry.
But a lot of the times, what we
do find is that lots of these big
questions, like, walk me through what your role
entails. Walk me through what does success look
like in your organization or in your role.
That's something that could apply across the board.
So I would say maybe about 60 to
70%
(16:58):
of the questions are very much
standardized Okay. Across all different functions and roles.
And then you get specific to know, well,
I know that in this function, x, y,
and z happens. So let's just use that
to say, what happens in this step? What
happens in this step? Well, it sounds like
once you have that mechanism and foundation, it
would be easy to slide into augmented reality
(17:20):
because what you're saying is that you're in
a digital room. You're in a conversation. You're
1 on 1 or a few on a
few
and you're discussion. You're you're trying to elicit
this content from an individual,
but not all things are derived from a
conversation. Sometimes,
oh, if you had a augmented reality,
(17:40):
then the person could go through the mechanisms.
Because if you sat there and ask, how
do you do a to z?
They're not doing it. They're trying to remember
it. So if you could actually catch them
in the process, like NASA or anything like
that, that's got a process process,
like NASA or anything like that that's got
a process oriented nature, then you can walk
through the actual doing and capture more tasks.
(18:01):
Right. You can. And I think so much
of this is when are you trying to
capture this information. Then just to what you
said about NASA. So they have it it
this information. Let's just see what you said
about NASA. So they have Mhmm. At each
location, they have a chief knowledge officer,
and they have people who are trained
to drive at these types of insights to
to say, okay. This project, we've reached a
milestone. What happened? What was supposed to happen?
(18:24):
How can we learn from this going forward?
I think those types of learning organizations are
incredibly interesting. Most organizations are not like that,
though. And so how do you make an
organization a learning organization if they haven't been
in the first place? And I wanna make
a distinction there on the learning organization. Just
because you capture
doesn't mean you're learning anything. Yeah. Right? So
(18:46):
you can build
content. Oh, we got all oh, what are
you doing with that? Is anybody using that?
And I think that's where the integrated piece
for me comes in the AI world is
that now for all this stuff, all this
content, now you've got AI can help bring
you new access points to that content without
much labor,
and that's where the goodness is. Right? But
(19:08):
here again, if the behavior of the culture
is to never look back, it doesn't mean
anything.
It's a record. It's a record. And in
NASA, I understand. You gotta have records of
what happened, who did what, and all that
sort of thing. It's more of accountability
as much as it is showing innovation.
In most organizations, they're moving 90 miles an
hour.
(19:28):
Most of the folks, and this is a
general statement in all the organizations I've been
in, I would say 79.8%
of the people never look back. They never
look what was under the hood. They don't
even look what they did last year. Right.
No. It's true. It's almost like they finished
it, and so we're going to move on.
Yeah. We're moving on. It's like Yeah. Yeah.
Moving on. We're we're not going to do
a retrospective
to understand
(19:49):
why
something happened. Can we improve?
That bothers me because the framework, similar to
the United States Army, is you have knowledge
management people instead of all the people having
a knowledge management capacity.
Everybody in the organization
had this base understanding of behaviors and why
why you should care to share,
(20:11):
why you should care to do anything in
a knowledge handling and development realm.
That's everybody's job. The organizations that look at
this, like the leaders who realize
that this is going to get you, like,
to 10 x every single year, they are
the ones who really do believe in this.
Like, I've worked with those types of organizations.
(20:31):
You have other ones that don't think about
this, and then they just basically got to
what I'd said in the beginning. They happen
to be in growth industries,
so you see them on a rocket ship.
And then the moment that growth pot toes,
you see them starting to crumble because they
didn't have those foundations of what are we
doing right that we wanna continue? What are
the risks in our business
(20:52):
so that we can manage that? What can
we do so we can prepare for when
it's going to be famine instead of a
feast condition?
Now granted, when you're in an industry that's
riding the wave of, you know, like, technology,
birth, and and all those things, that's a
whole different level than just starting up a
popsicle stand at the corner
as an entrepreneur because
(21:14):
the difference is is that you've got a
communal
activity in something that's riding the wave. You've
got this like my you know, things just
feed off each other in a fast way,
versus an industry that's kind of plateaued for
the last 100 years, and they just keep
perking along.
The idea that tacit knowledge feeds innovation, do
(21:35):
you find that as a truism
in that most organizations,
they want innovation, that's why they want this?
Or what's their motivation to even get started?
Their motivation,
and this is what we're seeing now. They
don't realize
what they have it until it's about to
walk out the door. Yeah. And and it's
more about risk mitigation then than it is
about, hey. This is about innovation. This is
(21:57):
about, let's make sure that we're not going
to get into trouble because this information that
has been around for this long time that
we've taken for granted is about to go
out. So if you take Boeing, for example,
and what has been happening to them over
the last 5, 6 years, the issue is
that they lost a lot of senior
experienced
engineers in their midst during the pandemic. And
(22:19):
then now you have a lot of, you
know, lack of a better word, rookies who
are building planes and who just don't have
that experience of this is a problem that
typically happens, and this is what we need
to do.
If they were to go back in time
to say, what could we have done to
harness that knowledge before I walked out the
door, I'm sure they would pay quite large
(22:40):
sums to avoid the mistakes that they've made
since. So you're you're talking about mitigating risk,
but not everybody gets that knowledge is a
mitigator. That's right. I don't think that people
realize it unless
they happen to be in industries or just
like, wait. This is, like, where I feel
the pain. Like, if you talk to the
business leaders who are leading their teams, they
see it again and again. They see it,
(23:01):
like, whenever somebody
who is really critical leaves the team, you
know you feel that vacuum.
Right. And you're just like, how am I
going to fill this out? I know this
is going to set us back. If you
multiply that across an organization, then you start
seeing, like, you're going to start getting in
trouble. The question is more about who is
responsible then or trying to correct that within
(23:22):
an organization.
I think that's hard because whose neck is
going to be on the line, really?
Of course, it's going to be the leadership
like the c suite. The ones who are
really thinking about it, they want to do
something about it, but they just don't even
know what tools are out there in their
midst.
You come to a fine point that I
think most organizations
skip over is that you've got dedication at
(23:45):
the c suite level
that is around
either operations,
finances,
sales marketing. You know, you you got all
these folks
that are at certain levels, but there's no
definition of who owns the accountability
of knowledge. Mhmm. And if you don't have
a CKO or a cognition officer this was
a recent show that we came up with
(24:07):
a new job. Cognition officer. If you had
a cognition officer yes.
