March 1, 2024 • 48 mins
Modern geospatial - not the bleeding edge of geospatial but modern geospatial - what is it?
Well my guest Will Cadell, the CEO of SparkGeo describes modern geospatial as the intersection of the cloud, smart space, open source data/standards, AI and smart devices - that's modern geospatial
And as you will hear during the discussion it's important to understand the difference between modernisation and innovation when we think about moving people from where they are now to where they want to be with regards to their geospatial capabilities.
You might be wondering - what does any of this have to do with me? I just want to make better things, I just want to help people use all this awesome geospatial stuff …
but you don’t get to do that without first understanding what “better” looks like for them - what is their version of awesome geo stuff … and that is why you should listen to this episode!
Connect with Will Cadell
Twitter https://twitter.com/geo_will
LinkedIn https://www.linkedin.com/in/willcadell/
SparkGeo https://sparkgeo.com/
https://www.strategicgeospatial.com/
This episode is sponsored by https://www.scribblemaps.com/
Recommended Listening
The Business of Web Maps
https://mapscaping.com/podcast/the-business-of-web-maps/
Modern GIS
https://mapscaping.com/podcast/what-is-modern-gis/
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:01):
Welcome to the Mapscaping podcast. My name is Daniel and this is a podcast for
the geospatial community.
Today on the podcast we're talking about modern geospatial. So note the word
modern, not the bleeding edge of geospatial, but modern geospatial.
What is it? Well, my guest Will Cadell, CEO of SparkGeo, describes modern geospatial
as the intersection of the cloud, smart space, open source data and standards,
(00:26):
AI and smart devices. That's modern geospatial.
And as you were here during the discussion, it's important to understand the
difference between modernization and innovation when we think about moving people
from where they are now to where they want to be with regards to their geospatial capabilities.
And you might be listening to this wondering, what does any of this have to
(00:46):
do with me? I just want to make better things.
I just want to help people use all this awesome geospatial stuff.
But you don't get to do that without first understanding what does better look
like for them? What is their version of awesome geospatial stuff?
And that is why you should listen to this podcast episode. If you enjoy this
episode and are interested in the topic of modern geospatial,
check out the conference called North 51.
(01:09):
I had the pleasure of attending this last year. It was fantastic.
And this year's conference theme is modern geospatial.
So it'd be well worth checking out if you're interested in that.
Before we get started today, I also want to...
My sponsor scribble maps augment your gis workflows
and bring gis to all levels of the organization
scribble maps so this is the marketing tag tagline
(01:29):
that i need to read out for you but i want to highlight a few things about this
augment not replace so scribble maps when i talk to them they completely understand
this is not a replacement for just desktop gis this is an augmentation of it
and i could see this being really powerful you know put together with with a
desktop GIS platform like QGIS, for example.
And the next bit in the tagline there, bring GIS to all levels of your organization.
(01:53):
This is really hard. This is a really hard problem to solve.
I'm currently working as a consultant for an organization, and this is one of
the challenges that I'm facing.
So people need access to the data, and I simply don't have the tools to give it to them.
I mean, I have some tools at my disposal, but they don't strike that right balance
of functionality and ease of use that Scribble Maps offers. Unfortunately.
(02:14):
I can't just click my fingers and move to Scribble Maps, but I think if you
are in a similar situation, check out Scribble Maps.
It might be the tool that you've been looking for.
So Scribble Maps offers collaborative editing, you know, that you can do business
intelligence annotation and they actually have a ton of functionality in there.
I'm not going to list them off now, but it would be worth checking out.
If you are interested, book a demo with them.
(02:36):
If you mention mapscaping, you'll get a discount. out. So I have had the CEO
of Scribble Maps on the podcast before.
The episode is called The Business of Web Maps and it's well worth listening
to. It'll change the way you think about web mapping as a business.
Jonathan, the CEO, is open, honest. It's a great conversation.
So thank you Scribble Maps for supporting the podcast.
You don't just make this episode possible, you make all of the episodes possible
(02:59):
and I really appreciate it.
Okay, let's move on and talk about Modern Geospatial with Will Cadell, CEO of Sparkgeo.
Hey Will, welcome to the podcast. Today we're going to talk about modern geospatial.
So this is something you've written a ton about in your Substack newsletter,
(03:20):
which I highly recommend to all the listeners.
But I think before we dive into that, let's have a bit of background.
So you are the founder, owner of SparkGeo.
Can you add something more to that brief, brief introduction? Sure.
SparkGeo has been around for, well, since 2010. So I guess almost 14 years.
Since before Before that, I was in government science. I did a little bit of municipal work.
(03:42):
And then I did some forestry work in Canada, came over to Canada from the UK.
You might be able to detect I have a silly accent.
I've been bathing in Tim Hortons for 20 years. And this is what it does to a Scottish accent.
It kind of flattens it out a bit. So I've been in Canada for 20 years.
I've run Spargeo for 14 of those.
(04:03):
Spent a bit of time in the forestry sector, the resource sector before that.
And yeah, since starting Spark Geo, we've been putting maps on the internet, if you like.
Cloud-centric geospatial software development.
I used to write a lot of code. I now think I am possibly the worst software
developer in the company.
So I end up talking about code now.
(04:25):
That's the background. We spent a lot of time interfacing with what I would
call innovative stroke, futuristic geospatial organizations and institutions and startups.
I count myself very lucky being able to think about the cutting edge of geospatial.
And how it is maybe a little bit different now from what it possibly once was
(04:49):
and possibly still is in different organizations.
So I think we're at a very exciting time. This is why I talk about this notion of modern geospatial.
And I think we have a lot of opportunities as a community, but we need to do
a few things in our own workflows and in our own thinking to realize those.
So I very much appreciate the opportunity to have a chat about this idea,
(05:15):
Daniel. Thank you very much.
Oh, no worries. I'm absolutely stoked to have you as a guest on the podcast.
Yeah. So before we get into that idea of what we need to do to take advantage
of these opportunities, let's start with a description of modern geospatial
definition, if you will. What does it mean to you? A definition?
I don't unfortunately have a very succinct sentence. I haven't thought through my value proposition.
(05:39):
I'm sorry. However, it's a series of observations that I think are important.
So firstly, the first observation I have, which is really, really obvious and
really, really simple, is that geospatial people excel at building geospatial
things for other geospatial people.
And the secondary observation is that there's a lot more other people than there are geospatial people.
(06:05):
So those two things combined tells you a little bit about the modern audience
of digital geography, shall we say.
I would argue that GIS people at large didn't invent the tools that we as a
population interface with on a day-to-day basis.
(06:25):
So I think the most popular geospatial tools on the internet are either weather,
they are navigation, or they are dialing up transportation.
And I think those three tools, so you can call them meteorology,
we can call them navigation, we could call it logistics to some extent, personal logistics.
Those three things dominate consumer geospatial, but I don't think any of them
(06:50):
were invented by the GIS sector at large.
So I'm really interested in how we can use modern tools, smart devices,
et cetera, et cetera, to enable more people, to get more people using digital geography.
I see that, and then I see this notion of complementary assets.
So those are assets which might support a secondary ecosystem. system.
(07:15):
So think about the cloud, think about smart devices I was just talking about,
think about AI, think about open source, think about smart space, commercial space.
All those things are independent of geospatial technology.
They operate in and of themselves. They are philosophies, they're workflows,
(07:35):
they're technologies that have grown independently and act as a kind of a complementary
springboard for us in the geospatial community to do more.
So we can leverage the cloud, we can leverage commercial space,
we can leverage smart devices, we can leverage all sorts of these things.
But the notion is, the key thing is that even five years ago,
(07:59):
some of those independent assets didn't really overlap with each other and now they all do.
So where all those things overlap together, we have this notion,
I think, of modern geospatial.
So I would argue that today we have a series of net new capabilities,
which lead to net new opportunities.
(08:22):
And I don't really think that the geospatial community at large sees the difference
in what we can do today with what we were doing five or even 10 years ago.
But I think there's a net new opportunity to do creative and new things within
(08:43):
our kind of community of practice, if you like.
So this combination of new potential or new people, this combination of new capabilities,
and you could argue that there is some notion of new demand in the finance space.
(09:03):
And I would argue that almost all the management and measurement techniques
involved in anything to do with climate change will involve some kind of geospatial,
some kind of geographic or remotely sensed data.
So there's going to be a demand for geospatial technology.
(09:27):
What that demand looks like, I have no idea. I don't know what the product for
climate looks like. so this is kind of what I would call it inchoate demand
it's like it's this notional demand that we think is going to be something but we don't know.
What the intrinsic products are going to look like. So if you think about those
things, we've got new people, we've got new capabilities, and we've got new demands.
(09:47):
I think that creates this new environment in which to do business.
And that's what I'm loosely and somewhat lazily calling modern geospatial.
So that's kind of how I'm packaging it. Does that make sense?
Yeah, it does. I got to say, you covered a lot of ground there.
But just let me recap for a second. So if we think about the intersection of the cloud, smart space.
