More than Just Lines on a Map: Best Practices for U.S Bike Routes
Efficient Data Center Transformation Requires Consolidation and Standardization Across Critical IT Tasks
1. Efficient Data Center Transformation Requires Consolidation
and Standardization Across Critical IT Tasks
Transcript of a sponsored podcast discussion in conjunction with an HP video series on the best
practices for developing a common roadmap for DCT.
Listen to the podcast. Find it on iTunes/iPod. Sponsor: HP
For more information on The HUB -- HP's video series on data center transformation, go
to www.hp.com/go/thehub.
Dana Gardner: Hi. This is Dana Gardner, Principal Analyst at Interarbor Solutions, and you’re
listening to BriefingsDirect.Today, we present a sponsored podcast discussion on quick and
proven ways to attain significantly improved IT operations and efficiency.
We'll hear from a panel of HP experts on some of their most effective
methods for fostering consolidation and standardization across critical IT
tasks and management. This is the second in a series of podcast on data
center transformation (DCT) best practices and is presented in conjunction
with a complementary video series. [Disclosure: HP is a sponsor of
BriefingsDirect podcasts.]
Here today we will specifically explore building quick data center project wins, leveraging
project tracking and scorecards, as well as developing a common roadmap for both facilities and
IT infrastructure.
With us now to explain how these solutions can drive successful data center transformation is our
panel. Please join me in welcoming Duncan Campbell, Vice President of Marketing
for HP Converged Infrastructure and small to medium-sized businesses (SMBs).
Second, we're here with Randy Lawton, Practice Principal for Americas West
Data Center Transformation & Cloud Infrastructure Consulting at HP.
And last, Larry Hinman, Critical Facilities Consulting Director and Worldwide
Practice Leader for HP Critical Facility Services and HP Technology Services. Welcome to you
all.
You don’t need to go very far in IT to find people who are diligently working to do more with
less, even as they're working to transform and modernize their environments.
2. One way to keep the interest high and those operating and investment budgets in place is to show
fast results and then use that to prime the pump for even more improvement and even more
funding with perhaps even growing budgets.
Let's go first to Duncan Campbell on communicating an ongoing stream of positive results, why
that’s important and necessary to set the stage for an ongoing virtuous adoption cycle for data
center transformation and converged infrastructure projects.
Duncan Campbell: You bet Dana. We've seen that when a customer is successful in breaking
down a large project into a set of quick wins, there are some very positive outcomes from that.
Breeds confidence
Number one, it breeds confidence, and this is a confidence that is actually felt within the
organization, within the IT team, and into the business as well. So it builds
confidence both inside and outside the organization.
The other key benefit is that when you can manifest these quick wins in
terms of some specific return on investment (ROI) business outcome, that
also translates very nicely as well and gets a lot of key attention, which I
think has some downstream benefits that actually help out the team in
multiple ways.
Gardner: I suppose it's not only getting these quick wins, but effectively communicating them
well. People really need to know about them.
Campbell: Right. So this is one of the things that some of the real leaders in IT realize. It's not
just about attracting the best talent and executing well, but it's about marketing the team’s results
as well.
One of the benefits in that is that you can actually break down these projects just in terms of
some specific type of wins. That might be around standardization, and you can see a lot of wins
there. You can quickly consolidate to blades. You can look at virtualization types of quick wins,
as well as some automation quick wins.
We would advocate that customers think about this in terms of almost a step-by-step approach,
knocking that down, getting those quick wins, and then marketing this in some very tangible
ways that resonate very strongly.
Gardner: When you start to develop a cycle of recognition, incentives, and buy-in, I suppose we
could also start to see some sort of a virtuous adoption cycle, whereby that sets you up for more
interest, an easier time evangelizing, and so on.
3. Campbell: That’s exactly right. A virtuous cycle is well put. That allows really the team to get
the additional green light to go to the next step in terms of their blueprint that they are trying to
execute on. It gets a green light also in terms of additional dollars and, in some cases, additional
headcount to add to their team as well.
What this does is, and I like this term the virtuous cycle, not only allow you to attract key talent,
but it really allows you to retain folks. That means you're getting the best team possible to
duplicate that, to get those additional wins, and it really does indeed become a virtuous cycle.
