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In the webinar, we will walk you through the value of geoscience data and its role in the journey to transformation. We’ll share Seequent’s software solution that’s achieving proven success for Lafarge Holcim and other Industrial Minerals companies.

Hear real world examples of how Industrial Minerals customers have:

  • Reduced operating costs by more than $2.5million USD per year
  • Decreased stripping ratio from 7:1 to 1.5:1
  • Developed more sustainable mining operations now and for the future

We will prove that you already have most of the tools you need to make this change with minimal disruption and cost.

Overview

Speakers

Luke Stewart
Regional Director – EMEA, Seequent

Duration

19 min

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Video Transcript

[00:00:01.600]
<v Instructor>Hello, everybody.</v>

[00:00:02.433]
And welcome to this Seequent webinar

[00:00:04.910]
around Digital Transformation in Industrial Minerals:

[00:00:07.750]
Maximizing Value from Geoscience Data.

[00:00:10.400]
I’m Luke Stewart, the EMEA regional director for Seequent,

[00:00:13.860]
and here in EMEA, we already have,

[00:00:15.790]
and have helped several industrial minerals companies

[00:00:18.620]
along this digital transformation journey.

[00:00:21.340]
Of course, we want to help more of you.

[00:00:23.910]
So let’s jump straight in.

[00:00:26.210]
And digital transformation.

[00:00:27.743]
This sort of digital transformation term has become such

[00:00:30.940]
a broad catch, catch-all term for technology-related change

[00:00:34.750]
in business that it can be difficult

[00:00:37.340]
to actually provide a single definition

[00:00:38.980]
for what digital transformation would mean

[00:00:40.840]
for your operations.

[00:00:42.490]
Gartner defines digital transformation as anything

[00:00:46.168]
from IT modernization, for example, cloud computing,

[00:00:49.500]
to digital optimization, to the invention

[00:00:54.310]
of new digital business models.

[00:00:57.080]
At a high level, though,

[00:00:57.913]
I think digital transformation can be seen

[00:01:00.387]
as the integration of digital technology

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into all areas of business,

[00:01:05.370]
resulting in fundamental changes to how businesses operate

[00:01:09.510]
and how they deliver value to customers.

[00:01:12.380]
Beyond that, it’s a cultural change

[00:01:14.420]
that requires organizations to continually challenge

[00:01:18.080]
the status quo, experiment often,

[00:01:20.810]
and get comfortable with failure.

[00:01:23.710]
This sometimes means walking away from legacy systems

[00:01:27.320]
and long-standing business processes

[00:01:29.550]
that companies were built upon

[00:01:31.270]
in favor of relatively new practices that are being defined.

[00:01:37.180]
Digital transformation should begin, though,

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with a problem statement, a clear opportunity,

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or an aspirational goal,

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the why of your organization’s digital transformation.

[00:01:47.610]
Over the next few slides,

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we’re going to discuss why, here at Seequent,

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we believe the greatest value to your business

[00:01:53.350]
is to start this journey with geoscience data.

[00:01:56.860]
And we’ll look

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at the 2020 Geoscience Data Management Survey,

[00:02:01.640]
which had over 709 responses from 320 organizations.

[00:02:07.250]
And this really showed geoscience data management continues

[00:02:11.200]
to be a key issue across various industries.

[00:02:23.120]
So what’s driving this change?

[00:02:26.670]
I quote from BCG, “Mining companies are investing

[00:02:30.170]
in digital technologies across the value chain,

[00:02:32.990]
from operations to procurement, to sales and marketing.

[00:02:36.450]
Unfortunately, many of these investments

[00:02:38.560]
have fallen short of their potential.”

[00:02:40.760]
According to BCG’s Digital Acceleration Index,

[00:02:44.250]
the mining industry is roughly 30 to 40%

[00:02:47.680]
less digitally mature compared to comparable industries,

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such as automotives or chemicals.

[00:02:54.180]
And as they pointed out, that is a huge deficit,

[00:02:56.870]
especially considering the enormous benefits

[00:02:59.530]
digital technology can bring to the sector.

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By accelerating digital transformation,

[00:03:05.180]
the mining sector can boost throughput,

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simplify processes, lower costs,

[00:03:10.960]
improve recovery and yield,

[00:03:12.620]
and reduce supply chain complexity.

[00:03:17.060]
External pressures are also a driving change

[00:03:19.240]
in the industry.

