Fixing Exploration Funding with Jon Hronsky

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Righto buddy miners, welcome to
another bloody JD and LEGC

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spectacular brought to you by
Axis Mining Technology, the

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trusted advisor for Drill Isle
survey instrumentation and their

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best people to talk to on the
phone about it 'cause there's a

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guru on the end of the line
every single time.

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Love your work Axis.
Oh, that's it.

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Nice.
So this was a bit of a little

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pre digger's amble that you too
kindly did while I went to a

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golf day.
Thank you very much by the way,

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I was doing some DD out there.
BDD.

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DDDDD.
Who we got?

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So we've got John Ronsky here
today and we've also got Ahmed

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to help us navigate the
conversation.

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John is a super switched on
geoscientist and Ahmed helped us

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kind of get through that more
technical part of the

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conversation.
I'd listen to John on a few

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podcasts he'd done in the past
and I thought the ideas he had

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were absolutely fascinating.
This is a guy with a couple

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decades at at Western mining few
years in there at BHB.

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Then he's been running his own
bit.

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He's been teaching out of out of
UWA for quite some time.

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And he's, he's got a few
different talking points that I

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find absolutely fascinating in
and around our kind of home

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ground of talking about the
funding of mining companies,

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getting exploration projects
online.

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And we're going to talk through
things like the.

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Search spaces.
Search spaces, that's one of

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these sort of big features about
how companies go about

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exploration.
He's got models and you know, a

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lot of it kind of ties in with
what BHB Explorer has kind of

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done, although this is a concept
model exactly.

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He'd come up with this concept a
good sort of decade ago now.

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So I think with that, we'll
we'll rip into it.

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Right now, good stuff.
Here we go.

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All right, money miners, we've
got a we've got a special chat

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here with John Ronski, Ahmad
Ali, a bit of a different line

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up today, but we're pretty
excited to to get into this.

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John, you've, you've spoken a
lot in, in over your career

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about a topic that's sort of
near and dear to our heart.

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But the way I want to kind of
segue into this is that that

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crossover between business and
the science of exploration

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discovery.
And you've spoken about four

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rules for exploration companies
in the past.

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And that kind of leads us into
talking about search spaces and,

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and the funding model for, for
juniors out there.

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And I want to start by hearing
about search spaces these these

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four rules that you have for
exploration companies out there

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and then kind of go from there.
OK.

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Well, the first rule is decide
what you're looking for, because

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you've got to focus on something
that's going to make a

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difference to you as a business.
And if you're BHP, that's one

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thing.
If you're a, a, a junior, you

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know, trying to break into the
industry, that's another thing.

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So you have to consider the
thresholds, you have to

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consider, you know, the, the
capital, you have to consider

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the risk that you you can take.
So for example, if you're a BHP,

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you have to be looking for a
very, very large deposit,

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something that can replace an
Escondido or an Olympic dam.

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So yeah, we in life have this
sort of risk reward

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relationship.
So if you want something that

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has a very, very high reward,
you have to be taking a high

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risk.
So if you're genuinely in the

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game to find one of those
deposits, it influences your

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strategy.
So that's the starting point.

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You've got to decide what you're
looking for and, and what's

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going to make a difference.
The second point is you have to

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identify a valid search space
where that could be.

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You know, it's no good saying,
well, I want to find this giant

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deposit, but it has to be within
50 kilometres of my existing

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infrastructure.
And I don't want it to be too

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deep or whatever because that
may well be a search space that

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doesn't exist.
So when we talk about the

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concept of search space, what
we're really saying is the

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search space is the intersection
between what we know

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geologically about what's going
to control the location of a

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deposit in space and what we
know about the economic

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environment.
And critically, the history of

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every bit of exploration that's
gone on before.

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Because if someone else has
already sterilised that search

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base, it doesn't matter how
smart your geology is, it

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doesn't matter how smart your
detection technology is.

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We already know it's not there.
It's a very, I mean, in some

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ways exploration is very
Bayesian approach.

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You know, you start off with I
don't know, and you collect more

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data and each bit of new data,
you know, reinforces a story.

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Either it is perspective or it
isn't perspective.

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And of course the big challenge
with the search base idea is

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that we find our biggest
deposits where we have the lease

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data.
Really, really important

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concept.
Kind of an obvious concept, but

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I restate it now because in the
era we currently live in where

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we hear a lot of stuff about big
data and AI, and the idea is,

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well, actually we've got lots of
data.

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All we need to do is analyse it
in a smart way and we'll find

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the deposits.
I fundamentally disagree with

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because we don't find deposits
where we have a lot of data.

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We find deposits in volumes
where we don't have any data or

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very, very limited data.
So that's that's a search based

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concept.
And I think just to interject

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here, I think one of the other
important things about search

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space is that they can change
over time as well.

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Yeah.
So, so lithium will be one,

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right, where people discovered,
you know, tin deposits before,

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but lithium was obviously not
invoked then.

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So no one actually did anything.
So yeah.

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So one of the things I think
here is that, yeah, like to

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John's comment that you often
find these things where there's

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no data.
Well, it has to be data that's

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relevant to what, what the
problem you're trying to solve

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as well is that they, they could
be actually data rich areas, but

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it's just that we haven't looked
for the specific thing like

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lithium in that data set and
hence we might have overlooked

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it.
So yes, so the concept of search

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space is, is like, you know,
it's not just a physical space

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that you will kind of look for.
It's also a philosophical kind

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of space and like, well, you
know, like how do your ideas

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evolve over time?
How does the technology change?

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You know, technology can have a
fundamental effect on how you

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find things.
You know, the detection limit of

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a certain technique gets lower
all of a sudden, you know, like

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you can, you can review that
data differently.

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So I often find that search
space becomes this concept where

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people think it's physical.
They go, oh, yeah, like I'm

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going to go physically out to
the edge of the world because no

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one's explored there.
Well actually search spaces can

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exist in well explored terrains
as well.

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It's just that you have changed
the the parameters of what you

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are looking for, hence you've
opened opened up a new search

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space in that sense.
Yeah, No, 100%, Ahmad, search

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space is, is, it's an abstract
parameter space.

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I mean, I didn't want to become
too technical about it, but

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there's a number of different
parameters that will govern

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whether a search space exists,
you know, including all the ones

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that you talked about that, you
know, the commercial regime in a

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country is an important part of
that search space.

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But just to to pick up a point
about different commodities

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actually now before I do that,
two points about search space.

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One, the reason why we coined
the term search space rather

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than the other concept of
exploration maturity, which you

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often hear people talk about
exploration maturity, is we felt

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like maturity seemed to relate
to just how much work had gone

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on in a particular area.
And if that work had not been

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been effective for the
particular search base that we

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were interested in, it was
irrelevant.

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So yeah, some textbook examples
from the history of exploration

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WA, the Cambalda nickel deposit
was discovered in January 1966.

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And up to that point within the
Yogan Craton of WA, no one knew

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anything about the presence of
nickel.

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In fact, no one knew that these
commodit rocks could host

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nickel.
And the world expert said, I

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know you don't find nickel in
those rocks because you found

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nickel in places like Sudbury.
So that instant that created a

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new search space.
Now that that result, that drill

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hole was basically right in the
middle of the Red Hill gold

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mining area.
So it was right in the middle of

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the of a almost on.
You know, some of those samples

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of nickel were first found on
the dumps of old gold mines.

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And of course the Kalgoorlie had
been at that point for 70 years,

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a major gold mining centre.
But that reset the search space

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and the more the most recent
sort of reset of search space

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we've had has been the lithium
boom.

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So, you know, if we're in a
world where we're looking for

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the traditional commodities of
gold and copper, which have been

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the two most important ones
we've explored for for a long

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time, it's a pretty reasonable
assumption globally to say that

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not many of these deposits are
going to be sticking out of the

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ground with an obvious surface
expression, right.

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This wasn't true of lithium 10
years ago because people hadn't

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focused on that.
So you could still go to places

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like Pill and Gore and say, oh,
there's a big outcropping Ridge

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of pegmatite.
OK, fantastic.

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Because the search space for
lithium was much less mature

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than, say, the search space for
gold.

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I mean, people have been looking
for gold around the world for a

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very long time.
So you know most of the surface

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with and you know, one of the
things to understand about

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search space is the technologies
we have for exploring things at

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the surface are vastly more
effective and cost, you know,

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cheaper than technologies for
exploring below the subsurface,

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even like only a few metres if
it's concealed.

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So this sort of.
Concept it, you know, we're

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getting right into the the
geology here, but we come at it

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from an investment lens
predominantly on on the show

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here.
Is this a concept you think is

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is widely held in the in the
geological community?

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Look, I thinking, I think
increasingly so and it is

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actually very relevant to
investment because if we look at

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the the opportunities for
investment in say the

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greenfields exploration space,
to me the valid search base

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criteria is a really important
philtre that would probably in

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my opinion separate about 20% of
the companies that actually have

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a chance and 80% that probably
don't.

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So going to an area where there
might have been lots of sniffs

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of mineralization, lots of drill
holes, but no actual discovery

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and going back to those areas
without coming up with some new

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search based concept is not
going to be successful.

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But often times, you know,
investors who don't see things

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through that lens will put money
into those sort of

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opportunities, right?
So I actually think that the

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search based concept, well our
teachers course, senior

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exploration management and one
of the things I say is the one

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concept that I'd like you to
take away from this course more

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than anything else is the
concept of the search space.

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Why?
Because it's the central concept

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that links the scientific things
that we do in this business with

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the business outcomes, with the
commercial outcomes.

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If you don't understand search
space, you really don't have the

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key central concept to
understand how mineral

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exploration delivers value to
investors.

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And I, and I think that concept
about, you know, like why it's

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important is, yeah, like maybe
from, if you're investing in a

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consumer product or something
like that, I think it's slightly

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different in that, yeah, like
you can always grow your

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consumer market in a different
way.

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You know, you can sell shoes,
but you can sell clothes at the

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same time, or you can sell hats.
You know, there's always

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something that you can add.
Whereas I think in, in, in

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mineral exploration, you know,
one of the key aspects of why

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search space is important is
because they're kind of

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exhaustive.
Like once someone has explored

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an area, it it kind of gets
removed.

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It's a non renewable kind of
yeah.

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So, so once someone has found
something there and they've

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mined it, that search space is
effectively kind of dead now.

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Or in order to grow that search
space, if you want to go deeper

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or something like that, there's
an economic parameter that comes

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00:12:01,120 --> 00:12:01,920
in.
It's not going to be more

228
00:12:01,920 --> 00:12:02,960
expensive.
Yeah.

229
00:12:02,960 --> 00:12:07,400
It's going to be harder to find
as a search space matures, you

230
00:12:07,400 --> 00:12:09,480
know, like the easier things
should be found first and the

231
00:12:09,480 --> 00:12:12,080
harder things now will be, will
be the ones that you'll be

232
00:12:12,080 --> 00:12:14,200
looking for.
And there's a pretty startling

233
00:12:14,200 --> 00:12:16,520
fact, though, that flies in the
face of that which you said in a

234
00:12:16,520 --> 00:12:20,640
previous interview, John, that
roughly 80% of money going into

235
00:12:20,640 --> 00:12:24,360
the ground is spent on depleted
search spaces.

236
00:12:24,720 --> 00:12:30,720
Why is this still the case?
Because the perception of, I

237
00:12:30,720 --> 00:12:32,960
think it's an incorrect
perception of risk, right.

238
00:12:33,520 --> 00:12:39,240
And let me just tell it from the
perspective if I'm a some sort

239
00:12:39,240 --> 00:12:43,200
of executive in some large
mining company and I can have a

240
00:12:43,200 --> 00:12:46,600
programme where I'm going to go
out into areas with no known

241
00:12:46,600 --> 00:12:49,800
mineralisation and it might be
several years before I can

242
00:12:49,800 --> 00:12:51,920
return a result.
But that might be what I need to

243
00:12:51,920 --> 00:12:54,120
do to make the discovery this
company needs.

244
00:12:54,400 --> 00:12:57,680
Or I can do joint ventures on
half a dozen projects where

245
00:12:57,680 --> 00:12:59,720
there's quite a lot of known
mineralisation.

246
00:13:00,040 --> 00:13:02,280
And I know that I'll be able to
report every quarter.

247
00:13:02,280 --> 00:13:04,400
I've got this drill hole
intersection and I've got this

248
00:13:04,400 --> 00:13:07,240
drill hole intersection.
Which option is lower risk for

249
00:13:07,240 --> 00:13:09,160
me professionally and
personally, right.

250
00:13:09,960 --> 00:13:13,120
And which option is lower risk
or higher risk for the company?

251
00:13:13,120 --> 00:13:15,080
They're not the same.
And.

252
00:13:15,960 --> 00:13:18,600
So just hang on a minute there.
We're talking about risk and

253
00:13:18,760 --> 00:13:20,760
reward.
And there's one company that

254
00:13:20,760 --> 00:13:23,440
popped into my mind and that's
MMS guys.

255
00:13:23,440 --> 00:13:26,960
Well, that like, well, in terms
of risk reward, like no risk,

256
00:13:27,360 --> 00:13:29,520
shit loads of reward.
That's it.

257
00:13:29,520 --> 00:13:31,720
They take the risk off your
hands.

258
00:13:31,800 --> 00:13:34,280
Yeah, they are the mining
company, trusted mining

259
00:13:34,280 --> 00:13:36,960
contractor out there.
And all I've made, all JD all

260
00:13:36,960 --> 00:13:40,200
think MMS are that good that
they probably don't even have

261
00:13:40,200 --> 00:13:42,280
risk either.
I think you're right.

262
00:13:42,840 --> 00:13:44,560
Yeah, absolutely.
And yet, you know what else

263
00:13:44,560 --> 00:13:47,920
stands out about MMS guys?
Bloody tailored service.

264
00:13:47,920 --> 00:13:51,840
They do they, you know, you've
got any problem, you just give

265
00:13:51,840 --> 00:13:54,200
Josh a buzz, they will sort it
out for you.

266
00:13:54,200 --> 00:13:57,600
I mean, we're talking about mine
site support, drill and busting

267
00:13:57,600 --> 00:13:59,760
services, contract mining
services.

268
00:13:59,760 --> 00:14:01,600
Obviously there's a few good
examples out there.

269
00:14:01,600 --> 00:14:05,160
Just Josh, it will talk you
through them dry and wet.

270
00:14:05,160 --> 00:14:08,240
Hire anything else you want.
And the tech, the Technical

271
00:14:08,240 --> 00:14:09,600
Support.
Technical.

272
00:14:09,600 --> 00:14:11,840
Evaluate the pit mate, don't
body.

273
00:14:11,840 --> 00:14:13,800
Try and figure out how to mine
it yourself.

274
00:14:13,800 --> 00:14:15,760
Get the miners to figure it out
for you.

275
00:14:15,760 --> 00:14:19,760
You're just moving dirt.
Love your work MMS, get on to

276
00:14:19,760 --> 00:14:22,160
them this good.
This is going to be how mining

277
00:14:22,160 --> 00:14:24,880
contracting is in the future.
Pioneering.

278
00:14:25,560 --> 00:14:26,040
Here we go.
Good.

279
00:14:26,200 --> 00:14:28,560
Work MMS.
We better get back to you, Jan.

280
00:14:29,040 --> 00:14:33,400
I think that the reality is
that, you know, particularly if

281
00:14:33,400 --> 00:14:38,400
you're going to fund expiration
from, you know, the risk capital

282
00:14:38,400 --> 00:14:42,480
market with a fairly sort of
volatile, fairly volatile source

283
00:14:42,480 --> 00:14:46,880
of capital, you, you, you need
to provide that excitement.

284
00:14:47,000 --> 00:14:49,800
Yeah, the idea of you've given
me your money and I'll report

285
00:14:49,800 --> 00:14:51,920
back to you in two years time
when I finish this programme.

286
00:14:52,040 --> 00:14:55,120
Who invests in that, right.
So that, so that's sort of the

287
00:14:55,120 --> 00:14:58,200
tension that that that goes on,
I think.

288
00:14:58,200 --> 00:15:00,280
I mean, effectively it's like,
you know, people will do what's

289
00:15:00,280 --> 00:15:03,960
expedient, either commercially
or, you know, from a point of

290
00:15:03,960 --> 00:15:06,160
view of releasing stuff to the
market or investor.