Gardner: I suppose one last positive benefit here might be that, as enterprises adopt more of
what we call social networking and social media, the ability for the rank and file, those users
involved with these products and services, can start to be your best word-of-mouth marketing
internally.
TCO savings
Campbell: That’s right. A good example is where we have been able to see a significant total
cost of ownership (TCO) type of savings with one of our customers, McKesson, that in fact was
taking one of these consolidated approaches with all their development tools. They saw a
considerable savings, both in terms of dollars, over $12.9 million, as well as a percentage of
TCO savings that was upwards of 50 percent.
When you see tangible exciting numbers like that, that does grab people’s attention and, you bet,
it becomes part of the whole social-media fabric and people want to go to a winner. Success
breeds success here.
Gardner: Thank you. Next, we're going to go to Randy Lawton and hear some more about why
tracking scorecards and managing expectations through proven data and metrics also contributes
to a successful ongoing DCT activity.
Randy, why is it so important to know your baseline tracks and then measure them each and
every step along the way?
Randy Lawton: Thank you, Dana. Many of the transformation programs we
engage in with our customers are substantially complex and span many
facets of the IT organization. They often involve other vendors and service
providers in the customer organization.
So there’s a tremendous amount of detail to pull together and organize in
these complex engagements and initiatives. We find that there’s really no
way to do that, unless you have a good way of capturing the data that’s necessary for a baseline.
It’s important to note that we manage these programs through a series of phases in our
methodology. The first phase is strategy and analysis. During that phase, we typically run a
4. discovery on all IT assets that would include the data center, servers, storage, the network
environment, and the applications that run on those environments.
From that, we bridge into the second phase, which is architect and validate, where we begin to
solution out and develop the strategies for a future-state design that includes the standardization
and consolidation approaches, and on that begin to assemble the business case. In a detailed
design, we build out those specifications and begin to create the data that determines what the
future-state transformation is.
Then, through the implementation phase, we have detailed scorecards that are required to be
tracked to show progress of the application teams and infrastructure teams that contribute to the
program in order to guarantee success and provide visibility to all the stakeholders as part of the
program, before we turn everything over to operations.
During the course of the last few years, our services unit has made investments in a number of
tools that help with the capture and management of the data, the scorecarding, and the analytics
through each of the phases of these programs. We believe that helps offer a competitive
advantage for us and helps enable more rapid achievement of the programs from our customer
perspective.
Gardner: As we heard from Duncan about why it’s important to demonstrate wins, I sense that
organizations are really data driven now more than ever. It seems important to have actual
metrics in place and be able to prove your work each step of the way.
Complex engagements
Lawton: That’s very true. In these complex engagements, it’s normally some time before there
are quick-win type of achievements that are really notable.
For example, in the HP IT transformation program we undertook over several years back through
2008, we were building six new data centers so that we could consolidate 185 worldwide. So it
was some period of time from the beginning of the program until the point where we moved the
first application into production.
All along the way we were scorecarding the progress on the build-out of the data centers. Then, it
was the build-out of the compute infrastructure within the data centers. And then it was a matter
of being able to show the scorecarding against the applications, as we could get them into the
next generation data centers.
If we didn't have the ability to show and demonstrate the progress along the way, I think our
stakeholders would have lost patience or would not have felt that the momentum of the program
was going on the kind of track that was required. With some of these tools and approaches and
the scorecarding, we were able to demonstrate the progress and keep very visible to management
the movements and momentum of the program.
5. Gardner: Randy, I know that many organizations are diligent about the scorecarding across all
sorts of different business activities and metrics. Have you noticed in some of these engagements
that these readouts and feedback in the IT and data center transformation activities are somehow
joined with other business metrics? Is there an executive scorecard level that these feed into to
give more of a holistic overview? Is this something that works in tandem with other scorecarding
activities in a typical corporation?
Lawton: It absolutely is, Dana. Often in these kind of programs there are business activities and
projects that are going on within the business units. There are application projects that work into
the program and then there are the infrastructure components that all have to be fit together at
some level.
What we typically see is that the business will be reporting its set of metrics, each of the
application areas will be reporting their metrics, and it’s typically from the infrastructure
perspective where we pull together all of the application and infrastructure activities and
sometimes the business metrics as well.
