>> From Washington DC, it's theCUBE.
Covering the ScienceLogic Symposium 2019.
Brought to you by ScienceLogic.
>> Hi, I'm Stu Miniman,
and this is theCUBE's special coverage
of ScienceLogic symposium 2019
here at the Ritz-Carlton,
in Washington DC,
about 460 people here,
I'm told over 50% growth,
from last year's event,
the first time we've had theCUBE here,
really excited to be able to dig in,
with a number of the executives,
customers and partners, and no better way,
to kick off than one of the users,
here at the event,
actually coming here from across the pond,
here to the district,
happy to welcome to the
program first-time guest,
Nigel Wilks who's the
Head of Global Tooling
at Computacenter, based in the UK,
Nigel, thanks so much for joinin' us.
>> Hey, a pleasure.
>> And joining him from ScienceLogic
we have Clive Spanswick,
who's the Vice President
of Sales from EMEA,
Clive thanks so much for joinin' us.
>> Pleasure to be here.
>> All right, so Nigel,
set the stage for us,
coming to the event here,
tell me what brings you here,
and tell us a little
bit about Computacenter.
>> Yeah sure, so,
we're a relatively new
customer to ScienceLogic so,
I think, what, we signed
two, three weeks ago?
So, not deployed yet, but
got great expectations.
So, there's a lot of background
research in the sessions.
Finding about more what
the additional capabilities
that we can unlock,
which will help drive our
business further forward.
So, Computacenter is a
large IT provider, global.
Based in the UK, as headquarters.
My area of the business is in
the Managed Services sector.
So realistically, we're looking
to reduce our cost to serve.
Be more proactive for our customers, and,
we've got great expectations
of what ScienceLogic can
do around those areas.
Unlocking more automation,
and eventually leading down the AI path.
>> So Nigel, what I
heard in the keynote is,
some of the same themes
I've been hearing around the industry,
we are unparalleled as to how fast
things are changing in the industry,
there's just more complexity,
there's more heterogeneous environments,
for companies like yours,
usually agility is one of those things
that's coming to the
top of the environment
and oh my gosh, when I became an analyst
about nine years ago,
it was the tooling and
management options out there
where usually some of the
things that customers would say
are weak in their environment,
and something I think I've
heard for my entire career,
so, maybe give us a little bit as to
some of what you're hearing
from the business side
and how it makes sure that
you can run your services faster
and ultimately serve your customers better
and how your look at,
I don't know whether you call it AI Ops,
but this whole space, fits
into that environment.
>> Sure, so--
>> Yeah.
>> We've with probably
a lot of organic growth
within Computacenter over
quite a short period of time.
Also through acquisitions,
we've got quite a fragmented
tooling landscape globally.
So, nearly two years ago, we
kind of set on the journey
to become more of a global entity,
and certainly from my
perspective a tooling landscape.
Looking to consolidate those down,
simplify our services, again
helping reduce our cost base,
and then leverage the automation stuff
I talked about earlier.
So, just going to ScienceLogic,
we're moving away from
some of the big names.
And consolidating over 50 tools
into the one ScienceLogic solution.
>> Wow.
That's great, let's bring ya
into the discussion Clive,
yeah, I heard in the keynote this morning,
it was, the typical customer,
it's at least 14 tools.
>> Yes.
>> That get consolidated down.
I think back about five years ago,
frictionless and simplicity
were the terms that I heard.
I talked to a lot of companies, it's like
"Oh okay, yes I've got
integrations I need to do
"if I'm doing acquisitions,
whether I be in,
"if I'm in services of
course that's there"
But, you know, financial industries,
and, heck, Cisco IT who I'm
going to be talking to later,
does an acquisition a
month, what are you seeing,
give us a little bit of
the EMEA flavor and--
>> Sure.
>> How what Nigel's saying,
how is that resonating
with your customer base?
>> Yeah, absolutely Stu.