291
00:15:06,440 --> 00:15:09,960
Then I think what would be the
harder thing to do, which is

292
00:15:10,080 --> 00:15:11,520
exactly what John's kind of
talking about.

293
00:15:11,520 --> 00:15:13,320
Like, yeah, it would be harder
to go and say we're going to

294
00:15:13,320 --> 00:15:16,400
raise money and for three years
we probably won't release a

295
00:15:16,400 --> 00:15:19,680
single announcement.
But after that, we'll know, you

296
00:15:19,680 --> 00:15:21,320
know, people will go.
I'm out of here.

297
00:15:21,600 --> 00:15:24,520
Yeah, because there's a couple
questions I wanted to ask about

298
00:15:24,520 --> 00:15:28,680
that because there's the the
concept of the search pace makes

299
00:15:28,680 --> 00:15:32,400
so much sense, right?
It's it's, it's so logical, but

300
00:15:32,400 --> 00:15:38,120
actually practically getting
people in companies to do it is

301
00:15:38,120 --> 00:15:41,480
such another challenge, right?
You know, the business element

302
00:15:41,480 --> 00:15:45,920
comes in people, there's a
resistance against change.

303
00:15:47,320 --> 00:15:51,920
And I think the other thing
which was actually touched on,

304
00:15:51,920 --> 00:15:55,360
you know, in a great Live Wire
article earlier this week about

305
00:15:55,560 --> 00:15:58,000
people are scared to go to risky
jurisdictions.

306
00:15:58,000 --> 00:16:02,000
And it's often the pressure from
the public markets and, you

307
00:16:02,000 --> 00:16:07,360
know, public money to it's like,
why, why should I go pursue this

308
00:16:08,000 --> 00:16:12,680
risky, as you know, or good
asset in a risky jurisdiction

309
00:16:12,680 --> 00:16:15,560
here where I can just do
something safe and easy, you

310
00:16:15,560 --> 00:16:19,720
know, over here.
And it sort of talked about how

311
00:16:19,720 --> 00:16:22,680
there's this particular article
talked about how there's a

312
00:16:22,680 --> 00:16:26,440
tussle between, oh, we need more
copper, although there's copper

313
00:16:26,440 --> 00:16:29,840
over here or it's too risky.
So it's the site.

314
00:16:31,160 --> 00:16:32,840
How do you breach that?
I guess I.

315
00:16:32,840 --> 00:16:34,640
Mean I think one of the most
overused terms of mineral

316
00:16:34,640 --> 00:16:36,760
exploration is risk.
I think.

317
00:16:37,400 --> 00:16:38,800
Yeah.
Like when everyone says risk, I

318
00:16:38,800 --> 00:16:40,960
always like to ask the question
like, what risk are you actually

319
00:16:40,960 --> 00:16:44,240
talking about here, Right.
That I mean, like fundamentally

320
00:16:44,240 --> 00:16:47,600
mineral exploration is not a
risky business, like financially

321
00:16:47,600 --> 00:16:49,680
risky because you only lose the
money you put in.

322
00:16:50,360 --> 00:16:53,160
So you know exactly how much
you're going to lose at any

323
00:16:53,160 --> 00:16:55,280
point.
But now is there other risk in

324
00:16:55,280 --> 00:16:56,800
exploration?
Yeah, there's technical risk

325
00:16:56,800 --> 00:16:58,880
that could be jurisdictional
risk because you're going in a

326
00:16:58,880 --> 00:17:01,040
new country and you don't know
how to work there or anything

327
00:17:01,040 --> 00:17:01,640
like that.
It's.

328
00:17:01,640 --> 00:17:05,720
Career risk, that's the.
Big one, and I think that's, you

329
00:17:05,720 --> 00:17:09,599
know, like to your comment in
that, you know, like why people,

330
00:17:10,839 --> 00:17:13,359
you know, like why people are
pushed by investors to behave a

331
00:17:13,359 --> 00:17:17,160
certain way is because if I
think if overall the investment

332
00:17:17,160 --> 00:17:22,040
crowd maybe doesn't want to take
the long term risk of actually

333
00:17:22,040 --> 00:17:25,040
finding something or, you know,
'cause mineral exploration in a

334
00:17:25,040 --> 00:17:28,880
lot of sense in, in a new search
space is a learning kind of

335
00:17:28,880 --> 00:17:30,920
exercise.
And so, you know, so our

336
00:17:30,920 --> 00:17:34,160
investors, you know, like how
many investors are there that

337
00:17:34,160 --> 00:17:36,800
would fund companies to learn
for a couple of years before

338
00:17:36,800 --> 00:17:39,200
they actually do it?
I'm not sure there's a lot of

339
00:17:39,200 --> 00:17:42,000
them, right?
Absolutely, and what a good

340
00:17:42,000 --> 00:17:46,720
exploration company should do is
explore a project and then say,

341
00:17:46,720 --> 00:17:49,560
you know what, it's not here.
I'm moving on.

342
00:17:50,080 --> 00:17:52,960
Market often though wants to see
people persist.

343
00:17:52,960 --> 00:17:56,240
They say, well, you raise the
money for, you know, to to do

344
00:17:56,240 --> 00:17:57,760
this, that's what you have to
spend the money on.

345
00:17:57,760 --> 00:18:00,800
Even to the point the ASX says,
well, you basically got to show

346
00:18:00,800 --> 00:18:02,760
the first two years what you're
going to spend the money on.

347
00:18:02,960 --> 00:18:06,120
So if you have a concept, you
raise the money and in six

348
00:18:06,120 --> 00:18:07,240
months you've done the work and
gone.

349
00:18:07,240 --> 00:18:08,840
There's nothing there
technically.

350
00:18:08,840 --> 00:18:10,840
You still have to spend.
That's right.

351
00:18:11,080 --> 00:18:13,200
You know, and so some of these
things are perhaps well

352
00:18:13,200 --> 00:18:15,000
intentioned but naive.
Yeah.

353
00:18:15,720 --> 00:18:20,840
Look, the, the, the reality is
that the beauty about expiration

354
00:18:21,240 --> 00:18:25,200
is you only ever have to commit
funds up to a critical decision

355
00:18:25,200 --> 00:18:29,480
point.
So if you manage that well, you

356
00:18:29,480 --> 00:18:32,560
can be very effective with, with
your use of funds.

357
00:18:32,560 --> 00:18:36,000
And it has the advantage that,
you know, particularly if you're

358
00:18:36,000 --> 00:18:38,960
in a sort of larger mining
company is it is actually

359
00:18:38,960 --> 00:18:41,040
discretionary.
You don't have to spend the

360
00:18:41,040 --> 00:18:45,480
money and as opposed to doing a
very large, you know, billion

361
00:18:45,480 --> 00:18:47,960
dollar transaction, it either
fails or it doesn't.

362
00:18:48,320 --> 00:18:51,360
Yeah.
And and the, the consequences of

363
00:18:51,360 --> 00:18:55,720
that, I, I think it's really
important just on this, I

364
00:18:55,720 --> 00:18:59,440
totally agree with Ahmad.
The concept of risk is used,

365
00:18:59,880 --> 00:19:02,480
it's a very overused word and
it's used in a number of

366
00:19:02,480 --> 00:19:05,160
different contexts.
So there's probably about 10

367
00:19:05,160 --> 00:19:08,480
definitions of risk that are
used in the mining and mineral

368
00:19:08,480 --> 00:19:10,320
exploration industry.
And they're all different.

369
00:19:10,640 --> 00:19:13,720
But often people will have
conversations not realising that

370
00:19:14,080 --> 00:19:17,560
I'm using definition risk 7 and
they're using definition risk

371
00:19:17,560 --> 00:19:18,680
three.
Yeah.

372
00:19:18,720 --> 00:19:20,880
So this is this is part.
Of the problem and you can kind

373
00:19:20,880 --> 00:19:24,080
of manifest that like, you know,
like say in a, in a group, like,

374
00:19:24,080 --> 00:19:26,120
yeah, in a mineral exploration
company, you might have someone

375
00:19:26,120 --> 00:19:28,920
that's operational, someone
that's BD commercial and someone

376
00:19:28,920 --> 00:19:31,040
that's a geologist.
Now, they may all use the term

377
00:19:31,040 --> 00:19:33,120
risk, but in fact, they're
actually all talking about

378
00:19:33,120 --> 00:19:34,880
completely different types of
risk.

379
00:19:35,440 --> 00:19:38,240
So even in one conversation,
people will just say, well, you

380
00:19:38,240 --> 00:19:40,400
know, is it risky from a
geologist point of view?

381
00:19:40,400 --> 00:19:42,880
He's, you know, they're asking a
completely different question

382
00:19:42,880 --> 00:19:44,640
than what the commercial person
might be asking.

383
00:19:44,920 --> 00:19:48,640
So, you know, let me just use
that as one example to sort of

384
00:19:48,640 --> 00:19:53,960
illustrate that many people will
say Greenfield's exploration is

385
00:19:53,960 --> 00:19:56,760
more risky than Brownfield's
exploration as an axiom.

386
00:19:56,760 --> 00:20:00,160
You know, no one debates it.
But actually it's something that

387
00:20:00,160 --> 00:20:03,800
should be debated because if you
say I'm going to define risk as

388
00:20:03,800 --> 00:20:07,640
the probability of an economic
return on my investment, there's

389
00:20:07,640 --> 00:20:09,920
quite a lot of evidence to say
that's not the case.

390
00:20:10,760 --> 00:20:13,800
A few years ago, Mike Christie,
who's the boss of exploration

391
00:20:13,800 --> 00:20:16,320
for First Quantum.
Just did a very simple study,

392
00:20:16,440 --> 00:20:18,600
looked at all the copper mines
that had been found over a

393
00:20:18,600 --> 00:20:21,080
period of time and looked at
whether they were greenfields

394
00:20:21,080 --> 00:20:23,960
discoveries or brownfields
discoveries.

395
00:20:23,960 --> 00:20:26,480
And remember that probably 70 or
80% of the dollars went into

396
00:20:26,480 --> 00:20:30,520
brownfields and found
greenfields found by far away

397
00:20:30,600 --> 00:20:34,800
more copper, right?
So is it more risky because

398
00:20:34,800 --> 00:20:40,760
people confuse risk with the,
the probability of an individual

399
00:20:40,760 --> 00:20:44,360
opportunity being successful,
whereas risk from an investment

400
00:20:44,360 --> 00:20:47,480
perspective is a portfolio level
concept, right?

401
00:20:47,480 --> 00:20:50,560
Because you're not just
targeting 1 greenfields project

402
00:20:50,560 --> 00:20:52,080
and continuing to do that
forever.

403
00:20:52,360 --> 00:20:57,480
So that and they often confuse
the the the risk profile of

404
00:20:58,200 --> 00:21:01,600
high, high profile, very
successful periods of

405
00:21:01,600 --> 00:21:05,640
brownfields exploration with the
overall profile of the

406
00:21:05,640 --> 00:21:09,080
greenfields exploration history.
Yet we know that in in most

407
00:21:09,080 --> 00:21:11,960
situations, periods of
successful brownfields

408
00:21:11,960 --> 00:21:14,520
ultimately then replaced by
periods of unsuccessful.

409
00:21:14,680 --> 00:21:16,240
Why?
Because you're depleting the

410
00:21:16,240 --> 00:21:18,680
search space.
That that flies massively, I

411
00:21:18,680 --> 00:21:21,400
think in the in the face of a
commonly held view.

412
00:21:21,400 --> 00:21:25,000
The brownfields is how you how
you yield better results.

413
00:21:25,000 --> 00:21:26,160
What?
Why do you think that is the

414
00:21:26,640 --> 00:21:30,840
commonly held view?
There's a period of time where

415
00:21:30,840 --> 00:21:33,680
that really works.
So if I've made a Greenfields

416
00:21:33,680 --> 00:21:37,920
discovery in a new terrain,
right, and I don't know much

417
00:21:37,920 --> 00:21:42,160
about it, it makes sense for a
period of time to focus all my

418
00:21:42,160 --> 00:21:46,920
resources there and find all
those additional deposits

419
00:21:46,920 --> 00:21:49,800
because that's the sort of
embedded option value really

420
00:21:50,000 --> 00:21:52,320
that relates to the original
greenfields discovery.

421
00:21:52,520 --> 00:21:55,880
So what you're really doing is,
is just optimising the value of

422
00:21:55,880 --> 00:21:57,800
the original greenfields
discovery, because when we make

423
00:21:57,800 --> 00:22:01,160
our first discovery,
particularly in a, in a new

424
00:22:01,160 --> 00:22:03,920
terrain, there's often a lot
more to be found and that, and

425
00:22:03,920 --> 00:22:07,120
that's why there's a real value
to making those discoveries.

426
00:22:07,440 --> 00:22:11,960
But at some point, what happens?
And in most companies, in most

427
00:22:12,120 --> 00:22:16,160
situations, money continues to
get spent beyond the point where

428
00:22:16,560 --> 00:22:19,240
it's best to stop spending it
there and spend it somewhere

429
00:22:19,240 --> 00:22:21,840
else, right?
And does that sort of analysis

430
00:22:21,840 --> 00:22:25,080
take take into account the fact
that you have economic

431
00:22:25,080 --> 00:22:28,560
advantages from discovering
copper or whatever you might be

432
00:22:28,560 --> 00:22:32,440
looking forgiven the the sort of
latent infrastructure in and?

433
00:22:32,440 --> 00:22:35,480
Around absolutely and that and
that's so in, in the brownfields

434
00:22:35,480 --> 00:22:39,360
environment for those reasons
your success threshold is a lot

435
00:22:39,480 --> 00:22:42,840
lower right.
But at the same time what you

436
00:22:42,880 --> 00:22:46,240
are doing is ultimately only
incrementally supporting that

437
00:22:46,240 --> 00:22:50,240
existing operation.
So that's fine, but what you're

438
00:22:50,240 --> 00:22:52,320
not doing is investing in
finding the next one.

439
00:22:52,560 --> 00:22:54,920
Yeah.
And to to sort of beat this out,

440
00:22:54,920 --> 00:22:58,360
you've you've spoken about
advanced projects with with a

441
00:22:58,360 --> 00:23:01,480
bit of disdain and you've
highlighted two types of risks,

442
00:23:01,480 --> 00:23:05,240
you know, high risk type
projects and no hope projects.

443
00:23:06,400 --> 00:23:09,240
I loved how you sort of, you
know, put forth that that

444
00:23:09,240 --> 00:23:11,320
concept.
Can you kind of expand on that

445
00:23:11,320 --> 00:23:14,600
because it's a, it's a topic
that comes up a lot on the show

446
00:23:14,600 --> 00:23:17,520
and you see the headlines,
advanced exploration project or

447
00:23:17,760 --> 00:23:20,600
you know, yadda, yadda, yadda.
And money just continually gets

448
00:23:20,600 --> 00:23:23,520
sunk into it.
People know about it and they

449
00:23:23,520 --> 00:23:25,680
think, oh, maybe in a slightly
better environment cause the

450
00:23:26,200 --> 00:23:27,840
yeah, the commodity price has
gone up.

451
00:23:28,040 --> 00:23:30,680
You know, never mind the fact
that inflation has ripped

452
00:23:30,680 --> 00:23:32,640
through in that.
Well, I think that's exactly

453
00:23:32,680 --> 00:23:34,720
right, Jonas.
So, you know, we have these

454
00:23:34,720 --> 00:23:39,080
projects and I it, it didn't, it
didn't make it before, but you

455
00:23:39,080 --> 00:23:42,720
know, now the commodity price is
higher.

456
00:23:43,280 --> 00:23:47,160
So maybe now it's economic, but
as you say, usually costs come

457
00:23:47,160 --> 00:23:50,320
up at the same time.
But the other, the other issue

458
00:23:50,320 --> 00:23:54,520
with those sort of projects is
there's an unfor because the

459
00:23:54,520 --> 00:23:57,960
dominant dynamic of our industry
is the price cycle, right?

460
00:23:58,400 --> 00:24:00,720
If you think about what
typically happens rising price

461
00:24:00,720 --> 00:24:06,080
cycle, we dust off this dormant
project in junior company, you

462
00:24:06,080 --> 00:24:08,920
know, blue sky mining and then
we go to the market, get

463
00:24:08,920 --> 00:24:12,840
everyone excited, you know, the
share price goes up.