Because it's more than just knowledge. It's behaviors.
It's learning. It's sharing. It's it's all those
things that I have always felt fell into
HR. I mean, those are all HR
responsibilities,
making sure they're hiring people that practice the
right things the organization
(24:27):
is committed to.
But, you know, in this regard, it is
tough to sell a solution if there's nothing
to back it up in the organization
anyway. So how do you walk that fine
line? Well, that's why we are now
talking to companies when they're going through change.
And when they're going through change, they are
thinking about these things. Yeah. Yeah. And the
(24:47):
moment you go in, you're like, wait a
second. This is what you should do. And
then once you get in there, they start
saying, well, why don't we do this all
the time? Like, why don't you? Yeah. Good
question. Why don't you? And so maybe you
should think about the transformation at a deeper
level. So where's your sweet spot for a
targeted audience or targeted client? Is it a
big that's going through transformation? Are you looking
at smalls? You're an entrepreneur,
(25:09):
apparently, genetically.
So, I mean, really, I mean, you're right.
All organizations should be doing this, but not
all organizations
will ever, ever, ever do it. We're looking
at companies that are large enough where of
course, like, the larger the organization, the more
complex and where you just don't even know
where this information lies. But if you know
(25:31):
that in those industries, there's going to be
change, there's going to be workforce transitions because
there are now large numbers retiring. Think about
our government, for instance.
I think I heard a stat that the
Internal Revenue Service has estimated that in the
next 3 to 5 years, maybe about 40,
45 percent of people working at the IRS
are going to be retiring. That is an
(25:53):
incredibly high number if you think about it.
It is. And you think about all these
other industries. You look at telecom, utilities. You
look oil and gas. You look at insurance.
These are industries where that type of of
subject matter expertise is projected to walk out
the door. So that's what we're trying to
capture because we know that for the longest
time, companies haven't had to think about this,
(26:16):
but now they're going to have to. Well,
they think about it the wrong times or
the wrong ways. You know, the exit interview
is always the
minimal effort to do something, and it was
never I've never seen it actually pay much.
No. The wisdom and knowledge that is valuable
to an organization
is a variable that changes with time.
(26:37):
What's valuable 5 years ago may not even
be relevant now. As you compile
tacit knowledge warehouse
of beneficial items, you hope, for the organization
it serves, who's gonna start shoveling stuff out
the door organization it serves.
Who's gonna start shoveling stuff out the door
when that knowledge is no longer relevant? Right.
Well, I think this this means that there
(26:58):
needs to be continuous knowledge gathering
and and outputs
for organizations to think about what does that
mean. Also about being able to deliver information
at the moments when people need it, like
documents
upon documents, upon documents, that's not going to
be helpful for anyone.
But if you can
embed this information
(27:19):
into tools that people are using already, if
there's a way to then acknowledge like, oh,
this is something that you're looking for, why
don't we just do a search for you
of whether or not someone has encountered this
before? That is incredibly helpful. That is, I
think, the holy grail that a lot of
technology companies are thinking about, which is how
do we deliver this critical information to you
(27:41):
at the moment that you need it the
most. And as industry has always
seemed to steer human behavior,
what is the expectation
at the home, at the ranch?
How is this gonna change how we act
at home? If you look at what's been
happening over the last decade, couple of decades,
people are very interested to know where are
(28:01):
they from, who are they related to. So
that's why these genealogy companies are doing quite
well. And I remember also
during the pandemic, I had my parents go
on to this site called Storyworth where every
week, they would be fed a different question.
And so and they would have to write
their answer about something that happened in their
childhood, something so that you can buy and
(28:22):
sell, like, the story of their lives together.
And I think people are starting to realize
that stories or their personal lives are just
as important
in the professional workplace as well. Alright. So
I like what you're saying because it sounds
like
the strength and this is my words.
The strength of a society is built on
its stories
or its ability to connect.
(28:44):
So what you're doing with Sugarworks is building
a stronger societal element in an organization.
So as a Microsoft guy, we have Copilot
as our beneficial thing. And, so what I
decided, audience, was to ask
what is cool about Vanessa Liu?
(29:06):
What is Is it pronounced Liu? Liu. It
Liu. Liu?
Liu. So I've asked Copilot what is cool
about Vanessa Liu.
And you wanna know what the answer is?
Vanessa Liu has a fascinating
and diverse career that makes her stand
out. Here are some cool things about her.
Entrepreneurial
spirit, paragraph.
(29:27):
Tech and innovation, paragraph.
Media and strategy,
paragraph.
Leadership and mentorship,
paragraph.
Global perspective.
So I'm gonna read that one. Global perspective.
Vanessa's career has taken her around the world
from consulting at McKinsey and Company to working
in Amsterdam, London, and New York. Her ability
(29:48):
to pivot across different industries and roles while
maintaining a focus on innovation and impact is
truly
inspiring.
The cool thing with that, and I wanna
demonstrate Copilot,
is that that's what's cool about AI. Right?
It gives you and I just learned this.
Let me bear this. I attended a grant
making or grant software as a nonprofit always
(30:10):
looking for money,
a grant software using AI. They said, I
didn't know this, but
you can tell AI to be active in
a role, and then you give it a
situation. And it will give you answers based
on the role you said to act like.
I was I was like, wow. That's that's
something. Yeah. So in the instance, in this
(30:30):
example,
it said, hey, AI. You you are the
grant reviewer
for a large foundation.
Please review the following document and tell me,
you know, blah blah blah. And it did.
And it was like, I don't know how
valuable or valid the content was, but
it's a start.
It's an absolute starter
(30:52):
in our nonprofit. Right. It has become an
extra person
because
it gives you a different perspective. It may
not be 100 percent accurate, but at least
it's a start. It's a start. It's a
start so that because blank pieces of paper,
blank slates are very hard to work with.
Even if something is wrong and, actually, you
know, it's great to hear that Microsoft Copilot
(31:12):
is is so accurate probably because of the
fact that LinkedIn
is one
of is one of their companies. Right? There's
something to work with.
And I think that is what makes it
that much easier. And that and if I
also think about how we are taking the
approach of how do you get knowledge out,
well, if you ask an expert, hey. Could
you share what you know? Yeah. They don't
(31:34):
even know where to start. So let's just
make this easier for you. Or if we
yeah. That's a great comparison to the blank
paper because it's like,
where do you want? Wanna know? So you
gotta have that first lead in to help
build the rapport.
