Lyceum 2021 | Together Towards Tomorrow
What have been the benefits of digital ground modelling, and how has it improved the project outcome?
If you could change one thing about how the industry does something today, what would it be and why? These are just two of the questions we’ll be posing to a panel of industry thought leaders from Mott MacDonald, DB Engineering and Arcadis. Join us and together let’s explore how digital transformation has already positively affected the role ground engineering plays in transport infrastructure projects, and what still need to change in the near future.
Senior Geotechnical Consultant, DB Engineering & Consulting GmbH
Geotechnical Data & 3D Ground Modelling Specialist, Mott MacDonald – UK
Technical Director, Geotechnical Engineering, Arcadis Consulting (UK) LTD
Regional Head of Civil, Environment and Energy, EMEA, Seequent
Hello, and welcome everybody
and thank you for joining us for this session
on Digital Information in Transportation Infrastructure
in Ground Engineering.
I’m going to be joined today
by three other panelists.
We have Bernd Heer from DB Engineering Consulting GmbH,
joining us from Germany,
Andrea Gillarduzzi from Arcadis,
and Peter Fair from Mott MacDonald.
And we’re going to be going through
talking about examples of where digital innovation
is helping in ground engineering to date,
and also, discussing some of the challenges
ahead in this sector where we can expect
to see improvements.
So without further ado,
let’s make best use of the time
and go round with some introductions.
Bernd, could I ask you to kick off please?
<v ->Yeah, so as you said, my name is Bernd Heer.</v>
I’m working with railway sector
for about 23 years now,
most of the time for companies within the German Railway.
Now, with DB Engineering and Consulting,
and I’m looking after the strategic
development of the geotechnical branch
of DB Engineering and Consulting.
<v ->Thank you, Andrea.</v>
<v ->Hello, my name is Andrea Gillarduzzi.</v>
I’m a Technical Director for Geotechnics for Arcadis UK.
I lead the Arcadis global initiative
for subsurface digital modeling,
and I lead the Arcadis UK Tunneling Community of Practice.
At present, I’m mostly working as engineering manager
for one of the lots of HS2.
<v ->Thank you, and finally, Peter.</v>
<v ->Hi there, so I worked for MacDonald</v>
within the geotechnics practice,
and currently, working on HS2 as a GI data manager,
making sure that the data is all there,
ready to be used by our designers,
and then bringing that into the 3D, 4D environment,
the BIM environment, making sure that
our geotechnical data is talking
with the wider BIM platforms.
<v ->Great, and so on that note, I’m sorry,</v>
I should add, I’m the Head of Segments,
which are Seequent’s regional business
for civil environment and energy.
And yeah, delighted to be joined by
far more about this industry
than I could expect to discuss here on my own,
so it’s great to have you joining.
With the ground conditions increasingly
being incorporated in the BIM environment,
the business information monitoring,
are there any examples of where going digital
is actually connecting things faster
within the project and improving the outcomes?
Maybe you could start with that, Bernd.
<v ->Yeah, well, the 3D models we’re providing now</v>
enable a faster and smoother tendering processes,
especially in relating to German regulations
called VOB Part C where we have to provide
the contractors with very detailed information
about the ground and the amount,
the volumes of soil or rocks
they’re expecting of a certain type,
and Leapfrog enables us to do just that,
to give detailed information about that,
which enables a more precise tendering.
And also, in the end,
during the production and conception process,
there is less room for discussion with the contractors,
which helps the project in general, really.
And we’re seeing that.
We’re working on that.
We’ll expect a lot better outcome in the future.
<v ->Thank you, how about you, Andrea?</v>
<v ->Yes, we use a digital subsurface modeling</v>
in the better plethora of jobs in Arcadis.
For example, when we prepare the tender documentation
and the DCO application for Lower Thames Crossing,
which is a major proposed new crossing
to the East of London,
we used an approach based on GIS
and the proprietary software.
The GIS included over 200 layers of information
ranging from aerial photograph, satellite imageries,
like InSAR, color-infrared
over 800 historical burrows which were digitized,
new information, burrows topography, bathymetry.
They were all integrated to create a ground model
which then it was used as the basis
for mast hole assessment for risk assessment,
including GI, for planning the GI and delivery,
and then effectively, as the core for the B model,
which included, obviously, the existing run conditions,
and the modification proposal,
and the assets at the area,
all the utilities, the proposed diversions,
and that land ownership,
stakeholder management, and the like.