464
00:24:13,240 --> 00:24:15,880
And then if we're really
unlucky, if the shareholders are

465
00:24:15,880 --> 00:24:17,840
really unlucky, there's a
decision to try and develop this

466
00:24:17,840 --> 00:24:20,720
thing.
And, and so we bring all that

467
00:24:20,720 --> 00:24:26,480
capital in and we build the mine
just in time for the price to

468
00:24:26,480 --> 00:24:31,280
crash and the down cycle.
But it's also, I think one of

469
00:24:31,280 --> 00:24:33,680
the reasons why advanced
projects get recycled is for the

470
00:24:33,680 --> 00:24:37,880
same thing where it's easier to
go to the market with a project

471
00:24:37,880 --> 00:24:41,640
that, you know, like has a
defined resource or has a study

472
00:24:41,640 --> 00:24:44,400
or, you know, like, and, and I
think, you know, like that's

473
00:24:44,400 --> 00:24:47,640
kind of the argument that in
that a part of the cycle, it's

474
00:24:47,640 --> 00:24:49,640
much easier to go to investors
and go, hey, we've got an

475
00:24:49,640 --> 00:24:52,840
advanced project, you know,
meaning it's much further along

476
00:24:52,840 --> 00:24:55,120
the line.
But in reality, you know, like

477
00:24:55,120 --> 00:24:57,760
there's a reason why, you know,
like John calls them no hope

478
00:24:57,760 --> 00:24:59,440
projects.
I called them stalled projects.

479
00:24:59,440 --> 00:25:01,600
You know, there's a reason why
that project has stalled along

480
00:25:01,600 --> 00:25:05,720
its development line is because
it has some fundamental flaw

481
00:25:05,720 --> 00:25:09,040
which prevented it from going
becoming an economically viable

482
00:25:09,040 --> 00:25:10,880
opportunity.
Now that might be commodity

483
00:25:10,880 --> 00:25:13,080
price that that's OK.
You know, like commodity price

484
00:25:13,080 --> 00:25:14,800
goes up, all of a sudden it
becomes economic.

485
00:25:14,800 --> 00:25:17,040
That's totally OK.
But other times there are some

486
00:25:17,040 --> 00:25:19,400
fundamental flaws in these
projects which which they

487
00:25:19,400 --> 00:25:21,480
haven't solved.
And people go, well, you know,

488
00:25:21,480 --> 00:25:23,400
like price is high, we're going
to dust this thing off.

489
00:25:23,400 --> 00:25:25,920
And look, it's now advanced and
it's on the development path,

490
00:25:26,240 --> 00:25:28,480
but it's not because it has the
exact same problems it had in

491
00:25:28,480 --> 00:25:30,120
the last like cycle.
No.

492
00:25:30,240 --> 00:25:32,760
There's always a new cycle of
investors to run through it

493
00:25:32,760 --> 00:25:33,280
though.
Yeah.

494
00:25:33,280 --> 00:25:35,160
Well, yeah.
Well, and the other thing is the

495
00:25:35,160 --> 00:25:37,640
project often changes its name.
Yes, I was going to.

496
00:25:37,640 --> 00:25:40,120
Mention the company as well.
Because you kind of hope the

497
00:25:40,120 --> 00:25:43,400
next batch of young investors
don't even remember that.

498
00:25:43,520 --> 00:25:45,040
Oh, this is exciting.
Yeah.

499
00:25:45,920 --> 00:25:48,400
And John just linked into that
as well.

500
00:25:49,080 --> 00:25:52,800
You talk a lot about behavioural
psychology as well that probably

501
00:25:52,800 --> 00:25:59,240
influences these these biases
companies and investors and that

502
00:25:59,240 --> 00:26:01,960
they have.
What's your thoughts on that?

503
00:26:02,480 --> 00:26:06,520
Well, you know, I'm a, I'm a big
fan of the Kahneman work, the

504
00:26:06,680 --> 00:26:09,360
the behavioural psychology and,
you know, it's a key part of

505
00:26:09,360 --> 00:26:13,640
what we teach in our, our senior
exploration management course.

506
00:26:13,640 --> 00:26:18,280
But you know, one of the things
that that that Kahneman looks at

507
00:26:18,280 --> 00:26:22,480
is how people make decisions in
the gain frame and in the loss

508
00:26:22,480 --> 00:26:24,360
frame.
And they make decisions based on

509
00:26:24,640 --> 00:26:29,000
whether there is a high degree
of certainty with the outcome

510
00:26:29,000 --> 00:26:32,040
and there's a risk that you
won't get it or there's really

511
00:26:32,040 --> 00:26:34,200
not much chance.
And you see different

512
00:26:34,200 --> 00:26:36,000
behaviours.
So in some of those quadrants

513
00:26:36,400 --> 00:26:40,120
you see risk seeking behaviour.
So, you know, people buy lottery

514
00:26:40,120 --> 00:26:44,280
tickets because not much chance,
but but also it's, it doesn't

515
00:26:44,280 --> 00:26:46,520
cost much to play.
And I think that's sort of the

516
00:26:46,520 --> 00:26:49,680
rationale between, you know,
investing in like junior

517
00:26:49,680 --> 00:26:53,320
companies or whatever.
On the other hand, you know, we,

518
00:26:53,320 --> 00:26:57,040
we also see this behaviour where
it's a relatively high certainty

519
00:26:57,040 --> 00:27:00,520
loss frame.
For example, a mine is running

520
00:27:00,520 --> 00:27:03,600
out of ore and it's often that's
the only time management get

521
00:27:03,600 --> 00:27:05,000
interested in funding
exploration.

522
00:27:05,000 --> 00:27:06,520
They should have been doing it
for 20 years.

523
00:27:06,880 --> 00:27:10,960
But in the lost frame, people
will end up taking bigger risks.

524
00:27:11,320 --> 00:27:14,360
But I, I do want to say
something about behavioural

525
00:27:15,440 --> 00:27:20,320
psychology and you know, this
concept of the fact that we make

526
00:27:20,320 --> 00:27:24,480
decisions in life as humans that
are not risk neutral, right?

527
00:27:24,800 --> 00:27:28,960
So a risk neutral decision would
be, you know, I've got, you

528
00:27:28,960 --> 00:27:36,280
know, 1% chance of getting $100
million is equivalent to 100%

529
00:27:36,280 --> 00:27:38,320
chance of getting $1,000,000,
right.

530
00:27:39,000 --> 00:27:42,520
So those are identical in a risk
neutral perspective.

531
00:27:42,520 --> 00:27:45,560
But I think for most of us, if
we were given that chance, I'd

532
00:27:45,560 --> 00:27:49,520
go, you know what, I'll take the
$1,000,000 and the 1% chance of

533
00:27:49,520 --> 00:27:52,200
getting 100 million I'm going to
leave behind.

534
00:27:52,640 --> 00:27:59,000
So we often risk discount and
one of the contexts that we risk

535
00:27:59,000 --> 00:28:04,440
discount in is when the actual
probability, yeah, the value of

536
00:28:04,440 --> 00:28:07,800
something which we can say the
expected value is probability by

537
00:28:07,800 --> 00:28:12,040
what it might be, might be high.
But because that probability is

538
00:28:12,040 --> 00:28:15,440
actually low, like in an early
stage exploration project, we

539
00:28:15,440 --> 00:28:18,560
discounted.
So what we see is that early

540
00:28:18,560 --> 00:28:22,520
stage exploration projects are
often, you know, and this is the

541
00:28:22,520 --> 00:28:24,800
good ones, you've got to philtre
out the no hope ones, right?

542
00:28:24,800 --> 00:28:31,160
But the good ones are often
valued at at quite low values

543
00:28:31,160 --> 00:28:33,720
compared to what AEMV would say
they should be.

544
00:28:33,800 --> 00:28:37,880
OK.
So and actually after discovery,

545
00:28:37,880 --> 00:28:40,960
they're often valued higher.
But what that means is there's a

546
00:28:40,960 --> 00:28:44,840
very interesting human
psychology creates a very

547
00:28:44,840 --> 00:28:48,240
interesting arbitrage
opportunity for investors in

548
00:28:48,240 --> 00:28:54,400
that if you have the the
wherewithal, if you've got the

549
00:28:54,400 --> 00:28:58,600
capital to be able to take the
risk that a number of these

550
00:28:58,600 --> 00:29:00,920
things are going to fail.
But ultimately you could be

551
00:29:00,920 --> 00:29:04,080
successful as a portfolio,
you're going to always do better

552
00:29:04,360 --> 00:29:07,160
being on the left hand side of
that discovery hole, right?

553
00:29:07,440 --> 00:29:10,360
Because you're in, you're
investing at at a much cheaper

554
00:29:10,520 --> 00:29:13,640
price than on the other side.
And you could just play the odds

555
00:29:13,640 --> 00:29:14,720
game to.
Some degree, right?

556
00:29:14,720 --> 00:29:18,360
So, so that's the logic for why,
you know, large, large companies

557
00:29:18,360 --> 00:29:20,480
with big balance sheets should
in fact do that.

558
00:29:21,000 --> 00:29:24,400
But this is this is I think an
important point in that, you

559
00:29:24,400 --> 00:29:28,200
know, like at some point in low
probability success rates, you

560
00:29:28,200 --> 00:29:30,920
have to play the odds at some
point to to succeed.

561
00:29:30,960 --> 00:29:34,360
You know, like you can't, you
either have to pay the odds or

562
00:29:34,360 --> 00:29:36,560
you have to play a very long
game, right?

563
00:29:36,560 --> 00:29:38,560
So you're so taking the bets,
but you're taking them over a

564
00:29:38,560 --> 00:29:41,440
long period of time.
And I think, you know, like one

565
00:29:41,440 --> 00:29:44,800
of the, the frustrations I think
I see is that a lot of people in

566
00:29:44,800 --> 00:29:47,040
mineral exploration are actually
doing the opposite, right?

567
00:29:47,040 --> 00:29:50,000
That they're, they're taking
very few bets, you know, like

568
00:29:50,000 --> 00:29:52,840
one project and they are putting
all their hopes on that one

569
00:29:52,840 --> 00:29:54,840
project to kind of get get to
the line.

570
00:29:55,080 --> 00:29:58,280
But fundamentally that project
almost always has a low

571
00:29:58,280 --> 00:30:01,080
probability of success, you
know, like that that hasn't

572
00:30:01,080 --> 00:30:03,720
really changed in that sense.
But it's just that their

573
00:30:03,720 --> 00:30:06,760
perception has changed about it
because they think, and this is

574
00:30:06,760 --> 00:30:09,840
often a problem with I guess
technical people in the industry

575
00:30:09,840 --> 00:30:12,760
where they think that project is
the is the one, you know, they

576
00:30:12,760 --> 00:30:14,400
have their false hope and that's
OK.

577
00:30:14,720 --> 00:30:18,000
But commercially, you know that
or investment wise, you know

578
00:30:18,000 --> 00:30:20,120
that that's probably not going
to pay out in the long run.

579
00:30:20,640 --> 00:30:25,320
So there's this.
This, you know, unease between

580
00:30:25,440 --> 00:30:30,320
the the risk that companies
outwardly express that they are

581
00:30:30,320 --> 00:30:33,280
going to take, that they want to
take, whereas their approach is

582
00:30:33,280 --> 00:30:35,600
actually quite timid.
This is something you've spoken

583
00:30:35,600 --> 00:30:37,640
about in.
Yeah, Richard Taylor, who got

584
00:30:37,640 --> 00:30:41,120
the Nobel Prize for economics, I
think it was in 2015.

585
00:30:41,360 --> 00:30:42,560
Yeah.
One of the things in his book

586
00:30:42,560 --> 00:30:47,560
he, he, he, he calls it bold
targets, timid choices.

587
00:30:48,400 --> 00:30:50,440
There's a company that comes to
mind, guys when we're talking

588
00:30:50,440 --> 00:30:53,760
about grand objectives, but not
timid action.

589
00:30:53,760 --> 00:30:57,320
I'm talking about grand outcomes
and that is bloody Greenlands.

590
00:30:57,560 --> 00:31:01,000
Great Great Grand is like sort
of shortfall Greenlands.

591
00:31:01,120 --> 00:31:02,360
I think, yeah.
In in a way.

592
00:31:02,560 --> 00:31:03,640
You're absolutely right.
One in the.

593
00:31:03,880 --> 00:31:05,400
Same.
Yeah, one, one in the same.

594
00:31:05,640 --> 00:31:07,680
And these guys, you know, you
open up their website and they

595
00:31:07,680 --> 00:31:09,680
got some of my favourite words
on the whole planet.

596
00:31:10,040 --> 00:31:12,560
Turnkey.
Solutions and the video how

597
00:31:12,560 --> 00:31:17,080
goods the video lie over the
friggin damn mate sensation.

598
00:31:17,120 --> 00:31:19,840
It just reeks of water.
These guys bloody do it all.

599
00:31:20,360 --> 00:31:22,960
Any any water related problem
you've got, these guys will sort

600
00:31:22,960 --> 00:31:24,160
out.
You want a day water?

601
00:31:24,160 --> 00:31:25,840
An open pit?
You want a day water an

602
00:31:25,840 --> 00:31:28,320
underground?
You want to transfer water

603
00:31:28,320 --> 00:31:30,840
across your mind site?
You want to line some ponds?

604
00:31:31,720 --> 00:31:34,080
Want to lay some pipes?
These guys will do it for you.

605
00:31:34,200 --> 00:31:38,280
Mate they will even drink water
and make you less dehydrated

606
00:31:38,280 --> 00:31:42,440
like that is how good they are.
Like they are absolute water

607
00:31:42,440 --> 00:31:44,240
magicians.
God's work the best way.

608
00:31:44,360 --> 00:31:47,560
Absolute doing God's work.
So my cheers Greenlands.

609
00:31:47,560 --> 00:31:50,520
Go, Greenlands, Go.
Australia hydration kings and.

610
00:31:50,520 --> 00:31:55,640
Let's go back to your episode.
And can you expand on this in

611
00:31:55,640 --> 00:31:58,680
the, in the context of major
mining companies out there that

612
00:31:58,680 --> 00:32:01,960
have, you know, not just the,
the small one asset companies,

613
00:32:01,960 --> 00:32:04,360
but the, the majors out there
that do have the ability to

614
00:32:04,360 --> 00:32:07,040
have, and they do have a, a
portfolio of assets that have

615
00:32:07,280 --> 00:32:10,080
the capital to, to pick and
choose how they go about it.

616
00:32:10,520 --> 00:32:14,240
How would you sort of guide them
or tweak their their decision

617
00:32:14,240 --> 00:32:17,400
making if if they came to you?
Well, once again, I get the

618
00:32:17,400 --> 00:32:18,840
point I made a little bit
earlier, right?

619
00:32:18,880 --> 00:32:22,360
I think it's understanding where
you want to be on the risk

620
00:32:22,360 --> 00:32:26,000
reward curve, right?
So there is no such thing as a

621
00:32:26,000 --> 00:32:28,520
free lunch, right?
We all know that if you want a

622
00:32:28,520 --> 00:32:32,200
really big reward and you know
the discovery of a world class

623
00:32:32,600 --> 00:32:35,440
or deposit is a massive reward
in terms of sort of the

624
00:32:35,440 --> 00:32:39,280
multiples and the uplift.
But it goes without saying that

625
00:32:39,520 --> 00:32:41,920
the risk or and I define risk
here in the sense of the

626
00:32:41,920 --> 00:32:45,000
probability of that occurring is
going to be relatively low,

627
00:32:45,080 --> 00:32:47,400
right.
So if we think about this risk

628
00:32:47,400 --> 00:32:51,840
reward curve, I would say that
as a big company, work out what

629
00:32:51,840 --> 00:32:55,640
you need to be and then work out
what that means in terms of

630
00:32:55,640 --> 00:32:58,520
risk.
So if you're a BHP and your

631
00:32:58,520 --> 00:33:03,800
portfolio looks the same as, I
don't know, an IGO or a company

632
00:33:03,920 --> 00:33:06,400
of a 10th the size, it's
probably telling you there's a

633
00:33:06,400 --> 00:33:10,520
problem, right?
But what I was getting to before

634
00:33:11,200 --> 00:33:14,480
the, the, the challenge we have
is what economists call a

635
00:33:14,480 --> 00:33:17,720
failure of agency, because at
the end of the day, there is no

636
00:33:17,880 --> 00:33:21,320
entity called BHP who's making
decisions based on what BHP

637
00:33:21,320 --> 00:33:23,280
needs to do.
There's a whole lot of

638
00:33:23,280 --> 00:33:27,600
individuals making decisions
based on, you know, a range of

639
00:33:27,600 --> 00:33:30,440
factors, including, you know,
what, what, what's rational to

640
00:33:30,440 --> 00:33:31,920
them.
And I'm not just picking on BHP,

641
00:33:31,920 --> 00:33:33,920
but just, you know, just because
they're the largest mining

642
00:33:33,920 --> 00:33:36,520
company in the world.
But but that sort of logic.