[00:03:20.320]
Socially conscious and tech-enabled consumers

[00:03:23.430]
are demanding greater transparency about what they buy

[00:03:27.740]
as sustainability becomes the forefront of consumers,

[00:03:32.130]
and investors’ conscious coordinated approaches

[00:03:35.040]
from the government and global bodies

[00:03:37.150]
are ensuring the responsibility

[00:03:38.860]
is on industrial minerals companies

[00:03:40.560]
to transform their business.

[00:03:44.430]
And a failure, where perceived or actual,

[00:03:48.850]
can impact a brand’s reputation

[00:03:51.090]
and lead to loss of revenue,

[00:03:53.970]
or even license to mine one of your most valuable assets.

[00:03:59.470]
And at the same time,

[00:04:00.560]
access to resources is becoming a critical factor,

[00:04:04.200]
as environmental social

[00:04:06.340]
and scarcity factors all come into play.

[00:04:09.640]
So there’s a lot driving this digital transformation change,

[00:04:14.470]
especially in industrial minerals in the mining sector.

[00:04:23.187]
At Seequent, we believe the greatest value lever

[00:04:26.850]
you can pull is to maximize the knowledge you extract

[00:04:30.340]
from your geoscience data.

[00:04:32.250]
The business case for investing

[00:04:33.640]
in things like procurement sales, marketing,

[00:04:36.610]
may be easier to define.

[00:04:38.390]
However, the efficiencies of these systems are built

[00:04:41.350]
on the premise that you fully understand

[00:04:43.620]
the product you are producing, and by its nature,

[00:04:46.310]
a resource is variable,

[00:04:48.110]
and variability is not conducive

[00:04:51.750]
to an efficient optimized supply chain,

[00:04:55.090]
reducing the variability of your product

[00:04:57.530]
through the supply chain that leads

[00:04:58.910]
to a more efficient system.

[00:05:01.150]
Greater efficiency translates directly to revenue.

[00:05:05.330]
So managing variability becomes harder and more expensive

[00:05:09.890]
the further along the supply chain it occurs.

[00:05:12.560]
Therefore, a smaller investment upfront can lead

[00:05:15.640]
to greater returns throughout.

[00:05:18.210]
The image on your screen is a small example

[00:05:20.520]
of the broad range of disciplines that are underpinned

[00:05:24.770]
by our resource knowledge.

[00:05:26.810]
As discussed, the value of your geoscience data

[00:05:29.760]
does not stop once the material is loaded.

[00:05:32.390]
It is also key to understanding your business value,

[00:05:36.090]
and critical to environmental, social, and technical risks.

[00:05:42.640]
So when it comes to assessing the value

[00:05:45.140]
of digital transformation to your business,

[00:05:47.680]
teams have to consider broader applications of geoscience.

[00:05:52.190]
A comprehensive resource model, for example,

[00:05:54.410]
that consistently incorporate changing data,

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and evaluates all spatial numerical

[00:06:00.980]
and intellectual information in a 3D plus temporal context

[00:06:04.810]
helps to identify problems early.

[00:06:08.260]
A continuously updated resource model enables

[00:06:12.140]
an adaptable design that allows material changes

[00:06:15.970]
in the design to be identified in the moment.

[00:06:19.010]
Informed field decisions can be made

[00:06:21.690]
to either alter the design,

[00:06:23.420]
or accept the current plan that meet

[00:06:25.630]
the required material specifications.

[00:06:29.480]
The resource model, therefore, becomes the basis for design,

[00:06:33.320]
used at all phases of the mine or career lifecycle.

[00:06:37.030]
Development of resource knowledge enables engineers

[00:06:40.240]
to understand the physical system,

[00:06:42.460]
and make informed decisions about the operations

[00:06:45.360]
and processing and minimizing waste.

[00:06:49.980]
So how does this actually work in practice?

[00:06:52.250]
And I think a great way to show that is a recent case study

[00:06:55.490]
we ran with one of our customers, LafargeHolcim,

[00:06:58.640]
and it is a great example of how improving

[00:07:01.330]
the technology process and culture led

[00:07:04.640]
to significant business impact

[00:07:06.550]
to their current plant operations.