We are also using GIS approach in extensively in G2S,
which is one of the lot of HS2
and is used for anything from mast-holding
to planning the works and including some
automatic construction, for example,
for the trenches, which are going
to be located at top of the embankments.
<v ->Wow, that’s quite a lot.</v>
Thank you, Andrea.
And to you, Peter, same question.
<v ->Yeah, we’ve certainly seen</v>
being able to work within BIM environment,
the 3D environment really beneficial, again,
working within the HS2 arena,
where we’ve got some on lots M1, M2.
We’ve got over 6,000 increasing
nearly to 7,000 boreholes of the route,
and so many cuttings that the contractor,
Balfour Beatty VINCI’s asking us
to use the BIM environment to help understand
the earthworks material class.
Probably a year ago, we did that
based on statistical analysis,
which wasn’t looking at the spatial data
apart from is it in the cutting
or is it not in the cutting?
So where we’re digging out the cutting,
which could be several hundred meters long
up to a couple of kilometers long,
and some of them, 20, 30 meters deep.
There’s a huge amount of material coming out there.
And being able to do a 3D analysis of that data,
so looking at the liquid limit,
the moisture state, percentage passing,
and the PSD, and total percent of sulfate,
and the final one which is the slate durability.
Bringing the actual GI data directly
into the BIM environment, 3D environment
using Leapfrog, we’ve been able
to do numerical 3D models based on that.
We’ve been able to use, combine those
with the original geological models
that we created for those cuttings,
and then the output of that has allowed us
to have a full earthworks material class
geological model that we can give real volumes
back to the conductor of the types of material
we’re expecting to excavate.
Now, one of the really key things about that
is it’s also been able to allow us
to see where not only the percentage
of the material, the volume of material,
but how easy that’s going to be to excavate.
So for example, if you’ve got lots of good material
across the whole length of the cutting,
but it’s only in small pockets here and there,
the contractor can’t actually excavate it.
So we can see that in 3D model,
much easier than we could
when we were just doing the statistical analysis.
So we can now assess whether we’re actually
able to get that good material out and reuse it,
or whether it will just be pulled out
as a mass of poorer quality material.
<v ->Thanks very much.</v>
So there’s quite a variety of use there
from tendering to in-project coordination
and even the material reuse there
during the construction.
So let’s move on and think about another question,
and that is thinking about how international standards
have already come in to improve
the digital project like ISO 19650.
As we think about the digital assets
and the design life, what are your
thoughts on improving the digital asset?
And maybe Andrea, we start with you on this one.
<v ->I think it’s fairly fundamental that any model</v>
which gets generated by consultant
during any phase of design development,
or indeed the maintenance needs
to be transferred to the owner.
Without a single model,
we’re not going to have a single
understanding of the other settings.
Information needs to be collected together
to be better understood.
I think of it that there is,
we’re still facing a challenge as an industry
about the transfer of data,
and the definition of ownership of the data,
and the liability attached to it.
At present, we are sometimes faced with a concern
that sharing data expands our liability,
and this discourages collaboration
between the different parties,
and is something which I believe we need
to overcome as soon as possible
to lose an immense opportunity.
<v ->Thanks, Andrea, and it’s a great point.</v>
Peter, do you have a comment on this?
<v ->Yes, sure, what I think is one of the key things</v>
is that we’re finding that on a lot of jobs
where the asset has already been built,
and we’re going back to do some surveying,
or inspections, or the client
wants some more information,
particularly on the national infrastructure type clients
is that we’re going back, and we’re doing say,
ground investigation or other assessments,
very close to where they’ve previously been done before,
and you can see that each year, borehole has been drilled
through that concrete lining or whatever it might be,
and that data is not being collected,
it’s not being saved,
it’s not being put back in a usable way.
There might be a PDF stuck somewhere
or a paper report even,
and we can’t access those very easily.
So being able to have those in an environment
where we can easily see what information was collected
and all of that information that was collected
is saved in a way that is usable going forward,
and that those investigations
aren’t just limited to whether
there was a void behind the liner or not, say,
but actually, what else was found
when they did that investigation.
Just collecting all that information,
making sure it’s stored in a reusable way is really key,
and something like ISO 19650 will enable us
to keep reaching towards that.