(10:12):
Open source data and standards, AI, algorithms, and smart devices,
if we think about the Venn diagram of that and where they intersect,
you're putting a circle there and saying, well, this is modern geospatial in
the intersection of all of these things.
I wonder, could we also say this is mature geospatial?
Are these mature products or are we on the bleeding edge when we think about
(10:32):
modern geospatial? That's a great segue into a discussion about technology maturity in general.
Because each one of those complementary assets that I talked about,
each one of them has its own what I would call an innovation curve.
Now, that's not my word. That's the word that the innovation community would use.
(10:53):
An innovation curve describes this kind of S-curve. It's an S,
whereby a particular technology product
starts off being very experimental. And then it goes up into this and it's slow to evolve and it's hard.
And you have this piece at the bottom of the S-curve where adoption is pretty slow.
(11:14):
And then you have this kind of linear piece in the middle where adoption is linear.
And that's where you have this kind of notion of incremental innovation.
Things are getting faster, things are getting better.
And then at the top of the S-curve, it kind of flattens out again where where
the innovation has reached the peak.
So if we think about, there's a great example in the literature about ice hunting,
(11:39):
which is where people in Northeastern USA in the 1800s, there would be this
big ice hunting industry where people would carve ice and then they would ship
it to various different places to have,
so people in India could have their gin and tonics and they could cool things in hot countries.
So in effect, moving cold stuff from a cold country to a hot country to keep
(12:01):
things cold in the hot country, if you imagine that, by boat.
And there would be incremental innovation. They would figure out how to move
the ice faster, how to chip it out quicker.
And you can imagine that piece would be the middle piece of the S-curve.
And then suddenly the adoption flattens out because, you know what,
our thermal capabilities in those boats reached a maximum.
(12:23):
We could only move those boats so fast. We could only chip out the ice so quickly.
So the actual adoption flattened out and then something amazing happened people
invented refrigeration home refrigeration which entirely disrupted that industry
and it just went away so think about that you've got one S curve which is.
(12:43):
We can ship ice, and then we can ship it to a place. And then suddenly it's
disrupted by an entirely different S-curve, which is we can build refrigerators
and sell them to people in those hot countries, and then we don't have to move any ice whatsoever.
So if you think about those two things, it describes two processes which sit
on two innovation curves.
Now, when we think about geospatial, we could argue a few things about innovation curves.
(13:08):
You could say desktop GIS is one innovation curve. You could argue web maps is the secondary one.
You could also argue that augmented reality might be a third one.
And each of these kind of hops to the other one.
However, you could also take apart those innovation curves and say,
well, desktop GIS is kind of evolving into web GIS in terms of these kind of
(13:32):
hybrid systems. ArcPro will be one.
QGIS has been hybrid for a while too. So if you think about that,
And this notion of the web is dependent upon the complementary asset that is
the internet, and one would argue these days the cloud.
So what we're trying to do here by talking about modern geospatial is challenging
(13:54):
our community to think about what are those assets that are available in our purview.
It could be the immediate purview, it could be a future purview.
It could also be looking a little bit back in time. I'll get to that in a second.
But what are those assets that are available that allow us to do net new things
and allow us to advance and answer better questions and inject more value into the broader community?
(14:21):
The interesting thing about those S-curves, too...
Is that different organizations feel comfortable in different places on that S-curve.
So if you have an enterprise organization, they may be less comfortable being
right on the cutting edge.
They want to make sure that things are just right now.
(14:42):
And that is a fairly safe bet. Yeah, it's a bit of technical risk,
but not very much technical risk.
It's more kind of business process oriented. oriented. Whereas startups and
more innovative companies are much more willing to take bets on what you'd call technical risk.
Yeah, they can figure out the business process piece, but they're very agile.
(15:03):
So business processes aren't so much of a burden. Whereas in a big enterprise
organization, the business process, the human piece, can be quite a burden.
So figuring out where different organizations sit within the context of an S-curve
is really interesting because that allows you to determine where that organization
is most willing to invest its time and what makes most sense from a technology
(15:27):
advancement perspective.
Does that help answer the question? Yeah, it does. I just want to highlight
that idea that innovation S-curves are not necessarily the same as an organizational S-curve.
At least that that's one of the many things that I got out of you.
And I think that that's really, really interesting because just because our
innovation curve looks like this, it doesn't mean that our organization,
(15:50):
those people that we're trying to move forward, that we're trying to help,
that we're seeking to serve,
that they are necessarily moving at the same rate as innovation.
I think adoption and innovation are quite different here.
That's the bit I'd like to sort of move on to now is knowing that,
how do we identify where people are, where an organization is on the S-curve,
and then how do we move them
(16:10):
along the S-curve? Yeah, yeah. Let me illustrate this with an example.
So Spark Geo, my organization, largely I made the assessment that we need to
do some of this spatial finance work.
The spatial finance is going to be really important. And a lot of it's going
to happen in the UK because it's going to be insurance-based first,
(16:32):
and then it's going to move up the value chain into different financial organizations.
So we made this assessment, And we made this rudimentary assumption,
and I'll come back to that.
Rudimentary assumption that we would be doing cloud-native, you know,
this and that. We'd be distributing data. We've got to do some analytics.
We've got to measure. The core observation and insight is that landscape change
(16:56):
is going to be important in the measurement of climate-related activities for
this notional spatial finance business.
I.e., if you measure landscape changes, you can figure out if there are more or less trees.
You can figure out if there's an increased amount of carbon in a particular place.
You can figure out if there's an increased flood risk in a particular place
(17:19):
based on landscape changes, if you like.
And you can use remote sensing to determine landscape changes amongst other
technologies, which allows you to create analytics.
So that was our assertion, our assumption. We go to the UK, start a business,
and we start talking to people.
And this makes us sound like we're utter fools, and we're not.
(17:43):
We did put a lot of research into this. But the first thing we discover is that
most of the financial sector isn't actually on the cloud, which when you're
thinking about cloud-native activities.
Is a bit of a barrier. We kind of fell at the first hurdle.
And I make this joke, I tell my kids not to assume anything because it makes an ass out of you and me.
(18:07):
And we definitely made an assumption.
And we've just basically got to this notion. And it's an interesting observation.
Daniel, because it talks exactly to the point you're talking to,
which is, where are organizations innovating?
Where do they feel comfortable?
So we discovered that a lot of the organizations that we were working with weren't
(18:30):
necessarily on the cloud.
So in terms of that S-curve, we had some work to do. We've got some modernization work to do.
We've got to encourage organizations to feel that the cloud is a safe and useful
place to do business before we get to do all this kind of cloud-native stuff.
Or maybe we provide a managed service and give these organizations an easy entry point.
(18:55):
So it's not as if it was a brick wall by any means.
It was just like, oh, this is interesting. We didn't think this would be the situation.
But it is. So we'll manage for it. And that's how small agile businesses can
operate. But it's an interesting note because you get to this point where,
yeah, we're a small, agile, innovative company and that's cool.
(19:20):
But sometimes we're helping larger organizations with this notion of modernization,
which might be a little bit different from innovation.
It might be innovative for the large organization, but if you were to reflect
back from the heady heights of a Silicon Valley startup, they might not view
(19:41):
that activity as quite so innovative.
They would view it as the default way of doing technology business,
which is just a really interesting...
For me, it was a really interesting object lesson in expectation and in this
notion of S-curves and figuring out that the S-curve doesn't just describe time.
(20:04):
It describes a willingness to innovate, and it describes almost exactly the
size of different organizations and where they are in the application of more
advanced technologies.
So it was a really interesting object lesson in S-curves in practice, I feel like.
So yeah like honestly that
(20:26):
that is that is really interesting so if i'm understanding you
correctly the assumption here was oh these people are ready to innovate when
in fact they needed to modernize first and you showed up with an innovation
plan or an innovation strategy when what was needed was modernization yeah maybe
the modernization could have been just lift and shift to the cloud do the exact same things just.
(20:48):
In a scalable environment. Maybe that was a form of modernization.
But we come back to this idea of S-curves and identifying where people are on them.
And so let's assume now that we understand where an organization is along the
S-curve. And in this example that you've just given us, they were ready to modernize.
What are the prerequisites for modernization?
I think it's a willingness to move forward and a comfort around the particular technology.
(21:16):
So So in the case of the cloud, it's been around for, I don't know, what, 15 years?
At least as long as Spark Geo. We've literally never owned a server.
So cloud technology has been around for at least that long.
I'm sure someone will correct us and tell us exactly how long it has.
But I think we can say for sure over 15 years.
(21:36):
And now we're getting to a place where some large organizations,
not just in the finance sector, but also across here in Canada,
have said, said, you know what, we feel more comfortable with this.
We can start moving this direction.
And for me, that's great.
It's like music to my ears. But also, it's a really interesting note on when
(21:57):
it makes sense for a certain company to do a certain thing.
And it might not necessarily even be cost-driven.
It might be driven by needs within the organization.
It might be driven by experiential needs. It might be driven by all sorts of different things.
Or it might just be the fact that their employees are giving them such a hard
(22:17):
time about not doing something that they've had to do something.