[00:07:08.920]
And in this example,

[00:07:10.020]
LafargeHolcim changed their approach

[00:07:12.230]
to modeling their resource by re-evaluating existing data

[00:07:16.240]
and improving on the quality of the interpretation,

[00:07:19.380]
improved collaboration by breaking down silos

[00:07:22.250]
between technical groups, geologists,

[00:07:24.370]
planners, engineers, plant safety,

[00:07:27.560]
to maximize the value of the information collected,

[00:07:31.180]
and improved communication of critical factors

[00:07:34.700]
that influenced the performance of their plant.

[00:07:37.490]
And by doing this,

[00:07:38.340]
you can see right here on the screen,

[00:07:40.150]
the savings and enormous value they achieved

[00:07:44.750]
by doing these things.

[00:07:46.357]
$2.5 million per year of operating costs,

[00:07:51.240]
not to mention the environment,

[00:07:52.880]
stripping ratio, and other monetary savings as well.

[00:07:57.330]
So the outcomes from doing these kinds of activities,

[00:08:01.880]
this digital transformation, can be huge.

[00:08:11.212]
So how is Seequent helping tackle these challenges,

[00:08:14.880]
and what we aim to provide an ecosystem

[00:08:18.110]
of connected solutions, which breaks down silos,

[00:08:21.800]
and enables data to flow seamlessly between users.

[00:08:25.890]
This effort empowers the user to extract further value

[00:08:29.740]
from individual products

[00:08:31.140]
by building an environment of integrated tools customized

[00:08:35.330]
to your needs.

[00:08:36.670]
And that’s exactly what we just saw with LafargeHolcim,

[00:08:40.070]
and we helped them to do, and again,

[00:08:42.410]
we want to help you do the same thing.

[00:08:51.160]
And this isn’t a departure from desktop applications,

[00:08:54.080]
but embraces the power of the cloud

[00:08:57.870]
to enable connectivity and integration.

[00:09:00.930]
The ecosystem works both internally

[00:09:04.040]
and with third-party applications to provide a variety

[00:09:07.280]
of consumption models.

[00:09:09.000]
Let’s call it ecosystem as a service,

[00:09:11.350]
and the design is about providing flexibility

[00:09:14.190]
to the customer to break down traditional data silos,

[00:09:17.930]
pick the tools your business needs,

[00:09:20.720]
and open up your processes to the available data.

[00:09:36.080]
Right, and the key to any solution

[00:09:38.960]
is that it provides the means

[00:09:41.010]
to work effectively as a team and ensure data transparency,

[00:09:47.300]
and these are the underlying principles that allow

[00:09:49.770]
for robust review and decision-making process.

[00:09:54.650]
But how has it actually accomplished?

[00:09:57.630]
Well, firstly, all stakeholders in the project,

[00:10:00.520]
whether modelers from different geoscientific sort of groups

[00:10:04.460]
or backgrounds, project managers,

[00:10:06.710]
or third parties, such as consultants,

[00:10:08.970]
joint venture partners, need to have access

[00:10:11.880]
to the latest data in near real time as possible.

[00:10:16.150]
Secondly, everyone needs to work collaboratively

[00:10:19.300]
from a single source of truth

[00:10:21.470]
to create up-to-date models that facilitate

[00:10:24.140]
the development of a digital twin,

[00:10:27.270]
and core to our solution is Seequent Central,

[00:10:29.960]
a cloud-hosted model and data management system

[00:10:33.450]
with web-based visualization capabilities

[00:10:36.390]
that facilitates collaboration,

[00:10:39.010]
’cause collaboration is cool,

[00:10:41.430]
and a robust model to design workflow bridges the gap

[00:10:47.310]
between typical disconnected interpretation

[00:10:50.890]
and planning workflows,

[00:10:52.880]
and with sequenced geoscience solutions,

[00:10:55.420]
a continuous modeling paradigm is established

[00:10:59.770]
that solves the data management

[00:11:02.680]
and multi-stakeholder conundrum,

[00:11:05.460]
and centers activities on optimizing your planning

[00:11:09.630]
with good communication,

[00:11:12.230]
which is key to the success of all this.

[00:11:16.350]
So let’s take a look at the role of our expert applications

[00:11:21.380]
in a little bit more detail.

[00:11:30.370]
Okay, so identifying that change is required,

[00:11:34.710]
I think, is easier than knowing how or where to start.

[00:11:37.840]
We believe the first step on this journey

[00:11:40.040]
is how your data is managed.

[00:11:42.250]
Your businesses run on data.

[00:11:44.330]
And as we highlighted earlier,

[00:11:46.400]
the information that describes the location,

[00:11:49.710]
quantity, and quality of your resource ultimately feed

[00:11:54.130]
into every other business decision you make.