<v ->Great, thanks, Peter.</v>
And over to you, Bernd.
<v ->Yeah, I think we’re in a data age</v>
where we look at data, or use data,
and try to store data that nonetheless,
we have to have a use case for storage and accessibility.
Whether we actually have a single asset
for the BIM model that is safe for the next 120 years
is a question of whether it’s worth the cost as well.
For critical infrastructure,
I think, there’s no question.
We need to have that model available
for use in emergencies for future projects
on that critical infrastructure.
For every little single building,
well, that discussion will come
if there is no use case,
and the cost outstrips the benefits for that.
I think, we have to talk about that,
and we have to find a way in the industry
to deal with that.
But generally, yes, we want that data stored.
We wanted access, and we want to have access
to the data in the future,
and we need to make sure that we have access
to that data in the future,
which is one of the challenges we face, I think.
<v ->Yeah, interesting observation on…</v>
And yeah, we all know the cost of storage
gets cheaper and cheaper over time,
but also, everything that we’re collecting
increases as well, so it’s always a delicate balance.
<v ->And also, if it’s not updated,</v>
if it’s not ensured that the data is continuously updated,
which is not such a big point for ground conditions,
but every other aspect of the building.
If there’s been work done in the building,
which is not being put into the model, well,
then we actually work on wrong assumptions, probably.
So there needs to be a standard for that.
<v ->And I’m hearing here that it’s not just</v>
about technological solutions
because in a lot of times, they exist,
or they just need a bit more connectivity,
or interoperability with another application,
but there’s systemic challenges within the industry
of agreeing how to, what to save from a project.
And talking about liability,
talking about exposure and risk throughout the project.
Any more comments on that?
<v ->Well, we need to address the question</v>
whether it’s, okay, Peter, please.
<v ->Sorry, Bernd, yes.</v>
<v ->Okay, we need to raise the question</v>
whether it’s actually more dangerous
to have an incomplete model
than to have no model at all.
If it’s not ensured that the model
is continuously updated for an asset,
well, is it worth keeping it then?
And I’m sure that’s the danger
we all have in mind that that might happen.
<v ->And Peter, did you have a point now?</v>
<v ->I was, oh yeah.</v>
And the comment I was going to say
is agreeing with Andrea in terms
of when models are passed on
from one consultant to another,
how do we ensure that that is able
to be used by the ongoing consultant?
I think that’s a really good point that Andrea raised.
So often, we don’t have the assurance of that model.
And then as a consultant, we then feel
that we have to rebuild that model from scratch
just to prove to ourselves that
it is of the required level,
and that seems to undermine all this.
<v ->I think that the interesting point</v>
is the fact that we shall share factual data,
but any kind of ground model is by its own,
inherently, an interpretation.
There is nothing right or wrong,
it’s just trying to collect information
and trying to make sense of it.
So in many respects, when we share a model,
we already shared a liability,
and we need to acknowledge that is the case.
I think it is important that
we become economical in the way we work.
If you bring, for example,
what is happening in London every day,
probably today, they must’ve been excavating
a couple of tens of meters of trenches for utilities.
Somebody must have overflown a drone
to over a canal to check whether something is leaking.
Somebody must have done a CCTV camera survey.
Old data which get lost,
they’re not even remotely recorded.
Imagine how much data, how much value
we deprive in ourself as a society,
and how much value that is bankable, which get wasted.
It is unnatural to keep on working this way.
<v ->It’s a great point.</v>
And especially, about starting again
on each contractor coming new to a project,
starting again with the ground modeling.
And an interesting observation from before
was around the boreholes being considered
as factual data when they are in fact,
their interpretations already being
run through human interpretation.
But largely, they’re considered as fact
at the start of the project,
but they’re their own form of interpretation, aren’t they?
It’s just that everybody’s agreed that that’s become fact.
<v ->Gareth, I think there is where it gets to the point,</v>
the significant of having standards.
We agree that there is a conventional way for logging
the burrows described in the geological information,
acquiring data and up-testing.
Similar, we need to agree a similar
approach to deal with data,
and that will make it more transferable,
and easier to user.
And to say that then there are also technology
which allow to overcome the subjectiveness of,
for example, the login,
or we got to these days,
scanners for a solid core of rock,
and this approach is extensively used
in other industry, other civil engineering,
for example, in mining.