643
00:33:36,680 --> 00:33:38,880
And I think, you know, like to
back to your question about like

644
00:33:39,120 --> 00:33:42,840
why behavioural psychology or
economics, you know, matters in

645
00:33:42,840 --> 00:33:45,520
this space is because, you know,
like, so yeah, like the

646
00:33:45,520 --> 00:33:47,840
condiment of these guys have
talked about like a number of

647
00:33:47,840 --> 00:33:49,520
kind of heuristics that people
use.

648
00:33:49,840 --> 00:33:52,280
And one of the ones I think, you
know, like aside from the one

649
00:33:52,280 --> 00:33:54,640
that John's mentioning is this
thing called the availability

650
00:33:54,640 --> 00:33:57,600
bias, right?
Which is that people will answer

651
00:33:57,600 --> 00:34:00,080
the the question that they can
instead of the one that they

652
00:34:00,080 --> 00:34:02,760
should.
And so so when you ask, you

653
00:34:02,800 --> 00:34:05,760
know, like when you ask someone
in VHP be like, you know, like

654
00:34:05,760 --> 00:34:09,520
what do you actually need to do
to find a world class asset?

655
00:34:09,760 --> 00:34:12,280
Well, the answer is that they
have to take on the commensurate

656
00:34:12,280 --> 00:34:14,159
level of risk in order to go and
do it.

657
00:34:14,480 --> 00:34:17,199
But the way they the answer is
by answering the question of

658
00:34:17,199 --> 00:34:19,000
what they can do.
And they go, well, actually

659
00:34:19,000 --> 00:34:21,719
we'll go look around our
existing asset for another world

660
00:34:21,719 --> 00:34:24,600
class, you know, but that's not
like, you know, that's not the

661
00:34:24,600 --> 00:34:26,320
question that need need to be
answering.

662
00:34:26,520 --> 00:34:31,440
Can incentives overcome this?
They they, they have to be

663
00:34:31,760 --> 00:34:36,000
longer term and and they also
have to acknowledge that there

664
00:34:36,000 --> 00:34:39,040
is a component of lacking here
with with good work.

665
00:34:39,040 --> 00:34:45,040
So, you know, it's like I said
before, exploring a project that

666
00:34:45,040 --> 00:34:48,800
was a genuine concept and
realising that we need to stop

667
00:34:48,800 --> 00:34:51,600
and moving on.
That's something that is

668
00:34:51,600 --> 00:34:53,639
actually behaviour that we do
want to reward.

669
00:34:54,080 --> 00:34:56,199
Is it being rewarded I.
I yeah, yeah.

670
00:34:56,440 --> 00:34:58,640
And I think I mean, like the
short answer to your question is

671
00:34:58,640 --> 00:35:00,840
yes, right.
Because that's, we know from the

672
00:35:00,840 --> 00:35:03,160
field of behavioural economics,
that's how you change behaviour

673
00:35:03,160 --> 00:35:05,120
by incentivizing.
Yeah.

674
00:35:05,120 --> 00:35:08,480
So John mentioned Richard Haley,
he has also another thing called

675
00:35:08,480 --> 00:35:11,560
the dump principle problem or
the asymmetrical risk problem.

676
00:35:12,000 --> 00:35:16,160
And yeah, like so to your
question about incentives, yes,

677
00:35:16,160 --> 00:35:19,160
they can overcome that because
in Taylor's example, you know,

678
00:35:19,160 --> 00:35:22,160
he kind of expressed that he was
in a multi conglomerate kind of

679
00:35:22,160 --> 00:35:26,880
media company and he asked the
CEO and the CEO wanted to take a

680
00:35:26,880 --> 00:35:28,960
high level of risk.
And then he asked all the

681
00:35:28,960 --> 00:35:31,360
managers that sat underneath and
they didn't want to take any

682
00:35:31,360 --> 00:35:32,400
risk at all.
Right.

683
00:35:32,760 --> 00:35:35,160
And the fundamentally it came
down to that if you were a

684
00:35:35,160 --> 00:35:37,760
manager and you took that level
of risk and it didn't pan out,

685
00:35:37,760 --> 00:35:39,640
you will probably lose your job.
Yeah.

686
00:35:40,000 --> 00:35:43,240
It's fascinating, right?
Because the the behaviour you

687
00:35:43,240 --> 00:35:46,440
want to incentivize them for is
to take the appropriate amount

688
00:35:46,520 --> 00:35:48,040
of risk.
You know, everything else.

689
00:35:48,320 --> 00:35:49,800
Everything else staying
constant.

690
00:35:49,920 --> 00:35:52,400
Yeah, but but then.
Doesn't mean they'll be at an

691
00:35:52,400 --> 00:35:54,600
individual level.
Successful, but you know, but

692
00:35:54,600 --> 00:36:01,400
the outcome of taking that risk
can can then not be career

693
00:36:01,400 --> 00:36:03,160
detrimental to them either,
right?

694
00:36:03,160 --> 00:36:05,200
You can't have it both ways.
You can't tell someone take a

695
00:36:05,200 --> 00:36:07,600
lot of risk which is going to
have a high degree of failure.

696
00:36:07,720 --> 00:36:09,360
But if you fail, I'm going to
sack you.

697
00:36:09,400 --> 00:36:10,960
But like, that's not the right
way to.

698
00:36:11,160 --> 00:36:16,560
So in that Taylor example,
right, so the C, the CEO wanted

699
00:36:16,560 --> 00:36:18,880
to take all these projects and I
think there was something like

700
00:36:19,760 --> 00:36:22,520
10 executives and each one of
them was told, well, here's a

701
00:36:22,520 --> 00:36:26,360
project that if you invest
$1,000,000, there's a 50% chance

702
00:36:26,360 --> 00:36:28,800
it's successful and you get
$3,000,000, right?

703
00:36:29,280 --> 00:36:31,760
And a 50% chance you, you lose
it all, right?

704
00:36:32,000 --> 00:36:36,480
And the CEO said we should take
all of those and very, very few

705
00:36:37,400 --> 00:36:41,120
of the individuals wanted to
because 50% is a pretty high

706
00:36:41,120 --> 00:36:43,200
probability, right?
One in two that you're going to

707
00:36:43,200 --> 00:36:46,400
lose it.
So, and, and that's said this

708
00:36:46,400 --> 00:36:51,800
whole idea of risk discounting
because pretty obviously 50%

709
00:36:51,800 --> 00:36:54,640
probability that you're going to
get three times your investment

710
00:36:54,640 --> 00:36:57,720
back is EMV positive scenario,
right?

711
00:36:57,960 --> 00:37:01,960
So in a risk neutral world, we
should take all EMV positive

712
00:37:01,960 --> 00:37:05,680
scenarios, but we don't because
because of risk and risk is

713
00:37:05,920 --> 00:37:08,920
ultimately an individual thing
and it's ultimately a

714
00:37:09,080 --> 00:37:12,920
psychological decision.
So we, we don't just want to

715
00:37:12,920 --> 00:37:15,960
talk about the, the issues
around there and the problems

716
00:37:15,960 --> 00:37:19,360
with exploration companies and
what the industry faces at the

717
00:37:19,360 --> 00:37:21,480
moment.
And you know, thankfully you've,

718
00:37:21,560 --> 00:37:24,400
you've thought a lot about this,
John, and you've put forward a

719
00:37:24,400 --> 00:37:27,600
really sort of succinct and
interesting paper on this idea

720
00:37:27,600 --> 00:37:32,600
of an exploration aggregator.
And I I believe this was written

721
00:37:32,600 --> 00:37:35,520
sort of late 20/10/2016.
Something like that.

722
00:37:35,520 --> 00:37:38,600
I think I, I spoke about it at
PDAC in 2016.

723
00:37:38,720 --> 00:37:41,680
Yeah, yeah.
So the basic idea there, it was

724
00:37:41,680 --> 00:37:47,560
actually to thinking through
some of these challenges and and

725
00:37:47,560 --> 00:37:51,560
feeling like as a global
industry, we did not efficiently

726
00:37:51,560 --> 00:37:55,040
allocate capital to this really
important task, which has only

727
00:37:55,040 --> 00:37:57,800
become more important of
Greenfield's exploration, right

728
00:37:57,800 --> 00:38:01,240
and finding, finding these new
mineral deposits.

729
00:38:01,360 --> 00:38:04,040
And I think just to interject
there, John, one of the, I think

730
00:38:04,640 --> 00:38:07,920
fundamental things about the
funding is to say, yeah, there's

731
00:38:07,920 --> 00:38:10,160
two schools of thought.
One of them says that, you know,

732
00:38:10,160 --> 00:38:12,400
we don't have enough funding.
The other says that we actually

733
00:38:12,400 --> 00:38:15,080
have enough funding is just
allocated badly.

734
00:38:15,080 --> 00:38:17,480
Yeah, like to some degree.
And I think like you know, and I

735
00:38:17,480 --> 00:38:20,120
think that's an important point
in your model is that it's not

736
00:38:20,120 --> 00:38:22,960
advocating that we need massive
amounts of in increased

737
00:38:22,960 --> 00:38:25,200
investments, It's just that the
investment we have could be

738
00:38:25,200 --> 00:38:26,680
better utilised.
Absolutely.

739
00:38:26,680 --> 00:38:31,400
The agents around, you know, we
may, we may need a, a bigger

740
00:38:31,400 --> 00:38:35,320
global quantum, but to do that,
we need to demonstrate the

741
00:38:35,320 --> 00:38:38,800
results.
And you know, you can sit down

742
00:38:38,800 --> 00:38:42,280
and, and, and do the numbers
where you kind of say, well, how

743
00:38:42,280 --> 00:38:44,920
many big deposits are being
found each year?

744
00:38:44,920 --> 00:38:47,000
And they're all like worth a
certain amount.

745
00:38:47,160 --> 00:38:49,440
How much are we spending as an
industry?

746
00:38:49,960 --> 00:38:52,520
And those numbers don't look
that good like they they have,

747
00:38:52,520 --> 00:38:56,040
they're, they're quite high.
You know, it's like probably of

748
00:38:56,040 --> 00:39:01,200
the order of 200 million US just
for any type of deposit, not a

749
00:39:01,200 --> 00:39:03,400
not a tier one.
And it's probably something like

750
00:39:03,680 --> 00:39:06,600
8,000,008 billion for like a, a
tier one.

751
00:39:07,160 --> 00:39:12,720
But the problem with all that
sort of analysis is that a very

752
00:39:12,720 --> 00:39:15,560
large chunk of that money, you
know, the global exploration

753
00:39:15,560 --> 00:39:19,360
industry spends.
It varies of course, but you

754
00:39:19,360 --> 00:39:22,880
know, somewhere of the order of
10 to 15 billion US a year.

755
00:39:23,600 --> 00:39:28,800
And a very large part of that
money is, is not focused on

756
00:39:28,800 --> 00:39:32,200
finding new Tier 1 deposits.
Exactly how large, I don't know.

757
00:39:32,200 --> 00:39:34,520
If I had to guess, I'd say
probably close to 90%.

758
00:39:34,840 --> 00:39:37,680
Now some of that's for good
reason in that the money's been

759
00:39:37,680 --> 00:39:41,560
allocated to, you know, around
existing operations and so on.

760
00:39:41,840 --> 00:39:44,600
Some of it for less good reason.
It's being allocated because to

761
00:39:44,600 --> 00:39:48,680
projects where there is an
opportunity to raise capital or

762
00:39:48,800 --> 00:39:51,520
some of it is because there is
an ecosystem in our industry and

763
00:39:52,000 --> 00:39:54,280
below the level of tier ones,
you can, you know, there,

764
00:39:54,280 --> 00:39:57,080
there's viable companies finding
smaller stuff, but that doesn't

765
00:39:57,080 --> 00:40:00,840
really solve sort of global
problems and it it's not got

766
00:40:00,840 --> 00:40:03,800
that sort of tier one type value
creation.

767
00:40:04,120 --> 00:40:11,280
So I guess my concept would be
being selective, right?

768
00:40:11,280 --> 00:40:13,280
So part of the exploration
aggregator model.

769
00:40:13,280 --> 00:40:18,960
The the first point is that you
you need the skill set in the

770
00:40:18,960 --> 00:40:21,160
aggregator to make sure that
the.

771
00:40:21,960 --> 00:40:24,920
The gating process is that the
only thing that ever gets funded

772
00:40:25,240 --> 00:40:28,960
are those projects that have the
genuine opportunity to find the

773
00:40:28,960 --> 00:40:32,120
tier one, right?
So that's the first thing.

774
00:40:32,120 --> 00:40:33,720
So you improve the odds,
essentially.

775
00:40:33,760 --> 00:40:35,840
Oh absolutely You're not.
You're not spending money on

776
00:40:35,840 --> 00:40:39,480
things you know are have no hope
of ever getting.

777
00:40:39,480 --> 00:40:43,640
Anywhere so, so just to be very
clear, I, I, you know, you, you

778
00:40:43,640 --> 00:40:45,120
obviously want to apply your
best science.

779
00:40:45,120 --> 00:40:47,360
And if you do that, you know,
some projects might be better

780
00:40:47,360 --> 00:40:50,720
than others, But the reality is
that I'm, you know, I'm not, I'm

781
00:40:50,720 --> 00:40:54,080
not saying you can be too, too
sophisticated at that early

782
00:40:54,080 --> 00:40:58,280
stage in saying, well, this
one's maybe a 1% probability,

783
00:40:58,280 --> 00:41:01,080
this one's a 1 1/2 percent
probability or whatever it is.

784
00:41:01,320 --> 00:41:05,360
But what I'm saying is you want
to cut out anything that's a 0%

785
00:41:05,360 --> 00:41:07,920
probability, right?
So that, that, that's, that's

786
00:41:07,920 --> 00:41:10,160
the key point.
You, you want to, you want to

787
00:41:10,160 --> 00:41:12,960
reduce it to those things that
have, you know, a genuine

788
00:41:12,960 --> 00:41:14,320
chance.
That's the first Philtre.

789
00:41:15,040 --> 00:41:18,880
The, the 2nd philtre is it has
to be managed as a portfolio.

790
00:41:19,440 --> 00:41:23,840
And you, you, you need that
capital pool that yeah, there's

791
00:41:23,840 --> 00:41:26,680
concept of, of gamblers ruin.
So even if something is EMV

792
00:41:26,720 --> 00:41:29,720
positive, right, you might go
broke before you get there.

793
00:41:30,320 --> 00:41:32,960
And your ability to avoid
gamblers ruin is a function of

794
00:41:32,960 --> 00:41:35,720
your pool of capital.
So you need a pool of capital to

795
00:41:35,720 --> 00:41:38,720
be able to manage this as a
portfolio.

796
00:41:39,080 --> 00:41:41,680
And your bet sizes, right?
That's right, That's right.

797
00:41:42,040 --> 00:41:45,640
And the, but the absolutely
critical thing about bet size is

798
00:41:46,800 --> 00:41:50,040
you've got to manage all your
projects with decision point

799
00:41:50,040 --> 00:41:52,640
planning, right?
So this is, this is getting into

800
00:41:52,640 --> 00:41:56,400
the not the micro, but a really
fundamental concept.

801
00:41:56,680 --> 00:41:59,600
It's not like I've got this
exploration project and I'm

802
00:41:59,600 --> 00:42:03,120
going to spend 20 million or 30
million on it's like I've got

803
00:42:03,120 --> 00:42:05,720
this exploration project.
It could be the next Escondida,

804
00:42:06,040 --> 00:42:10,440
but after I've spent, I don't
know, two or three million doing

805
00:42:10,440 --> 00:42:13,720
these drill holes, I will know
whether an Escondida is there or

806
00:42:13,720 --> 00:42:15,440
not.
Now, if I'm unsuccessful, it

807
00:42:15,440 --> 00:42:18,040
still could be something small.
Yeah, but I know it's not the

808
00:42:18,040 --> 00:42:19,000
big one.
Yeah, right.