[00:11:56.780]
And my colleague, Dave Pierce,

[00:11:58.700]
likens our relationship with databases

[00:12:00.890]
to growing up with our favorite superheroes,

[00:12:03.210]
believing them to be invincible.

[00:12:04.630]
No task is too big. And the challenge is insurmountable.

[00:12:08.050]
Unfortunately, though, even though we’re all much older now,

[00:12:11.780]
and grown up with no other particular piece of software,

[00:12:16.530]
it’s very tempting to think the same way.

[00:12:19.870]
Long-term, everyday use breeds a cozy familiarity.

[00:12:24.300]
And our belief in that program’s abilities

[00:12:27.050]
can grow to be wildly optimistic.

[00:12:30.180]
And there’s probably no better example

[00:12:32.150]
of this than Microsoft Excel.

[00:12:33.820]
It’s been around for, say, 30 years,

[00:12:36.890]
and it’s, by definition, a superhero,

[00:12:40.250]
or a heroic spreadsheet program,

[00:12:43.150]
that has helped to power vast numbers of businesses,

[00:12:46.290]
and perhaps whole industries.

[00:12:48.160]
I use it pretty much daily myself, but it’s not a database.

[00:12:52.370]
And for hundreds, if not thousands

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of geologists in our industry,

[00:12:56.380]
Excel has been the go-to place for inputting data.

[00:13:00.760]
It’s a data habit we can hardly be blamed for,

[00:13:04.120]
because it’s been the only flexible cheap tool

[00:13:07.490]
at our fingertips for so long,

[00:13:12.060]
but immensely powerful Excel is,

[00:13:14.800]
its use as a data repository in sectors such as ours comes

[00:13:18.870]
with risks and big burdens on our geologists.

[00:13:22.120]
And just a few sort of reasons why this is,

[00:13:24.830]
geologists need data automation and clear audit trails

[00:13:28.400]
for project success.

[00:13:29.930]
Using Excel for data storage is a 100% manual process.

[00:13:34.270]
This means that creating the audit trail is crucial

[00:13:37.010]
to the success of any project involving drill hole,

[00:13:41.830]
and point sample data is all but impossible.

[00:13:45.670]
Teams need to feel confident,

[00:13:48.710]
and there is security and governance in place

[00:13:51.490]
on their projects.

[00:13:52.380]
With Excel, a user can modify any Excel spreadsheet

[00:13:56.210]
pretty much anytime, and geologists are frustrated

[00:13:59.800]
that they can’t be 100% certain

[00:14:01.950]
of a single source of truth.

[00:14:04.150]
There is no such thing as one Excel file.

[00:14:07.120]
It’s inevitable that users will have a number

[00:14:09.540]
of them at different stages of completion,

[00:14:11.930]
partially backed up or not backed up at all,

[00:14:14.950]
with no real record of what’s been changed,

[00:14:17.090]
deleted, omitted, across sort of vast libraries

[00:14:22.750]
of different spreadsheets.

[00:14:25.290]
So how can we know which of these files is the one

[00:14:28.210]
that needs to be passed on?

[00:14:31.830]
Geologists are particular about accuracy.

[00:14:34.550]
Yeah, we know that, right?

[00:14:36.250]
But when we’re having to manually input

[00:14:39.520]
and manage millions of lines of data,

[00:14:41.320]
it’s human nature that mistakes will happen.

[00:14:45.000]
And the types of data and the sheer volume of data

[00:14:48.060]
that geologists need to handle

[00:14:49.670]
means Excel isn’t really cut for the job.

[00:14:52.130]
Easy integration with third-party tools is problematic.

[00:14:55.560]
The automation of files to fit with modeling packages,

[00:14:58.890]
core photos, Downhole Surveys,

[00:15:01.410]
this sort of thing, is becoming increasingly essential

[00:15:04.080]
for geologists to be able to work

[00:15:06.010]
to their maximum efficiency,

[00:15:07.650]
and is, again, largely beyond Excel.

[00:15:11.550]
Our next Deposit, however, solves a lot of these problems,

[00:15:13.940]
logging tools to standardize data capture, flexible pricing.

[00:15:18.090]
It works out of the box with no install.

[00:15:19.960]
You can still work offline, however.

[00:15:22.190]
You can customize the solution

[00:15:23.840]
for your need if you need to.