Or it might be that the incumbent technology provider has provided this opportunity,
which has subsequently started to make sense for the organization.
So there's many different reasons why certain companies adopt certain technologies.
But it It doesn't always make a ton of sense.
(22:40):
Sometimes there's externalities that drive that. But number one,
I would say, is willingness.
And within that willingness, there is definitely a piece of, what I would say,
the management of career risk of individuals in the middle management who actually
might be the ones actually making the decisions, actually doing the work and
(23:03):
actually taking the risk.
As an executive, it's easy for me to wave my hands and say innovation is great
and collaboration is wonderful.
But in the end, when the rubber hits the road in that middle management,
that's where people are taking a risk on a new thing.
So as a technology provider, I have to be very kind of empathic towards those
(23:28):
individuals who are taking a risk within their organization.
They were doing a process, a value creation process in a certain way.
And now they want to do it in a different way, which tells me that there's a
piece of risk in there and they're willing to manage it and they're willing
to let us help them with that process.
(23:50):
I mean, there's a lot of trust in that relationship. So we have to be quite careful with that too.
So you talked a lot about risk just then and this sort of gets back to one of
my questions right at the start was, could we change modern geospatial to mature geospatial?
All of these elements that we named right at the start, the cloud,
smart space, open source data, standards, AI algorithms, smart devices.
(24:12):
These are relatively mature, at least in my mind. Not to say they're stagnated,
but they've been around for a while. They're well understood.
And I think this is one of the ways of managing risk for organizations.
Not showing up with something brand new, showing up with something that is mature,
something that is modern.
And I think too that larger organizations, and please correct me on this,
(24:34):
I think they They are probably more risk adverse than they are price sensitive.
I totally agree with that statement. I just think the word mature makes it sound
like it's old. But, you know, whatever.
Different people see different words in different ways. I think we're getting at the same idea.
It comes down to nomenclature and the understanding of different things.
(24:56):
The key idea here is finding a way to raise expectations of broader organizations
by illustrating the possible through exemplar applications.
So that's what I say to my team is that we need to provide excellence so the
(25:19):
broader community understands what is possible when we think about modern geospatial,
when we think about applying the cloud,
when we think about all those sensors floating around in low Earth orbit,
all these things that are now possible that weren't before.
When we think about 8 billion GPS-enabled smart devices on the population of
(25:44):
our planet, that wasn't possible a decade ago.
Music.
(26:06):
And just raising expectations and encouraging the geospatial community not to
do the minimum, but to do the possible.
That's where I have been trying to encourage my team to go.
But that's also within the context of, this is the exemplar,
but we can move you towards that, because we all know that life is a spectrum.
(26:29):
You're not just there. You don't just get there by paying enough money.
You have to move your organization incrementally towards this notional sort
of exemplar situation, which means that it's a vision, not a goal,
because unfortunately, that exemplar is always going to get further away.
(26:52):
You know, it's always going to get, there's always going to be something new happening.
And that's good. I mean, that will allow us one day to, you know,
to fly to Mars and all the rest of it.
But as we move up or move forward, side note, it kind of bugs me when people
say move forward because I'm never sure what direction forward is.
But nevertheless, I'll take a step back.
(27:13):
As we advance, again, forward, direction, I don't know.
As we make our technology better, our expectation of technology should also change.
So we need to make sure that as enterprises, they don't get left behind,
that they're pushed forward, that there is a need, a desire,
an expectation that technology can move at an appropriate pace.
(27:37):
I think injecting that higher level of expectation into the technology stacks
of large organizations is important. important.
And some are natively, they have native expectations, i.e.
They have high expectations built into their genetics, but some really don't.
And those are the ones that we really need to empower, I think,
(27:59):
with some good thinking.
And just a second, I want to ask a question about making promises that we can
keep, because I think when you show up with these grand ideas,
you also need to make a promise that you can keep.
And I think broken promises are part of the reasons why organizations less
willing to you know take on this risk and to change but
we'll leave that just for a second do you see the gap between
(28:20):
what we could consider modern and innovative do
you see that shortening with time so you've owned or operated a spark geo for
what do you say 10 years now do you have you seen like a change in that gap
or has it remained relatively constant that gap that gap definitely fluctuates
i would hazard that so yeah spark Spark Geo has been around for 14 years, my gosh.
(28:43):
I would hazard that by saying that most of the work we did in the first few
years of Spark Geo was very much in the tech sector.
So we didn't do a large amount of what I would call.
Enterprise-oriented geospatial activity at that point.
Except a couple of notable exceptions around Google Maps implementations,
like ATM finders and stuff, and such like that.
(29:05):
So it was overly user-centric, slightly innovative for the time kind of activity.
But we weren't rebuilding major geospatial systems inside enterprise.
So I can't really comment on what it was like when we first started out.
But I would say that I think these complementary assets have accelerated in
(29:27):
their own domains significantly within the last five years. And we look at cloud technology.
It's got so much wildly more capable.
It seems very few organizations think about doing on-prem work,
except within the context of higher security needs.
There are some notable exceptions. exceptions 37 signals for
(29:48):
instance are you know they're very vocal about building systems
which are not not cloud-based these days which is
fine i mean it's good to have that argument being well articulated by that team
but i would say that cloud technology for geospatial as a like a big large data
play which is what geospatial really is is a massive enabler and it has enabled in In particular,
(30:13):
the commercial space sector, the EO sector.
So smart space enabling EO, the cloud enabling EO through storage,
AI and algorithms enabling EO through the pipeline delivery of algorithms through
the cloud to create analytics. That's a workflow.
I mean, then publishing those analytics with an open standard,
(30:35):
so it's easily consumable by other organizations to collide different data with it.
All that stuff is within this kind of Venn diagram, and all those things are
growing and evolving independently of each other,
each of those things independently making this concept of modern geospatial
more functional every day.
(30:57):
So thinking about how all those
things join together, your notes on making promises is absolutely spot on.
I think Earth Observation in the early 2000s made a lot of promises which were
not kept. And I'm not even sure those promises were made by the Earth observation sector.
(31:18):
I think they were kind of sort of made by Hollywood and the Earth observation
people were left kind of holding very hard expectation of like video from space of anywhere at any time.
Which is so far from the reality, it's almost comedic.
But I think it's still a really important concept because I think a lot of those promises can be kept.
(31:45):
They're just really hard to manage for. Does that make sense?
Yeah, it really does make sense. The reason I want to mention it is because
I think it's really important.
If you're going to show up to an organization and say, hey, we're with you on this journey.
My guess is an organization being risk adverse, They want you to be there also
next year and the year after that.
And they don't want to work with multiple different partners,
(32:08):
a new partner every month. That's not what they're into.
They want to sign a contract and say, great, you're going to be here for the
next five years. And in that time, we're going to move from here to there.
And I think that if you can make that promise and actually fulfill it and keep
the promise, I think you're really going to make some big changes happen.
Happen, not just in geospatial, of course, in terms of modern geospatial,
(32:29):
but also the flow-on effects of that are going to be humongous.
Make those longer-term promises and keep them.
Yeah, and I think that's credible these days. I think that's very possible.
I see a number of organizations on the market who are helping larger enterprise
organizations kind of manage for innovation and manage for advancement.
(32:52):
And what we've been most challenged with in Spark Geo recently hasn't been the
deployment of geospatial code or anything like that.
It's learning how to help organizations change, which is super business-y.
And you see all this stuff on the internet about change management and transformation,
(33:13):
this and all the rest of it.
But in reality, having a level of empathy around helping organizations and ultimately
people, because it's people that are making decisions and it's people that are
having having to do a new thing.
And it's middle management who ultimately have to lead.
Helping those individuals win is literally the purpose of our organization's
(33:38):
existence now, which is so interesting.
So yeah, we write code. And yeah, we do very interesting like cloud deployments.
And we talk to interesting geospatial companies all the time.
But ultimately, our job is to help organizations win through geospatial.
And winning sounds so binary.
(33:58):
Winning has got many, many different connotations. And I'm not winning,
and I'm by no means a zero-sum game guy.
I just want an organization to succeed through the use of geospatial technology.
And in many ways, this notion of winning is confusing because I think you could
also win in collaboration.
You don't have to win on your own. I said it in a video we made years ago,
(34:22):
but I think those organizations that are willing to team up and are willing
to collaborate will necessarily out-compete anyone who's not because it's very hard to do,
any of this kind of stuff on your own. It's much, much easier when you have
a team, when you collaborate, when you collaborate with different agile organizations.
(34:43):
Almost everything gets easier when you have teams.
Not necessarily big teams, but just teams of different people and teams of different
organizations partnering because you get this diversity of thought.
So there's a whole bunch of different interesting elements in there to unpack.
Yeah, there sure is. I want to stay with this idea of winning just for a second
thing because I think it's important to sort of emphasize that a win for an
(35:06):
organization is one thing, but throughout the different levels in that organization
and right down to individuals,
they all need to win too in some way, shape or form.
I think this is not just important for people starting businesses in the geospatial
world, but I think it's really important for practitioners as well.