809
00:42:19,000 --> 00:42:20,600
That's right.
So and that's your decision to

810
00:42:20,600 --> 00:42:21,880
kind of walk, right?
That's right.

811
00:42:21,880 --> 00:42:24,600
You know, if you're not going to
get that pay off, yeah, then

812
00:42:24,600 --> 00:42:27,240
you're not, you know, committing
funds just for the sake of

813
00:42:27,400 --> 00:42:30,240
because that's the only project
you have or, or whatever other

814
00:42:30,240 --> 00:42:33,960
kind of metric that comes in.
And the, the sort of the third

815
00:42:33,960 --> 00:42:37,480
aspect and why I call it the
aggregator is, is I think, you

816
00:42:37,480 --> 00:42:39,520
know, one of the things we
learned from the history of the

817
00:42:39,520 --> 00:42:43,280
exploration industry is it's
very hard to do things as a big

818
00:42:43,520 --> 00:42:47,080
sort of global conglomerate
because there is a real value in

819
00:42:47,080 --> 00:42:51,760
being close to the ground, you
know, close to the, the local

820
00:42:51,760 --> 00:42:53,720
people, close to the local
geology.

821
00:42:54,440 --> 00:42:56,960
And you know, I remember a few
years ago there was a study on

822
00:42:56,960 --> 00:43:00,080
gold exploration which showed
the most successful explorers

823
00:43:00,080 --> 00:43:02,400
were the ones that were focused
in a particular region.

824
00:43:02,560 --> 00:43:04,800
Makes a lot of sense, right?
And the reason why it makes a

825
00:43:04,800 --> 00:43:07,280
lot of sense, and I'll, I'll
come to this in a minute, is the

826
00:43:07,280 --> 00:43:11,240
learning curve, right?
But how can you simultaneously

827
00:43:11,240 --> 00:43:16,240
have a big global portfolio, but
also have, let's call it local

828
00:43:16,240 --> 00:43:18,760
expertise, local skill set,
local learning?

829
00:43:19,000 --> 00:43:22,720
Well, you've got to support a
diversity of organisations.

830
00:43:23,160 --> 00:43:26,680
So you know, whatever this sort
of overarching source of capital

831
00:43:26,680 --> 00:43:28,320
is.
And I think the BHP explore

832
00:43:28,320 --> 00:43:31,240
model is, is, is sort of one
model globally, which is kind of

833
00:43:31,240 --> 00:43:36,240
trying to do this at the moment.
And it, it, it seeks, you know,

834
00:43:36,240 --> 00:43:38,560
high quality opportunities from
around the world.

835
00:43:38,560 --> 00:43:41,680
Whether it's got the critical
mass it needs yet, I, I don't

836
00:43:41,680 --> 00:43:43,040
know.
But I think it's it, you know,

837
00:43:43,040 --> 00:43:46,080
it's a very good step in, in the
right direction.

838
00:43:46,520 --> 00:43:49,720
But you need to be able to
support a diversity of groups

839
00:43:49,720 --> 00:43:52,760
that have that local expertise,
that local knowledge, so they

840
00:43:52,760 --> 00:43:56,960
can be effective.
And then fundamentally, there

841
00:43:56,960 --> 00:44:00,600
needs to be a commercial
framework, which is win win,

842
00:44:00,800 --> 00:44:04,200
right?
So the larger corporation

843
00:44:04,360 --> 00:44:07,560
obviously ultimately wants
continuity of its business by

844
00:44:07,560 --> 00:44:11,520
getting access to these things.
But it has to be has to be

845
00:44:11,520 --> 00:44:14,880
prepared to give enough away.
Because you think about why

846
00:44:14,880 --> 00:44:17,960
someone invests in a junior
exploration company doing

847
00:44:17,960 --> 00:44:22,520
exploration, it's not for like a
50% return on their money, 100%.

848
00:44:22,520 --> 00:44:26,680
It's the, the, the small, but
non 0 probability of a very,

849
00:44:26,680 --> 00:44:29,400
very large return.
So it's very important that

850
00:44:29,400 --> 00:44:34,680
that's not not capped.
So but just what just just

851
00:44:34,680 --> 00:44:39,760
sorry, I'm learning because one
of the things about exploration

852
00:44:39,760 --> 00:44:43,800
is that if you look at sort of
average success rates, it

853
00:44:43,800 --> 00:44:47,600
doesn't look economic, right?
But if you think about one of

854
00:44:47,600 --> 00:44:50,720
these curves of I'm going to
explore 100 projects and it's

855
00:44:50,720 --> 00:44:56,360
going to cost me X and what's
the MPV of my programme, what

856
00:44:56,360 --> 00:45:00,080
those models imply is the
probability of success of your

857
00:45:00,080 --> 00:45:02,840
100th project is the same as
your first project.

858
00:45:03,360 --> 00:45:05,720
And what that implies is that
you haven't learned anything.

859
00:45:06,200 --> 00:45:10,800
And in real life, if we're doing
exploration, well, we're

860
00:45:10,800 --> 00:45:13,640
exploring an area, we're
unsuccessful, but that

861
00:45:13,640 --> 00:45:17,360
information is fed back into the
next set of targets we drill and

862
00:45:17,360 --> 00:45:20,320
the next set and we improve that
probability of success.

863
00:45:20,560 --> 00:45:25,200
So that the learning theme, that
that's the key, that that's the

864
00:45:25,200 --> 00:45:30,400
key juice that that drives this
and why, you know, persisting in

865
00:45:30,400 --> 00:45:33,840
local areas or persisting around
a particular commodity type is

866
00:45:33,840 --> 00:45:36,200
so critical.
And I think this is, you know,

867
00:45:36,200 --> 00:45:38,440
like this last point about the
learning curve is I think when

868
00:45:38,440 --> 00:45:42,040
we look at companies that were
really good explorers, that's I

869
00:45:42,040 --> 00:45:44,480
think one of the, you know, like
in the, in the stuff that we did

870
00:45:44,480 --> 00:45:46,600
in our podcast, that's one of
the themes that kind of comes

871
00:45:46,600 --> 00:45:51,680
out is that actually they kept
a, a group of people together

872
00:45:51,680 --> 00:45:54,280
for enough time so that the
learning could kind of bounce

873
00:45:54,280 --> 00:45:57,600
around between them to a point.
And that, and that's kind of a,

874
00:45:57,800 --> 00:45:59,800
and it's not a nebulous concept.
Like, you know, if you think

875
00:45:59,800 --> 00:46:01,920
about sports teams, you know,
like the teams that are really

876
00:46:01,920 --> 00:46:05,640
good, you know, they tend to
have in an organisational

877
00:46:05,640 --> 00:46:10,240
culture or, you know, like the
organisation is set up a certain

878
00:46:10,240 --> 00:46:13,680
way, whether that that learning
feedback loop is kind of getting

879
00:46:13,760 --> 00:46:15,400
passed around.
You know, like if they're

880
00:46:15,400 --> 00:46:17,800
drafting players, you know, they
learn from the mistakes that

881
00:46:17,800 --> 00:46:19,360
they've made.
So they're not making the same

882
00:46:19,360 --> 00:46:21,000
dumb mistakes the same time
again.

883
00:46:21,320 --> 00:46:24,280
Whereas organisations, yeah,
like in sports organisations are

884
00:46:24,280 --> 00:46:27,920
really easy to look at when they
go through this period of, you

885
00:46:27,920 --> 00:46:30,280
know, like the board is cleared
out, all the executives are

886
00:46:30,280 --> 00:46:32,080
cleared out, the coaches sacked,
all of that stuff.

887
00:46:32,280 --> 00:46:37,240
You can see that they don't have
great like success rate in that.

888
00:46:37,320 --> 00:46:38,840
And you can think about, you
know, if you're a basketball

889
00:46:38,840 --> 00:46:41,040
fan, you think about the San
Antonio Spurs or something like

890
00:46:41,040 --> 00:46:43,440
that, you know, a massively
successful organisation for a

891
00:46:43,440 --> 00:46:45,520
long, long time.
And they've basically kept the

892
00:46:45,520 --> 00:46:48,120
same people there for for a
large period.

893
00:46:48,120 --> 00:46:50,960
And that's kind of like the
learning curve model is that if

894
00:46:50,960 --> 00:46:53,320
you can keep them around without
having to sack them every like

895
00:46:53,320 --> 00:46:55,800
three or four years, then you
know, like that's kind of the,

896
00:46:55,800 --> 00:46:58,040
the, the critical mass you want
to build, I think.

897
00:46:58,040 --> 00:47:00,800
The Chicago Bulls might be a a
slightly better example there as

898
00:47:00,840 --> 00:47:02,800
well.
And you can sort of see there's

899
00:47:02,840 --> 00:47:06,000
a, a long teething period and
then eventually, you know, the,

900
00:47:06,080 --> 00:47:08,640
the flywheel starts humming and
you get championship.

901
00:47:08,640 --> 00:47:10,880
After that, and I think that,
and then that's kind of the

902
00:47:10,880 --> 00:47:13,840
concept is that, you know, like
you like exactly the point you

903
00:47:13,840 --> 00:47:16,480
made is that there are there is
a period of lean years because

904
00:47:16,480 --> 00:47:17,920
you you're still figuring it
out.

905
00:47:17,920 --> 00:47:20,120
You know, like in a sports
organisation, you're figuring

906
00:47:20,120 --> 00:47:21,960
out your drafting strategy and
all these things.

907
00:47:22,400 --> 00:47:24,600
And in middle exploration, I
think when you go into a new

908
00:47:24,600 --> 00:47:27,640
area, you're still figuring this
thing, these things out, right?

909
00:47:27,640 --> 00:47:30,880
You're figuring out which areas
you can really work in, the type

910
00:47:30,880 --> 00:47:33,840
of techniques that work best,
you know, like how effective you

911
00:47:33,840 --> 00:47:36,320
can be from a dollar point of
view in exploring in certain

912
00:47:36,320 --> 00:47:38,680
areas.
And so there's this, you know,

913
00:47:38,680 --> 00:47:42,040
basically flat line kind of
payoff period.

914
00:47:42,280 --> 00:47:44,840
But then when you get to that
point, it's kind of like the

915
00:47:44,960 --> 00:47:47,640
Chicago Bulls model is that the
success comes really quickly

916
00:47:47,640 --> 00:47:49,800
after that because you've now
amalgamated.

917
00:47:49,960 --> 00:47:52,840
And if I can just sort of make
one technical point about

918
00:47:52,840 --> 00:47:56,280
learning, the most important
thing to learn is what is a

919
00:47:56,280 --> 00:48:00,880
false positive, right?
Because mineral expiration, it's

920
00:48:00,880 --> 00:48:04,080
a low base rate environment,
which means that the targets

921
00:48:04,080 --> 00:48:07,480
that we test very rarely have
what we're looking for, which is

922
00:48:07,480 --> 00:48:11,760
an economic or deposit.
And simple, you know, Bayesian

923
00:48:12,040 --> 00:48:15,640
probability tells you that in
that environment, the key factor

924
00:48:15,640 --> 00:48:18,480
if I'm looking at an anomaly and
deciding whether it's associated

925
00:48:18,480 --> 00:48:21,720
with an ore body or not is the
false positive rate of that

926
00:48:21,720 --> 00:48:23,680
anomaly.
In other words, how easy is it

927
00:48:23,680 --> 00:48:26,040
to create the same anomaly
that's not an ore body?

928
00:48:26,560 --> 00:48:29,320
And that has some really
important consequences.

929
00:48:29,520 --> 00:48:32,640
So I like to say that, you know,
when my daughter was 10, I

930
00:48:32,640 --> 00:48:36,600
taught her how to assess ASX
releases of exploration

931
00:48:36,600 --> 00:48:38,120
companies.
Very, very simple method.

932
00:48:38,480 --> 00:48:42,200
So go to the page where they
have a plot of all their targets

933
00:48:42,520 --> 00:48:44,760
and count them up.
And if there's more than three,

934
00:48:44,760 --> 00:48:50,600
they're no good.
And the reason is all bodies are

935
00:48:50,600 --> 00:48:53,080
rare.
So if we're going to say this is

936
00:48:53,120 --> 00:48:55,720
this is the signature, I've got
a geochemical anomaly or a

937
00:48:55,720 --> 00:49:00,120
geophysical anomaly, you know,
it needs to really stand out to

938
00:49:00,120 --> 00:49:03,040
have a high probability.
If we've got a lot of targets by

939
00:49:03,040 --> 00:49:06,160
definition, and it's a
fundamental output of Bayesian

940
00:49:06,160 --> 00:49:09,120
analysis, the targets are not
very good.

941
00:49:09,360 --> 00:49:12,360
And yet you still get people
saying, well, we've got lots and

942
00:49:12,360 --> 00:49:14,280
lots of targets.
That's that's a good thing.

943
00:49:14,320 --> 00:49:16,440
Particularly like geophysics,
like, yeah, this is a classic

944
00:49:16,440 --> 00:49:19,160
one where they go, we've got 50
anomalies and you go, I think

945
00:49:19,160 --> 00:49:20,560
you've missed the definition of
anomaly.

946
00:49:20,680 --> 00:49:22,200
Anomaly, yeah.
That's good.

947
00:49:22,200 --> 00:49:25,640
Well, I, I, the, the heuristic I
have is, I like to say that

948
00:49:25,800 --> 00:49:28,400
green and yellow are not your
friends.

949
00:49:29,240 --> 00:49:32,240
And by that I mean, you know, if
you've got your map and you're

950
00:49:32,240 --> 00:49:35,480
using a typical sort of spectral
stretch, you want to have the

951
00:49:35,480 --> 00:49:38,200
big red and white dot on a blue
background, then you've got a

952
00:49:38,200 --> 00:49:40,800
good a good anomaly if you've
got lots of green and yellow in

953
00:49:40,800 --> 00:49:42,720
that map.
Yeah, that's fine.

954
00:49:44,040 --> 00:49:46,200
One comment I wanted to make
about John's like you know, like

955
00:49:46,200 --> 00:49:48,280
model about the aggregator
because you know, we kind of had

956
00:49:48,280 --> 00:49:49,600
this discussion a couple of
times.

957
00:49:49,880 --> 00:49:53,720
And I think one of the the
fundamental things why you would

958
00:49:53,720 --> 00:49:57,080
want an aggregated model is if
you start off with the premise

959
00:49:57,080 --> 00:50:00,200
that every dollar being spent in
exploration is not the same,

960
00:50:00,560 --> 00:50:02,920
then you can see that there are
people that are spending dollars

961
00:50:02,920 --> 00:50:04,880
effectively and they're people
that are spending in

962
00:50:04,960 --> 00:50:07,800
ineffectively.
And so, you know, like what you

963
00:50:07,800 --> 00:50:10,120
want to start off with.
So if you start off with that as

964
00:50:10,120 --> 00:50:13,160
your premise, you can say that
they are some agents.

965
00:50:13,160 --> 00:50:16,240
And you know, John said 90%, you
know, Rick has his own kind of

966
00:50:16,240 --> 00:50:18,640
the Rick rule has his own
percentage of how many companies

967
00:50:18,640 --> 00:50:21,280
are lifestyle companies and not
really wanting to find things,

968
00:50:21,880 --> 00:50:23,280
right.
And so I think that's always the

969
00:50:23,280 --> 00:50:27,520
premise that when people say
this, you know, like we take the

970
00:50:27,520 --> 00:50:31,080
total expended in mineral
exploration worldwide and we say

971
00:50:31,080 --> 00:50:32,640
this is the amount of metal that
we found.

972
00:50:33,080 --> 00:50:35,440
You know, like the the basic
assumption you're making is that

973
00:50:35,440 --> 00:50:36,960
every dollar being spent is the
same.

974
00:50:37,320 --> 00:50:40,920
Now if you change that around to
actually looking at companies

975
00:50:40,920 --> 00:50:44,200
that spent effective dollars and
ineffective dollars, that rate

976
00:50:44,200 --> 00:50:46,720
of return would be much better.
100% right, Yeah.