We've seen multiple examples with our customers where they are either all consolidated into
executive scorecards that come out of the reporting from the infrastructure portion of the
program that rolls it all together, or that the business may be running separate metrics and then
application teams and infrastructure are running the IT level metrics that all get rolled together
into some consolidated reporting on some level.
Gardner: And that, of course, ensures that IT isn’t the odd man out, when it comes to being on
time and in alignment with these other priorities. That sounds like a very nice addition to the way
things may have been done 5 or 10 years ago.
Lawton: Absolutely.
Gardner: Any examples, Randy, either with organizations you could name, or use cases where
you could describe, where the use of this ongoing baselining, tracking, measuring, and delivering
metrics facilitates some benefits? Any stories that you can share?
Cloning applications
Lawton: A very notable example is one of our telecom customers we worked with during the
last year and finished a program earlier this year. The company was purchasing the assets of
another organization and needed to be able to clone the applications and infrastructure that
supported business processes from the acquired company.
Within the mix of delivery for stakeholders in the program, there were nine different companies
represented. There were some outsourced vendors from the application support side in the
acquiree’s company, outsourcers in the application side for the acquiring company, and
6. outsourcers in the data centers that operated data center infrastructure and operations for the
target data centers we were moving into.
What was really critical in pulling all this together was to be able to map out, at a very detailed
level, the tasks that needed to be executed, and in what time frame, across all of these teams.
The final cutover migration required over 2,500 tasks across these 9 different companies that all
needed to be executed in less than 96 hours in order to meet the downtime window of
requirements that were required of the acquiring company’s executive management.
It was the detailed scorecarding and operating war rooms to keep those scorecards up to date in
real-time that allowed us to be able to accomplish that. There’s just no possible way we would
have been able to do that ahead of time.
I think that HP was very helpful in working with the customer and bringing that perspective into
the program very early on, because there had been a failed attempt to operate this program prior
to that, and with our assistance and with developing these tools and capabilities, we were able to
successfully achieve the objectives of that program.
Gardner: One thing that jumped out at me there was your use of the words real time. How
important is it to capture this data and adjust it and update it in real-time, where there’s not a lot
of latency? How has that become so important?
For more information on The HUB -- HP's video series on data center transformation, go
to www.hp.com/go/thehub.
Lawton: In this particular program, because there were so many activities taking place in
parallel by representatives from all over the world across these nine different companies, the
real-time capture and update of all of the data and information that went into the scorecarding
was absolutely essential.
In some of the other programs we've operated, there was not such a compressed time frame that
required real-time metrics, but we, at minimum, often required daily updates to the metrics. So
each program, the strategies that drive that program, and some of the time constraints will drive
what the need is for the real-time update.
We often can provide the capabilities for the real-time updates to come from all stakeholders in
the program, so that the tools can capture the data, as long as the stakeholders are providing the
updates on a real-time basis.
Gardner: So as is often the case, good information in, good results back.
Lawton: Absolutely.
7. Organizing infrastructure
Gardner: Let’s move now to our third panelist today. We're going to hear about why organizing
facilities and infrastructure planning in conjunction in relationship to one another is so important.
Now to Larry Hinman. Larry, let’s go historical for a second. Has there usually been a
completely separate direction for facilities planning in IT infrastructure? Why was that the case,
and why is it so important to end that practice?
Larry Hinman: Hi, Dana. If you look over time and over the last several years,
everybody has data centers and everybody has IT. The things that we've seen
over the last 10 or 15 years are things like the Internet and criticality of IT and
high density and all this stuff that people are talking about these days. If you
look at the ways companies organized themselves several years ago, IT was a
separate organization, facilities was a separate organization, and that actually
still exists today.
One of the things that we're still seeing today is that, even though there is this push to try to get
IT groups and facilities organizations to talk and work each other, this gap that exists between
truly how to glue all of this together.
If you look at the way people do this traditionally -- and when I say people, I'm talking about IT
organizations and facilities organization -- they typically will model IT and data centers, even if
they are attempting to try and glue them together, they try to look at power requirements.
One of the things that we spotted a few years ago was that when companies do this, the risk of
over provisioning or under provisioning is very high. We tried to figure out a way to back this up
a few notches.
How can we remedy this problem and how can we bring some structure to this and bring some,
what I would call, sanity to the whole equation, to be able to have something predictable over
time? What we figured out was that you have to stop and back up a few notches to really start to
get all this glued together.