And that we can have then,
much more information from scanning
because it’s just not optical scanning,
we can use a color-infrared, we can use X-ray,
we can use a lot of other techniques
which allow to squeeze out more
from the same set of data,
and once again, to become economical.
<v ->Very good, and there’s…</v>
Is it then becoming a thing to go back
to the core imagery within a project
and not just the borehole logs?
<v ->I think that the matter is, at present,</v>
out of a borehole, we use only visual.
Fundamentally, somebody described a core,
and that is the only thing
which is get the perceived
and then transmitted to others.
Should anybody has been a field engineer,
field geologist would understand that
when you touch a core,
you got your tenant information.
If you can smell the core,
you can get that information
about the organic material and so on.
At present, we’re at the primordial
of transferring the information
we acquired in the field to a user,
which is located remotely.
And that there are a lot of new,
there’s a lot on new technology,
which in future, will help us
to get a more rounded experience
of what happened in the field,
even if you’re not there.
And I don’t know, augmented reality,
fully-immersive VR, and so on are all tools,
which probably would come to user,
and will enhance our experience,
and that will bring a new layer of datas
which are presently are completely disregarded.
<v ->So we could end up with a multi-sensory</v>
experience for the information acquired.
So I’m just thinking,
with the effects of future climate change,
more extreme weather events,
the volatile weather that we’re seeing
with heat waves and flash flooding becoming more common,
and seeing the effects of that
on our transportation infrastructure,
could digital assets and common data environments
be the key to updating ground models from sensor data?
And how would you like to see this evolving?
Maybe we start with you, Peter, on this one.
<v ->Okay, thanks, Gareth.</v>
Yeah, the key thing for me, I think,
in terms of understanding the sort of first part
of that question, Gareth, is actually
when we have the digital assets,
it allows us to respond quicker.
So it’s not so much in terms of the design,
but more, if we’ve got the digital asset,
when events happen, we can respond quicker
’cause we’ve got information at our fingertips.
And we understand the ground,
we can see the ground, we can see the bores,
we can see the structures that are being put in them,
and very quickly, with a drone survey,
we can see now, what’s happened.
So you’ve got a cutting that slipped
or embankment that slipped on a highway
or a railway asset alignment, longitudinal asset.
And we can quickly make a good,
informed, data-driven decision
without having to wait for further
ground investigation to be done
or further intrusion investigation.
We’ve got the data there,
we’ve got the asset there,
we’ve got the model there,
and we can very quickly respond to that
in a much more informed way
than we have been able to in the past.
<v ->Great, Bernd, any comment there?</v>
<v ->Well, I agree with Peter that’s one use of this.</v>
Based from the experience in Germany,
we just had four weeks back in the Atal
with our complete infrastructure
from German River completely destroyed
over 35, 40 kilometers.
We were looking a bit deeper,
and if we have prognosis systems
like rain forecast, weather forecast,
and we know the terrain,
and we can make all that smart
in an internet of systems, on internet of things,
and they can actually talk to our assets,
to our structures, then I can see a vision
that the structure actually puts out warnings
about what’s going to happen to it within that
sort of parameter sets that’s going happen
within the next few days or weeks, so.
But that’s just based on the experience we just had.
Even if we can’t save the infrastructure itself,
we can save other infrastructure,
or we can save human lives.
<v ->It’s a great goal, but Andrea, any comment?</v>
<v ->I think that going digital is going</v>
to have a potential significant impact
in having a better strategy to deal with climate change.
At present, we tend to deal a lot with the climate change
by changing the range of assumptions we use in our design,
and that typically, we make them broader
to deal with the greater variability.
In terms of this might, will result
in infrastructure which is more expensive
and let’s say, bigger to construct,
which means in turns are likely
or significant carbon footprint,
which then triggers more climate change,
and so on, and so on.
I think that should we start to use BIM
and the digital more in a more clever way,
we would be able to obtain much more significant data
about the real range of our ability,
and that might result in economical design.
And then as mentioned by my colleagues,
we would be able to maintain the infrastructure
in a much more effective way,
and therefore, we will be able to design it
less robust in the sense that we will start
to use a leaner design, which then in turns,
will have a lesser impact on the environment.
So I would suggest that data, data, data.