You get to do interesting work if you make it a win for somebody else.
And I think for me anyway, this is a really hard lesson to learn.
(35:30):
I've tried to drag organizations and at
the end of the day people kicking and screaming into the past and
you know like from the deep deep past into
the more the more recent past and it's been tough because it hasn't been an
immediate win for them and it was a complete mistake on my behalf a total fail
but my learning from that was like well what would be a win for this person
(35:52):
what would be a win at that level of this organization what would be a win for
the organization as a whole those are completely different things,
but they need to be packaged together into whatever it is that you're promoting, selling.
Trying to do. Yeah, it's so interesting. I remember my second job,
I worked in Perth and Kinross Council, this is in Scotland, as their corporate
(36:14):
address gazetteer engineer.
And so there was this big movement in the UK around normalizing addresses,
which sounds like the most stupid thing.
But in reality, in a city council like Perth and Kinross Council,
there there would be about four or five different address databases.
So there'd be a health one, there'd be a tax one, there'd be an education one,
(36:36):
blah, blah, blah. And the idea was, let's squidge it all into one.
So there would be this single view of addresses in one city council,
and then you could multiply that up across all the councils,
so there'd be this one view of addresses in the UK.
It's a great idea. BS 766, it's ingrained into my existence. distance.
(36:58):
And so me and my boss, Ewan Walker, we would get all these addresses and we'd
have a piece of software and we would squidge them all together.
Which is the right address? That's the right address.
A lot of it was automated, but it was surprisingly manual, as you can imagine.
Anyway, we ended up having to go to this point in our project where we would
be talking to all the users of the address data.
(37:20):
And we would be like, okay, so we've got this new address database.
It's going to be amazing. It's way more accurate. It's great.
How do you use addresses is in your day-to-day business. So it's like classic
business process modeling.
And what I came to realize, and I can't remember if it was observation from
you or myself, but the point is we realized that how someone described their
(37:43):
job, what their job title was,
and what their boss thought they did were three entirely different processes,
which was really interesting to figure out.
And I think about that in terms of what you're just saying around.
Deploying new technologies and change management. So actually finding out what
(38:03):
somebody does, like what buttons do you press to do this thing?
And what boxes do you click to make this thing happen? And then asking them
to describe what they do.
And like, it's so interesting to find out, oh, actually, you don't do that.
You actually circumvent that entire process by doing this other thing instead.
(38:24):
And if I give you something that's going to be slower more than this other thing
that you've figured out yourself through whatever purpose, then you're going
to be upset and it's not going to work.
Or if I give you this new process, which for some reason doesn't do this other
thing which you like to do, then you're not going to do it.
So it's all this stuff, which is really interesting.
(38:47):
So finding out how you can help an organization win by actually digging right
into the nuts and bolts of what a company does, And what individuals do on a
day-to-day basis is so important.
But boy, at scale, that's incredibly hard to do.
It's a very, very, very kind of manual consulting thing just to sit around and
(39:10):
actually watch somebody do something and then compare that thing that you're
watching them do to how they describe it.
It's such an interesting process to go through it.
I mean, I say this a lot, but almost every technology problem is actually a
human problem in disguise.
So it's like, how do you solve this individual's problem, make their life easier,
(39:34):
make something go faster?
And you do it through, in air quotes, the guise of technology.
And I think that's such an interesting thing. So when you start thinking about
modern geospatial, the cloud has such an opportunity to provide technology at
a much faster pace. pace.
(39:54):
Smart devices have this opportunity for you to do things in the field more effectively
and with much better user interfaces than you ever had before.
AI acts as your co-pilot. I mean, AI allows you to make better decisions faster.
And then smart space allows us to look in places that we can never look before.
(40:15):
So if we care about monitoring landscape changes, then we can do that.
We can do that not just for one house, but a portfolio of mortgages.
Suddenly, that scale becomes possible because you've got all this other stuff.
All this stuff that you kind of had to just assume was okay,
now you can actually check because you can see all the mortgages for our bank
(40:38):
across North America or all the mortgages in Florida.
And like, how much flood risk do we actually have? I'm not sure.
Wouldn't it be nice to know?
Or do you not want to know? I mean, those are really interesting human questions.
And in the end, it is a human question because we can choose to know this information
or we can choose to not know.
Another thing I often say to my team is like, there's not many industries that
(41:02):
are willing to pay for bad news. So think about that.
How often is landscape change data giving you good news?
So think about those two things and then think about how to describe what it
is that we're doing in the most effective manner.
And there's a lot of nuance in there, but it is definitely what's ruminating.
(41:26):
So I just want to share a little story about that, not the idea that people
don't want to pay for bad news.
I talked to a company a while back. They had this interesting idea.
They could look for water leaks from space.
Great idea, right? There's been ages developing the technology,
and then they would show up to a couple of sort of leaps in the process,
which led to them, this being a success.
(41:48):
One of them was the observation that companies were more willing to pay for
if the cost was OPEX as opposed to CAPEX.
Another one was that if they showed people what they could do,
that was a big leap forward.
That meant that they got further in the sales process each time because they
said, I'm not going to tell you, I'm going to show you what I can do.
One of the last ones was not to
(42:08):
overwhelm people because let's say they went to
the i don't know a utilities company in copenhagen said
look here are all of your leaks you know here are all of your problems expose
the lot for them and you would think oh great now i can go and fix them but
it wasn't like that it was overwhelming and people didn't want to know where
they all were they just wanted to know whether ones they should be fixing they
(42:29):
wanted someone to sort of break down that problem into bite-sized chunks.
That's what they did. This was another leap forward for them as a company,
was understanding that people need it.
Don't create another problem for them. Don't overwhelm them.
Give it to them in small chunks and things they can solve and,
you know, win. Yeah. Give me my top 10 leagues. Yeah. Give me my next top 10. Yeah. It's good. Yeah.
(42:55):
Like we make it a win for them, right? It wasn't a win going,
Oh, this is going to take us 58 years to figure all this stuff out.
A win was I can do something today.
Yeah. I don't want to know why I'm not an Olympic athlete.
I just want to know why I could be a little bit better than I am tomorrow. Yeah. It makes sense.
(43:17):
If you give me a list of all my failings i won't even
bother getting off the couch but if you just tell me a little thing
i can do then maybe i will yeah yeah it's funny yeah yeah makes a lot of sense
i want to own around this off do you have any predictions for next year for
2024 predictions that's unfair you know what i think i think we're going to
(43:37):
see a lot of willingness to modernize.
Last year was a bit of a kick in the pants for the technology sector, I would say.
But I feel that there'll be a little bit more capital flowing towards efficiency.
I think supply chain concerns are going to go through the roof again.
(43:57):
Seeing very difficult times in the Red Sea, which means that supply chains are
going to be stretched in many different directions.
So understanding supply chain risk, I think will be really interesting.
We're also in the midst of an El Nino, so who knows what's going to happen in
terms of climate-related stoppages and delays and such.
(44:20):
So yeah, I think there'll be a lot of talk about supply chains.
In the supply chain, there is a lot of talk about logistics,
and logistics is a central question of geospatial.
It's the question of where. So we as a community should be deeply involved in
everything around logistics.
And I think there are worthwhile Earth observation activities, which would help that.
(44:44):
But I think there's a lot in that kind of smart devices space and AI space,
which is, and in fact, open standards and open data space where that matters a lot too.
So I would say from an enterprise perspective, those two things are going to be important.
I think commercial space will continue to be important and interesting.
(45:05):
I think if we get Starship working, then there are going to be even more sensors in the sky.
And I think I would challenge the broader geospatial community with the assertion
that I don't think chat GPT understands space.
I think it implicitly understands location through text, but having a generative
(45:29):
spatial model would be really interesting.
I don't know who's working on that, but that would be...
Somewhat revolutionary geospatial application stroke opportunity.
So I don't think it might, it might not happen next year, but I mean, it's going to happen.
So someone is going to create that and then deploy it and it'll be game changing.
(45:53):
So those are my forward looking observations.
You're right. That question was unfair. That was beautiful.
Well done. Well done. Thank you very much for mentioning ChatGPT.
I think it's always great to have that in the conversation somewhere along the line.
I also wanted to highlight, again, you said organizations be more willing to
(46:14):
modernize, not to innovate.
Back to the idea of modern geospatial modernization.
I think that's a really important take-home message for a lot of people that
are going to listen to this. Appreciate that. Will, fantastic.
Really enjoyed the conversation. Thank you very much for showing up.
Where can people go if they want to reach out to you, if they want to follow
along, if they want to continue this conversation? Yeah, I'm easy to find on
(46:37):
LinkedIn and X, Twitter X.
Also, sparkgeo.com for our corporate website.
And my sub stack is strategicgeospatial.com. So you can find that there too.
Those would be the main spots.
Thanks very much, Will. Really appreciate your time. Super cool.
Thanks very much, Daniel. Take care.