But I wanna example this because now,
if you've got internalized knowledge and you can
(31:54):
use AI to start building and answering questions
like this, hey, if we wanted to increase
our sales by 10%, what would we do
based on our internal content already? Or start
to that,
like, really having a I hate to say
advisor, but it's kind of
Oracle, your own business, in order to help
(32:15):
give you deeper understanding.
That is what people should be looking at
this as, that it is a way so
that you can get a boost. It's not
going to it should not replace the work
that you're doing. This should make you that
much more productive just like when the calculator
came out or when the computers
computers first became much more ubiquitous.
Mhmm. And there was just such a fear
(32:36):
that, wait a second. This means that we
don't have to work in the way that
we used to. And that that is something
that I hear again and again, so many
people being very worried. Like, oh, AI is
gonna take away our jobs, or is it
more AI is going to enable us to
do more things so that will free up
our time so that we could do more
value out of things. Things like I can
now spend time really building the rapport with
my team members,
or I can really just understand you have
(32:58):
all sides of this issue. If I think
about the legal profession, which is, of course,
one of the industries being most disrupted,
How do I make that better, and how
do I find a solution better so it's
not just about looking for
the comma in the right place? Right? There's
that type of, like, thinking time. What do
you do with that? I'm gonna summarize everything
(33:19):
that we've just talked about. So this is
a transformational
agent to advance
operational capacity
is what AI is.
And that organization can be anything to a
civic unit, to a girl scout troop, whatever.
I mean, it doesn't have to be formal.
It doesn't have to be for profit. Mhmm.
That's right. So where's your impact? You talk
(33:41):
a lot about impact. So what impact is
your design and target to do with SugarWorks?
So my desire is that this type of
information is going to enable companies to remain
competitive
so that they can continue to grow, so
that they continue to do the things that
they are doing to bring out new products,
bring out new services.
(34:02):
Really, where this where SugarBear came from is
the fact that I'm seeing a generation
of wisdom walking out the door. If you
look at the baby boomers who are now
leaving, and they have decades of experience. And
our society is one where
the moment people leave and are out of
the picture, it's almost like, oh, if so
and so was never around, that knowledge was
never around.
(34:23):
Mhmm. I want people to be able to
build off of ideas. I want people to
solve more problems.
And I feel like, especially in this day
and age where we have so many issues,
having that wisdom loop so that you can
glue generations together. You have that intergenerational
type of respect. That's what I'm thinking a
lot about.
(34:43):
All of that hinges on an organization that
believes knowledge is an asset. I've encountered other
organizations where they're just like, actually, we don't
want that knowledge anymore. We wanna get rid
of it. I'm like, oh, okay.
And you'll always have those outliers.
What is the hardest no you've gotten on
a sale to SugarWorks and why? I think
the hardest no has come from people not
(35:04):
realizing
that it's tacit knowledge that's going to be
most important. They just think like, well, if
I just take a recording of how people
do things on their screens, I'm getting the
same knowledge. I'm like, no.
That means that you don't really understand
the knowledge that's in your midst.
That's the toughest know where, philosophically,
we're thinking about fundamentally different things. Is there
(35:27):
a convincing of that, or you just say,
okay. Good luck. Basically, I just say, okay.
Let's let's regroup in a few months.
Let's touch base.
Let's see.
Maybe the maybe the leadership will change or
something will change, and then they'll be like,
what? Oh, yeah. We love that. Exactly. So
does it come down to leadership, or is
it the culture? Is it leadership that's the
(35:49):
hard yes, no, or the culture is like,
yeah. We're not done. I think, like, it
comes from leaders,
very convincing leaders.
Like, basically, just very forward thinking
can drive that cultural change. And so that's
why for us, we we talk to the
leaders at the top. Alright. Well, my friend,
everybody wants to know what you think knowledge
management is.
(36:10):
Oh.
So
the way that I see it is that
you are harnessing the wisdom within an organization,
and you're making it available to others and
having a system for doing that. That's sweetened
to the point, and it gets to the
form and function of why. Any last words
of Vanessa Wisdom to pass on to the
listeners?
I don't know if I have that much
(36:31):
wisdom, but
I
You're golden moment, tacit woman. Come on. Let's
go.
For me, you know, just asking the why,
always asking the why will get you to
some incredible
answers.
You know? I think 3 year olds have
it. They're 3 year olds. Like, they always
(36:52):
say, why?
So the why behavior it's funny you bring
that up. So the childlike
behavior
of being inquisitive and wanting to know and
not knowing anything. Right? You gotta start somewhere.
It's
like There is a behavioral switch that I
think happens in most humans that that gets
shut down. Right? That why questioning gets shut
(37:13):
down by people, environments,
communities,
and a dog that barks like crazy.
So this idea of the child
being
because not everybody makes it out of childhood
to adulthood still asking why. Right? Something is
switched in their mode of behavior.
This I like because you also want to
(37:34):
create
inquisitive people
to gain tacit knowledge, and I think one
of the benefits of producing tacit knowledge is
then people
say, oh, I didn't know that. Once they
start to see the value of the effort,
then it's like,
ah, okay. I get that. So that childlike
behavior has to be reignited.
(37:54):
So there should be a little summary test
that you've got devised that says, are you
a inquisitor?
Do you inquire? Do you have questions all
the time because you wanna know stuff? Or
are you just like the I'm good. I
know enough. I'm good. It it almost like
applies to our society nowadays. We are not
asking enough of why. Why do people think
a certain way? Why do they have ingrained
(38:17):
perceptions or or beliefs? If we were to
try to truly understand
instead of assuming, then I think that we'd
be in a much better place.
Well, it sounds like you've got a fix
for everything. No. I don't. I just have
questions for everything.
I think it's a zen thing. I forget
(38:38):
which philosophy that this is applicable to, but
the wisest person never has the answers, but
just a better question. That's true. You know?
That's what you're getting to. Thank you, Vanessa.
It was a pleasure to speak with you.
All the best with you and this endeavor
Richard. Thank you so much,
(38:58):
Edwin.
Thank you for joining this extraordinary journey, and
we hope the experiences gained add value to
you and yours.
See you next time at Because You Need
to Know. If you'd like to contact us,
(39:19):
please
email byndk@mioneerdashks.org,
or find us on LinkedIn.