977
00:50:47,040 --> 00:50:49,720
And and again to to my sports
analogy is actually the same

978
00:50:49,720 --> 00:50:51,680
right at the start of the
season, you have X number of

979
00:50:51,680 --> 00:50:54,440
teams, but you know that there's
only a handful that are

980
00:50:54,440 --> 00:50:56,240
legitimately going to be at the
top of the table.

981
00:50:56,240 --> 00:50:58,440
And the others are just making
kind of numbers up, right,

982
00:50:58,440 --> 00:50:59,840
because they're they're not good
enough.

983
00:51:00,000 --> 00:51:01,600
Yeah.
And I think it's the same in in

984
00:51:01,600 --> 00:51:03,960
middle exploration.
Oh, I was just going to say just

985
00:51:03,960 --> 00:51:06,880
sort of on that theme as well.
Do you think that that the

986
00:51:06,880 --> 00:51:14,040
nature of the exploration sort
of aggregator and the these sort

987
00:51:14,040 --> 00:51:18,720
of behavioural economics that we
sort of say heuristics, we sort

988
00:51:18,720 --> 00:51:23,880
of say, do you think it makes it
sort of a more suitable in a

989
00:51:23,880 --> 00:51:27,000
sort of private capital market
as opposed to public look, I

990
00:51:27,040 --> 00:51:28,000
think.
Naturally, yeah.

991
00:51:28,480 --> 00:51:32,440
I think there is a natural
tendency for that to be so,

992
00:51:32,480 --> 00:51:34,440
yeah.
Well, like long term patient

993
00:51:34,440 --> 00:51:37,280
capital because it's just the
public markets just I don't

994
00:51:37,280 --> 00:51:39,520
think could could cope with
something like this even though

995
00:51:39,520 --> 00:51:42,240
it makes.
Well, the public markets could

996
00:51:42,240 --> 00:51:45,800
invest in the in the in the
aggregator in the same way

997
00:51:45,800 --> 00:51:48,680
people invest in sort of
Berkshire Hathaway, for example,

998
00:51:48,720 --> 00:51:51,160
if it was successful, but they
probably wouldn't do it until it

999
00:51:51,480 --> 00:51:53,960
had demonstrated some success.
Yeah, I think those investors

1000
00:51:53,960 --> 00:51:55,520
are few and far between.
Yeah.

1001
00:51:55,920 --> 00:51:58,720
But you can see, sorry, the
yeah, you can see that in I

1002
00:51:58,720 --> 00:52:01,520
guess other industries.
I think the VC world, you know,

1003
00:52:01,520 --> 00:52:04,920
like they there is very little
involvement in in kind of the

1004
00:52:04,920 --> 00:52:08,320
startup world, the VC driven
startup world from public

1005
00:52:08,440 --> 00:52:10,320
entities, right.
Like they're often the, you

1006
00:52:10,320 --> 00:52:12,200
know, they're never come in in
the early money, but they're

1007
00:52:12,200 --> 00:52:15,600
happy to come in in like, you
know, series BC whatever after

1008
00:52:15,600 --> 00:52:18,000
that.
But yeah, that I think, I think

1009
00:52:18,000 --> 00:52:19,560
that is a fundamental kind of
constraint.

1010
00:52:20,080 --> 00:52:23,120
I want to just really tie this
into a real world example

1011
00:52:23,120 --> 00:52:25,760
because you've, you've put all
this, this work in, but what

1012
00:52:25,760 --> 00:52:29,080
we've seen since this paper come
out is like you say, BHP

1013
00:52:29,080 --> 00:52:32,560
explores programme and you know
it, it, it is remarkable to me

1014
00:52:32,560 --> 00:52:36,320
at at every turn in incentives
are just in your face and you,

1015
00:52:36,360 --> 00:52:39,240
you highlight there that you
need to incentivize the, the

1016
00:52:39,240 --> 00:52:41,760
smaller company, whether that be
the people, everyone at every

1017
00:52:41,760 --> 00:52:46,040
stage needs to be incentivized
by the ultimate outcome.

1018
00:52:47,120 --> 00:52:50,080
Now BHB explore has actually
started to do this.

1019
00:52:50,080 --> 00:52:53,080
They've had a couple schools now
or groups of.

1020
00:52:53,400 --> 00:52:55,560
Cohorts, I think they call.
Them cohorts that that's the

1021
00:52:55,560 --> 00:52:57,640
one.
And I mean in your model you put

1022
00:52:57,640 --> 00:53:00,120
forward the example that it can
be a major mining company, it

1023
00:53:00,120 --> 00:53:03,840
could be a direct agent, it
could be a specialist third

1024
00:53:03,840 --> 00:53:08,920
party.
Do you think a a BHB is the the

1025
00:53:08,920 --> 00:53:12,640
best type of company to do this?
And given that they've now put

1026
00:53:12,640 --> 00:53:15,640
this into practise, where would
you sort of guide them on

1027
00:53:15,960 --> 00:53:17,680
improving what they've?
Done well, first of all, I think

1028
00:53:17,680 --> 00:53:21,320
it's great that they're doing it
because I, I think they need to

1029
00:53:21,320 --> 00:53:22,960
do it.
And one of the reasons they need

1030
00:53:22,960 --> 00:53:25,560
to do it is I actually don't
think we have a globally

1031
00:53:25,560 --> 00:53:28,800
successful model.
And I've worked in, in large

1032
00:53:28,800 --> 00:53:31,640
global companies have tried to
do global exploration.

1033
00:53:31,800 --> 00:53:35,720
It's very difficult to do as as
one company there are there, you

1034
00:53:35,720 --> 00:53:37,480
know, there's a lot of
overheads, there's an increasing

1035
00:53:37,480 --> 00:53:40,960
amount of internal friction that
prevents that being done.

1036
00:53:40,960 --> 00:53:43,000
So.
Just the also just the level of

1037
00:53:43,000 --> 00:53:46,200
organisational complexity you
need to work in, you know,

1038
00:53:46,200 --> 00:53:49,320
Australia at the same time work
in the high Andies, you know,

1039
00:53:49,320 --> 00:53:51,400
like it's just not like it's a
complicated.

1040
00:53:51,400 --> 00:53:54,960
Exercise, yeah, yeah.
So, so I, I, and I don't, I

1041
00:53:54,960 --> 00:53:57,440
don't think, you know, and if
you think about the history of

1042
00:53:57,440 --> 00:54:02,720
our industry, you know, when I
started, unfortunately over 40

1043
00:54:02,720 --> 00:54:06,200
years ago now, but we didn't
really have this concept of

1044
00:54:06,200 --> 00:54:08,480
people exploring globally.
You know, there was only four or

1045
00:54:08,480 --> 00:54:10,280
five countries in the Western
world.

1046
00:54:10,280 --> 00:54:12,080
People would mostly explore in
any way.

1047
00:54:12,360 --> 00:54:14,000
And if you're in Australia, you
explored there.

1048
00:54:14,000 --> 00:54:15,360
If you're in America, you
explore there.

1049
00:54:15,400 --> 00:54:18,480
And it was only really after the
end of the Cold War and we had

1050
00:54:18,480 --> 00:54:23,040
this big era of globalisation
that we started to try and think

1051
00:54:23,040 --> 00:54:25,400
about exploring globally.
And I think at one point in the

1052
00:54:25,400 --> 00:54:28,440
late 90s, BHP, for example, in
48 countries, right?

1053
00:54:29,160 --> 00:54:34,000
And that's 48 officers, 48, you
know, groups of people now that

1054
00:54:34,000 --> 00:54:36,360
didn't last that long.
Western mining we're in about

1055
00:54:36,360 --> 00:54:39,000
25.
It's, it's not really

1056
00:54:39,080 --> 00:54:41,760
sustainable.
And I just think it's too

1057
00:54:41,760 --> 00:54:45,120
difficult with, with time zones
with as Ahmad says, internal

1058
00:54:45,120 --> 00:54:50,000
complexities, all the, the, the
constraints, particularly around

1059
00:54:51,200 --> 00:54:53,120
licence to operate issues and so
on.

1060
00:54:53,480 --> 00:54:58,520
So a model like Explorer is
probably what is what is

1061
00:54:58,520 --> 00:55:02,200
required.
But there there's a few key

1062
00:55:02,200 --> 00:55:04,520
aspects that are required to
make that model work.

1063
00:55:04,760 --> 00:55:09,040
One, you need really, really
good experienced technical

1064
00:55:09,040 --> 00:55:12,560
people who are providing that
philtre, right.

1065
00:55:12,880 --> 00:55:17,240
So you know, you need people who
really have been in the industry

1066
00:55:17,440 --> 00:55:19,640
for many, yeah, this is an
industry where it actually

1067
00:55:19,640 --> 00:55:21,280
matters.
Experience matters, the right

1068
00:55:21,280 --> 00:55:24,000
sort of experience, but it
actually is important.

1069
00:55:24,000 --> 00:55:26,480
So it needs to be guided by
that.

1070
00:55:27,120 --> 00:55:31,560
Secondly, the commercial
frameworks need to be such that

1071
00:55:31,760 --> 00:55:35,040
people want to bring their best
projects in, not just the

1072
00:55:35,040 --> 00:55:38,480
projects they don't think could
get funded in the risk capital

1073
00:55:38,480 --> 00:55:40,920
market, right?
So, you know, to me, that's the

1074
00:55:40,920 --> 00:55:45,080
test of a model like Explore.
Are people bringing a project in

1075
00:55:45,080 --> 00:55:47,640
because it's their core project,
it's the one they really believe

1076
00:55:47,640 --> 00:55:50,800
in, or are they bringing it in
because it's not their core

1077
00:55:50,800 --> 00:55:53,080
project, they're kind of
interested in it and they think

1078
00:55:53,080 --> 00:55:55,840
this is an alternative Ave for
funding.

1079
00:55:56,240 --> 00:55:59,320
And that gets back to you know,
you know, and I'm not not

1080
00:55:59,320 --> 00:56:02,280
familiar with any of those sort
of details of those commercial

1081
00:56:02,280 --> 00:56:05,720
agreements, but but
fundamentally that gets back to

1082
00:56:05,720 --> 00:56:08,080
that attractiveness.
And of course like everything in

1083
00:56:08,080 --> 00:56:09,680
life, branding and marketing,
right.

1084
00:56:10,360 --> 00:56:13,880
So if you have successes and
this is a successful model and

1085
00:56:15,520 --> 00:56:19,680
to be a successful model it has
to be successful for BHP and

1086
00:56:19,680 --> 00:56:23,920
it's shareholders, but also
successful for individual

1087
00:56:23,920 --> 00:56:28,880
companies within that, you know,
So by being part of the scheme,

1088
00:56:28,880 --> 00:56:31,920
companies have to be at least
not worse off, maybe a bit

1089
00:56:31,920 --> 00:56:35,080
better off just by being in it.
And then of course, not all of

1090
00:56:35,080 --> 00:56:37,360
them are going to be successful,
but if they are successful,

1091
00:56:37,600 --> 00:56:40,080
they're going to have have to be
seen to have benefited

1092
00:56:40,080 --> 00:56:44,200
significantly from that success
as opposed to the default

1093
00:56:44,200 --> 00:56:46,920
alternative which is raising
capital on the risk capital

1094
00:56:46,920 --> 00:56:48,880
market, the public markets and
so on.

1095
00:56:50,200 --> 00:56:51,840
I think I think to your
question, like, you know,

1096
00:56:51,840 --> 00:56:54,800
whether it could be done most
effectively the major mining

1097
00:56:54,800 --> 00:56:58,160
company or or not.
You know, like if you take the

1098
00:56:58,160 --> 00:57:01,440
example out of out of mining
into other industries, you know,

1099
00:57:01,440 --> 00:57:04,240
like say like AVC that does it,
you know, accelerate a programme

1100
00:57:04,240 --> 00:57:06,080
or something like that.
You know, I think the one

1101
00:57:06,080 --> 00:57:08,640
fundamental difference is that
the VC doesn't have a vested

1102
00:57:08,640 --> 00:57:12,640
interest in the entity that's
being produced by the startup or

1103
00:57:12,640 --> 00:57:14,520
the product that's being
produced by the startup.

1104
00:57:14,880 --> 00:57:18,280
Whereas I think in BHP that you
know, like that's where I think

1105
00:57:18,280 --> 00:57:22,600
you have to have a really sound
commercial model because ABHP is

1106
00:57:22,600 --> 00:57:25,360
kind of facilitating the
accelerator programme, you know,

1107
00:57:25,360 --> 00:57:28,280
call it whatever.
But then at the end, they're

1108
00:57:28,280 --> 00:57:31,200
also the customer that wants to
kind of get right.

1109
00:57:31,200 --> 00:57:33,160
And I'm and I think they're.
Existential for them.

1110
00:57:33,160 --> 00:57:35,880
Isn't it really ultimately that
this programme is successful?

1111
00:57:35,880 --> 00:57:37,760
That's a.
That is a pretty pretty

1112
00:57:37,760 --> 00:57:40,160
important distinction.
So I think they have to navigate

1113
00:57:40,160 --> 00:57:43,440
that internally as well as the
the companies that are coming to

1114
00:57:43,440 --> 00:57:47,040
them in a, in a, in a different
way I think than a standard kind

1115
00:57:47,040 --> 00:57:49,640
of accelerator model where, you
know, VCs are just coming in as

1116
00:57:49,640 --> 00:57:51,800
an investor.
And then they, you know, like

1117
00:57:51,800 --> 00:57:54,680
they want to help the company
get somewhere, but they don't

1118
00:57:54,680 --> 00:57:57,560
have a vested interest in that,
in that product or that outcome

1119
00:57:57,560 --> 00:57:59,840
of that of that company.
I think that's a very good

1120
00:57:59,840 --> 00:58:02,200
point.
So that, I think is a challenge

1121
00:58:02,200 --> 00:58:05,480
of how you do it internally.
But, you know, like, to be

1122
00:58:05,480 --> 00:58:07,640
honest, the best agents we
currently have in the industry

1123
00:58:07,640 --> 00:58:10,080
to do that I think are probably
major mining companies, yeah.

1124
00:58:10,400 --> 00:58:13,320
Well, I think they're the ones
with the most skin in the game,

1125
00:58:13,320 --> 00:58:14,000
right?
Yeah.

1126
00:58:14,000 --> 00:58:17,200
So if you analyse, you know, and
I've done this thought process

1127
00:58:17,200 --> 00:58:19,600
of sort of analysing, who cares,
right?

1128
00:58:19,640 --> 00:58:22,200
Ultimately, who cares that
there's not efficient allocation

1129
00:58:22,200 --> 00:58:25,120
of capital to global greenfields
exploration?

1130
00:58:25,440 --> 00:58:27,960
Well, the the biggest
stakeholders are these large

1131
00:58:28,040 --> 00:58:30,320
multi generational mining
companies, right?

1132
00:58:30,760 --> 00:58:33,160
And then that's just like, you
know, like if like in the space

1133
00:58:33,160 --> 00:58:35,520
of exploration, if you're a
major mining company and there's

1134
00:58:35,520 --> 00:58:39,240
not an effective allocation of
capital to make new discoveries,

1135
00:58:39,560 --> 00:58:41,720
then you know, like at some
point your business is going to

1136
00:58:41,720 --> 00:58:43,880
struggle because it's going to
have to buy things at a higher

1137
00:58:43,880 --> 00:58:47,880
and higher premium to add to
your, your reserve base or your

1138
00:58:47,880 --> 00:58:49,920
business base.
But at some point, they just

1139
00:58:49,920 --> 00:58:53,520
won't be the assets that can
generate the metal, correct, at

1140
00:58:53,520 --> 00:58:56,480
a cost that makes sense.
So I suppose just thinking

1141
00:58:56,560 --> 00:58:59,800
through that one step further,
at some point it becomes

1142
00:58:59,800 --> 00:59:02,800
societal or a, or a, or a
governmental issue.

1143
00:59:02,800 --> 00:59:06,440
And of course, that's something
that's changed in my career

1144
00:59:06,440 --> 00:59:10,120
because it's only been in the
last half a decade or so that

1145
00:59:10,120 --> 00:59:14,960
we've started to see a serious
involvement at a global level in

1146
00:59:14,960 --> 00:59:17,720
terms of governments and people
thinking about minerals.

1147
00:59:17,720 --> 00:59:20,480
Because, you know, for most of
my career, minerals and mining

1148
00:59:20,480 --> 00:59:23,480
was, was to be honest, looked
down on and, and seen as somehow

1149
00:59:23,480 --> 00:59:26,240
inferior to technology and all,
all these other things.