(46:59):
Thank you very much for listening all the way to the end i really
appreciate it there'll be a bunch of links in the show notes today
one of them will be to our sponsor scribble maps so
if you want to augment your gis workflows and bring gis to all levels of your
organization check out scribble maps it might just be the tool that you have
been looking for they offer a ton of functionality they have collaborative editing
(47:19):
you can do business intelligence in there you can annotate maps obviously it's
very very shareable and to be honest there's so much functionality that i I simply can't read it,
list it off right here, right now. It'd be worth going to their website and checking it out.
I'll put a link to that in the show notes of this episode.
And also, if you need more information, you can just book a demo with them.
Mention Mapscaping for a discount. Thank you very much, Scribble Maps.
(47:42):
I really appreciate your support.
Music.
Welcome to the Mapscaping podcast. My name is Daniel and this is a podcast for
the geospatial community.
Today on the podcast we're talking about modern geospatial. So note the word
modern, not the bleeding edge of geospatial, but modern geospatial.
What is it? Well, my guest Will Cadell, CEO of SparkGeo, describes modern geospatial
as the intersection of the cloud, smart space, open source data and standards,
(00:26):
AI and smart devices. That's modern geospatial.
And as you were here during the discussion, it's important to understand the
difference between modernization and innovation when we think about moving people
from where they are now to where they want to be with regards to their geospatial capabilities.
And you might be listening to this wondering, what does any of this have to
(00:46):
do with me? I just want to make better things.
I just want to help people use all this awesome geospatial stuff.
But you don't get to do that without first understanding what does better look
like for them? What is their version of awesome geospatial stuff?
And that is why you should listen to this podcast episode. If you enjoy this
episode and are interested in the topic of modern geospatial,
check out the conference called North 51.
(01:09):
I had the pleasure of attending this last year. It was fantastic.
And this year's conference theme is modern geospatial.
So it'd be well worth checking out if you're interested in that.
Before we get started today, I also want to...
My sponsor scribble maps augment your gis workflows
and bring gis to all levels of the organization
scribble maps so this is the marketing tag tagline
(01:29):
that i need to read out for you but i want to highlight a few things about this
augment not replace so scribble maps when i talk to them they completely understand
this is not a replacement for just desktop gis this is an augmentation of it
and i could see this being really powerful you know put together with with a
desktop GIS platform like QGIS, for example.
And the next bit in the tagline there, bring GIS to all levels of your organization.
(01:53):
This is really hard. This is a really hard problem to solve.
I'm currently working as a consultant for an organization, and this is one of
the challenges that I'm facing.
So people need access to the data, and I simply don't have the tools to give it to them.
I mean, I have some tools at my disposal, but they don't strike that right balance
of functionality and ease of use that Scribble Maps offers. Unfortunately.
(02:14):
I can't just click my fingers and move to Scribble Maps, but I think if you
are in a similar situation, check out Scribble Maps.
It might be the tool that you've been looking for.
So Scribble Maps offers collaborative editing, you know, that you can do business
intelligence annotation and they actually have a ton of functionality in there.
I'm not going to list them off now, but it would be worth checking out.
If you are interested, book a demo with them.
(02:36):
If you mention mapscaping, you'll get a discount. out. So I have had the CEO
of Scribble Maps on the podcast before.
The episode is called The Business of Web Maps and it's well worth listening
to. It'll change the way you think about web mapping as a business.
Jonathan, the CEO, is open, honest. It's a great conversation.
So thank you Scribble Maps for supporting the podcast.
You don't just make this episode possible, you make all of the episodes possible
(02:59):
and I really appreciate it.
Okay, let's move on and talk about Modern Geospatial with Will Cadell, CEO of Sparkgeo.
Hey Will, welcome to the podcast. Today we're going to talk about modern geospatial.
So this is something you've written a ton about in your Substack newsletter,
(03:20):
which I highly recommend to all the listeners.
But I think before we dive into that, let's have a bit of background.
So you are the founder, owner of SparkGeo.
Can you add something more to that brief, brief introduction? Sure.
SparkGeo has been around for, well, since 2010. So I guess almost 14 years.
Since before Before that, I was in government science. I did a little bit of municipal work.
(03:42):
And then I did some forestry work in Canada, came over to Canada from the UK.
You might be able to detect I have a silly accent.
I've been bathing in Tim Hortons for 20 years. And this is what it does to a Scottish accent.
It kind of flattens it out a bit. So I've been in Canada for 20 years.
I've run Spargeo for 14 of those.
(04:03):
Spent a bit of time in the forestry sector, the resource sector before that.
And yeah, since starting Spark Geo, we've been putting maps on the internet, if you like.
Cloud-centric geospatial software development.
I used to write a lot of code. I now think I am possibly the worst software
developer in the company.
So I end up talking about code now.
(04:25):
That's the background. We spent a lot of time interfacing with what I would
call innovative stroke, futuristic geospatial organizations and institutions and startups.
I count myself very lucky being able to think about the cutting edge of geospatial.
And how it is maybe a little bit different now from what it possibly once was
(04:49):
and possibly still is in different organizations.
So I think we're at a very exciting time. This is why I talk about this notion of modern geospatial.
And I think we have a lot of opportunities as a community, but we need to do
a few things in our own workflows and in our own thinking to realize those.
So I very much appreciate the opportunity to have a chat about this idea,
(05:15):
Daniel. Thank you very much.
Oh, no worries. I'm absolutely stoked to have you as a guest on the podcast.
Yeah. So before we get into that idea of what we need to do to take advantage
of these opportunities, let's start with a description of modern geospatial
definition, if you will. What does it mean to you? A definition?
I don't unfortunately have a very succinct sentence. I haven't thought through my value proposition.
(05:39):
I'm sorry. However, it's a series of observations that I think are important.
So firstly, the first observation I have, which is really, really obvious and
really, really simple, is that geospatial people excel at building geospatial
things for other geospatial people.
And the secondary observation is that there's a lot more other people than there are geospatial people.
(06:05):
So those two things combined tells you a little bit about the modern audience
of digital geography, shall we say.
I would argue that GIS people at large didn't invent the tools that we as a
population interface with on a day-to-day basis.
(06:25):
So I think the most popular geospatial tools on the internet are either weather,
they are navigation, or they are dialing up transportation.
And I think those three tools, so you can call them meteorology,
we can call them navigation, we could call it logistics to some extent, personal logistics.
Those three things dominate consumer geospatial, but I don't think any of them
(06:50):
were invented by the GIS sector at large.
So I'm really interested in how we can use modern tools, smart devices,
et cetera, et cetera, to enable more people, to get more people using digital geography.
I see that, and then I see this notion of complementary assets.
So those are assets which might support a secondary ecosystem. system.
(07:15):
So think about the cloud, think about smart devices I was just talking about,
think about AI, think about open source, think about smart space, commercial space.
All those things are independent of geospatial technology.
They operate in and of themselves. They are philosophies, they're workflows,
(07:35):
they're technologies that have grown independently and act as a kind of a complementary
springboard for us in the geospatial community to do more.
So we can leverage the cloud, we can leverage commercial space,
we can leverage smart devices, we can leverage all sorts of these things.
But the notion is, the key thing is that even five years ago,
(07:59):
some of those independent assets didn't really overlap with each other and now they all do.
So where all those things overlap together, we have this notion,
I think, of modern geospatial.
So I would argue that today we have a series of net new capabilities,
which lead to net new opportunities.
(08:22):
And I don't really think that the geospatial community at large sees the difference
in what we can do today with what we were doing five or even 10 years ago.
But I think there's a net new opportunity to do creative and new things within
(08:43):
our kind of community of practice, if you like.
So this combination of new potential or new people, this combination of new capabilities,
and you could argue that there is some notion of new demand in the finance space.
(09:03):
And I would argue that almost all the management and measurement techniques
involved in anything to do with climate change will involve some kind of geospatial,
some kind of geographic or remotely sensed data.
So there's going to be a demand for geospatial technology.
(09:27):
What that demand looks like, I have no idea. I don't know what the product for
climate looks like. so this is kind of what I would call it inchoate demand
it's like it's this notional demand that we think is going to be something but we don't know.
What the intrinsic products are going to look like. So if you think about those
things, we've got new people, we've got new capabilities, and we've got new demands.
(09:47):
I think that creates this new environment in which to do business.
And that's what I'm loosely and somewhat lazily calling modern geospatial.
So that's kind of how I'm packaging it. Does that make sense?
Yeah, it does. I got to say, you covered a lot of ground there.
But just let me recap for a second. So if we think about the intersection of the cloud, smart space.
(10:12):
Open source data and standards, AI, algorithms, and smart devices,
if we think about the Venn diagram of that and where they intersect,
you're putting a circle there and saying, well, this is modern geospatial in
the intersection of all of these things.
I wonder, could we also say this is mature geospatial?
Are these mature products or are we on the bleeding edge when we think about
(10:32):
modern geospatial? That's a great segue into a discussion about technology maturity in general.
Because each one of those complementary assets that I talked about,
each one of them has its own what I would call an innovation curve.
Now, that's not my word. That's the word that the innovation community would use.