So we took this whole complex framework and data center program and broke it into four key
areas. It looks simplistic in the way we've done this, and we have done this over many, many
years of analysis and trying to figure out exactly what direction we should take. We've actually
spun this off in many directions a few times, trying to continually make it better, but we always
keep coming back to these four key profiles.
Business and risk is the first profile. IT architecture, which is really the application suite, is the
second profile. IT infrastructure is the third. Data center facilities is the fourth.
8. One of the things that you will start to hear from us, if you haven’t heard it already via the data
center transformation story that you guys were just recently talking about, is this nomenclature of
IT plus facilities equals the data center.
Getting synchronized
Look at that, look at these four profiles, and look at what we call a top-down approach, where I
start to get everybody synchronized on what risk profiles are and tolerances for risk are from an
IT perspective and how to run the business, gluing that together with an IT infrastructure
strategy, and then gluing all that into a data center facility strategy.
What we found over time is that we were able to take this complex program of trying to have
something predictable, scalable, all of the groovy stuff that people talk about these days, and
have something that I could really manage. If you're called into the boss’s office, as I and others
have been over the many years in my career, to ask what’s the data center going to look like over
the next five years, at least I would have some hope of trying to answer that question.
That is kind of the secret sauce here, and the way we have developed our framework was
breaking this complex program into these four key areas. I'm certainly not trying to say this is an
easy thing to do. In a lot of companies, it’s culture changes. It’s a threat to the way the very
organization is organized from an IT and a facilities perspective. The risk and recovery teams
and the management teams all have to start working together collaboratively and collectively to
be able to start to glue this together.
Gardner: You mentioned earlier the issues around energy and the ongoing importance around
the cost structure for that. I suppose it's not just fitting these together, but making them fit for
purpose. That is to say, IT and facilities on an ongoing basis.
It’s not really something that you do and sit still, as would have been the case several years ago,
or in the past generation of computing. This is something that's dynamic. So how do you allow a
fit-for-purpose goal with data-center facilities to be something that you can maintain over time,
even as your requirements change?
Hinman: You just hit a very important point. One of the the big lessons learned for us over the
years has been this ability to not only provide this kind of modeling and predictability over time
for clients and for customers. We had to get out of this mode of doing this once and putting it on
a shelf, deploying a future state data center framework, keep client pointing in the right direction.
The data is, as you said, gets archived, and they pick it up every few years and do it again and
again and again, finding out that a lot of times there's an "aha" moment during those periods, the
gaps between doing it again and again.
One thing that we have learned is to not only have this deliberate framework and break it into
these four simplistic areas, where we can manage all of this, but to redevelop and re-hone our
9. tools and our focus a little bit, so that we could use this as a dynamic ongoing process to get the
client pointing the right direction. Build a data center framework that truly is right size,
integrated, aligned, and all that stuff. But then, to have something that was very dynamic that
they could manage over time.
That's what we've done. We've taken all of our modeling tools and integrated them to common
databases, where now we can start to glue together even the operational piece, of data center
infrastructure management (DCIM), or architecture and infrastructure management, facilities
management, etc., so now the client can have this real-time, long-term, what we call a 10-year
view of the overall operation.
So now, you do this. You get it pointing the right direction, collect the data, complete the
modeling, put it in the toolset, and now you have something very dynamic that you can manage
over time. That's what we've done, and that's where we have been heading with all of our tools
and processes over the last two to three years.
EcoPOD concept
Gardner: I also remember with great interest the news from HP Discover in Las Vegas last
summer about your EcoPOD and the whole POD concept towards facilities and infrastructure.
Does that also play a part in this and perhaps make it easier when your modularity is ratcheted up
to almost a mini data center level, rather than at the server or rack level?
Hinman: With the various what we call facility sourcing options, which PODs are certainly one
of those these days, we've also been very careful to make sure that our framework is completely
unbiased when it comes to a specific sourcing option.
What that means is, over the last 10 plus years, most people were really targeted at building new
green-field data centers. It was all about space, then it became all about power, then about
cooling, but we were still in this brick and mortar age, but modularity and scalability has been
driving everything.
With PODs coming on the scene with some of the other design technologies, like multi-tiered or
flexible data center, what we've been able to do is make sure that our framework is targeted at
almost a generic framework where we can complete all the growth modeling and analysis,
regardless of what the client is going to do from a facilities perspective.