There is an old adage, one that you
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Now take our nonprofit,
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that you're listening to right now takes a
(00:22):
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We hope that you obtain value from our
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(00:59):
Pioneer in all eight services welcomes you to
the next because you need to know. I'm
your host, Edwin k Morris. I serve as
president and founder of this organization, and we
are thrilled to offer this educational program. These
design conversations
bring you people's experiences
from all over the globe in the field
of knowledge management, nonprofit work, and innovation.
(01:29):
My name is Vanessa Dew. I live in
New York City.
I absolutely
love working in technology, data, and innovation. I've
worked over 25 years in this field.
And the thing I get asked a lot
is what makes someone successful?
The thing I have learned
is that growth in an industry
plus dumb luck
(01:50):
leads to success
more than any other factors combined.
Wait a minute. So part of your research
is defined by dumb luck.
That's what you're saying is the dividing rod
for success. Plus
growth of an industry.
It's true. It's so much of it isn't
about being in the right place at the
right time. If I look around me and
(02:10):
I think there have been books written about
this too. Right? I think Malcolm Gladwell
recently wrote about, oh, there's this whole slew
of these founders that were born at the
right time. You look at Bill Gates. You
look at Michael Dell. They were born in
this heyday where
computing was coming into the foray. So let's
talk about growth
of an industry. And then they happen to
(02:32):
have had the luck, like, the lucky breaks
that they had because there were many people
working at it so that they could succeed.
Of course, it's it's something I've seen again
and again. It's it's something that I've resigned
myself to accept because there are only so
many things you can't control.
And so I love talking about my mentors
because I've had the honor and privilege of
(02:53):
having some
who have been incredibly formatives and just transformational
for my personal growth and my career. I
think back to when I was 14,
and that was when I met the late
Space Shuttle commander, David Walker.
We went on a trip together as part
of a NASA student delegation
(03:14):
to what was formerly the USSR.
He was just an incredible
leader, and so he led 10 of us,
10 14 year old students,
who always then the USSR
as part of a diplomatic delegation.
You know? But what was so special was
that we kept a relationship afterwards, and fax
was one of the ways that you would
(03:34):
write one another. And I remember there was
this one time he saw me winning an
award or heard about the news, and he
faxed to my parents' fax machine to say,
I just wanna let you know I'm just
so proud of you. And it just touched
me so much. I mean, here's, like, a
a man who was, like, you know, busy
busy commanding base level missions saying, like, let
me just drop Vanessa a note.
That's amazing. It was amazing. He he sadly
(03:57):
passed in
2,001.
His widow Paige,
a few years ago sent me a photo
he found of the 2 of us. She
said, like, look at what I found, this
photo of the 2 of you when one
of his space shuttle missions was scrubbed.
And I had gone down to
watch the launch, but, unfortunately,
the space shuttle mission was scrubbed. But the
(04:17):
plus side was that all of the astronauts
came out of quarantine and said we were
able to hang out together. It's like one
of my most treasured possessions. So he's definitely
a mentor I think about very often. Well,
I'm glad you decided to bring the mentor
in because I think a lot of folks
forget what put them where they are. And
it's always good to reflect on that and
put the honor where it is and where
(04:39):
it should be to those that have helped
others. That's right. Because I think that type
of giving mentality is actually something I've been
trying to use to to pay it forward.
I've read recently
what gets you up out of bed every
day, and it has something to do with
artificial intelligence. Could you tell me something about
why that exists? In in terms of why
(05:00):
artificial intelligence
exists, or why does it get me out
of bed? Why? Why? Exactly. You know,
Some people, it's about food or coffee or
something, but you're like, oh, artificial food. Been
thinking I guess, like, my whole entire career
has been about solving problems, solving problems that
I see around me, or maybe I should
(05:21):
say it's like resolving pain points.
I think so much about wisdom. I think
so much about what people have known. I
guess maybe when I was younger,
and I remember when I was learning physics,
physics was actually one of my favorite subjects
because, basically, we would adjust things that I
would be thinking about when I was younger.
Like, why is it that when you're on
a trade and you drop a ball, that
(05:42):
ball is not, like, far behind you? Why
is it, like, with you? Either things with
us or would just keep me up at
night. Maybe I was just a
total total nerd,
throwing me out. But I, you know, I
just think about the wisdom that people have
had for centuries.
And so you think about the big philosophers
and
how they were able
(06:03):
to do the work that they did with
very little resources around them, and how did
they know how to do things, and how
can we tap into that and build upon
it? Why is it that, like, as humans,
we seem to be making the same mistakes
over and over again.
And so
Yeah. So wait a minute now. So what
I hear you say is
(06:23):
you like puzzles. Yes. You like to figure
out things. That's right. So there's inquisitiveness.
Some of it is physics. I understand because
you wanna understand
why. Why does this do this? Why doesn't
it not do that? You pose different questions,
and then you try to figure out the
answer. But in the world of artificial intelligence,
(06:44):
you're expanding that concept. That's right. Because now
it is beyond your little circle of knowledge.
It is global knowledge on call. That's right.
It's global knowledge on call. It's also the
ability to build upon that knowledge. And I
think about the work that I've done in
the past. I spent a decade at McKinsey,
the consulting firm. And I remember what I
(07:05):
loved most about it besides the people, of
course, just in terms of the day to
day work was the fact that you would
build upon what other people had done in
similar situations.
And I just remember thinking like, wow. This
is saving so much time. This is turbocharging
the thinking.
And to be able to do that, it
(07:25):
just pushes you in a different dimension. And
what if you can rely on technology to
help you to do a lot of that
work? It democratizes it for many people. It
also allows you to make these leaps that
would have just been that much harder to
bring things together just that much more quickly
when it would have taken maybe days or
(07:46):
weeks to crunch through analyses.
For me, I get up in the beginning
of the day just thinking like, oh, you
know, what types of problems can we solve
using this type of technology?
And as we have gone from the thinking
machine, the idea that a mechanism
can produce results the human cannot
or at least in a way the human
(08:08):
cannot.
There's a couple things here. So we're we've
advanced beyond the binary yes, no, such a
simplistic model
to something so sophisticated.
Does it also produce AI philosophy? Is there
a philosophical
stance of just the AI itself?
Itself is based on the rules and parameters
(08:30):
that humans give it. That's where the topic
of ethics, the topic
of what inputs are going in is so
important. I mean, I'm thinking
a lot about how do you make sure
that what is being built is free from
bias, free from discrimination
when humans, unfortunately,
have those tendencies.