(10:53):
An innovation curve describes this kind of S-curve. It's an S,
whereby a particular technology product
starts off being very experimental. And then it goes up into this and it's slow to evolve and it's hard.
And you have this piece at the bottom of the S-curve where adoption is pretty slow.
(11:14):
And then you have this kind of linear piece in the middle where adoption is linear.
And that's where you have this kind of notion of incremental innovation.
Things are getting faster, things are getting better.
And then at the top of the S-curve, it kind of flattens out again where where
the innovation has reached the peak.
So if we think about, there's a great example in the literature about ice hunting,
(11:39):
which is where people in Northeastern USA in the 1800s, there would be this
big ice hunting industry where people would carve ice and then they would ship
it to various different places to have,
so people in India could have their gin and tonics and they could cool things in hot countries.
So in effect, moving cold stuff from a cold country to a hot country to keep
(12:01):
things cold in the hot country, if you imagine that, by boat.
And there would be incremental innovation. They would figure out how to move
the ice faster, how to chip it out quicker.
And you can imagine that piece would be the middle piece of the S-curve.
And then suddenly the adoption flattens out because, you know what,
our thermal capabilities in those boats reached a maximum.
(12:23):
We could only move those boats so fast. We could only chip out the ice so quickly.
So the actual adoption flattened out and then something amazing happened people
invented refrigeration home refrigeration which entirely disrupted that industry
and it just went away so think about that you've got one S curve which is.
(12:43):
We can ship ice, and then we can ship it to a place. And then suddenly it's
disrupted by an entirely different S-curve, which is we can build refrigerators
and sell them to people in those hot countries, and then we don't have to move any ice whatsoever.
So if you think about those two things, it describes two processes which sit
on two innovation curves.
Now, when we think about geospatial, we could argue a few things about innovation curves.
(13:08):
You could say desktop GIS is one innovation curve. You could argue web maps is the secondary one.
You could also argue that augmented reality might be a third one.
And each of these kind of hops to the other one.
However, you could also take apart those innovation curves and say,
well, desktop GIS is kind of evolving into web GIS in terms of these kind of
(13:32):
hybrid systems. ArcPro will be one.
QGIS has been hybrid for a while too. So if you think about that,
And this notion of the web is dependent upon the complementary asset that is
the internet, and one would argue these days the cloud.
So what we're trying to do here by talking about modern geospatial is challenging
(13:54):
our community to think about what are those assets that are available in our purview.
It could be the immediate purview, it could be a future purview.
It could also be looking a little bit back in time. I'll get to that in a second.
But what are those assets that are available that allow us to do net new things
and allow us to advance and answer better questions and inject more value into the broader community?
(14:21):
The interesting thing about those S-curves, too...
Is that different organizations feel comfortable in different places on that S-curve.
So if you have an enterprise organization, they may be less comfortable being
right on the cutting edge.
They want to make sure that things are just right now.
(14:42):
And that is a fairly safe bet. Yeah, it's a bit of technical risk,
but not very much technical risk.
It's more kind of business process oriented. oriented. Whereas startups and
more innovative companies are much more willing to take bets on what you'd call technical risk.
Yeah, they can figure out the business process piece, but they're very agile.
(15:03):
So business processes aren't so much of a burden. Whereas in a big enterprise
organization, the business process, the human piece, can be quite a burden.
So figuring out where different organizations sit within the context of an S-curve
is really interesting because that allows you to determine where that organization
is most willing to invest its time and what makes most sense from a technology
(15:27):
advancement perspective.
Does that help answer the question? Yeah, it does. I just want to highlight
that idea that innovation S-curves are not necessarily the same as an organizational S-curve.
At least that that's one of the many things that I got out of you.
And I think that that's really, really interesting because just because our
innovation curve looks like this, it doesn't mean that our organization,
(15:50):
those people that we're trying to move forward, that we're trying to help,
that we're seeking to serve,
that they are necessarily moving at the same rate as innovation.
I think adoption and innovation are quite different here.
That's the bit I'd like to sort of move on to now is knowing that,
how do we identify where people are, where an organization is on the S-curve,
and then how do we move them
(16:10):
along the S-curve? Yeah, yeah. Let me illustrate this with an example.
So Spark Geo, my organization, largely I made the assessment that we need to
do some of this spatial finance work.
The spatial finance is going to be really important. And a lot of it's going
to happen in the UK because it's going to be insurance-based first,
(16:32):
and then it's going to move up the value chain into different financial organizations.
So we made this assessment, And we made this rudimentary assumption,
and I'll come back to that.
Rudimentary assumption that we would be doing cloud-native, you know,
this and that. We'd be distributing data. We've got to do some analytics.
We've got to measure. The core observation and insight is that landscape change
(16:56):
is going to be important in the measurement of climate-related activities for
this notional spatial finance business.
I.e., if you measure landscape changes, you can figure out if there are more or less trees.
You can figure out if there's an increased amount of carbon in a particular place.
You can figure out if there's an increased flood risk in a particular place
(17:19):
based on landscape changes, if you like.
And you can use remote sensing to determine landscape changes amongst other
technologies, which allows you to create analytics.
So that was our assertion, our assumption. We go to the UK, start a business,
and we start talking to people.
And this makes us sound like we're utter fools, and we're not.
(17:43):
We did put a lot of research into this. But the first thing we discover is that
most of the financial sector isn't actually on the cloud, which when you're
thinking about cloud-native activities.
Is a bit of a barrier. We kind of fell at the first hurdle.
And I make this joke, I tell my kids not to assume anything because it makes an ass out of you and me.
(18:07):
And we definitely made an assumption.
And we've just basically got to this notion. And it's an interesting observation.
Daniel, because it talks exactly to the point you're talking to,
which is, where are organizations innovating?
Where do they feel comfortable?
So we discovered that a lot of the organizations that we were working with weren't
(18:30):
necessarily on the cloud.
So in terms of that S-curve, we had some work to do. We've got some modernization work to do.
We've got to encourage organizations to feel that the cloud is a safe and useful
place to do business before we get to do all this kind of cloud-native stuff.
Or maybe we provide a managed service and give these organizations an easy entry point.
(18:55):
So it's not as if it was a brick wall by any means.
It was just like, oh, this is interesting. We didn't think this would be the situation.
But it is. So we'll manage for it. And that's how small agile businesses can
operate. But it's an interesting note because you get to this point where,
yeah, we're a small, agile, innovative company and that's cool.
(19:20):
But sometimes we're helping larger organizations with this notion of modernization,
which might be a little bit different from innovation.
It might be innovative for the large organization, but if you were to reflect
back from the heady heights of a Silicon Valley startup, they might not view
(19:41):
that activity as quite so innovative.
They would view it as the default way of doing technology business,
which is just a really interesting...
For me, it was a really interesting object lesson in expectation and in this
notion of S-curves and figuring out that the S-curve doesn't just describe time.
(20:04):
It describes a willingness to innovate, and it describes almost exactly the
size of different organizations and where they are in the application of more
advanced technologies.
So it was a really interesting object lesson in S-curves in practice, I feel like.
So yeah like honestly that
(20:26):
that is that is really interesting so if i'm understanding you
correctly the assumption here was oh these people are ready to innovate when
in fact they needed to modernize first and you showed up with an innovation
plan or an innovation strategy when what was needed was modernization yeah maybe
the modernization could have been just lift and shift to the cloud do the exact same things just.
(20:48):
In a scalable environment. Maybe that was a form of modernization.
But we come back to this idea of S-curves and identifying where people are on them.
And so let's assume now that we understand where an organization is along the
S-curve. And in this example that you've just given us, they were ready to modernize.
What are the prerequisites for modernization?
I think it's a willingness to move forward and a comfort around the particular technology.
(21:16):
So So in the case of the cloud, it's been around for, I don't know, what, 15 years?
At least as long as Spark Geo. We've literally never owned a server.
So cloud technology has been around for at least that long.
I'm sure someone will correct us and tell us exactly how long it has.
But I think we can say for sure over 15 years.
(21:36):
And now we're getting to a place where some large organizations,
not just in the finance sector, but also across here in Canada,
have said, said, you know what, we feel more comfortable with this.
We can start moving this direction.
And for me, that's great.
It's like music to my ears. But also, it's a really interesting note on when
(21:57):
it makes sense for a certain company to do a certain thing.
And it might not necessarily even be cost-driven.
It might be driven by needs within the organization.
It might be driven by experiential needs. It might be driven by all sorts of different things.
Or it might just be the fact that their employees are giving them such a hard
(22:17):
time about not doing something that they've had to do something.
Or it might be that the incumbent technology provider has provided this opportunity,
which has subsequently started to make sense for the organization.
So there's many different reasons why certain companies adopt certain technologies.
But it It doesn't always make a ton of sense.
(22:40):
Sometimes there's externalities that drive that. But number one,
I would say, is willingness.
And within that willingness, there is definitely a piece of, what I would say,
the management of career risk of individuals in the middle management who actually
might be the ones actually making the decisions, actually doing the work and
(23:03):
actually taking the risk.