So we see this a lot with the
leading service providers now
that are really being
challenged by their customers
to really extend their
portfolio of services,
over an ever more diverse
range of technologies,
and this is one of the big challenges
that has driven tool sprawl
over the course of the
last seven to ten years,
so simplification of the toolset,
is really one of the key drivers
to really deliver outcomes for efficiency,
so a lot of the way we see
modern service providers
operating today really
is all about automation,
to get to better
automation at a lower cost
you have to drive simplification
into the tool chain.
So, we see this a lot with our
customers across the region
and indeed worldwide, that
taking the tools landscape
and really collapsing that into
a much more simplified model
is an essential ingredient
to drive efficiencies
that then in turn can be
delivered to the customer
as lower-cost services,
so that's the real driving force
that we see for customers today.
>> Alright.
Nigel, we'd love to hear,
I know you've just gone
through the process of choosing
but, what are you looking for,
are there specific business drivers,
how will success be measured
in your environment?
>> Part of the process was,
to look at what our
business requirements were.
And map those on through an RFI process.
Of which ScienceLogic
were one of the vendors
that took part.
So I think at the benchmark
of everything we did,
at the heart of the whole process,
was that business requirements.
Just making sure that
whichever toolsets we selected,
would go down that route.
We never expected to have
a single-vendor solution,
which, fortunately we've got ScienceLogic
which covers the majority, but
with the partner ecosystem,
some of those guys are here today.
It kind of rounds it up for us.
But moving away from
our current providers,
some of those, they present
challenges to us as well.
Tryin' to unlock data
that's within the platforms,
some of those tools are
through acquisitions.
So as much as you've got a brand name
as part of a whole stable of tools,
they don't inter-operate very well.
And the beauty of going
to ScienceLogic was,
everything comes in together,
even the partner tools,
which allows us to really look
at what we can do in the future.
>> Alright, so, Nigel I've got
the tough question for you.
When I came into the show,
one of the things that really struck me,
is how data's at the center
of what's important here,
you know, when we look at companies,
digital transformation
often is a buzzword,
but, we've really defined
the difference between
the old way and the modern environment is,
how is data something that can
actually drive your business,
are you data-driven in your decisions,
can you monetize data,
what I heard in the keynote discussion is,
data's such an important,
not just the collecting but leveraging,
and that's driving the
intelligence, the automation.
How much did that focus on data
play into your decision,
and can you give us a
little bit of insight
as to how your company
looks at the role of data
in the IT world today?
>> Well, it's very important,
that's quite a simple
solution to that one.
So for me, an infrastructure
tooling perspective,
being able to bring all
the data into one place
but contextualize it as well,
means that we can then do some good stuff.
Again, driving us down
that automation path
but from an end-user point of view
we've got end-user analytics,
that can open up a lot of
different worlds for us,
predicting what issues users have,
rather than calling a service desk,
theoretically, going
further down the future,
we'll be calling them to say,
"I can see you've got a problem,
"I can fix it for you remotely."
Those kind of decisions that
we can make from that data.
But in my kind of space, the
infrastructure tooling side,
we need to go onto that AI Ops journey,
and as you heard this morning, now,
or at least a few weeks ago, to get there,
it's like getting the
data into a good shape,
knowing what we want to do
with the AI Ops moving forward.
So, automation's a good candidate,
that helps up achieve
some of our objectives,
reduces customers' downtime as well but,
we've also got to be careful
that we're not tryin' to automate
resolution to poor behavior.
>> Yeah
>> Yeah, so,
rather than fixing the root cause,
we need to actually
look at things and say,
"Is this an incident-worthy event,
"is this something that
"we need to actually do something with,
"or is it just an automation candidate?"
And it's going to drive some
of those behaviors for us.
>> Clive, I'd love to get your viewpoint
as to what you're hearing from customers,
when I listened to the
analyst this morning,
he's like "You need to
really differentiate
"between that machine learning piece,
"and the automation."
