0:02

Welcome to the Mapscaping podcast.

0:04

My name is Daniel and this

0:06

is a podcast for the geospatial

0:08

community. Today on the podcast we're

0:10

talking about modern geospatial. So note

0:12

the word modern, not the bleeding

0:14

edge of geospatial, but modern geospatial.

0:16

What is it? Well, my guest

0:18

Will Caddell, CEO of SparkGeo, describes

0:20

modern geospatial as the intersection of

0:22

the cloud, smart space, open

0:25

source data and standards, AI

0:27

and smart devices. That's modern geospatial.

0:29

And as you were here during

0:31

the discussion, it's important to understand

0:33

the difference between modernisation and innovation when

0:35

we think about moving people from where

0:38

they are now to where

0:40

they want to be with regards to their

0:42

geospatial capabilities. And you might be listening

0:44

to this wondering, well, what does any of this have

0:46

to do with me? I just want to make better

0:48

things. I just want to help

0:51

people use all this awesome geospatial stuff. But

0:53

you don't get to do that without first

0:55

understanding what does better look like for them.

0:57

What is their version of awesome geospatial stuff?

0:59

And that is why you should listen to

1:02

this podcast episode. If you enjoy this episode,

1:04

and are interested in the topic of modern

1:06

geospatial, check out the conference called North 51.

1:08

I had the pleasure of attending this last

1:10

year. It was fantastic. And this year's conference

1:13

theme is modern geospatial. So it'd be well

1:15

worth checking out if you're interested in that.

1:17

Before we get started today, I also want

1:19

to thank my sponsor Scribble Maps, augment your

1:21

GIS workflows and bring GIS to all levels

1:24

of the organisation with Scribble Maps. So this

1:26

is the marketing tagline that I need to

1:28

read out for you. But I want to

1:30

highlight a few things about this. Augment

1:32

not replace. So Scribble Maps, when I talk

1:35

to them, they completely understand this is now

1:37

a replacement for desktop GIS.

1:39

This is an augmentation of it. And

1:41

I could see this being really powerful,

1:43

you know, put together with a desktop

1:45

GIS platform like QGIS, for example. And

1:47

in the next bit in the tagline

1:49

there, bring GIS to all levels of

1:51

your organisation. This is really hard. This

1:54

is a really hard problem to solve.

1:56

I'm currently working as a consultant for

1:58

an organisation. one of the

2:00

challenges that I'm facing. So people need access to

2:02

the data and I simply don't have the tools

2:04

to give it to them. I mean,

2:06

I have some tools at my disposal, but

2:08

they don't strike that right balance of functionality

2:10

and ease of use that Scribble Maps offers.

2:13

Unfortunately, I can't just click my fingers and

2:15

move to Scribble Maps, but I think if

2:18

you are in a similar situation, check out

2:20

Scribble Maps. It might be the tool that

2:22

you've been looking for. So Scribble Maps offers

2:24

collaborative editing, you know, that you can do

2:26

business intelligence annotation and they actually have a

2:28

ton of functionality in there. I'm not going

2:31

to list them off now, but it would

2:33

be worth checking out. If you are interested,

2:35

book a demo with them. If you mention mapscaping,

2:38

you'll get a discount. I have

2:40

had the CEO of Scribble Maps on the

2:42

podcast before. The episode is called The Business

2:44

of Web Maps and it's well worth listening

2:46

to. It'll change the way you think about

2:48

web mapping as a business. Jonathan,

2:50

the CEO, is open, honest, it's a

2:52

great conversation. So thank you Scribble Maps

2:55

for supporting the podcast. You don't just

2:57

make this episode possible, you make all

2:59

of the episodes possible. I really appreciate

3:01

it. Okay, let's move on and talk

3:04

about modern geospatial with Will Caddell, CEO

3:06

of SparkGeo. Hey

3:11

Will, welcome to the podcast. Today we're going

3:14

to talk about modern geospatial. So this is

3:16

something you've written a ton about in your

3:18

sub-stack newsletter, which I highly recommend to all

3:20

the listeners. But I think before we dive

3:23

into that, let's have a

3:25

bit of background. So you are the

3:27

founder owner of SparkGeo. Can you add

3:29

something more to that brief, brief introduction?

3:31

Sure. SparkGeo has been around for, well,

3:33

since 2010, so I guess almost

3:36

14 years. Before

3:38

that I was in government science. I did

3:40

a little bit of municipal work and then

3:42

I did some far few work in Canada,

3:44

came over to Canada from the UK. You

3:46

might be able to detect. I have

3:48

a silly accent. I've been

3:50

gazing in Tim Hortons for

3:53

20 years and this is what it does to

3:55

the Scottish accent. It kind of flattens it out

3:57

a bit. So I've been in Canada for

3:59

20 years. years I've run Spar

4:01

Geo for 14 of those, spent

4:03

a bit of time in the forestry sector, the

4:05

resource sector before that. And yeah, since

4:08

starting Spar Geo, we've been putting maps

4:10

on the internet, if you like, cloud-centric

4:12

geospatial software development. I used to

4:15

write a lot of code. I

4:18

now think I am possibly

4:20

the worst software developer in the company.

4:23

So I end up talking about code now.

4:26

Just the background, we spent a

4:29

lot of time interfacing with what

4:31

I would call innovative stroke

4:33

futuristic geospatial organizations

4:36

and institutions and startups. I

4:39

count myself very lucky being able to think

4:42

about the cutting edge of

4:44

geospatial and how it is

4:46

maybe a little bit different now from

4:49

what it possibly once was and

4:51

possibly still is in

4:53

different organizations. I

4:55

think we're at a very exciting time. This is

4:57

why I talk about this notion of modern geospatial.