When you obtain the data,
you never know from what they might be used,
but if you’ve got the data,
you can decide that something that
you haven’t got is just guesswork,
and it’s not a nice place to be
for any engineering practice.
<v ->So then, during-</v>
<v ->Andrea, in your mind,</v>
okay, just a question for Andrea.
In your mind, are you doing something
like a backend analysis as well with that?
<v ->So Peter, would you mind to repeat?</v>
The volume went down a bit.
<v ->Okay, if you think about producing leaner designs</v>
using all the data you have
and having a custom maintenance system on the asset,
really, we’ll also looking back during the asset life
and seeing how could you’ve designed it differently,
even leaner or where you went tooling,
sort of a cycle of learning?
<v ->Yep, this, in the future,</v>
we’re going to move it to some
sort of internet of things.
And so, asset will be installed with sensors.
So going by the sector, software, other technologies,
and the like to provide some feedback on their performance,
which might help to design something
in future which is better,
but also, to retrofit and to adopt what is already there.
In many respects, this is already
been happening for decades and decades.
I remember jobs I designed 20 years ago,
I could design it 20 years ago
on highways on unstable slopes,
and the entire asset were installed
with the someters, inclinometers
that recurrent light for interferometry, and so on,
and that allowed to have a linear design.
So I don’t think that there is anything new.
It’s just that we’re going to use more
extensively than in the past.
And the present technology is going to use it
in a more effective manner to transfer
the information rather than to be owned
by a single project or single entities.
<v ->So then maybe back to you, Bernd.</v>
You’ve touched on it earlier,
in fact, you all have, on the sensors
driving the ongoing design and maintenance.
Where do you see the biggest
and most disruptive technology changes
coming from in the future with regards
to internet of things, kind of smart everything?
<v ->It’s everything, I think,</v>
everything will change eventually.
There’s a midterm effect, I think,
in the next five years where we learn
to integrate the available data much quicker,
which is, mostly for me, in the design phase,
where we start doing automated foundation design
with the 3D modeling be available,
and also, other, the data comes into play
where which we automate directly,
or which we generate directly from available sources.
Probably, what Andrea has already mentioned
with pipes and cables with augmented reality
during the conceptual process as well.
In the long-term, I think,
the role of the geotechnician, as it is today,
will change more to a curator of the results
to a curator of the data that has been
automatically gathered by sensors,
by different systems from historical sources.
And we, as the geotechnicians,
we actually only look, curate,
and validate that data before it gets put into the system.
I think that’s one of the main changes we will see.
There will be a lot less report-writing,
a lot less checking for drawings,
a lot less setting up meetings,
talking about what that actually means
’cause we will all agree on available data.
<v ->Great, anyone else got a comment, Andrea?</v>
<v ->I think that I totally agree with Bernd</v>
is that I think it’s going to be the way forward.
I have to say that if we start where the data
coming from different sources, which are independent,
not that, they having different databases
helps to validate the data.
An example is if we have to go
to the traditional geotechnical engineering,
if you got the geophysics for the ground by itself,
it has to validate, so.
If you combine it with burrows that you can calibrate,
then it takes a completely different dimension.
If then you combine it with, for example,
excavation of the very same size
when you got geophysic and burrows,
you squeeze out even more.
The same happens with a whole other set of data.
Data by a single set of data by its own
lack of certain value.
If you combine it with the rest, it’s much better.
So for example, let’s say, you got to monitor
an expansion joint over a bridge.
You combine it with a meteorological monitoring,
you get a better understanding of why things change.
You combine it with the traffic data
over a long period, you can understand,
for example, the wear of the joint, and so on, and so on.
So have the data, you add value.
And a lot of the data can be easily obtained
by embedding sensors and other technology
in what we build over to retrofit existing structures,
existing assets with sensors.
<v ->Great, Peter, any thoughts on this?</v>
<v ->A couple of quick ones.</v>
In the short term, I’m thinking
in terms of the amount of rigs that we have out onsite
and the feedback we get from those.
They’re recording so much data all the time
that the drilling rigs or the piling rigs,
and being able to use that directly to refine,
to lean, to help create more leaner designs,
almost as we’re building the assets
could be something that could change,
being able to bring that data
directly back into the design.