Because any of us that've worked
in operations environment,
you can automate a bad process.
>> Yeah.
>> And data doesn't necessarily
mean good information,
so we need to manage those
things a little bit separately,
and that maturation of where customers are
for both automation and
intelligence, is a tough one,
when they did a poll when
your CEO was up on stage,
nobody's fully, turn things
over to the computers.
>> Yep, yep.
>> So,
where are your customers,
how are they thinking through
the AIML, the use of
data, and those pieces?
>> So see, I think to be fair,
a lot of customers today,
AI Ops as we know is a relatively
new term to the market,
so I think a lot of businesses
are struggling to recognize
their own maturity,
and I think, what we
learned from this morning
from Dave Link, our CEO,
about how you characterize yourself
on the journey to AI Ops maturity
I think is a very valuable thing,
and I think as I look at
a lot of the customers
and we saw from the poll
earlier in the main session,
that a lot of businesses today
are fairly in the middle of maturity,
so they're really at about the point
of consolidating all
the data in one place,
the next big step of that of course
is to clean that data
up and contextualize it,
so that you can start
to leverage that data
for the meaningful outcomes,
and that's really where the
smarts of machine learning
and early-stage AI really start to play.
We still, to be fair, still a long way off
from the realization of full AI,
but there are many pragmatic
things that you can do,
to get you very well level set,
to take full advantage
when those opportunities
start to present themselves.
>> Alright.
So, Nigel, you're goin'
through this process
to really modernize your toolset
you said you're replacing
a whole bunch of things with the new one,
what ultimately will this mean
to your end-user customers?
>> I think a more proactive service.
Just dialing it back down
to the simple things.
If we simplify our service, we can have,
from a business point of view,
we can be consistent in how
we deliver service globally.
But from an end-user point of view.
At the end of the day, most
of the stuff is event-driven.
End users typically find
those out before systems do.
Just from whole new cycles,
reducing false positives and things.
But it also means that, again,
automation is being at the heart
of what we want to try and achieve.
We can automatically fix these things,
so it's less downtime.
And then hopefully we
can just kind of prevent.
Automation's great, but
prevention's better.
>> Yeah.
How do you see your journey going forward,
when you look at that automation,
I mean I can't imagine you
at a day one, your desk,
putting everything in
and everything's there,
do you have a roadmap out there
as to how you look at your deployment
and how you're going to
change things internally?
Yeah.
This, realistically,
is going to be a catalyst
to how we do things.
So what starts off as a
tooling replacement project,
becomes that overall, we can
do things global process.
Working a little bit smarter
than we have been before,
doing things on a larger scale,
but using common processes.
That's quite a big shift
in how we work now.
But also means from our
sales forces perspective,
they're selling the same thing,
it doesn't matter which
country they're in.
It becomes more about delivery
location, and a language.
>> Great.
Clive, give us a little bit as to,
what are customers like Nigel,
what should they expect once
they've made the deployment,
how long does that transformation take--
>> Sure.
>> And what's the day one
and then, three months, six months out?
>> Sure, great questions.
So the whole journey that we're exploring,
with all of our customers,
is this move to AI Ops
and they've done really the support
of the resilient digital
experience for their customers.
The journey itself is continuous.
So, one of the big challenges
that we know to be true
in the space that we operate in,
is the demand for constant change.
So the idea and the process
that we're going on with,
with computer sensor is that,
we will take you through a
series of maturity stages,
of crawl, walk and run.
And then once we get them to run,
it will be a case of
continuous improvement
and continuous development.
We expect to get to
the first break of that
within the first quarter,
we're going to be delivering
instant value from the platform
pretty much from the word go,
but once we get into the
process of business as usual,
running the operation, it really becomes
about the improvement of moving,
from really the stages
of helping them react better to incidents,
and then moving into a much more
proactive and predictive state,
and then finally, the
endgame of this of course,
is to really get to the point of,
automate to avoid the
incidents happening altogether,
and that really, I guess, is
where we start to step towards
the ultimate vision of AI Ops
and the things that
that can bring to bear.