5:01

I think we have a lot of opportunities

5:03

as a community, but we need

5:05

to do a few things in our own

5:08

workflows and in our own thinking to

5:11

realize those. So I very much

5:13

appreciate the opportunity to have

5:15

a chat about this idea, Daniel. Thank

5:17

you very much. Oh, no worries. I'm

5:19

absolutely stoked to have you as a

5:21

guest on the podcast. So before we

5:23

get into that idea of what we

5:25

need to do to take advantage of

5:27

these opportunities, let's start with a description

5:29

of modern geospatial definition, if you will.

5:32

What does it mean to you? A definition? I don't

5:36

unfortunately have a very succinct

5:38

sentence. I haven't thought through

5:40

my value proposition. I'm sorry. However,

5:42

it's a series of observations

5:45

that I think are important.

5:47

So firstly, the

5:49

first observation I have, which is really, really

5:51

obvious and really, really simple, is

5:53

that geospatial people excel

5:55

at building geospatial things

5:57

for other geospatial people.

6:00

And the secondary observation is

6:02

that there's a lot more

6:04

other people than there are geospatial

6:07

people. So those two

6:09

things combined tells you a little

6:11

bit about the modern audience of

6:13

digital geography, shall

6:17

we say. I would argue

6:19

that GIS people at large

6:22

didn't invent the tools that

6:24

we as a population interface with

6:27

on a day-to-day basis. So I

6:29

think the most popular geospatial tools

6:32

on the internet are either whether

6:34

they are navigation or

6:36

they are dialing up

6:38

transportation. And I think

6:40

those three tools, so you can call

6:42

them meteorology, we can call them navigation,

6:45

we can call it logistics to some extent,

6:47

personal logistics. Those three things

6:49

dominate consumer geospatial, but I

6:52

don't think any of them were

6:54

invented by the GIS sector at

6:56

large. So I'm really interested in

6:58

how we can use modern tools,

7:00

smart devices, et cetera, et cetera,

7:04

to enable more people, to

7:06

get more people using digital

7:08

geography. I see that, and then I

7:11

see this notion of complementary

7:13

assets. So those are assets which

7:15

might support a secondary

7:17

ecosystem. So think about

7:19

the cloud, think about smart devices

7:21

I was just talking about, think

7:23

about AI, think about open

7:26

source, think about smart space,

7:28

commercial space. All those things

7:30

are independent of

7:33

geospatial technology. They operate

7:35

in and of themselves. They are

7:38

philosophies, they are workflows, they are

7:40

technologies that have grown independently

7:43

and act as a kind

7:45

of complementary springboard for us

7:48

in the geospatial community to

7:50

do more. So we can

7:52

leverage the cloud, we can leverage commercial space,

7:55

we can leverage smart devices, we can

7:57

leverage all sorts of these things, but the

7:59

notion is... The key thing is

8:01

that even five years ago,

8:03

Some of those independent assets

8:06

didn't really overlap with each

8:08

other. and know the old

8:10

do. So. We're all. those

8:12

things overlap together. We. Have

8:14

this notion: Ice Age. Of modern

8:17

zero spatial so I would argue. That.

8:19

Today. We. Have a

8:21

series of net you capabilities

8:23

which leads a net new

8:25

opportunities. I don't really think

8:28

that the Jews spatial community

8:30

at large sees the difference,

8:32

but we can do today.

8:34

With. For we were doing five

8:37

or even ten years ago. But.

8:39

I think there's a net new. Opportunity

8:42

to do creates is

8:44

a new things within

8:46

our. Kind of community

8:48

of practice if you like.

8:51

So this combination of. New.

8:53

Potential or new people.

8:55

Combination of new capabilities,

8:58

And. You could argue. That

9:00

there is some. Notion.

9:03

Of new Demand. In

9:06

the finance space and

9:09

I would argue that

9:11

almost all the management

9:13

and measurement techniques involved

9:15

in. Anything. To do

9:17

with climate change will involve some

9:20

kind of jews space or some

9:22

kind of see a graphics or

9:24

remotely census data. So there's going

9:27

to be at the mind. Produce

9:29

base will take those you follow them on. Looks

9:31

like I have no idea. I don't know what

9:33

the products. For climate looks like so

9:35

this is kind of wow color in Kuwait

9:37

the mandates it's like it's is no snow demand

9:40

that we think is going to be something

9:42

but we don't know. What? The

9:44

intrinsic. Products are going to

9:46

look like so everything. By those

9:48

things we've got new people, We

9:50

got your capabilities, We go New

9:52

demands. I think that creates this

9:54

new environment in which to to

9:56

do business. And that's why I'm.

9:59

Loosely. And. somewhat lazily

10:01

calling smart

10:19

devices. If we think about the Venn diagram of

10:21

that and where they intersect, you're putting

10:23

a circle there and saying, this is modern geospatial

10:25

in there. It's the intersection of all of these

10:28

things. I wonder, could we

10:30

also say this is mature

10:32

geospatial? Are these mature products or are

10:34

we on the bleeding edge when we

10:36

think about modern geospatial? That's a great

10:39

segue into a discussion about technology

10:41

maturity in general. Because

10:44

each one of those complementary assets

10:46

that I talked about, each

10:48

one of them has its own what I would call like

10:50

an, in her quotes, an innovation curve. Now,

10:52

that's not my word. That's the

10:54

word that the sort of innovation

10:56

community would use. An innovation curve

10:58

describes this kind of S-curve. It's

11:00

an S whereby a particular

11:03

technology starts off

11:06

being very experimental and

11:08

then it goes up into this and it's slow

11:10

to evolve and it's hard. And you have this

11:12

piece at the bottom of the S-curve where

11:15

adoption is pretty slow.

11:18

And then you have this kind of linear

11:20

piece in the middle where adoption is

11:22

linear. And that's where you have this kind of notion

11:24

of incremental innovation. Things are

11:27

getting faster. Things are getting better.