(08:50):
Mhmm. I think that's one of the biggest
questions to date. When you have this type
of technology that could democratize, it could also,
at the same time, make problems even more
persistent
and dangerous,
frankly. Or twist it. Yeah. Twist it and
make it even weaponized weaponizable AI. I mean,
I'm sure that exists.
People like to spend
(09:10):
energy on destruction
as much as creation.
Just for those that are just catching up
now, let's go look at a definition of
artificial intelligence. I'm surprised they start with the
theory.
It's a theory? Is is it a theory?
I thought it was an actual product. It
says the theory and development of computer systems
able to perform tasks that normally require
(09:32):
human intelligence. Mhmm. So facial recognition,
visual perception, speech recognition, decision making,
translation
on the spot.
There's a lot of productivity
bonuses to this. So where does this sit
for you? Let's talk about SugarWorks. Let's talk
about where you're parking your wagon in this
(09:52):
domain of artificial intelligence
and what does it do? In terms of
what I'm doing in artificial intelligence,
I am using AI to help and enable
organizations or companies
to capture tacit institutional knowledge. So if you
think about what makes a company tick, what
makes a company really distinctive,
(10:14):
it's, of course, like, about the people the
people who are there, but also the people
who have been there before, building upon that
knowledge. But if you think about how much
of that knowledge is captured,
maybe 15%,
20%
is documented.
The rest of it is in people's heads.
And so the whole notion of how do
you get that out
(10:35):
so that the whole organization can benefit is
something I'm incredibly
obsessed with because I think that that could
make organizations go faster. And not just that.
When we are in this phase now where
baby boomers are retiring in droves,
Attrition is at an all time high in
companies.
You also have, of course, remote and hybrid
(10:56):
work
making it very difficult for people to share
information. And then there's also the rise of
independent contractors.
That makes it just that much tougher to
share knowledge. What I'm trying to do is
to essentially create a way so that you
can capture this knowledge and then summarize it
and create outputs using AI. You know, I
(11:17):
understand I understand about the tacit and the
expressed knowledge, 2 different things.
But in the process of combining artificial intelligence
as a game changer for organization,
you're depending
on all users to be inquisitive
and to find answers
in a different way than what they're normally
(11:38):
ever did. Right? I mean, you're gonna change
behaviors. Behaviors
are changing already. I think that if that
if if there's, like of course, like everybody
says, there's one constant there is change. Right?
That it it is change and in terms
of how people do things. I think how
people are doing things now post pandemic,
if you just think about it in organizations,
it's just that much harder. Like, where do
(11:58):
I go to to find x, y, and
z? How do I find that? Are there
better tools out there for me to do
it? Or, you know, the people who are
most resourceful know that the quickest way is
to find the experts in an organization and
to try to get out that information. The
ones who are not as resourceful don't know.
Let's back this down to prehistoric
(12:19):
digital age of what that behavior used to
be. Mhmm. And in an organization, either you
had a formal mentorship,
apprenticeship
kind of thing where knowledge was built and
shared and
developed, and that was usually down a track
of a skill, right, or or something of
a specialized nature.
Now, we are in this century and now
(12:40):
we are not so much, in my view,
particularly,
building people with deep knowledge around one skill.
We're fostering a an ability to adapt, overcome,
and connect.
So the idea that
not long ago in an organization, you would
have 1 person or a few people that
were your go to for answers,
(13:01):
either they had institutional knowledge or experience
and they had all the data. You know,
if you're the new person and somebody said,
where do I oh, call Joe. Call Sally.
She she knows everything.
That tacit knowledge was, like, in a straw,
and now you've got tacit knowledge in an
idea that is more flat and more available.
(13:23):
We're trying to get it so that it's
not just about
knowing that it's Sally or Joe that you
have to go after. That maybe that there
are also these other folks who have this
knowledge, but they just never had a chance
to share it is also something that you
can tap into. That's essentially part of what
we're trying to do is to say that
there are subject matter experts throughout an organization.
(13:45):
Some of them are very well known to
the org. Actually, some others, their immediate teams
might know, but the rest of the organization
might not know that.
And
personality wise, not everybody wants the phone to
ring to ask them all kinds of questions.
Right? They're introverts, and they're like, hey. Go
figure it out yourself. I don't have time
for you. And I think we've all encountered
those folks who just know so much.
(14:09):
And and you're just like, wait a second.
What else do you know? And then I
think when you find those people, you're just
like, wait. Wait. I could
ask you basically 50 questions and be here
all day and just learn so much from
what is spewing out. Yes. And that's that's
that's, like, the the gold that we're trying
to mine for organizations.
SugarWorks in and of itself is
(14:31):
a platform.
Yes. It is. It's a software as a
service platform.
And it is one that I presume
would combine with whatever you're using. If you're
using Google or if you're using
Microsoft, you know, whatever that is, it ponies
up to whatever you've got because you've gotta
be able to touch all the documentation, all
(14:51):
the resources. So we're actually not touching the
resources per se. We're touching the people. So
we basically
get the folks to go in a video
meeting just like the one we're having right
now. We send in an AI notetaker, which
records, transcribes, summarizes the meeting. But if I'm
in this type of knowledge sharing session and
I'm referring to documents,
(15:13):
that is something that we do pull out
to say this document
is being referenced,
so you should be able to go to
that document. But we are integrating into these
solutions so that you can drive and get
to that document. Okay. So the deeper knowledge
and interconnectedness
with the historical perspective
(15:33):
is not the first thing you guys are
doing. Your first thing you're doing is conversations.
Conversations,
but elicited
conversations. It's not just about saying we're going
to be a fly on the wall in
every conversation. These are very structured.
Right. Right. Structured. Got it. Alright. So let's
talk about that. I guess it would be
mission dependent on the customer. I mean, who
(15:55):
you talk to and why.
Right? Because you gotta set all these things
up. Or does the customer that's their job.
They they figure all that. Yeah. So the
customers then they come to us to say
this is the type of information we're trying
to elicit, and then we help them create
those structured discussion guides. Like, what we find
is that a lot of people don't even
know what questions to ask so that you're
(16:17):
driving towards the insights. And it's almost like
an an art form to be able to
ask the big questions like, what would you
change if you can wave a magic wand,
walk me through the problems you typically see?
Who do you go to when x, y,
and z happens?
What does great look like? That's what we're
trying to bring out. So how do you
manufacture the questions?