>> Alright, so, Nigel,
I want you to take me inside your team,
'cause on the one hand we say,
"I have a whole bunch of tools,
"I'm going to simplify
and I'm going to unify
"and that's going to be great."
And I'm sure there's many
on your team they're like,
"Ah, I hate this tool,
and this one's a pain
"and this and that.
"But we kind of know how
"to do everything that I'm doing today."
So, one, give us a little insight as to,
is there some of that
clinging to the past,
and, on the other hand, are
there some things that, like,
"Oh my gosh, I'm glad
I will never have to do
"one two or three ever again,
"once I've gone through this process"?
>> Great, great question, so,
everyone has their favorite tool,
or favorite bit of software.
I think, internally,
we've clearly got that challenge as well.
But it's fair to say, the reverse is true,
there's a lot of tools out
there that the user base
are more than happy to get rid of.
But ultimately, I think as
we've gone through the cycle
with ScienceLogic,
and certainly we've
had some good workshops
with the various user base,
highlighting what's possible,
we've had some really
really positive feedback.
I still expect challenges,
change, change is a big thing,
most people don't like change but,
I think there's a great
opportunity for people to,
at the end of the day learn a new tool.
Something different, something fresh.
And also then, they can think
about what the tool can do,
how can we exploit it more, so,
we're not locked into the
model that we were in before,
the tools that we'd use for years
and we've worked in the same way.
We've got an exciting journey
to start looking at how we
can derive better services,
how we can simplify our services.
How we can let customers
self-serve, to a degree as well.
So you know, I think it's an
exciting journey that we're on.
And I think it'll be good
to come back next year
and demonstrate where we are.
>> I love that, I definitely
want to talk about that,
Clive, give you the final word on this.
What final advice to you give him,
he's made the decision,
he's goin' onboard.
Tell him, I'm sure, unicorns and rainbows
and everything's going
to be phenomenal, but,
what are some of the things
you hear from your customers
as they roll things out,
give him a little bit of the "Yay"
and a little bit of the--
>> Sure
>> Just "Hey make sure
"we've educated everybody on this."
>> Yeah, again, great question Stu.
So, from working with our customer base,
the big thing that we see
is that this is a continuous journey.
The journey doesn't stop.
What we do is we make
things progressively easier,
and the opportunities
to scale and standardize
are almost limitless.
I guess the one word
of counsel I would give
is that, one of the
big things that we see,
with any major transformation,
we're talking about the automations
we can deliver around monitoring but,
with any transformation it is really how
you start to shift the
culture of the organization
to work a way around the
new ways of operating,
and really winning the hearts
and minds of the guys that
this stuff is going to make
the biggest difference to.
So, we're talking in the
first instance of course
about the operational
stakeholders and the key users,
having them engaged, and
really working that process
to get the maximum benefit
out of the platform.
From there, really is about
the improvements that they can achieve
in customer experience and of course,
as Nigel has already said,
a lot of that is really centered
around the opportunities
it's going to present them
to show real innovations,
around their service portfolio
and my guidance there would be,
don't be shy to show the
world of the possible,
to your enterprise customers,
because they are demanding more,
and there is so much that
they can do with the platform
to really unleash super
value to their customer base.
>> Yeah I love that, the
world of the possible,
we understand all the stresses and strains
put on business and IT
today so, Clive, Nigel,
thank you so much for joining us,
Nigel we look forward to
hearin' how things go,
catch up with you in a year maybe.
>> Pleasure.
>> Of course, thank you.
>> Alright,
so we'll be here all day
at the Ritz-Carlton in Washington DC,
ScienceLogic Symposium
2019, I'm Stu Miniman
and as always, thank you
for watchin' theCUBE.
(groovy techno music)