As an executive, it's easy for me to wave my hands and say innovation is great
and collaboration is wonderful.
But in the end, when the rubber hits the road in that middle management,
that's where people are taking a risk on a new thing.
So as a technology provider, I have to be very kind of empathic towards those
(23:28):
individuals who are taking a risk within their organization.
They were doing a process, a value creation process in a certain way.
And now they want to do it in a different way, which tells me that there's a
piece of risk in there and they're willing to manage it and they're willing
to let us help them with that process.
(23:50):
I mean, there's a lot of trust in that relationship. So we have to be quite careful with that too.
So you talked a lot about risk just then and this sort of gets back to one of
my questions right at the start was, could we change modern geospatial to mature geospatial?
All of these elements that we named right at the start, the cloud,
smart space, open source data, standards, AI algorithms, smart devices.
(24:12):
These are relatively mature, at least in my mind. Not to say they're stagnated,
but they've been around for a while. They're well understood.
And I think this is one of the ways of managing risk for organizations.
Not showing up with something brand new, showing up with something that is mature,
something that is modern.
And I think too that larger organizations, and please correct me on this,
(24:34):
I think they They are probably more risk adverse than they are price sensitive.
I totally agree with that statement. I just think the word mature makes it sound
like it's old. But, you know, whatever.
Different people see different words in different ways. I think we're getting at the same idea.
It comes down to nomenclature and the understanding of different things.
(24:56):
The key idea here is finding a way to raise expectations of broader organizations
by illustrating the possible through exemplar applications.
So that's what I say to my team is that we need to provide excellence so the
(25:19):
broader community understands what is possible when we think about modern geospatial,
when we think about applying the cloud,
when we think about all those sensors floating around in low Earth orbit,
all these things that are now possible that weren't before.
When we think about 8 billion GPS-enabled smart devices on the population of
(25:44):
our planet, that wasn't possible a decade ago.
Music.
(26:06):
And just raising expectations and encouraging the geospatial community not to
do the minimum, but to do the possible.
That's where I have been trying to encourage my team to go.
But that's also within the context of, this is the exemplar,
but we can move you towards that, because we all know that life is a spectrum.
(26:29):
You're not just there. You don't just get there by paying enough money.
You have to move your organization incrementally towards this notional sort
of exemplar situation, which means that it's a vision, not a goal,
because unfortunately, that exemplar is always going to get further away.
(26:52):
You know, it's always going to get, there's always going to be something new happening.
And that's good. I mean, that will allow us one day to, you know,
to fly to Mars and all the rest of it.
But as we move up or move forward, side note, it kind of bugs me when people
say move forward because I'm never sure what direction forward is.
But nevertheless, I'll take a step back.
(27:13):
As we advance, again, forward, direction, I don't know.
As we make our technology better, our expectation of technology should also change.
So we need to make sure that as enterprises, they don't get left behind,
that they're pushed forward, that there is a need, a desire,
an expectation that technology can move at an appropriate pace.
(27:37):
I think injecting that higher level of expectation into the technology stacks
of large organizations is important. important.
And some are natively, they have native expectations, i.e.
They have high expectations built into their genetics, but some really don't.
And those are the ones that we really need to empower, I think,
(27:59):
with some good thinking.
And just a second, I want to ask a question about making promises that we can
keep, because I think when you show up with these grand ideas,
you also need to make a promise that you can keep.
And I think broken promises are part of the reasons why organizations less
willing to you know take on this risk and to change but
we'll leave that just for a second do you see the gap between
(28:20):
what we could consider modern and innovative do
you see that shortening with time so you've owned or operated a spark geo for
what do you say 10 years now do you have you seen like a change in that gap
or has it remained relatively constant that gap that gap definitely fluctuates
i would hazard that so yeah spark Spark Geo has been around for 14 years, my gosh.
(28:43):
I would hazard that by saying that most of the work we did in the first few
years of Spark Geo was very much in the tech sector.
So we didn't do a large amount of what I would call.
Enterprise-oriented geospatial activity at that point.
Except a couple of notable exceptions around Google Maps implementations,
like ATM finders and stuff, and such like that.
(29:05):
So it was overly user-centric, slightly innovative for the time kind of activity.
But we weren't rebuilding major geospatial systems inside enterprise.
So I can't really comment on what it was like when we first started out.
But I would say that I think these complementary assets have accelerated in
(29:27):
their own domains significantly within the last five years. And we look at cloud technology.
It's got so much wildly more capable.
It seems very few organizations think about doing on-prem work,
except within the context of higher security needs.
There are some notable exceptions. exceptions 37 signals for
(29:48):
instance are you know they're very vocal about building systems
which are not not cloud-based these days which is
fine i mean it's good to have that argument being well articulated by that team
but i would say that cloud technology for geospatial as a like a big large data
play which is what geospatial really is is a massive enabler and it has enabled in In particular,
(30:13):
the commercial space sector, the EO sector.
So smart space enabling EO, the cloud enabling EO through storage,
AI and algorithms enabling EO through the pipeline delivery of algorithms through
the cloud to create analytics. That's a workflow.
I mean, then publishing those analytics with an open standard,
(30:35):
so it's easily consumable by other organizations to collide different data with it.
All that stuff is within this kind of Venn diagram, and all those things are
growing and evolving independently of each other,
each of those things independently making this concept of modern geospatial
more functional every day.
(30:57):
So thinking about how all those
things join together, your notes on making promises is absolutely spot on.
I think Earth Observation in the early 2000s made a lot of promises which were
not kept. And I'm not even sure those promises were made by the Earth observation sector.
(31:18):
I think they were kind of sort of made by Hollywood and the Earth observation
people were left kind of holding very hard expectation of like video from space of anywhere at any time.
Which is so far from the reality, it's almost comedic.
But I think it's still a really important concept because I think a lot of those promises can be kept.
(31:45):
They're just really hard to manage for. Does that make sense?
Yeah, it really does make sense. The reason I want to mention it is because
I think it's really important.
If you're going to show up to an organization and say, hey, we're with you on this journey.
My guess is an organization being risk adverse, They want you to be there also
next year and the year after that.
And they don't want to work with multiple different partners,
(32:08):
a new partner every month. That's not what they're into.
They want to sign a contract and say, great, you're going to be here for the
next five years. And in that time, we're going to move from here to there.
And I think that if you can make that promise and actually fulfill it and keep
the promise, I think you're really going to make some big changes happen.
Happen, not just in geospatial, of course, in terms of modern geospatial,
(32:29):
but also the flow-on effects of that are going to be humongous.
Make those longer-term promises and keep them.
Yeah, and I think that's credible these days. I think that's very possible.
I see a number of organizations on the market who are helping larger enterprise
organizations kind of manage for innovation and manage for advancement.
(32:52):
And what we've been most challenged with in Spark Geo recently hasn't been the
deployment of geospatial code or anything like that.
It's learning how to help organizations change, which is super business-y.
And you see all this stuff on the internet about change management and transformation,
(33:13):
this and all the rest of it.
But in reality, having a level of empathy around helping organizations and ultimately
people, because it's people that are making decisions and it's people that are
having having to do a new thing.
And it's middle management who ultimately have to lead.
Helping those individuals win is literally the purpose of our organization's
(33:38):
existence now, which is so interesting.
So yeah, we write code. And yeah, we do very interesting like cloud deployments.
And we talk to interesting geospatial companies all the time.
But ultimately, our job is to help organizations win through geospatial.
And winning sounds so binary.
(33:58):
Winning has got many, many different connotations. And I'm not winning,
and I'm by no means a zero-sum game guy.
I just want an organization to succeed through the use of geospatial technology.
And in many ways, this notion of winning is confusing because I think you could
also win in collaboration.
You don't have to win on your own. I said it in a video we made years ago,
(34:22):
but I think those organizations that are willing to team up and are willing
to collaborate will necessarily out-compete anyone who's not because it's very hard to do,
any of this kind of stuff on your own. It's much, much easier when you have
a team, when you collaborate, when you collaborate with different agile organizations.
(34:43):
Almost everything gets easier when you have teams.
Not necessarily big teams, but just teams of different people and teams of different
organizations partnering because you get this diversity of thought.
So there's a whole bunch of different interesting elements in there to unpack.
Yeah, there sure is. I want to stay with this idea of winning just for a second
thing because I think it's important to sort of emphasize that a win for an
(35:06):
organization is one thing, but throughout the different levels in that organization
and right down to individuals,
they all need to win too in some way, shape or form.
I think this is not just important for people starting businesses in the geospatial
world, but I think it's really important for practitioners as well.
You get to do interesting work if you make it a win for somebody else.
And I think for me anyway, this is a really hard lesson to learn.
(35:30):
I've tried to drag organizations and at
the end of the day people kicking and screaming into the past and
you know like from the deep deep past into
the more the more recent past and it's been tough because it hasn't been an
immediate win for them and it was a complete mistake on my behalf a total fail
but my learning from that was like well what would be a win for this person
(35:52):
what would be a win at that level of this organization what would be a win for
the organization as a whole those are completely different things,
but they need to be packaged together into whatever it is that you're promoting, selling.