11:29

And then at the top of

11:31

the S-curve, it kind of flattens

11:33

out again where the innovation has

11:35

reached the peak. So if

11:38

we think about, there's a great

11:40

example in the literature about ice

11:42

hunting, which is where people in

11:45

Northeastern USA in the 1800s, there

11:47

would be this big ice hunting

11:50

industry where people would carve ice

11:52

and then they would ship it to various different

11:55

places to have. So people in India could have

11:57

their gin and tonics and they could cool things

11:59

in hot countries. So in

12:01

effect, moving cold stuff from a cold country to

12:03

a hot country to keep things cold in the

12:05

hot country, if you imagine that, by boat. And

12:08

there would be incremental innovation. They would

12:10

figure out how to move the ice

12:12

faster, how to chip it out quicker.

12:15

And you can imagine that piece would be the middle piece of

12:17

the S-curve. And then suddenly the adoption

12:20

flattens out because you know what? Our

12:23

thermal capabilities in those boats

12:25

reached a maximum. We

12:28

could only move those boats so fast. We

12:30

could only chip out the ice so quickly. So

12:33

the actual adoption flattened out.

12:36

And then something amazing happened.

12:39

People invented refrigeration, home

12:41

refrigeration, which entirely disrupted that industry

12:43

and it just went away. So

12:45

think about that. You've got one S-curve, which is we

12:48

can chip ice and then we can ship it to a

12:50

place. And then suddenly it's disrupted

12:52

by an entirely different S-curve, which is we

12:54

can build refrigerators and sell them to people in

12:56

those hot countries. And then we don't have to

12:59

move any ice whatsoever. So if

13:01

you think about those two things,

13:03

it describes two processes, which

13:06

sit on two innovation curves. Now, when

13:08

we think about geospatial, we can argue

13:10

a few things about innovation curves. You

13:13

could say desktop GIS is

13:15

one innovation curve. You could argue web

13:17

maps is the secondary one. You could

13:19

also argue that augmented reality might be

13:21

a third one. And each of these

13:23

kind of hops to the other one.

13:26

However, you could also take apart

13:28

those innovation curves and say, well,

13:31

desktop GIS is kind of

13:33

evolving into web GIS

13:36

in terms of these kind of hybrid systems. So ArcPro will

13:38

be one. QGIS has

13:40

been hybrid for a while too. So if you

13:42

think about that, and this

13:45

notion of the web is

13:47

dependent upon the complementary asset,

13:50

that is the internet, and one would argue these

13:52

days the cloud. So what we're

13:54

trying to do here by talking about

13:56

modern geospatial is challenging our

13:59

community to... think about what

14:01

are those assets that are available

14:04

in our purview. It

14:06

could be the immediate purview, it could be a future purview.

14:08

It could also be looking a little bit back in time.

14:11

I'll get to that in a second. What

14:13

are those assets that are available that

14:15

allow us to do net new things and

14:17

allow us to advance and

14:19

answer better questions and

14:21

inject more value

14:24

into the broader community?

14:27

The interesting thing about those S-curves too

14:30

is that different organizations feel

14:33

comfortable in different places

14:36

on that S-curve. If you have

14:38

an enterprise organization, they may

14:40

be less comfortable being

14:43

right on the cutting edge. They

14:45

want to make sure that things are just right now.

14:48

It's a fairly safe bet. Yeah, it's

14:50

a bit of technical risk, but not

14:52

very much technical risk. It's

14:55

more business process oriented. Whereas

14:57

startups and more innovative

15:00

companies are much more willing to

15:02

take bets on what you'd call

15:04

technical risk. Yeah, they can figure out the

15:06

business process piece, but they're very agile. So

15:08

business processes aren't so much of a burden.

15:11

Whereas in the big enterprise organization, the business

15:13

process, the human piece, can be quite a

15:15

burden. Figuring

15:17

out where different organizations sit within the

15:19

context of an S-curve is

15:22

really interesting because that allows you

15:24

to determine where

15:26

that organization is most willing to

15:28

invest its time and what

15:30

makes most sense from

15:32

a technology advancement perspective.

15:35

Does that help answer the question? Yeah, it does.

15:38

I just want to highlight that

15:40

idea that innovation S-curves are not

15:42

necessarily the same as an organizational

15:44

S-curve. At least that's

15:46

one of the many things that I got

15:49

out of you. I think that's really interesting

15:51

because just because our innovation curve looks like

15:53

this, it doesn't mean that our

15:55

organization, those people that we're trying to Move

15:58

forward, that we're trying to help, that we're seeking to solve. The

16:00

that they aren't necessarily moving at the same

16:02

rate as as innovation. I think adoption and

16:04

innovation a quite different here is that that

16:06

I'd like to sort of move onto now

16:09

is not knowing that how do we identify

16:11

where people are we're an organization, is on

16:13

the As curve and is how to remove

16:15

them. Along the East coast?

16:18

Yeah, yeah, let me I'm

16:20

plenty. Illustrate this with an

16:22

example. So far, Geo, my

16:24

organization. I like largely. I

16:26

made the assessment that we need to

16:28

do some some of the spatial finance

16:30

work. With. Special violence is going to be

16:33

really important. And a lot of is gonna

16:35

happen. In. The Uk because it's gonna

16:37

be insurance based first and then as good

16:39

a move. Up the volume

16:41

turned into different financial organizations so

16:43

we made a success of a

16:45

we made this rudimentary assumption. An

16:48

hour or I'll come back to that

16:50

rudimentary some some that will be doing

16:52

cloud native you know this and that

16:54

we be distributing dates the go to

16:57

some analytics. We got a measured by

16:59

the big for observation and inside his

17:01

dad. Landscape change is going

17:03

to be important in the

17:05

measurement of. Climate. Related

17:07

activities for that and the disc

17:10

notional Spatial Finance business I if

17:12

you measure landscape changes you can

17:14

figure out of her more or

17:16

less treats you can figure out.