(16:38):
Because you're not gonna know every industry. No.
We don't. We definitely don't know every industry.
But a lot of the times, what we
do find is that lots of these big
questions, like, walk me through what your role
entails. Walk me through what does success look
like in your organization or in your role.
That's something that could apply across the board.
So I would say maybe about 60 to
70%
(16:58):
of the questions are very much
standardized Okay. Across all different functions and roles.
And then you get specific to know, well,
I know that in this function, x, y,
and z happens. So let's just use that
to say, what happens in this step? What
happens in this step? Well, it sounds like
once you have that mechanism and foundation, it
would be easy to slide into augmented reality
(17:20):
because what you're saying is that you're in
a digital room. You're in a conversation. You're
1 on 1 or a few on a
few
and you're discussion. You're you're trying to elicit
this content from an individual,
but not all things are derived from a
conversation. Sometimes,
oh, if you had a augmented reality,
(17:40):
then the person could go through the mechanisms.
Because if you sat there and ask, how
do you do a to z?
They're not doing it. They're trying to remember
it. So if you could actually catch them
in the process, like NASA or anything like
that, that's got a process process,
like NASA or anything like that that's got
a process oriented nature, then you can walk
through the actual doing and capture more tasks.
(18:01):
Right. You can. And I think so much
of this is when are you trying to
capture this information. Then just to what you
said about NASA. So they have it it
this information. Let's just see what you said
about NASA. So they have Mhmm. At each
location, they have a chief knowledge officer,
and they have people who are trained
to drive at these types of insights to
to say, okay. This project, we've reached a
milestone. What happened? What was supposed to happen?
(18:24):
How can we learn from this going forward?
I think those types of learning organizations are
incredibly interesting. Most organizations are not like that,
though. And so how do you make an
organization a learning organization if they haven't been
in the first place? And I wanna make
a distinction there on the learning organization. Just
because you capture
doesn't mean you're learning anything. Yeah. Right? So
(18:46):
you can build
content. Oh, we got all oh, what are
you doing with that? Is anybody using that?
And I think that's where the integrated piece
for me comes in the AI world is
that now for all this stuff, all this
content, now you've got AI can help bring
you new access points to that content without
much labor,
and that's where the goodness is. Right? But
(19:08):
here again, if the behavior of the culture
is to never look back, it doesn't mean
anything.
It's a record. It's a record. And in
NASA, I understand. You gotta have records of
what happened, who did what, and all that
sort of thing. It's more of accountability
as much as it is showing innovation.
In most organizations, they're moving 90 miles an
hour.
(19:28):
Most of the folks, and this is a
general statement in all the organizations I've been
in, I would say 79.8%
of the people never look back. They never
look what was under the hood. They don't
even look what they did last year. Right.
No. It's true. It's almost like they finished
it, and so we're going to move on.
Yeah. We're moving on. It's like Yeah. Yeah.
Moving on. We're we're not going to do
a retrospective
to understand
(19:49):
why
something happened. Can we improve?
That bothers me because the framework, similar to
the United States Army, is you have knowledge
management people instead of all the people having
a knowledge management capacity.
Everybody in the organization
had this base understanding of behaviors and why
why you should care to share,
(20:11):
why you should care to do anything in
a knowledge handling and development realm.
That's everybody's job. The organizations that look at
this, like the leaders who realize
that this is going to get you, like,
to 10 x every single year, they are
the ones who really do believe in this.
Like, I've worked with those types of organizations.
(20:31):
You have other ones that don't think about
this, and then they just basically got to
what I'd said in the beginning. They happen
to be in growth industries,
so you see them on a rocket ship.
And then the moment that growth pot toes,
you see them starting to crumble because they
didn't have those foundations of what are we
doing right that we wanna continue? What are
the risks in our business
(20:52):
so that we can manage that? What can
we do so we can prepare for when
it's going to be famine instead of a
feast condition?
Now granted, when you're in an industry that's
riding the wave of, you know, like, technology,
birth, and and all those things, that's a
whole different level than just starting up a
popsicle stand at the corner
as an entrepreneur because
(21:14):
the difference is is that you've got a
communal
activity in something that's riding the wave. You've
got this like my you know, things just
feed off each other in a fast way,
versus an industry that's kind of plateaued for
the last 100 years, and they just keep
perking along.
The idea that tacit knowledge feeds innovation, do
(21:35):
you find that as a truism
in that most organizations,
they want innovation, that's why they want this?
Or what's their motivation to even get started?
Their motivation,
and this is what we're seeing now. They
don't realize
what they have it until it's about to
walk out the door. Yeah. And and it's
more about risk mitigation then than it is
about, hey. This is about innovation. This is
(21:57):
about, let's make sure that we're not going
to get into trouble because this information that
has been around for this long time that
we've taken for granted is about to go
out. So if you take Boeing, for example,
and what has been happening to them over
the last 5, 6 years, the issue is
that they lost a lot of senior
experienced
engineers in their midst during the pandemic. And
(22:19):
then now you have a lot of, you
know, lack of a better word, rookies who
are building planes and who just don't have
that experience of this is a problem that
typically happens, and this is what we need
to do.
If they were to go back in time
to say, what could we have done to
harness that knowledge before I walked out the
door, I'm sure they would pay quite large
(22:40):
sums to avoid the mistakes that they've made
since. So you're you're talking about mitigating risk,
but not everybody gets that knowledge is a
mitigator. That's right. I don't think that people
realize it unless
they happen to be in industries or just
like, wait. This is, like, where I feel
the pain. Like, if you talk to the
business leaders who are leading their teams, they
see it again and again. They see it,
(23:01):
like, whenever somebody
who is really critical leaves the team, you
know you feel that vacuum.
Right. And you're just like, how am I
going to fill this out? I know this
is going to set us back. If you
multiply that across an organization, then you start
seeing, like, you're going to start getting in
trouble. The question is more about who is
responsible then or trying to correct that within
(23:22):
an organization.
I think that's hard because whose neck is
going to be on the line, really?
Of course, it's going to be the leadership
like the c suite. The ones who are
really thinking about it, they want to do
something about it, but they just don't even
know what tools are out there in their
midst.
You come to a fine point that I
think most organizations
skip over is that you've got dedication at
(23:45):
the c suite level
that is around
either operations,
finances,
sales marketing. You know, you you got all
these folks
that are at certain levels, but there's no
definition of who owns the accountability
of knowledge. Mhmm. And if you don't have
a CKO or a cognition officer this was
a recent show that we came up with
(24:07):
a new job. Cognition officer. If you had
a cognition officer yes.