So we’ve done an initial design,
and then we’re out onsite, we’re drilling,
and using that data in a way
that can directly influence the design
as almost as the asset’s being constructed
could be something that’s of interest.
And then longer term, with the AI stuff,
I could see that actually, the data,
then I think Bernd touched on it earlier,
was we can use that data to almost do automatic design.
And as Bernd said, we become more curators,
and then we become the checkers
and the approvers of an automated design.
We’re starting to see that now with the CPT assessments
where the AI is doing better assessment
and doing less errors than some
of the human resources are doing already.
And so, being able to get the technology
to do a lot of the hard grafting,
the initial assessment first up
would be certainly, something that’s very interesting.
<v ->Great stuff.</v>
<v ->Yep, Peter, it’s two</v>
very good points.
<v ->Good to see some.</v>
<v ->Yeah, Peter, two very good points.</v>
In terms of drilling, I cannot agree more with you.
Even now, when we do, for example, investigation,
we record the machinery that they got
to use to record a lot of data,
which you don’t get to transfer.
For example, the torque used by the rig,
which can give information about the strengths
of the rock and of the soil.
All data that are available,
should that somebody be in the field,
they’ll probably will use it.
When we’re remote, we, at present, miss them,
and that is a waste.
Regarding automatic design,
another good, very good point,
effectively, automatic design is already
happening in certain industry.
For example, in drill and blast,
we have already have a jumbo,
so which effectively position the drilling holes
for the blaster in almost automatically,
the best position to obtain the best rate of production,
and the safest production,
and avoidance of over-excavation, over-profiling.
So something is already happening,
probably not as fast as it should,
but it is probably the way forward,
especially for certain jobs of significant lengths
and linear, its function rather linear.
For a more tricky one, so which might request
a significant say, manual input.
<v ->Good, all right, so.</v>
<v ->It requires a change of thought within the industry.</v>
If I think about what Peter said,
that we actually adapt the design
during the construction process
based on the results from piling platforms.
I think that will take a lot of what,
change management, within the civil engineering community,
at least in Germany, because the design
has been checked, has been approved
by the states and local government.
So you have to provide an automated circle system
that actually repeats that approval,
as I called, on very quickly,
so you can adjust the design onsite.
It’s a big step for everybody involved in the industry,
and we have to walk that way,
but we’re not there yet, at least not over here.
<v ->So that probably brings us</v>
to our final question,
which is Magic Wand Time.
If you could change one thing about the industry today,
what would it be and why?
Bernd, do you want to kick that off?
<v ->I can start.</v>
What springs to mind is that from personal experience
with the company in the next few years, we,
and even now, with Leapfrog,
and bringing Leapfrog data into other systems,
what we notice is that software providers have an interest,
but not enough interest in making their systems
not propriety, but open to everybody.
I think there’s a lot of work to be done
if we want to share data across different platforms,
across different processes.
And if that can be done,
it will be a big help to all of us
in the industry, I think.
<v ->Very good.</v>
<v ->I’m sorry for that, Gareth.</v>
<v ->Hey, no, we’re on a continual journey</v>
where we’re trying to be open to all,
all the connectors and all the types.
In fact, we’ve got APIs being developed
as an open API into the cloud repository.
So yeah, it’s a continual journey for us.
<v ->I see that, I see that in Seequent,</v>
and I already said there’s a conversation going on
with we were being asked what we can change,
and I want to see that it crosses
of our industry to make it available to everybody, really.
<v ->Great, thank you.</v>
And Andrea, your Magic Wand moment.
<v ->I will like to be sure that the digitalization</v>
is not for only an elite of engineers.
There is a risk that people
which is more technologically savvy,
possibly a younger generation and so on,
will take over, or as a private company have an interest,
or having people driving the initiative,
and they might not be able to invest in that
and train everybody.
And there’s a serious risk of a disconnect
between the younger generation,
which is technologically savvy and maybe the older one,
which have a plethora of experience
and can bring an immense value to jobs.
We need to be sure that the knowledge of a driller
in the field, where he might have worked
for 20, 30 years, gets used.
We need to be sure that we’re not just waiting
for the older generation to be phased out
because we’re going to miss
entire generation of knowledge.
And we really look really scared to lose quite a lot.
Therefore, my wish would be let’s go digital
but all together.
Everybody might have a different pace
and different take in it
but we cannot leave anybody behind in this industry.