17:19

If. There's an increased amount of

17:21

carbon in a particular place. You

17:23

can figure out if there's an increase flood

17:25

risk in a particular place. Based. On.

17:27

Landscape changes if you like.

17:30

And you can use. Remote. Sensing to

17:32

determine landscape changes amongst other technologies

17:35

which allows you to in a.

17:37

Tree. Analytic. So I was are

17:40

assertion or assumption. We. Go to

17:42

the Uk Star business and was I talking

17:44

to people? And an ideal this

17:46

makes us I like were utter fools

17:48

and I went all we did put

17:50

a lot of research since the into

17:52

this but the first thing we discover.

17:55

Is that most of the financial

17:57

sector isn't actually on the cloud?

17:59

Which. When you're thinking about cloud native

18:02

activities, it's a bit of a

18:04

barrier. We kind of fell

18:06

at the first hurdle. And I

18:08

make this joke, I tell

18:10

my kids not to assume anything because it makes

18:12

an asset of you and me. And

18:15

we definitely made an assumption. And

18:17

we just basically got to this notion. And

18:20

it's an interesting observation, Daniel, because

18:22

it talks exactly to

18:24

the point you're talking to,

18:26

which is where are organizations

18:29

innovating? Where do they feel comfortable? So

18:32

we discovered that a lot of the

18:34

organizations that we were working with weren't

18:37

necessarily on the cloud. So

18:39

in terms of that S curve, we

18:41

had some work to do. We got some modernization work to

18:44

do. We've got to encourage

18:46

organizations to feel that the

18:48

cloud is a safe

18:50

and useful place to do business. Or

18:53

we get to do all this kind of cloud data

18:55

stuff. Or maybe we

18:57

provide a managed service and

18:59

give these organizations an easy

19:01

entry point. So it's

19:03

not as if it was a brick wall by any means.

19:08

It was just like, oh, this is interesting.

19:10

We didn't think this would be the situation. But

19:12

it is. So we'll manage for it. And

19:15

that's how small-scale businesses can operate.

19:19

It's an interesting note because you

19:21

get to this point where, yeah, we're

19:24

a small, agile, innovative company and that's

19:26

cool. But sometimes

19:28

we're helping larger organizations

19:31

with this notion of

19:33

modernization, which might be a

19:35

little bit different from innovation. It might

19:37

be innovative for the large organization.

19:40

But if you were to reflect back from

19:43

the heady heights of a

19:45

Silicon Valley startup, they might

19:47

not view that activity as quite

19:50

so innovative. They would view it as

19:52

the default way of doing technology

19:55

business, which is just a really

19:57

interesting... For me, it was a

19:59

really... interesting object

20:01

lesson in expectation

20:04

and in this notion of S-curves and figuring

20:06

out that the S-curve

20:09

doesn't just describe time, it

20:12

describes a willingness to innovate and it

20:14

describes almost exactly

20:17

the size of different organizations and

20:19

where they are in the

20:21

application of more

20:23

advanced technologies. So

20:25

it was a really interesting object lesson in

20:28

S-curves in practice. So

20:31

honestly that is really interesting. So

20:35

if I'm understanding you correctly, the

20:37

assumption here was, oh, these people are

20:40

ready to innovate when in fact they

20:42

needed to modernize first and

20:44

you showed up with an innovation plan

20:46

or an innovation strategy when what was

20:48

needed was modernization. Yeah. Maybe

20:50

the modernization could have been just lift and shift

20:52

to the cloud, do the exact same things just

20:55

in a scalable environment. Maybe

20:57

that was a form of modernization. But we

21:00

come back to this idea of S-curves and

21:02

identifying where people are on them. So

21:05

let's assume now that we understand where an

21:07

organization is along the S-curve and in this

21:09

example that you've just given us, they were

21:11

ready to modernize. What are

21:13

the prerequisites for modernization? I

21:15

think it's a willingness to move

21:18

forward and a comfort around

21:20

the particular technology.

21:23

So in the

21:25

case of the cloud, it's been

21:27

around for, I don't know, what, 15 years?

21:30

At least as long as it's part of the deal. We've

21:32

literally never owned a server. So cloud technology

21:34

has been around for at least that long.

21:37

I'm sure someone will correct us and tell us exactly how

21:40

long it has, but I think we can

21:42

say for sure over 15 years. And

21:44

now we're getting to a place where some large

21:47

organizations, not just in the finance

21:49

sector, but also across here in

21:51

Canada, have said, you know what,

21:53

we feel more comfortable with this. We

21:55

can start moving this direction. And

21:58

for me, that's great. It's

22:00

like music to my ears. But also,

22:02

it's a really interesting note on when

22:05

it makes sense for a certain company to do

22:07

a certain thing. And it might

22:09

not necessarily even be cost-driven.

22:12

It might be driven by needs

22:15

within the organization. It might

22:17

be driven by experiential needs. It

22:20

might be driven by all sorts of different

22:22

things. Or it might just be the fact

22:24

that their employees are giving them such a

22:26

hard time about not doing something, that

22:28

they've had to do something. Or

22:31

it might be that the incumbent technology

22:34

provider has provided this opportunity,

22:36

which has subsequently started to

22:38

make sense for the organization.

22:40

So there's many different reasons

22:43

why certain companies adopt certain

22:45

technologies. But it

22:47

doesn't always make a ton

22:49

of sense. Sometimes

22:52

there's externalities that drive that.

22:55

But number one, I would say, is

22:58

willingness. And within that willingness,

23:00

there's definitely a piece of

23:02

what I would say, the

23:04

management of career risk of

23:07

individuals in the middle management

23:09

who actually might be the ones actually making

23:12

the decisions, actually doing the work and actually

23:14

taking the risk. Honestly, as

23:16

an executive, as what I am, it's

23:19

easy for me to wave my hands and

23:21

say, innovation is great and collaboration is wonderful.