1150
00:59:26,720 --> 00:59:28,560
And it's just something you took
for granted.

1151
00:59:28,560 --> 00:59:31,080
And now we know that we're in a
world where we can't do that.

1152
00:59:31,720 --> 00:59:33,640
There's no interest like self
interest, right?

1153
00:59:33,960 --> 00:59:37,760
That's the companies get on it.
There's this concept I, I read

1154
00:59:37,760 --> 00:59:41,600
about, I hear about a lot of
these companies from, you know,

1155
00:59:42,240 --> 00:59:44,800
you know, from back in the day
that were really technically

1156
00:59:44,800 --> 00:59:48,240
focused, that had great cultures
and everything and Western

1157
00:59:48,240 --> 00:59:50,880
mining comes to mind and there's
a few others.

1158
00:59:51,160 --> 00:59:54,840
Do you think this is a rose
tinted view on the past or was

1159
00:59:54,840 --> 00:59:57,520
there something distinctly
different about how they

1160
00:59:57,520 --> 01:00:01,200
operated?
I think first of all that there.

1161
01:00:02,360 --> 01:00:05,200
I mean, some of it is obviously,
you know, there was always those

1162
01:00:05,200 --> 01:00:07,160
raised tinted glasses, but I
think there's some real

1163
01:00:07,160 --> 01:00:08,880
substance to it.
But I think you've also got to

1164
01:00:08,880 --> 01:00:11,960
see it in in context, right.
So one of the things that

1165
01:00:11,960 --> 01:00:15,400
Western mining did, for example,
very concrete thing that I don't

1166
01:00:15,400 --> 01:00:18,800
think any organisation does on
the same scale today is its

1167
01:00:18,800 --> 01:00:20,040
study leave scheme.
Yeah.

1168
01:00:20,120 --> 01:00:23,760
So it would provide, and pretty
much any, any talented

1169
01:00:24,520 --> 01:00:27,800
geoscientist would get funded
for half salary for a year to go

1170
01:00:27,800 --> 01:00:29,760
and do a master's.
And then in the end, yeah, I

1171
01:00:29,760 --> 01:00:32,480
mean, I, I got funded to a PhD,
for example, I never would have

1172
01:00:32,480 --> 01:00:35,720
been able to do it otherwise.
So I was a beneficiary of that.

1173
01:00:36,040 --> 01:00:40,400
So there was that very, very
significant investment in

1174
01:00:40,400 --> 01:00:42,920
development.
It's one of the reasons why, you

1175
01:00:42,920 --> 01:00:45,480
know, people used to talk about
Western mining as the university

1176
01:00:45,480 --> 01:00:49,160
to the industry because it did
that and it probably did that a

1177
01:00:49,160 --> 01:00:53,000
lot more than other companies,
but but that was a more common

1178
01:00:53,000 --> 01:00:55,000
thing.
But they held on to the people.

1179
01:00:55,200 --> 01:00:58,080
Yeah, correct.
So, so there's a couple aspects

1180
01:00:58,080 --> 01:01:00,600
about that.
One, it was a world where the

1181
01:01:00,600 --> 01:01:03,320
culture was more like, I've
joined this company and I'll

1182
01:01:03,320 --> 01:01:06,440
work for them, you know, for a
long time to retirement that,

1183
01:01:06,680 --> 01:01:10,480
that was a different world to,
to, to, to what we have today.

1184
01:01:11,400 --> 01:01:14,760
But the flip side of it is when
you invest in your people,

1185
01:01:14,800 --> 01:01:16,520
you're more likely to keep them
anyway.

1186
01:01:16,520 --> 01:01:21,400
So I, I do feel that it's
interesting that companies

1187
01:01:21,400 --> 01:01:26,040
today, which are, you know, plus
10 times the sort of market cap

1188
01:01:26,040 --> 01:01:30,360
of what Western mining ever was,
don't invest in, in this sort of

1189
01:01:30,360 --> 01:01:31,880
training.
I mean, if they do it, they do

1190
01:01:31,880 --> 01:01:35,640
it very, very sporadically.
But one of their pillars is

1191
01:01:35,640 --> 01:01:38,240
people is our biggest resource,
John, But yeah.

1192
01:01:38,280 --> 01:01:40,440
Yeah, I know they're.
Far more profitable than than

1193
01:01:40,440 --> 01:01:41,640
Western.
Yeah, yeah.

1194
01:01:42,000 --> 01:01:44,120
I mean, I can only give my
example, you know, like I

1195
01:01:44,120 --> 01:01:47,160
remember going into, you know,
like my career corresponded with

1196
01:01:47,160 --> 01:01:49,640
the end of WMC and the start of
it being in BHP.

1197
01:01:49,800 --> 01:01:51,840
And I remember going into a
group where there was, you know,

1198
01:01:51,840 --> 01:01:54,480
like eight of us.
And I think all of them were ex

1199
01:01:54,480 --> 01:01:58,160
WMC people and all of them had
been there 15 plus years, right.

1200
01:01:58,160 --> 01:02:01,160
Like I, I don't think I've ever
walked into a group now where

1201
01:02:01,160 --> 01:02:06,120
you could get that level of of
kind of longevity in, in the

1202
01:02:06,120 --> 01:02:08,240
company, right.
But but to your point, you know,

1203
01:02:08,240 --> 01:02:10,520
like we're talking about that
learning curve kind of kind of

1204
01:02:10,520 --> 01:02:13,160
model, you know, like I think
that was a great thing that they

1205
01:02:13,160 --> 01:02:16,880
could a, allow people to get
better to like train them, but

1206
01:02:16,880 --> 01:02:19,680
also just keep them for a long,
long time in in that sense.

1207
01:02:19,680 --> 01:02:23,240
And then that IP stays in the
business, yeah, because

1208
01:02:23,280 --> 01:02:26,640
otherwise that learning curve,
as we sort of discussed before,

1209
01:02:28,040 --> 01:02:30,440
yeah, obviously there's, you
know, the physical and the data

1210
01:02:30,440 --> 01:02:33,880
and all that, but the IP that
sits up here is now gone over

1211
01:02:33,880 --> 01:02:36,520
there and over there and it just
stalls that whole.

1212
01:02:36,520 --> 01:02:40,160
Process so one of the unusual
aspects of that western mining

1213
01:02:40,160 --> 01:02:42,360
system was the concept of the
guilds.

1214
01:02:42,360 --> 01:02:43,960
The geoscientists were in a
Guild.

1215
01:02:43,960 --> 01:02:47,240
So I might be working as a mine
geologist of a particular mine

1216
01:02:47,480 --> 01:02:50,320
or I might be working as an
exploration geologist somewhere.

1217
01:02:50,600 --> 01:02:53,840
But there was the idea that
someone was looking at the whole

1218
01:02:53,840 --> 01:02:57,520
group of geoscientists and
actually making decisions like

1219
01:02:57,800 --> 01:03:00,720
we're going to send him to a
mind for two years to get this

1220
01:03:01,320 --> 01:03:04,720
experience or they're going on
study leave or they're going to

1221
01:03:04,720 --> 01:03:08,200
exploration.
So the discipline was managed

1222
01:03:08,400 --> 01:03:11,200
holistically.
And you know, what we saw

1223
01:03:11,200 --> 01:03:15,200
changing in the 90s with the
rise of HR culture and and

1224
01:03:15,200 --> 01:03:17,720
direct sort of, you know,
management control that I mean

1225
01:03:17,720 --> 01:03:22,240
that was seen as and a
necrotistic archaic and maybe a

1226
01:03:22,760 --> 01:03:24,440
challenge to.
And a cost item.

1227
01:03:25,320 --> 01:03:28,400
Yeah, and a challenge to to sort
of management authority.

1228
01:03:28,400 --> 01:03:30,800
And so all that got got
dismantled.

1229
01:03:31,240 --> 01:03:34,680
And I don't think in large
organisations there's much

1230
01:03:34,680 --> 01:03:38,000
discussion that goes on of, you
know, here's my org chart of the

1231
01:03:38,000 --> 01:03:40,360
300 geologists I have in this
organisation.

1232
01:03:40,360 --> 01:03:43,480
And this is how, you know,
we're, we're going to these, we

1233
01:03:43,480 --> 01:03:45,560
think these are the talent,
these are the ones we have to do

1234
01:03:45,560 --> 01:03:47,320
it.
It's very much individuals

1235
01:03:47,320 --> 01:03:50,520
fighting their way through
whatever silos that exist,

1236
01:03:50,520 --> 01:03:54,000
whether it's at an operation or
in an exploration group.

1237
01:03:55,240 --> 01:03:57,920
It's amazing because, you know,
there are other industries that

1238
01:03:57,920 --> 01:04:00,760
that try and do this, but what
they do is just make your pay

1239
01:04:00,760 --> 01:04:03,520
vest way down the track and they
try and lock you in.

1240
01:04:03,520 --> 01:04:06,000
So the fact that Western mining
could could do this without

1241
01:04:06,000 --> 01:04:08,760
just, you know, essentially
holding your pay from you.

1242
01:04:08,760 --> 01:04:09,960
Yeah.
Yeah, that's why.

1243
01:04:09,960 --> 01:04:12,960
And it's also like, you know, to
your common alley about like the

1244
01:04:12,960 --> 01:04:15,480
IP and like there's there's this
great book and I can't remember

1245
01:04:15,480 --> 01:04:17,560
the author's name.
It's called where good ideas

1246
01:04:17,560 --> 01:04:18,680
come from.
All right.

1247
01:04:18,680 --> 01:04:21,320
And then, and then in the book
they talk about that if you look

1248
01:04:21,320 --> 01:04:25,480
at kind of like the stream of
innovation over the last 100

1249
01:04:25,480 --> 01:04:28,800
years, you know, like it often
develops with this, you know,

1250
01:04:28,800 --> 01:04:32,000
like one person has one piece of
the puzzle and this other person

1251
01:04:32,000 --> 01:04:33,040
has the other piece of the
puzzle.

1252
01:04:33,200 --> 01:04:36,480
What you need is that
connectedness between those

1253
01:04:36,480 --> 01:04:39,480
ideas to kind of come together
and, and become something, you

1254
01:04:39,480 --> 01:04:42,280
know, so, so my like view on
this is like, you know, like the

1255
01:04:42,280 --> 01:04:46,560
reason why I think organisations
like WMC and like CRA was

1256
01:04:46,560 --> 01:04:49,280
another one that that was I
think successful is because

1257
01:04:49,560 --> 01:04:52,400
they, they had this right, that
they kept that IP kind of

1258
01:04:52,400 --> 01:04:55,160
bouncing around and hitting each
other in, in, in that same

1259
01:04:55,160 --> 01:04:58,280
organisation.
Now I think, you know, we, we

1260
01:04:58,280 --> 01:05:00,840
may have still the same number
of geologists, but now they're

1261
01:05:00,840 --> 01:05:02,880
spread out over, you know, 1000
companies.

1262
01:05:03,160 --> 01:05:05,880
So I think that
interconnectedness of ideas

1263
01:05:05,880 --> 01:05:10,280
probably is not as efficient as
it could be when it's in one

1264
01:05:10,280 --> 01:05:13,720
organisation and it's being
managed, like the talent is

1265
01:05:13,720 --> 01:05:16,640
being managed holistically in
that sense, you know.

1266
01:05:16,640 --> 01:05:19,360
So I think that's kind of the
challenge of why, you know, like

1267
01:05:19,360 --> 01:05:22,520
we sometimes struggle to kind of
progress along with ideas in

1268
01:05:22,520 --> 01:05:25,040
some way as well.
John, the the last thing I want

1269
01:05:25,040 --> 01:05:27,160
to hear from you and you've,
you've touched on this earlier,

1270
01:05:27,160 --> 01:05:31,800
but AI, machine learning, all
these things are clearly the,

1271
01:05:31,880 --> 01:05:34,840
the buzzword of the last three
years.

1272
01:05:34,880 --> 01:05:38,920
Now I want to hear from you,
given your, your sort of deep

1273
01:05:38,920 --> 01:05:41,520
technical experience here and
you, you've spoken about it in

1274
01:05:41,520 --> 01:05:44,680
the, in the sense of big data
and these sorts of things and

1275
01:05:45,160 --> 01:05:46,880
search spaces.
And we're going, we should be

1276
01:05:46,880 --> 01:05:48,720
going to places that don't have
the data.

1277
01:05:49,200 --> 01:05:53,600
But what do you think will be
the implications from this sort

1278
01:05:53,600 --> 01:05:57,160
of wave of investment in AI
specific to the the mineral

1279
01:05:57,160 --> 01:06:00,320
exploration field?
Look, this should have been the

1280
01:06:00,320 --> 01:06:01,360
last thing we should have talked
about.

1281
01:06:01,360 --> 01:06:02,800
This should be the first thing
we should have talked about

1282
01:06:02,800 --> 01:06:05,200
that.
Look, my, my opinion is

1283
01:06:05,200 --> 01:06:08,120
extremely limited will be the,
the impact.

1284
01:06:08,120 --> 01:06:13,160
And I, I, I say this both on the
basis of empirical experience.

1285
01:06:14,600 --> 01:06:17,480
You know, we talked about the
last three years there, there've

1286
01:06:17,480 --> 01:06:20,680
been people, very, very smart
people way ahead of the curve

1287
01:06:20,680 --> 01:06:24,600
doing this over a decade ago,
spent probably $100 million

1288
01:06:24,600 --> 01:06:26,440
without any success.
And not because they weren't

1289
01:06:26,440 --> 01:06:29,800
very smart and not because they
didn't have the best technology.

1290
01:06:30,880 --> 01:06:33,320
So that's sort of the empirical
experience.

1291
01:06:33,920 --> 01:06:40,120
The the conceptual reason is
that I think the critical thing

1292
01:06:40,120 --> 01:06:43,680
that we need to understand is
what defines a big data

1293
01:06:43,680 --> 01:06:47,720
environment, meaning, you know,
big data as in a set of a

1294
01:06:47,720 --> 01:06:50,240
problem set that is amenable to
AI.

1295
01:06:50,680 --> 01:06:54,280
And in my opinion, where people
get confused is I think it's a

1296
01:06:54,280 --> 01:06:57,240
big data environment if the
available data can be measured

1297
01:06:57,240 --> 01:07:01,600
in the terabytes.
But if that available data does

1298
01:07:01,600 --> 01:07:07,560
not very well represent the
parameter space of interest, I I

1299
01:07:07,560 --> 01:07:08,880
think you've got a problem,
right.

1300
01:07:08,960 --> 01:07:13,280
Yeah, because our parameter
space of interest I think is a

1301
01:07:13,280 --> 01:07:17,880
poor data environment.
So conceptually, I don't think

1302
01:07:18,240 --> 01:07:21,880
AI can ever do very well at
targeting in these poor data

1303
01:07:21,880 --> 01:07:25,520
environments.
In principle, what it should be

1304
01:07:25,520 --> 01:07:30,600
able to do is help us learn in
our data rich environments and

1305
01:07:30,600 --> 01:07:34,520
extract patterns from that.
So in principle, I accept that

1306
01:07:34,520 --> 01:07:37,280
as a possibility.
But I have to say I haven't yet

1307
01:07:37,280 --> 01:07:40,000
seen any good examples.
And you know, some of the

1308
01:07:40,000 --> 01:07:42,640
companies I'm involved with have
invested in, in some of this.

1309
01:07:42,640 --> 01:07:45,040
And to be honest, we've been
disappointed with the examples.

1310
01:07:45,040 --> 01:07:51,080
But I'm not an AI specialist so
I I don't know exactly why these

1311
01:07:51,080 --> 01:07:56,200
things have not worked but but
my just lived experience so far

1312
01:07:56,480 --> 01:08:00,160
is I haven't seen anything that
that's added value.