Trying to do. Yeah, it's so interesting. I remember my second job,
I worked in Perth and Kinross Council, this is in Scotland, as their corporate
(36:14):
address gazetteer engineer.
And so there was this big movement in the UK around normalizing addresses,
which sounds like the most stupid thing.
But in reality, in a city council like Perth and Kinross Council,
there there would be about four or five different address databases.
So there'd be a health one, there'd be a tax one, there'd be an education one,
(36:36):
blah, blah, blah. And the idea was, let's squidge it all into one.
So there would be this single view of addresses in one city council,
and then you could multiply that up across all the councils,
so there'd be this one view of addresses in the UK.
It's a great idea. BS 766, it's ingrained into my existence. distance.
(36:58):
And so me and my boss, Ewan Walker, we would get all these addresses and we'd
have a piece of software and we would squidge them all together.
Which is the right address? That's the right address.
A lot of it was automated, but it was surprisingly manual, as you can imagine.
Anyway, we ended up having to go to this point in our project where we would
be talking to all the users of the address data.
(37:20):
And we would be like, okay, so we've got this new address database.
It's going to be amazing. It's way more accurate. It's great.
How do you use addresses is in your day-to-day business. So it's like classic
business process modeling.
And what I came to realize, and I can't remember if it was observation from
you or myself, but the point is we realized that how someone described their
(37:43):
job, what their job title was,
and what their boss thought they did were three entirely different processes,
which was really interesting to figure out.
And I think about that in terms of what you're just saying around.
Deploying new technologies and change management. So actually finding out what
(38:03):
somebody does, like what buttons do you press to do this thing?
And what boxes do you click to make this thing happen? And then asking them
to describe what they do.
And like, it's so interesting to find out, oh, actually, you don't do that.
You actually circumvent that entire process by doing this other thing instead.
(38:24):
And if I give you something that's going to be slower more than this other thing
that you've figured out yourself through whatever purpose, then you're going
to be upset and it's not going to work.
Or if I give you this new process, which for some reason doesn't do this other
thing which you like to do, then you're not going to do it.
So it's all this stuff, which is really interesting.
(38:47):
So finding out how you can help an organization win by actually digging right
into the nuts and bolts of what a company does, And what individuals do on a
day-to-day basis is so important.
But boy, at scale, that's incredibly hard to do.
It's a very, very, very kind of manual consulting thing just to sit around and
(39:10):
actually watch somebody do something and then compare that thing that you're
watching them do to how they describe it.
It's such an interesting process to go through it.
I mean, I say this a lot, but almost every technology problem is actually a
human problem in disguise.
So it's like, how do you solve this individual's problem, make their life easier,
(39:34):
make something go faster?
And you do it through, in air quotes, the guise of technology.
And I think that's such an interesting thing. So when you start thinking about
modern geospatial, the cloud has such an opportunity to provide technology at
a much faster pace. pace.
(39:54):
Smart devices have this opportunity for you to do things in the field more effectively
and with much better user interfaces than you ever had before.
AI acts as your co-pilot. I mean, AI allows you to make better decisions faster.
And then smart space allows us to look in places that we can never look before.
(40:15):
So if we care about monitoring landscape changes, then we can do that.
We can do that not just for one house, but a portfolio of mortgages.
Suddenly, that scale becomes possible because you've got all this other stuff.
All this stuff that you kind of had to just assume was okay,
now you can actually check because you can see all the mortgages for our bank
(40:38):
across North America or all the mortgages in Florida.
And like, how much flood risk do we actually have? I'm not sure.
Wouldn't it be nice to know?
Or do you not want to know? I mean, those are really interesting human questions.
And in the end, it is a human question because we can choose to know this information
or we can choose to not know.
Another thing I often say to my team is like, there's not many industries that
(41:02):
are willing to pay for bad news. So think about that.
How often is landscape change data giving you good news?
So think about those two things and then think about how to describe what it
is that we're doing in the most effective manner.
And there's a lot of nuance in there, but it is definitely what's ruminating.
(41:26):
So I just want to share a little story about that, not the idea that people
don't want to pay for bad news.
I talked to a company a while back. They had this interesting idea.
They could look for water leaks from space.
Great idea, right? There's been ages developing the technology,
and then they would show up to a couple of sort of leaps in the process,
which led to them, this being a success.
(41:48):
One of them was the observation that companies were more willing to pay for
if the cost was OPEX as opposed to CAPEX.
Another one was that if they showed people what they could do,
that was a big leap forward.
That meant that they got further in the sales process each time because they
said, I'm not going to tell you, I'm going to show you what I can do.
One of the last ones was not to
(42:08):
overwhelm people because let's say they went to
the i don't know a utilities company in copenhagen said
look here are all of your leaks you know here are all of your problems expose
the lot for them and you would think oh great now i can go and fix them but
it wasn't like that it was overwhelming and people didn't want to know where
they all were they just wanted to know whether ones they should be fixing they
(42:29):
wanted someone to sort of break down that problem into bite-sized chunks.
That's what they did. This was another leap forward for them as a company,
was understanding that people need it.
Don't create another problem for them. Don't overwhelm them.
Give it to them in small chunks and things they can solve and,
you know, win. Yeah. Give me my top 10 leagues. Yeah. Give me my next top 10. Yeah. It's good. Yeah.
(42:55):
Like we make it a win for them, right? It wasn't a win going,
Oh, this is going to take us 58 years to figure all this stuff out.
A win was I can do something today.
Yeah. I don't want to know why I'm not an Olympic athlete.
I just want to know why I could be a little bit better than I am tomorrow. Yeah. It makes sense.
(43:17):
If you give me a list of all my failings i won't even
bother getting off the couch but if you just tell me a little thing
i can do then maybe i will yeah yeah it's funny yeah yeah makes a lot of sense
i want to own around this off do you have any predictions for next year for
2024 predictions that's unfair you know what i think i think we're going to
(43:37):
see a lot of willingness to modernize.
Last year was a bit of a kick in the pants for the technology sector, I would say.
But I feel that there'll be a little bit more capital flowing towards efficiency.
I think supply chain concerns are going to go through the roof again.
(43:57):
Seeing very difficult times in the Red Sea, which means that supply chains are
going to be stretched in many different directions.
So understanding supply chain risk, I think will be really interesting.
We're also in the midst of an El Nino, so who knows what's going to happen in
terms of climate-related stoppages and delays and such.
(44:20):
So yeah, I think there'll be a lot of talk about supply chains.
In the supply chain, there is a lot of talk about logistics,
and logistics is a central question of geospatial.
It's the question of where. So we as a community should be deeply involved in
everything around logistics.
And I think there are worthwhile Earth observation activities, which would help that.
(44:44):
But I think there's a lot in that kind of smart devices space and AI space,
which is, and in fact, open standards and open data space where that matters a lot too.
So I would say from an enterprise perspective, those two things are going to be important.
I think commercial space will continue to be important and interesting.
(45:05):
I think if we get Starship working, then there are going to be even more sensors in the sky.
And I think I would challenge the broader geospatial community with the assertion
that I don't think chat GPT understands space.
I think it implicitly understands location through text, but having a generative
(45:29):
spatial model would be really interesting.
I don't know who's working on that, but that would be...
Somewhat revolutionary geospatial application stroke opportunity.
So I don't think it might, it might not happen next year, but I mean, it's going to happen.
So someone is going to create that and then deploy it and it'll be game changing.
(45:53):
So those are my forward looking observations.
You're right. That question was unfair. That was beautiful.
Well done. Well done. Thank you very much for mentioning ChatGPT.
I think it's always great to have that in the conversation somewhere along the line.
I also wanted to highlight, again, you said organizations be more willing to
(46:14):
modernize, not to innovate.
Back to the idea of modern geospatial modernization.
I think that's a really important take-home message for a lot of people that
are going to listen to this. Appreciate that. Will, fantastic.
Really enjoyed the conversation. Thank you very much for showing up.
Where can people go if they want to reach out to you, if they want to follow
along, if they want to continue this conversation? Yeah, I'm easy to find on
(46:37):
LinkedIn and X, Twitter X.
Also, sparkgeo.com for our corporate website.
And my sub stack is strategicgeospatial.com. So you can find that there too.
Those would be the main spots.
Thanks very much, Will. Really appreciate your time. Super cool.
Thanks very much, Daniel. Take care.
(46:59):
Thank you very much for listening all the way to the end i really
appreciate it there'll be a bunch of links in the show notes today
one of them will be to our sponsor scribble maps so
if you want to augment your gis workflows and bring gis to all levels of your
organization check out scribble maps it might just be the tool that you have
been looking for they offer a ton of functionality they have collaborative editing
(47:19):
you can do business intelligence in there you can annotate maps obviously it's
very very shareable and to be honest there's so much functionality that i I simply can't read it,
list it off right here, right now. It'd be worth going to their website and checking it out.
I'll put a link to that in the show notes of this episode.
And also, if you need more information, you can just book a demo with them.
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(47:42):
I really appreciate your support.
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