23:24

But in the end, when the rubber hits

23:26

the road in that middle management, that's where

23:28

people are taking a risk on

23:31

a new thing. So

23:33

as a technology provider, I have

23:35

to be very empathic

23:37

towards those individuals who

23:40

are taking a risk within their

23:43

organization. They were doing a process,

23:45

a value creation process in

23:47

a certain way. And now, they want

23:49

to do it in a different way, which

23:52

tells me that there's a

23:54

piece of risk in there and they're willing

23:56

to manage it and they're willing to let

23:58

us help them with our own. process. I

24:00

mean there's a lot of people

24:04

who are really quite careful with

24:08

that too. So you talked a lot about risk,

24:10

Justine, and this sort of gets back to

24:13

one of my questions right at the start

24:15

was could we change modern geospatial

24:17

to mature geospatial? All of these elements that

24:19

we named right at the start, the cloud,

24:22

smart space, open source data, standards, AI

24:24

algorithms, smart devices, these are relatively mature,

24:26

at least in my mind. Not to say

24:29

they're stagnated but they've been around for a

24:31

while, they're well understood and I think risk

24:33

for organizations. Not showing up with something brand

24:35

new, showing up with something that is mature,

24:38

something that is modern. And I think too

24:40

that larger organizations, and please correct me on

24:42

this, I think they are probably more

24:47

risk adverse than they are price sensitive. I totally agree

24:49

with that statement. I

24:51

just think the word mature makes it sound like it's

24:53

old. But you know, whatever. Different

24:55

people see different words in different ways. I

24:57

think we're getting at the same, the same

25:01

idea. It comes down to nomenclature and

25:03

sort of the understanding of different things.

25:06

The key idea here is finding

25:09

a way to raise expectations of

25:13

broader organizations by

25:16

illustrating the possible through

25:20

exemplar applications. So that's what I say to my team.

25:23

We need to provide excellence

25:27

to the people who are excellence.

25:30

So the broader community

25:33

understands what is possible when we

25:35

think about modern geospatial. When we

25:38

think about applying the cloud, when

25:40

we think about all

25:42

those sensors floating around in low Earth

25:44

orbit. All these things that

25:46

are now possible that weren't before. When we

25:48

think about 8 billion

25:51

GPS enabled smart devices like

25:53

on the population of our

25:56

planet. That wasn't

25:58

possible a decade. to go.

26:00

And now a lot of those devices

26:03

even have lidar built in. Like what

26:05

does that even mean for mapping? All

26:07

these questions are really interesting and

26:10

I see kind of hard to parse,

26:12

but thinking about this notion

26:14

of exemplar applications

26:17

and just raising expectations

26:20

and encouraging the geospatial community not

26:23

to do the minimum but to

26:25

do the possible. That's

26:27

where I have been trying to

26:29

encourage my team to go. But

26:31

that's also within the context

26:34

of this is the exemplar, but

26:36

we can move you towards that because

26:38

we all know that life is a

26:41

spectrum. You're not just there. You

26:43

don't just get there by paying enough

26:45

money. You have to move your organization

26:48

incrementally towards this

26:50

notional sort of exemplar situation,

26:54

which means that it's a vision,

26:57

not a goal because unfortunately

27:00

that exemplar is always going to

27:02

get further away. There's always going

27:04

to be something new

27:06

happening and that's good. That will

27:10

allow us one day to fly

27:12

to Mars and all the rest of it. But as

27:15

we move up or move forward,

27:18

side note, it kind of bugs me when

27:20

people say move forward because I'm never sure

27:22

what direction forward is. But nevertheless, I'll take

27:24

a step back. As

27:26

we advance again, forward

27:28

direction, I don't know, as we make our

27:31

technology better, our expectation of

27:33

technology should also change. So we

27:35

need to make sure that as

27:37

enterprises, they don't get left behind,

27:39

that they're pushed forward, that there

27:41

is a need,

27:44

a desire, an expectation, that

27:46

technology can move at an

27:49

appropriate pace. I think injecting

27:51

that higher level of expectation

27:54

into the technology stacks of

27:56

large organizations is important. natively,

28:01

they have native expectations, i.e. they

28:04

have high expectations built into their genetics

28:07

but some really don't. And those

28:09

are the ones that we really need to empower,

28:11

I think, with some good thinking. And

28:14

just a second, I want to ask a question

28:16

about making promises that we can keep because I

28:18

think when you show up with these

28:20

grand ideas, you also need to make a promise

28:22

that you can keep. And I think broken promises

28:24

are part of the reasons why organizations

28:26

are less willing to take on this

28:29

risk and to change. We'll

28:31

leave that just for a second. Do you see

28:33

the gap between what we could consider modern

28:36

and innovative? Do you see

28:38

that shortening with time? So you've

28:40

owned or operated SparkGEO

28:43

for, what do you say, 10 years now?

28:45

Have you seen a change in that

28:47

gap or has it remained relatively constant?

28:50

That gap definitely fluctuates. I would hazard that.

28:52

So, yeah, SparkGEO has been there for 14

28:54

years, my gosh. I would hazard that by

28:56

saying that most of the work we did

28:58

in the first few years of SparkGEO was

29:00

very much in the tech sector. So

29:03

we didn't do a large amount

29:05

of what I would call enterprise-oriented

29:07

geospatial activity at that

29:10

point, except a couple

29:12

of notable exceptions around Google

29:14

Maps implementations like ATM finders and

29:16

stuff and such like that. So

29:19

it was like overly kind of user-centric,

29:21

slightly innovative for the time kind

29:23

of activity. But we weren't

29:26

rebuilding major geospatial

29:28

systems inside enterprise. So I can't

29:30

really comment on what it was

29:32

like when we first started out.