Because it's more than just knowledge. It's behaviors.
It's learning. It's sharing. It's it's all those
things that I have always felt fell into
HR. I mean, those are all HR
responsibilities,
making sure they're hiring people that practice the
right things the organization
(24:27):
is committed to.
But, you know, in this regard, it is
tough to sell a solution if there's nothing
to back it up in the organization
anyway. So how do you walk that fine
line? Well, that's why we are now
talking to companies when they're going through change.
And when they're going through change, they are
thinking about these things. Yeah. Yeah. And the
(24:47):
moment you go in, you're like, wait a
second. This is what you should do. And
then once you get in there, they start
saying, well, why don't we do this all
the time? Like, why don't you? Yeah. Good
question. Why don't you? And so maybe you
should think about the transformation at a deeper
level. So where's your sweet spot for a
targeted audience or targeted client? Is it a
big that's going through transformation? Are you looking
at smalls? You're an entrepreneur,
(25:09):
apparently, genetically.
So, I mean, really, I mean, you're right.
All organizations should be doing this, but not
all organizations
will ever, ever, ever do it. We're looking
at companies that are large enough where of
course, like, the larger the organization, the more
complex and where you just don't even know
where this information lies. But if you know
(25:31):
that in those industries, there's going to be
change, there's going to be workforce transitions because
there are now large numbers retiring. Think about
our government, for instance.
I think I heard a stat that the
Internal Revenue Service has estimated that in the
next 3 to 5 years, maybe about 40,
45 percent of people working at the IRS
are going to be retiring. That is an
(25:53):
incredibly high number if you think about it.
It is. And you think about all these
other industries. You look at telecom, utilities. You
look oil and gas. You look at insurance.
These are industries where that type of of
subject matter expertise is projected to walk out
the door. So that's what we're trying to
capture because we know that for the longest
time, companies haven't had to think about this,
(26:16):
but now they're going to have to. Well,
they think about it the wrong times or
the wrong ways. You know, the exit interview
is always the
minimal effort to do something, and it was
never I've never seen it actually pay much.
No. The wisdom and knowledge that is valuable
to an organization
is a variable that changes with time.
(26:37):
What's valuable 5 years ago may not even
be relevant now. As you compile
tacit knowledge warehouse
of beneficial items, you hope, for the organization
it serves, who's gonna start shoveling stuff out
the door organization it serves.
Who's gonna start shoveling stuff out the door
when that knowledge is no longer relevant? Right.
Well, I think this this means that there
(26:58):
needs to be continuous knowledge gathering
and and outputs
for organizations to think about what does that
mean. Also about being able to deliver information
at the moments when people need it, like
documents
upon documents, upon documents, that's not going to
be helpful for anyone.
But if you can
embed this information
(27:19):
into tools that people are using already, if
there's a way to then acknowledge like, oh,
this is something that you're looking for, why
don't we just do a search for you
of whether or not someone has encountered this
before? That is incredibly helpful. That is, I
think, the holy grail that a lot of
technology companies are thinking about, which is how
do we deliver this critical information to you
(27:41):
at the moment that you need it the
most. And as industry has always
seemed to steer human behavior,
what is the expectation
at the home, at the ranch?
How is this gonna change how we act
at home? If you look at what's been
happening over the last decade, couple of decades,
people are very interested to know where are
(28:01):
they from, who are they related to. So
that's why these genealogy companies are doing quite
well. And I remember also
during the pandemic, I had my parents go
on to this site called Storyworth where every
week, they would be fed a different question.
And so and they would have to write
their answer about something that happened in their
childhood, something so that you can buy and
(28:22):
sell, like, the story of their lives together.
And I think people are starting to realize
that stories or their personal lives are just
as important
in the professional workplace as well. Alright. So
I like what you're saying because it sounds
like
the strength and this is my words.
The strength of a society is built on
its stories
or its ability to connect.
(28:44):
So what you're doing with Sugarworks is building
a stronger societal element in an organization.
So as a Microsoft guy, we have Copilot
as our beneficial thing. And, so what I
decided, audience, was to ask
what is cool about Vanessa Liu?
(29:06):
What is Is it pronounced Liu? Liu. It
Liu. Liu?
Liu. So I've asked Copilot what is cool
about Vanessa Liu.
And you wanna know what the answer is?
Vanessa Liu has a fascinating
and diverse career that makes her stand
out. Here are some cool things about her.
Entrepreneurial
spirit, paragraph.
(29:27):
Tech and innovation, paragraph.
Media and strategy,
paragraph.
Leadership and mentorship,
paragraph.
Global perspective.
So I'm gonna read that one. Global perspective.
Vanessa's career has taken her around the world
from consulting at McKinsey and Company to working
in Amsterdam, London, and New York. Her ability
(29:48):
to pivot across different industries and roles while
maintaining a focus on innovation and impact is
truly
inspiring.
The cool thing with that, and I wanna
demonstrate Copilot,
is that that's what's cool about AI. Right?
It gives you and I just learned this.
Let me bear this. I attended a grant
making or grant software as a nonprofit always
(30:10):
looking for money,
a grant software using AI. They said, I
didn't know this, but
you can tell AI to be active in
a role, and then you give it a
situation. And it will give you answers based
on the role you said to act like.
I was I was like, wow. That's that's
something. Yeah. So in the instance, in this
(30:30):
example,
it said, hey, AI. You you are the
grant reviewer
for a large foundation.
Please review the following document and tell me,
you know, blah blah blah. And it did.
And it was like, I don't know how
valuable or valid the content was, but
it's a start.
It's an absolute starter
(30:52):
in our nonprofit. Right. It has become an
extra person
because
it gives you a different perspective. It may
not be 100 percent accurate, but at least
it's a start. It's a start. It's a
start so that because blank pieces of paper,
blank slates are very hard to work with.
Even if something is wrong and, actually, you
know, it's great to hear that Microsoft Copilot
(31:12):
is is so accurate probably because of the
fact that LinkedIn
is one
of is one of their companies. Right? There's
something to work with.
And I think that is what makes it
that much easier. And that and if I
also think about how we are taking the
approach of how do you get knowledge out,
well, if you ask an expert, hey. Could
you share what you know? Yeah. They don't
(31:34):
even know where to start. So let's just
make this easier for you. Or if we
yeah. That's a great comparison to the blank
paper because it's like,
where do you want? Wanna know? So you
gotta have that first lead in to help
build the rapport.