It would be disastrous for us.
<v ->That’s a great sentiment.</v>
So we’ve got open software engagement
where you can move your data
and your observations around
we’ve got, keeping hold of experience
and making sure that it’s opened up
to the technology generation,
and that experience isn’t lost.
Peter, your Magic Wand?
<v ->Magic One, yeah, it’s actually very similar to Andrea’s.</v>
It’s about the training, the learning environment.
It’s a very real question for me at the moment.
That is so much new stuff coming out,
especially with these big providers
that have been on Autodesk.
When I say been, I was not necessarily meaning
that the Seequent side of things,
but that there is so much to learn.
And many of my colleagues are struggling
just to keep up with all the new softwares
and new environments, how to even use things
like ProjectWise, or BIM 360,
or the Seequent Central environment.
They’re all similar but when I start introducing
something like the Seequent Central environment,
they get confused very quickly
because they’re trying to learn
several other environments at the same time.
Or when you’re talking about modeling,
then they’re used to another environment,
or they’re trying to train up in that environment too.
We were trying to encourage people to use
in the Seequent Central environment as a visualization tool,
but they’re also being told
they need to look at iTwin
or one of the other navigator,
or these other visualization tools.
And so really, I don’t know what the answer is.
Implant into brains, I’m not sure.
But for me, that seems to be a real struggle,
but I think even the trainers need to do
or something about the software providers kind of things,
just to recognize that there is so much new technology,
software technology that’s coming out,
that some people are just getting bamboozled by it all.
And I was going back to Andrea’s point,
especially some of the colleagues now
that have been around a few years,
so they’ve really got that wisdom in them,
central to the geotechnical triangle.
But if they can’t use it,
then we’re worried of getting it lost.
So that’s it from me.
<v ->Great, great, great sentiment.</v>
Again, that’s around kind of workflows,
and best practice, and trying to figure out
how we can utilize the great tools
that are coming out in the software environment,
but to solve the problems that we have.
So it kind of always bringing it back
to what problem are we trying to solve?
What tools do we need to do that?
How much do we understand about
the workflows and the technology?
And then how do we set that in
as how we’re going to do it for the short-term future
until it’s surpassed by something else.
But I absolutely agree with you.
It’s such a pace of change at the moment
with everything that’s coming out,
and the possibilities that we will start
racing onto the next thing.
<v ->Gareth, some times back,</v>
I came across a very interesting paper
from an author called Maca Eka,
which effectively have developed
effectively a cube matrix to identify
what are the priorities of a company
when they buy software or develop software.
And effectively, you’ve got the three axes.
On one axis, you’ve got the interactivity
between the humans and the machines.
So effectively, it ranges from people using that,
for example, threat model for doing analysis
or other which might use it simply for visualizations
just to a replacement from paper and pencil.
Then there is the knowledge dimension
where you need to acknowledge these people
which will it be an expert in geology and geotechnics,
civil engineering, and others that
will not be in an organization.
For example, the management might have lost
certain kind of skills.
And then you got to use a dimension,
which is effectively arranged between the people,
which is for attitude, skills, or any other reason,
they would remain fairly passive,
passive engaging in the others,
which will become a leading force behind the software,
and possibly, start to develop scripts, and so on.
There is a very fine line between the three axes.
And effectively, what is successful for a company
who in turn will select the software,
is trying to find a balance between the three,
and identify a product which allows
most people to use it, doesn’t alienate
who is over-skilled and or who is under-skilled.
That can be used by pretty much
by the average Joe or the hyper expert.
And at the end, that they leave us
with what we needed for our own databases.
It’s quite important that this kind of analyses
are carried out by companies and by developers
because there is hardly any point of dabbling in something
which is not going to be used
and going to be effective.
And that is a good way also
to assess the software we got
and understanding whether they’re really fit
for purpose for what we do on a daily basis.
<v ->Brilliant, great, great final observation.</v>
So I think we’re probably at time.
We may even need some trimming on this one
but I’d like to thank you all
for taking part in this conversation.
There’s many things illuminated in here
that I think we should solve over a beer or two
at some point in the future.
And we’ll have the courage,
hopefully, a lot of thinking outside of this,
that will continue us on our path
for a while to come.
But thanks very much for your contributions,
and I’m sure we can answer things
in the Chat as well.