29:34

But I would say that I

29:37

think these complementary assets

29:39

have accelerated in their

29:41

own domains significantly

29:44

within the last five years. We

29:46

look at cloud technology. It's got

29:49

so much wildly more capable. It

29:52

seems very few organizations think about doing

29:54

on-prem work, except within

29:56

the context of higher security

29:58

needs. notable exceptions,

30:01

37 signals, for instance, are

30:03

very vocal about building systems which are not

30:06

cloud-based these days, which is fine. I mean,

30:08

it's good to have that argument

30:11

being well articulated by that team. But

30:14

I would say that

30:16

cloud technology for geospatial

30:18

as a big,

30:20

large data play,

30:22

which is what geospatial really is,

30:24

is a massive enabler. And it

30:26

has enabled, in particular, the commercial

30:28

space sector, the EO sector, so

30:30

smart space enabling EO, the

30:32

cloud enabling EO through storage,

30:35

AI and algorithms enabling EO

30:37

through the pipeline

30:39

delivery of algorithms

30:41

through the cloud to create

30:44

analytics. That's a workflow. I

30:47

mean, then publishing those analytics with

30:49

an open standard is so easily

30:51

consumable by other organizations to collide different

30:54

data with it. All that stuff

30:56

is within this kind of Venn diagram.

30:59

And all those things are

31:01

growing and evolving independently of

31:04

each other. Each of those things

31:06

independently making this concept of

31:09

modern geospatial more functional

31:11

every day. So thinking about

31:13

how all those things are going together,

31:15

your notes on making

31:17

promises is absolutely

31:20

spot on. I think

31:22

Earth observation in the

31:24

early 2000s made a lot of promises

31:26

which were not kept. And

31:29

I'm not even sure those promises were

31:31

made by the Earth observation sector. I

31:33

think they were sort of

31:35

made by Hollywood and the

31:37

Earth observation people were left holding

31:41

very hard expectation of

31:44

video from space of anywhere at

31:47

any time, which is so

31:49

far from the reality. It's

31:51

almost comedic, but I think

31:53

it's still a really important

31:56

concept because I think a lot of those

31:58

promises can be kept. just really

32:00

hard to manage for. Does

32:05

that make sense? Yeah, it really does make sense. But

32:08

I think the reason I want to mention it is because I think

32:10

it's really important. If you're going to show up to an

32:12

organization and say, hey, we're with you on

32:14

this journey and my guess is an organization being risk-adverse,

32:19

they want you to be there also next year and the year

32:21

after that. They don't want to work

32:23

with multiple different partners, a

32:26

new partner every month. That's not what they're into. Great. You're

32:28

going to be here for the next five years and in

32:30

that time, we're going to move from here to there. I

32:33

think that if you can make that promise

32:35

and actually fulfill it and keep the promise,

32:38

I think you're really going to make some

32:40

big changes happen, not just

32:42

in geospatial of course in terms of

32:44

modern geospatial, but also the flow

32:46

and effects of that are going to be humongous. But I think

32:49

we need to make those longer

32:51

term promises and keep them. Yeah,

32:53

and I think that's credible these

32:55

days. I think that's very possible.

32:57

I see a number of organizations

32:59

on the market who are helping

33:01

larger enterprise organizations manage

33:04

for innovation and

33:06

manage for advancement. And what

33:09

we've been most challenged with since far as

33:11

geo recently hasn't been the

33:13

deployment of geospatial code or anything

33:16

like that. It's learning how to

33:19

help organizations change, which

33:21

is super kind of business-y and you

33:24

see all this stuff on the internet

33:26

about change management and transformation this and

33:28

all the rest of it. But

33:31

in reality, having a

33:33

level of empathy around helping

33:35

organizations and ultimately people because it's

33:37

people that are making decisions and it's

33:40

people that are having to do a

33:42

new thing and

33:44

it's middle management who ultimately have to

33:46

lead. Helping those

33:49

individuals win is literally

33:52

the purpose of our organization's existence now, which

33:55

is so interesting. So yeah, we

33:57

write code and yeah, we do

33:59

very... interesting cloud deployments

34:02

and we talk to interesting

34:04

geospatial companies all the time. But

34:06

ultimately, our job is to help

34:09

organizations win through geospatial.

34:11

And winning sounds so binary.

34:14

Winning has got many different

34:16

connotations. And I'm not winning, and I'm by

34:19

no means a zero-sum game guy. I

34:21

just want an organization to succeed through

34:24

the use of geospatial technology. And

34:26

in many ways, this notion of

34:28

winning is confusing because

34:31

I think you could also win in collaboration. You

34:33

don't have to win on your own. I said

34:37

it in a video we made years ago, but

34:40

I think those organizations that are willing

34:42

to team up and are willing to

34:44

collaborate will necessarily

34:47

out-compete anyone who's not because it's

34:49

very hard to do any

34:51

of this kind of stuff on your own. It's

34:53

much, much easier when you have a team, when

34:56

you collaborate, when you collaborate with different

34:59

agile organizations. Almost everything

35:01

gets easier when you have teams.

35:03

Not necessarily big teams, but just

35:05

teams of different people and teams

35:07

of different organizations partnering

35:10

because you get this diversity of thought. So

35:12

there's a whole bunch of different interesting elements in

35:14

there to unpack. Yeah, there sure is. I want

35:17

to stay with this idea of winning just for

35:19

a second because I think it's important

35:21

to emphasize that a win for an

35:23

organization is one thing, but throughout the

35:25

different levels in that organization and right

35:27

down to individuals, they all need to

35:29

win too, in some way, shape or

35:31

form. I think this is not just

35:33

important for people starting businesses in the

35:35

geospatial world, but I think it's really

35:37

important for practitioners as well. You

35:40

get to interesting work if

35:42

you make it a win for somebody else. For

35:45

me anyway, this is a really hard lesson

35:48

to learn. I've tried to drag organizations and

35:50

at the end of the day, people kicking

35:52

and screaming into the past and from

35:55

the deep, deep past into the more

35:57

recent past and it's been tough. it

36:00

hasn't been an immediate win for my

36:04

behalf, a total fail. But my

36:07

learning for

36:09

this person, what would be a win at the

36:13

organization as a whole? Those are

36:15

completely different things, but they need to

36:17

be packaged together into whatever it is

36:19

that you're promoting, selling, trying

36:22

to do. Yeah, it's so interesting.