1313
01:08:01,040 --> 01:08:04,040
And I think to like to the
comment about like why I think

1314
01:08:04,040 --> 01:08:05,960
it's somewhat struggle.
I mean, John and I've talked

1315
01:08:05,960 --> 01:08:09,320
about this a fair bit where, you
know, like we get approaches by

1316
01:08:09,320 --> 01:08:12,240
people trying to come in and you
know, like apply and more AI

1317
01:08:12,240 --> 01:08:15,400
machine learning approach.
And I think one of the, the, the

1318
01:08:15,400 --> 01:08:18,200
fundamental issues I think comes
from is that, you know, like,

1319
01:08:18,479 --> 01:08:20,880
like John said, in mineral
exploration, we are very data

1320
01:08:20,880 --> 01:08:23,720
poor environment.
You know, like we collect data,

1321
01:08:23,720 --> 01:08:28,040
but we collected in, you know,
select areas quite well, but we

1322
01:08:28,040 --> 01:08:30,720
don't like, we rarely collect
holistic data.

1323
01:08:30,720 --> 01:08:33,479
You know, the data resolutions
are always quite different in

1324
01:08:33,479 --> 01:08:36,160
different parts of what we are
trying to solve, unless it's a

1325
01:08:36,160 --> 01:08:38,399
very small area, then you know,
like maybe someone flies a

1326
01:08:38,399 --> 01:08:40,160
geophysics survey or something
like that at the same

1327
01:08:40,160 --> 01:08:43,200
resolution.
So there's two kind of problems.

1328
01:08:43,200 --> 01:08:47,720
One is that we are a data poor
environment and B, we, we have

1329
01:08:47,720 --> 01:08:50,359
this, I think changing rate of
false positives, right?

1330
01:08:50,359 --> 01:08:53,279
Like once you, you have to have
a certain level of testing to

1331
01:08:53,279 --> 01:08:56,359
figure out whether the anomalies
that you've identified are

1332
01:08:56,359 --> 01:08:59,000
appropriate or not.
And so, and machine learning

1333
01:08:59,000 --> 01:09:02,560
works really well when you have
a large base rate of, of a

1334
01:09:02,560 --> 01:09:05,120
training data set.
You know, we don't always have

1335
01:09:05,120 --> 01:09:07,200
that, you know, we're always
tired to build this as we kind

1336
01:09:07,200 --> 01:09:10,040
of go along.
But one of the fundamental

1337
01:09:10,040 --> 01:09:12,800
reasons, you know, like, like
I've been guilty of applying a

1338
01:09:12,800 --> 01:09:16,040
lot of AI in in, you know,
expression with limited success.

1339
01:09:16,359 --> 01:09:19,840
And one of the issues I think I
find with it is that, yeah, like

1340
01:09:19,960 --> 01:09:21,880
AI machine learning, I think
mineral exploration will be

1341
01:09:21,880 --> 01:09:25,160
really good at interrogating the
data sets when we have them.

1342
01:09:25,479 --> 01:09:27,920
But often the challenge in
mineral exploration is

1343
01:09:28,080 --> 01:09:31,439
identifying where you should go
collect data sets.

1344
01:09:31,800 --> 01:09:34,720
And I don't think that is a
question that will be best

1345
01:09:34,720 --> 01:09:38,760
answered by machine learning.
Unless we just accept that we're

1346
01:09:38,760 --> 01:09:41,319
going to spend millions of
dollars collecting data sets

1347
01:09:41,319 --> 01:09:44,960
everywhere at a set resolution,
you know, like how we want to do

1348
01:09:44,960 --> 01:09:49,000
it, then I think, yeah, maybe we
can take our intellectual

1349
01:09:49,000 --> 01:09:51,600
insights of what's an anomaly
and what's not an anomaly and

1350
01:09:51,600 --> 01:09:54,560
model it into a a, you know, ML
model.

1351
01:09:54,560 --> 01:09:55,840
And then you can go and look for
that.

1352
01:09:56,160 --> 01:09:58,040
But I don't think we're there
yet, right?

1353
01:09:58,040 --> 01:10:00,080
Like we just don't have the
amount of data.

1354
01:10:00,400 --> 01:10:02,840
Look, I think the the issue of
data is an important one.

1355
01:10:02,840 --> 01:10:07,000
And I've had a number of of, of
conversations, you know, the

1356
01:10:07,080 --> 01:10:10,640
government agencies who want to
improve their prospectivity.

1357
01:10:10,640 --> 01:10:13,000
And it's like, well, should we
invest in all this AI?

1358
01:10:13,520 --> 01:10:15,800
And you say, well, don't do
that.

1359
01:10:15,880 --> 01:10:18,480
Invest in getting your
fundamental data right.

1360
01:10:18,680 --> 01:10:22,080
So for example, if you're
dealing with an area that

1361
01:10:22,080 --> 01:10:25,680
doesn't have, say, something
like one kilometre grid gravity,

1362
01:10:25,960 --> 01:10:27,720
you can't do best practise
targeting.

1363
01:10:28,160 --> 01:10:32,760
So to me it's, it's kind of sort
of irrelevant whether you're

1364
01:10:32,760 --> 01:10:36,000
developing your best AI to look
at the magnetics and all the

1365
01:10:36,000 --> 01:10:38,720
other datas you have when you're
missing a key data set.

1366
01:10:39,200 --> 01:10:43,680
So I have a very, very strong
bias to saying if you've got an

1367
01:10:44,440 --> 01:10:47,880
increment of capital that you
want to invest in moving a

1368
01:10:47,880 --> 01:10:50,320
problem forward, collect that
data.

1369
01:10:50,560 --> 01:10:52,480
And yeah, we started this
conversation.

1370
01:10:52,480 --> 01:10:54,840
Jonas, you asked me about my 4
rules and I only really got to

1371
01:10:54,840 --> 01:10:56,600
rule 2.
Yeah, I was just about to say

1372
01:10:56,680 --> 01:10:59,440
#3.
Rule 3 was collect your own

1373
01:10:59,440 --> 01:11:02,080
primary data in the search space
of interest.

1374
01:11:02,360 --> 01:11:05,840
And to Amad's point that he was
just articulating, working out

1375
01:11:05,840 --> 01:11:07,840
what that search base of
interest is, is also an

1376
01:11:07,840 --> 01:11:11,160
intellectual process and in fact
a key value creating process.

1377
01:11:11,400 --> 01:11:14,600
But once you've done that, go
and collect your your own own

1378
01:11:14,720 --> 01:11:17,280
primary data.
And rule 4, of course, something

1379
01:11:17,280 --> 01:11:20,400
we've touched on again and again
is learning from, test those

1380
01:11:20,400 --> 01:11:22,960
targets and learn, learn from
that.

1381
01:11:23,320 --> 01:11:29,280
So I will any day of the week,
say in most situations, you'd be

1382
01:11:29,280 --> 01:11:33,080
better off investing in
collecting primary data.

1383
01:11:33,080 --> 01:11:36,280
It has to be a primary data set
that really helps you with what

1384
01:11:36,280 --> 01:11:38,520
you're doing.
Things like gravity are good

1385
01:11:38,520 --> 01:11:41,000
because it goes to the
fundamental architecture of the

1386
01:11:41,000 --> 01:11:43,400
crust, which is which is always
important.

1387
01:11:44,080 --> 01:11:47,360
But you know, just coming back
to, I think an interesting

1388
01:11:47,360 --> 01:11:51,840
analogy when we think about
domains where, you know, AI,

1389
01:11:51,840 --> 01:11:54,800
deep learning or all of these
things can work and they aren't,

1390
01:11:54,800 --> 01:11:57,920
is the comparison between
weather forecasting over the

1391
01:11:57,920 --> 01:12:01,040
last few decades and earthquake
forecasting, right.

1392
01:12:01,440 --> 01:12:04,480
So these are both very, very
complex, non linear systems.

1393
01:12:04,480 --> 01:12:07,160
You know, weather forecasting is
a classic chaotic, you know, the

1394
01:12:07,160 --> 01:12:11,680
butterfly flaps its wings and
you know, the typhoon in in, or

1395
01:12:11,680 --> 01:12:15,280
the tornado in Texas, whatever.
But we've actually got a lot

1396
01:12:15,280 --> 01:12:18,000
better with weather forecasting.
Weather forecasts are quite

1397
01:12:18,120 --> 01:12:20,440
reasonable now.
And that's through, you know,

1398
01:12:20,440 --> 01:12:24,000
massive computing power and
making all these models and, and

1399
01:12:24,000 --> 01:12:26,800
doing all this.
On the other hand, earthquake

1400
01:12:26,800 --> 01:12:28,880
forecasting is still really
poor.

1401
01:12:29,200 --> 01:12:33,360
And we had a big earthquake in
Christchurch going back a few

1402
01:12:33,360 --> 01:12:37,000
years ago.
Devastating it was on a fault

1403
01:12:37,000 --> 01:12:39,440
that wasn't even recognised.
It wasn't even in the model,

1404
01:12:39,480 --> 01:12:42,080
right.
So with weather forecasting, we

1405
01:12:42,080 --> 01:12:45,480
now through satellites and
whatever, we have a pretty good

1406
01:12:45,480 --> 01:12:49,120
characterization of our system,
IE the atmosphere and the ocean

1407
01:12:49,120 --> 01:12:51,360
atmosphere or the land
atmosphere interface.

1408
01:12:51,560 --> 01:12:53,960
So, so we've got a pretty and
we'll get better, but we've got

1409
01:12:53,960 --> 01:12:56,400
a pretty good model for it.
When it comes to something like

1410
01:12:56,400 --> 01:13:02,560
earthquake forecasting, we have
a very poor model of the

1411
01:13:02,560 --> 01:13:05,080
relevant search base, which is
the rock mass underneath us.

1412
01:13:05,560 --> 01:13:07,520
And then you think about mineral
deposits, it's not just

1413
01:13:07,520 --> 01:13:10,160
forecasting 1 earthquake, it's
forecasting a bunch of

1414
01:13:10,160 --> 01:13:12,840
earthquakes that happened 2 1/2
billion years ago, right, so.

1415
01:13:13,440 --> 01:13:15,480
And the time interaction and all
these type of things.

1416
01:13:15,680 --> 01:13:18,560
And so I think this is kind of
the the concept like, yeah, like

1417
01:13:18,560 --> 01:13:23,440
I think machine learning solves
computationally heavy tasks.

1418
01:13:23,440 --> 01:13:25,520
Like, you know, that's where
it's got to, you know, we're not

1419
01:13:25,520 --> 01:13:29,160
at a point now where the true
artificial intelligence that,

1420
01:13:29,160 --> 01:13:31,200
you know, we've created
something that that that can

1421
01:13:31,200 --> 01:13:33,240
kind of come in and, and solve
that problem.

1422
01:13:33,440 --> 01:13:35,520
And so the domains where it's
really struggled is where you

1423
01:13:35,520 --> 01:13:37,880
actually need that.
The answer is in the

1424
01:13:37,880 --> 01:13:42,080
intelligence of how you
contextualise data and review it

1425
01:13:42,080 --> 01:13:44,520
and do that.
And humans are still, I think,

1426
01:13:44,520 --> 01:13:47,400
far better at it, you know, than
than any computer we have

1427
01:13:47,400 --> 01:13:50,840
currently.
I just had one final question

1428
01:13:51,400 --> 01:13:54,160
reflecting on sort of what we've
discussed today.

1429
01:13:54,720 --> 01:13:57,520
Do you think there is really a
case for a single asset

1430
01:13:57,520 --> 01:14:01,400
exploration company?
That's a good question.

1431
01:14:01,920 --> 01:14:04,320
A Greenfield's expiration.
No, no, I don't.

1432
01:14:04,360 --> 01:14:06,680
But I think that pretty much you
have to.

1433
01:14:07,520 --> 01:14:11,640
I mean, one of the issues here
relates to the quantum of

1434
01:14:11,640 --> 01:14:15,000
capital like that can be raised.
And I don't know whether any of

1435
01:14:15,000 --> 01:14:17,080
you guys have heard of Mike
Etheridge.

1436
01:14:17,080 --> 01:14:19,680
He was a big leader of our
industry about 20 years ago.

1437
01:14:20,400 --> 01:14:24,680
He wrote some pretty influential
stuff and he was the first guy

1438
01:14:24,680 --> 01:14:28,040
to really sit down and try and
provide some quantitative

1439
01:14:28,520 --> 01:14:31,800
analysis around exploration.
And he actually published a

1440
01:14:31,800 --> 01:14:36,120
paper, I think it was about
early 2000s, where he bemoaned

1441
01:14:36,120 --> 01:14:39,720
the fact that when you looked at
the dynamics of the industry,

1442
01:14:39,720 --> 01:14:43,160
the typical IPO raise was 4 or
5,000,000 bucks.

1443
01:14:43,160 --> 01:14:46,120
And that was pathetic.
Of course, it's still about four

1444
01:14:46,120 --> 01:14:47,360
or five billion, correct?
Yeah.

1445
01:14:47,480 --> 01:14:51,040
And that four or 5 billion bucks
is now worth about half as much

1446
01:14:51,040 --> 01:14:53,560
as what it was.
That's how when ASX costs have

1447
01:14:53,560 --> 01:14:57,520
only gone up.
Yeah, and ASX costs, heritage

1448
01:14:57,520 --> 01:15:03,200
costs, ground costs.
So, you know, the, the reality

1449
01:15:03,200 --> 01:15:07,360
is that you know, companies, you
know, they float, they raise

1450
01:15:07,360 --> 01:15:09,000
money.
This is my project, right?

1451
01:15:09,440 --> 01:15:12,360
And I suppose that's what the
investors are investing in.

1452
01:15:12,760 --> 01:15:16,920
But realistically, what you are
always investing in is a team

1453
01:15:17,640 --> 01:15:21,160
that hopefully will explore that
project.

1454
01:15:21,600 --> 01:15:25,480
And if that fails, if you're
not, which it probably will if

1455
01:15:25,480 --> 01:15:28,040
you're not very lucky, it will
then get the next project and

1456
01:15:28,040 --> 01:15:29,880
the next project and the next
project right.

1457
01:15:30,840 --> 01:15:33,360
I think that's the the perfect
spot to leave the conversation.

1458
01:15:33,400 --> 01:15:35,200
Thanks a lot for your time, John
and Ahmad.

1459
01:15:35,200 --> 01:15:36,680
This has been a fascinating
conversation.

1460
01:15:36,720 --> 01:15:37,720
Appreciate it.
Thanks a lot.

1461
01:15:37,920 --> 01:15:39,160
I love this stuff.
Cheers.

1462
01:15:39,520 --> 01:15:42,920
Alrighty, thank you very much
Ahmed Ali and John Ronsky.

1463
01:15:42,920 --> 01:15:46,120
I was a great chat and.
Thank you to you too for you

1464
01:15:46,120 --> 01:15:48,440
smashed it out.
No, I loved it lots.

1465
01:15:48,440 --> 01:15:52,240
And yeah, no, there's certainly
sometimes it's easy to forget

1466
01:15:52,240 --> 01:15:55,640
all the, the heuristics and
biases we have as a, you know,

1467
01:15:55,640 --> 01:15:57,200
investors and mining companies
have.

1468
01:15:57,200 --> 01:16:00,440
So that was, that was a really
interesting pace that I, I loved

1469
01:16:00,440 --> 01:16:02,320
about that chat.
Absolutely fascinating.

1470
01:16:02,320 --> 01:16:03,560
We got a couple other people to
thank.

1471
01:16:03,560 --> 01:16:04,920
Oh.
I love to think of those people.

1472
01:16:05,240 --> 01:16:08,600
Access mining technology MMS we
had in the show.

1473
01:16:08,600 --> 01:16:10,320
We also had greenlands in the
show.

1474
01:16:10,320 --> 01:16:14,160
Give them a buzz verify smack
power and technology, DSI

1475
01:16:14,160 --> 01:16:19,280
underground, Silverstone CRE
insurance K drill and use spark.

1476
01:16:19,280 --> 01:16:21,280
Use it.
Get on to Spark.

1477
01:16:22,880 --> 01:16:24,000
Have a good weekend, money
miners.

1478
01:16:26,160 --> 01:16:28,720
Information contained in this
episode of Money of Mine is of

1479
01:16:28,720 --> 01:16:30,760
general nature only and does not
take into account the

1480
01:16:30,760 --> 01:16:34,400
objectives, financial situation
or needs of any particular

1481
01:16:34,400 --> 01:16:36,440
person.
Before making any investment

1482
01:16:36,440 --> 01:16:39,480
decision, you should consult
with your financial advisor and

1483
01:16:39,480 --> 01:16:42,640
consider how appropriate the
advice is to your objectives,

1484
01:16:42,840 --> 01:16:44,840
financial situation and needs.