It lays the groundwork for the customer to get their arms around all of this and tie together IT
and facilities with risk and business, and then start to map out an appropriate facility sourcing
option.
We find these days that POD is actually a very nice fit with all of our clients, because it provides
high density server farms, it provides things that they can implement very quickly, and gets the
power usage effectiveness (PUE) and power and operational cost down. We're starting to see that
take a stronghold in a lot of customers.
10. Gardner: As we begin to wrap up, I should think that these trends are going to be even more
important, these methods even more productive, when we start to factor in movement towards
private cloud. There's the need to support more of a mobile tier set of devices, and the fact that
we're looking for of course even more savings on those long-term energy and operating costs.
Back to you, Randy Lawton. Any thoughts about how scorecards and tracking will be even more
important in the future, as we move, as we expect we will, to a more cloud-, mobile-, and eco-
friendly world?
Lawton: Yes, Dana. In a lot of ways, there is added complexity these days with more customers
operating in a hybrid delivery model, where there may be multiple suppliers in addition to their
internal IT organizations.
Greater complexity
Just like the example case I gave earlier, where you spread some of these activities not only
across multiple teams and stakeholders, but also into separate companies and suppliers who are
working under various contract mechanism, the complexity is even greater. If that complexity is
not pulled into a simplified model that is beta driven, that is supported by plans and contracts,
then there are big gaps in the programs.
The scorecarding and data gathering methods and approaches that we take on our programs are
going to be even more critical as we go forward in these more complex environments.
Operating the cloud environments simplifies things from a customer perspective, but it does add
some additional complexities in the infrastructure and operations of the organization as well. All
of those complexities add up to, meaning that even more attention needs to be brought to the
details of the program and where those responsibilities lie within stakeholders.
Gardner: Larry Hinman, we're seeing this drive towards cloud. We're also seeing consolidation
and standardization around data center infrastructure. So perhaps more large data centers to
support more types of applications to even more endpoints, users, and geographic locations or
business units. Getting that facilities and IT equation just right becomes even more important as
we have fewer, yet more massive and critical, data centers involved.
Hinman: Dana, that's exactly correct. If you look at this, you have to look at the data center
facilities piece, not only from a framework or model or topology perspective, but all the way
down to the specific environment.
It could be that based on a specific client’s business requirements and IT strategy that it will
require possibly a couple of large-scale core data centers and multiple remote sites and/or it
could just be a bunch of smaller types of facilities.
11. It really depends on how the business is being run and supported by IT and the application suite,
what the tolerances for risk are, whether it’s high availability, synchronous, all the groovy stuff,
and then coming up with a framework that matches all those requirements that it’s integrating.
We tell clients constantly that you have to have your act together with respect to your profile, and
start to align all of this, before you can even think about cloud and all the wonderful technologies
that are coming down the pike. You have to be able to have something that you can at least
manage to control cost and control this whole framework and manage to a future-state business
requirement, before you can even start to really deploy some of these other things.
So it all glues together. It's extremely important that customers understand that this really is a
process they have to do.
Gardner: Very good. You've been listening to a sponsored BriefingsDirect podcast discussion on
how quick and proven ways to attain productivity can significantly improve IT operations and
efficiency.
This is the second in an ongoing series of podcasts on data center transformation best practices
and is presented in conjunction with a complementary video series.
I'd like to thank our guests. We've been joined by Duncan Campbell, Vice President of Marketing
for HP Converged Infrastructure and SMB. Also, Randy Lawton, Practice Principal in the
Americas West Data Center Transformation & Cloud Infrastructure Consulting at HP.
And last, Larry Hinman, Critical Facilities Consulting Director and Worldwide Practice Leader
for HP Critical Facility Services and HP Technology Services. So thanks to you all.
This is Dana Gardner, Principal Analyst at Interarbor Solutions. Also, thanks to our audience for
listening, and come back next time.
For more information on The HUB -- HP's video series on data center transformation, go
to www.hp.com/go/thehub.
Listen to the podcast. Find it on iTunes/iPod. Sponsor: HP
Transcript of a sponsored podcast discussion in conjunction with an HP video series on the best
practices for developing a common roadmap for DCT. Copyright Interarbor Solutions, LLC,
2005-2011. All rights reserved.
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