36:24

I remember my second job, I

36:26

worked in Perth and

36:28

Kenross Council, this is in

36:30

Scotland, as their corporate

36:32

address gazetteer engineer.

36:35

And so there was this big movement in the UK

36:38

around normalizing addresses,

36:40

which sounds like the most stupid thing. But

36:43

in reality, in a city council like Perth

36:45

and Kenross Council, there would be about four

36:47

or five different address databases. So there'd be

36:49

a health one, there'd be a tax one,

36:52

there'd be an education one, blah, blah, blah.

36:54

And the idea was, let's squish it all into

36:57

one. So there would be a

36:59

single view of addresses in

37:01

one city council. And then you can

37:04

multiply that up across all the councils.

37:06

So there'd be like this

37:08

one view of addresses in

37:10

the UK. It's a great idea, BS7, triple

37:12

six, ingrained into

37:15

my existence. And so me and my

37:17

boss, Ewan Walker, we would

37:19

get all these addresses and we'd have a piece of

37:21

software. And we would squish them all together,

37:23

which is the right address. That's the right address. A

37:26

lot of it was automated, but it was

37:28

surprisingly manual, as you can imagine. Anyway, we

37:30

ended up having to go to this point

37:32

in our project where we would

37:34

be talking to all the users of the

37:37

address data. And we would be like,

37:39

okay, so we've got this new address database. It's

37:41

going to be amazing. It's way more accurate. It's

37:43

way, it's great. How do you use addresses in

37:46

your day-to-day business? So it's like classic

37:49

business process modeling. And what I

37:51

came to realize, and I can't remember if

37:53

it was an observation from you or myself,

37:56

but the point is we

37:58

realized that... someone

38:00

described their job, what their

38:02

job title was, and what

38:04

their boss thought they did

38:07

were three entirely different processes,

38:10

which was really interesting to figure out. And I

38:12

think about that in terms of what

38:14

you're just saying around deploying new

38:17

technologies and change management. So

38:19

actually finding out what somebody does,

38:21

like what buttons do you press

38:23

to do this thing? And what

38:25

boxes do you click to make

38:27

this thing happen? And then asking

38:29

them to describe what they do.

38:32

It's so interesting to find out,

38:34

oh, actually you don't

38:36

do that. You actually circumvent that entire

38:39

process by doing this other thing instead.

38:41

And if I give you something that's

38:44

going to be slower than this other

38:46

thing that you figured out yourself through

38:48

whatever purpose, then you're going to be

38:50

upset. And it's not going to work. Or if I give

38:52

you this new process, which

38:54

for some reason doesn't do this

38:56

other thing, which you like

38:58

to do, then you're not going

39:01

to do it. So it's all this

39:03

stuff, which is really interesting. So finding

39:05

out how you can help an organization

39:08

win by actually digging

39:10

right into the nuts and bolts

39:12

of what a company does and

39:14

what individuals do on a day-to-day

39:16

basis is so important. But boy,

39:19

at scale, that's incredibly hard to

39:21

do. It's a very,

39:23

very, very manual consulting

39:26

thing just to sit around and actually

39:28

watch somebody do something. And

39:30

then compare that thing that you're

39:32

watching them do to how

39:34

they describe it. It's such an

39:37

interesting process to go through. I

39:39

mean, I say this a lot, but almost

39:41

every technology problem is

39:44

actually a human problem in disguise.

39:46

So how

39:49

do you solve this individual's problem, make their

39:51

life easier, make something go faster?

39:53

And you do it through

39:55

an air quotes, the guise of technology.

39:57

And I think that's such an interesting

40:00

process. interesting thing. So when you start

40:02

thinking about modern geospatial, the

40:04

cloud has such an

40:06

opportunity to provide

40:09

technology at a much faster

40:11

pace. Smart

40:13

devices have this opportunity for you

40:15

to do things in the field

40:18

more effectively and with much better user

40:20

interfaces than you ever had before. AI

40:24

acts as your co-pilot. I mean, AI

40:26

allows you to make better decisions faster. And

40:28

then smart space allows us to look in

40:31

places that we can never look before. So if

40:33

we care about monitoring

40:35

landscape changes, then we

40:37

can do that. We can do that not just

40:39

for one house, but a portfolio of mortgages. Suddenly

40:43

that scale becomes possible

40:45

because you've got all this other stuff.

40:48

All this stuff that you kind of had to

40:50

just assume was okay. Now

40:52

you can actually check because you can see

40:54

all the mortgages for our bank across

40:57

North America or all the mortgages

40:59

in Florida. And they're like, how much flood risk

41:01

do we actually have? I'm not sure. Wouldn't it

41:03

be nice to know? Or do you not want to know? I

41:05

mean, those are really interesting human questions.

41:07

And in the end, it is

41:10

a human question because we can choose to

41:12

know this information or we can

41:14

choose to not know. Another thing I

41:16

often say to my team is like, there's not

41:18

many industries that are willing

41:21

to pay for bad news. So think

41:23

about that. How

41:26

often is landscape change data

41:29

giving you good news? So think

41:31

about those two things and then

41:33

think about how to describe what it is that we're

41:36

doing in the most effective manner. And

41:38

there's a lot of nuance in

41:40

there, but it's definitely

41:43

worth ruminating on. I

41:45

just want to share a little story about the

41:48

idea that people don't want to pay for bad

41:50

news. I talked to a company a while back.