But I wanna example this because now,
if you've got internalized knowledge and you can
(31:54):
use AI to start building and answering questions
like this, hey, if we wanted to increase
our sales by 10%, what would we do
based on our internal content already? Or start
to that,
like, really having a I hate to say
advisor, but it's kind of
Oracle, your own business, in order to help
(32:15):
give you deeper understanding.
That is what people should be looking at
this as, that it is a way so
that you can get a boost. It's not
going to it should not replace the work
that you're doing. This should make you that
much more productive just like when the calculator
came out or when the computers
computers first became much more ubiquitous.
Mhmm. And there was just such a fear
(32:36):
that, wait a second. This means that we
don't have to work in the way that
we used to. And that that is something
that I hear again and again, so many
people being very worried. Like, oh, AI is
gonna take away our jobs, or is it
more AI is going to enable us to
do more things so that will free up
our time so that we could do more
value out of things. Things like I can
now spend time really building the rapport with
my team members,
or I can really just understand you have
(32:58):
all sides of this issue. If I think
about the legal profession, which is, of course,
one of the industries being most disrupted,
How do I make that better, and how
do I find a solution better so it's
not just about looking for
the comma in the right place? Right? There's
that type of, like, thinking time. What do
you do with that? I'm gonna summarize everything
(33:19):
that we've just talked about. So this is
a transformational
agent to advance
operational capacity
is what AI is.
And that organization can be anything to a
civic unit, to a girl scout troop, whatever.
I mean, it doesn't have to be formal.
It doesn't have to be for profit. Mhmm.
That's right. So where's your impact? You talk
(33:41):
a lot about impact. So what impact is
your design and target to do with SugarWorks?
So my desire is that this type of
information is going to enable companies to remain
competitive
so that they can continue to grow, so
that they continue to do the things that
they are doing to bring out new products,
bring out new services.
(34:02):
Really, where this where SugarBear came from is
the fact that I'm seeing a generation
of wisdom walking out the door. If you
look at the baby boomers who are now
leaving, and they have decades of experience. And
our society is one where
the moment people leave and are out of
the picture, it's almost like, oh, if so
and so was never around, that knowledge was
never around.
(34:23):
Mhmm. I want people to be able to
build off of ideas. I want people to
solve more problems.
And I feel like, especially in this day
and age where we have so many issues,
having that wisdom loop so that you can
glue generations together. You have that intergenerational
type of respect. That's what I'm thinking a
lot about.
(34:43):
All of that hinges on an organization that
believes knowledge is an asset. I've encountered other
organizations where they're just like, actually, we don't
want that knowledge anymore. We wanna get rid
of it. I'm like, oh, okay.
And you'll always have those outliers.
What is the hardest no you've gotten on
a sale to SugarWorks and why? I think
the hardest no has come from people not
(35:04):
realizing
that it's tacit knowledge that's going to be
most important. They just think like, well, if
I just take a recording of how people
do things on their screens, I'm getting the
same knowledge. I'm like, no.
That means that you don't really understand
the knowledge that's in your midst.
That's the toughest know where, philosophically,
we're thinking about fundamentally different things. Is there
(35:27):
a convincing of that, or you just say,
okay. Good luck. Basically, I just say, okay.
Let's let's regroup in a few months.
Let's touch base.
Let's see.
Maybe the maybe the leadership will change or
something will change, and then they'll be like,
what? Oh, yeah. We love that. Exactly. So
does it come down to leadership, or is
it the culture? Is it leadership that's the
(35:49):
hard yes, no, or the culture is like,
yeah. We're not done. I think, like, it
comes from leaders,
very convincing leaders.
Like, basically, just very forward thinking
can drive that cultural change. And so that's
why for us, we we talk to the
leaders at the top. Alright. Well, my friend,
everybody wants to know what you think knowledge
management is.
(36:10):
Oh.
So
the way that I see it is that
you are harnessing the wisdom within an organization,
and you're making it available to others and
having a system for doing that. That's sweetened
to the point, and it gets to the
form and function of why. Any last words
of Vanessa Wisdom to pass on to the
listeners?
I don't know if I have that much
(36:31):
wisdom, but
I
You're golden moment, tacit woman. Come on. Let's
go.
For me, you know, just asking the why,
always asking the why will get you to
some incredible
answers.
You know? I think 3 year olds have
it. They're 3 year olds. Like, they always
(36:52):
say, why?
So the why behavior it's funny you bring
that up. So the childlike
behavior
of being inquisitive and wanting to know and
not knowing anything. Right? You gotta start somewhere.
It's
like There is a behavioral switch that I
think happens in most humans that that gets
shut down. Right? That why questioning gets shut
(37:13):
down by people, environments,
communities,
and a dog that barks like crazy.
So this idea of the child
being
because not everybody makes it out of childhood
to adulthood still asking why. Right? Something is
switched in their mode of behavior.
This I like because you also want to
(37:34):
create
inquisitive people
to gain tacit knowledge, and I think one
of the benefits of producing tacit knowledge is
then people
say, oh, I didn't know that. Once they
start to see the value of the effort,
then it's like,
ah, okay. I get that. So that childlike
behavior has to be reignited.
(37:54):
So there should be a little summary test
that you've got devised that says, are you
a inquisitor?
Do you inquire? Do you have questions all
the time because you wanna know stuff? Or
are you just like the I'm good. I
know enough. I'm good. It it almost like
applies to our society nowadays. We are not
asking enough of why. Why do people think
a certain way? Why do they have ingrained
(38:17):
perceptions or or beliefs? If we were to
try to truly understand
instead of assuming, then I think that we'd
be in a much better place.
Well, it sounds like you've got a fix
for everything. No. I don't. I just have
questions for everything.
I think it's a zen thing. I forget
(38:38):
which philosophy that this is applicable to, but
the wisest person never has the answers, but
just a better question. That's true. You know?
That's what you're getting to. Thank you, Vanessa.
It was a pleasure to speak with you.
All the best with you and this endeavor
Richard. Thank you so much,
(38:58):
Edwin.
Thank you for joining this extraordinary journey, and
we hope the experiences gained add value to
you and yours.
See you next time at Because You Need
to Know. If you'd like to contact us,
(39:19):
please
email byndk@mioneerdashks.org,
or find us on LinkedIn.
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