[00:15:25.560]
And it provides global access to data for view, comment,

[00:15:29.680]
and automatic data validation.

[00:15:31.850]
It captures a full audit trail.

[00:15:34.080]
And so it will be integrated with Leapfrog to you as well.

[00:15:38.570]
So it really can provide a solution to the Excel dependency

[00:15:44.040]
that we’ve become used to in the industry.

[00:15:50.810]
Okay, so once you have your data taken care of,

[00:15:53.600]
it’s time to look at the geological model,

[00:15:56.080]
and the geological model forms the foundation

[00:15:58.430]
of the rest of your downstream processes.

[00:16:01.400]
An accurate understanding of the orientation, volume,

[00:16:04.977]
and physical controls on your resource

[00:16:07.170]
is critical to be able to define the quantity,

[00:16:11.260]
quality, and spatial distribution of your material,

[00:16:14.930]
but it’s not enough to build one model in isolation.

[00:16:18.340]
Our model should constantly evolve as additional data

[00:16:21.620]
is collected and new ground exposed.

[00:16:24.840]
These live inputs to your understanding

[00:16:28.030]
should not be limited by process.

[00:16:31.260]
Data needs to flow seamlessly from source to destination,

[00:16:35.570]
ensuring appropriate quality controls and checks

[00:16:39.550]
are performed on the way to provide confidence

[00:16:42.170]
in the knowledge being developed.

[00:16:45.390]
As change occurs,

[00:16:46.500]
the impacts need to be communicated widely

[00:16:49.520]
to ensure all stakeholders understand impact

[00:16:53.300]
of the processes,

[00:16:54.410]
enabling a proactive approach to handling variability

[00:16:58.210]
in the supply chain.

[00:17:00.030]
So in summary,

[00:17:01.440]
an accurate representation of geological conditions

[00:17:04.470]
is fundamental to developing optimized designs, schedules,

[00:17:09.260]
and ultimately ensuring a constant,

[00:17:12.570]
consistent product is provided to your customers.

[00:17:19.840]
And the data we collect is never exhaustive.

[00:17:23.650]
So the last piece of this particular puzzle is how

[00:17:27.220]
to calculate a global understanding of your resource

[00:17:30.380]
from a limited amount of physical sample points.

[00:17:33.330]
Amongst there are many solutions in the market

[00:17:35.490]
that can perform this task,

[00:17:37.220]
we’re focusing on how you can transform your business

[00:17:41.810]
to drive greater value in efficiencies.

[00:17:44.460]
And here, we believe that removing the barriers to data flow

[00:17:47.710]
is critical to ensure that your resources

[00:17:49.980]
are dynamically updated

[00:17:51.780]
based on the latest information available,

[00:17:54.920]
and your updates of resources and reserves give you

[00:17:57.920]
a long-term view of your business’s business,

[00:18:00.370]
and meet reporting requirements for public-facing companies.

[00:18:04.170]
However, the cadence of these updates,

[00:18:06.570]
often driven by the time taken to complete,

[00:18:10.620]
lack the granularity required to identify the variations

[00:18:15.470]
in your resource that can significantly impact

[00:18:18.520]
the efficiency of your systems, and potentially,

[00:18:21.280]
they’ll increase the environmental risks

[00:18:23.600]
associated with contaminants and emissions.

[00:18:26.950]
So moving to a solution that enables a resource

[00:18:29.510]
to be updated on a monthly, weekly,

[00:18:32.810]
or even on a daily basis requires

[00:18:35.540]
a truly integrated environment.

[00:18:42.090]
So we’ve come to the end, and in summarizing,

[00:18:46.430]
this shift in the approach of how geoscience data

[00:18:49.700]
is managed and used in your operations

[00:18:52.720]
does not require significant investment.

[00:18:55.170]
It does not require significant retraining.

[00:18:57.390]
It requires a recognition of the value

[00:19:00.430]
that geoscience data provides to your businesses,

[00:19:03.700]
and an innovative partner who will work with you

[00:19:06.660]
to support your people and business through this change.

[00:19:11.840]
So thank you for your time, your attention,

[00:19:15.260]
and, of course, if you’d like to get in touch,

[00:19:18.070]
please reach out to myself or any of my colleagues.

[00:19:20.930]
We would be delighted to help you

[00:19:22.920]
on this digital transformation journey

[00:19:25.160]
on industrial minerals.

[00:19:26.390]
So thank you again. We’ll speak soon.