41:52

They had this interesting idea. They could

41:54

look for water leaks from space. Great

41:57

idea. Great idea, right? Then

42:00

they would show up to, they

42:04

had a couple of sort of leaps in the process

42:06

which led to them being a success. One of

42:08

them was the observation that companies were more willing

42:10

to pay for if the cost

42:12

was OPEX as opposed to CAPEX. Another one

42:14

was that if they showed

42:16

people what they could do, that was a big

42:19

leap forward. That meant that they got further in

42:21

the sales process each time because they said, I'm

42:23

not going to tell you, I'm going to show

42:25

you what I can do. One of the last

42:27

ones was not to overwhelm people because let's say

42:30

they went to the utilities company

42:32

in Copenhagen and said, look, here are all of

42:34

your leaks. Here are all of your

42:36

problems. Expose the lot for them. You

42:38

would think, oh, great, now I can go and

42:40

fix them. It wasn't like that. It was

42:43

overwhelming. People didn't want to know where they

42:45

all were. They just wanted to know whether

42:47

ones they should be fixing. They wanted

42:49

someone to break down that problem and to bite size

42:51

chunks. That's what they

42:53

did. This was another sort of leap forward for them

42:55

as a company. Understanding

42:57

that people need to

43:00

be... Don't create another problem for them. Don't

43:02

overwhelm them. Give it to them in small

43:04

chunks in things they can solve and win.

43:08

Give me my top 10 leaks. Give

43:12

me my next top 10. It's going wild. Make

43:16

it a win for them. It wasn't a win going, oh, this is going

43:18

to take us 58 years to

43:20

figure all this stuff out. A win was, I can

43:22

do something today. I don't want

43:24

to know why I'm not an Olympic athlete. I

43:27

just want to know why I

43:29

could be a little bit better than I

43:31

am tomorrow. It makes sense. If

43:36

you give me a list of all my feelings, I

43:38

won't even bother getting off the couch. If you just

43:40

tell me a little thing I can do, then maybe

43:43

I will. It makes a lot

43:45

of sense. Do

43:48

you have any predictions for next year, for 2024? I

43:52

think we're going to see a lot

43:54

of willingness

43:56

to modernize life. Last

44:00

year was a bit

44:03

of a kick in the pants for the

44:05

technology sector, I would say. But

44:07

I feel that there will be a little bit

44:09

more capital flowing towards

44:11

efficiency. I think supply

44:13

chain concerns are going to go

44:16

through the roof again,

44:18

seeing very difficult times in the Red

44:20

Sea, which means that supply chains

44:22

are going to be stretched

44:24

in many different directions. So

44:26

understanding supply chain risk, I think

44:29

will be really interesting. We're

44:31

also in the midst of an El Nino, so who

44:33

knows what's going to happen in terms of climate

44:36

related stoppages

44:38

and delays and such. So

44:40

yeah, I think there'll be a lot of talk

44:42

about supply chains. In

44:44

the supply chain, there is a lot of

44:47

talk about logistics. And logistics is a central

44:49

question of geospatial, it's a question of where.

44:51

So we as a

44:53

community should be deeply involved in

44:56

everything around logistics. And

44:59

I think there are worthwhile

45:02

Earth observation activities, which would help

45:04

that. But I think there's

45:06

a lot in that smart devices

45:08

space and AI space, which is, and

45:11

in fact, open standards

45:13

and open data space where that

45:16

matters a lot too. So I

45:18

would say from an enterprise perspective, those

45:20

two things are going to be important.

45:22

I think commercial space will continue

45:24

to be important and

45:26

interesting. I think

45:28

if we get Starship working, then there

45:30

are going to be even more

45:33

sensors in the sky. And

45:35

I think I would challenge

45:37

the broader geospatial community

45:40

with the assertion that I

45:42

don't think chat GPT understands

45:44

space. I think it implicitly

45:47

understands location through text. But

45:50

having a generative spatial

45:53

model would be really

45:55

interesting. I don't know who's working on

45:57

that. But that would be... somewhat

46:01

revolutionary geospatial application

46:06

stroke opportunity. So I don't think it might, it might not happen next

46:09

year, but I mean it's going to happen. So

46:11

someone is going to create

46:13

that and then deploy it and

46:15

it'll be game-changing. So those are

46:18

my forward-looking

46:20

observations. You're

46:22

right, that question was unfair. That

46:26

was beautiful. Well done. Well done. And thank

46:28

you very much for mentioning chat GPT. I

46:30

think it's always it's great to have that in

46:32

the conversation somewhere along the line. I

46:34

also wanted to highlight again, you said

46:37

organizations be more willing to modernize,

46:39

not to innovate, back to the

46:41

idea of modern geospatial modernization.

46:43

I think that's a really important take-home message

46:45

for a lot of people that are going

46:47

to listen to this. Appreciate that. Will,

46:51

fantastic. Really enjoyed the conversation. Thank you very much

46:53

for showing up. Where can people go

46:55

if they want to reach out to you, if they want to

46:57

follow along, if they want to continue

46:59

this conversation? Yeah, I'm easy to find

47:01

on LinkedIn and X, Twitter

47:03

X. Also sparkgeo.com

47:07

for our corporate website and by

47:09

sub-stack is strategicgeospatial.com so

47:12

you can find that there

47:14

too. Those would be the main

47:16

main spots. Thanks very much, Will. Really appreciate

47:18

your time. Super cool. Thanks very much, Daniel.

47:20

Take care. Thank

47:23

you very much for listening all the way to the

47:25

end. I really appreciate it. There'll be a bunch of

47:27

links in the show notes today. One of them will

47:29

be to our sponsor Scribble Maps. So

47:32

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