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Perspective   Stefan Stroh
              Dr. Germar Schröder
              Dr. Florian Gröne




Keeping the Data
Center Competitive
Six Levers for
Boosting Performance,
Reducing Costs, and
Preparing for an
On-Demand World
Contact Information

Beirut                            Frankfurt                         London                      New York
Ramez Shehadi                     Stefan Stroh                      Louise Fletcher             Jeff Tucker
Partner                           Partner                           Partner                     Partner
+961-1-336433                     +49-69-97167-423                  +44-20-7393-3530            +1-212-551-6653
ramez.shehadi@booz.com            stefan.stroh@booz.com             louise.fletcher@booz.com    jeff.tucker@booz.com

Berlin                            Dr. Germar Schröder               Milan                       Sydney
Dr. Florian Gröne                 Principal                         Enrico Strada               Chris Manning
Senior Associate                  +49-69-97167-426                  Partner                     Partner
+49-30-88705-844                  germar.schroeder@booz.com         +39-02-72-50-93-00          +61-2-9321-1924
florian.groene@booz.com                                             enrico.strada@booz.com      chris.manning@booz.com
                                  Hong Kong                          
Chicago                           Edward Tse                        Mumbai                      Tokyo
Mike Cooke                        Senior Partner                    Suvojoy Sengupta            Shigeo Kizaki
Partner                           +852-3650-6100                    Partner                     Partner
+1-312-578-4639                   edward.tse@booz.com               +91-22-2287-2001            +81-3-3436-8647
mike.cooke@booz.com                                                 suvojoy.sengupta@booz.com   shigeo.kizaki@booz.com




Christopher Schmitz and Christian Beekes also contributed to this Perspective.




                                                                                                            Booz & Company
EXECUTIVE        Cost and capacity pressures on the corporate data center are
                 mounting. Increasing computing power demands, poor asset
SUMMARY
                 utilization, excess complexity, and growing concerns about
                 energy usage and costs are forcing companies to reassess how
                 they manage their data centers. Whether they operate their
                 data centers for internal customers or as third-party providers
                 of data center services to others, companies that don’t make the
                 effort to rethink their data center strategy face a future of rising
                 costs and declining performance relative to their competitors.
                 Companies that do make the effort can expect to cut the cost
                 of operating their data centers by as much as 40 percent.

                 Managers of data centers should look at six areas in which
                 their operations can be improved. The greatest potential sav-
                 ings lie in improved utilization of data center assets, through
                 server and storage virtualization and by making better use of
                 the data center facility itself—including a careful analysis of
                 the total worldwide footprint of data center facilities as well
                 as how operations are organized. Understanding how and
                 when data center resources are consumed can further improve
                 asset utilization and save energy. Restructuring the data cen-
                 ter’s operating model can increase efficiency, as can devising
                 a global sourcing strategy for data center services. Finally,
                 moving to a demand-driven model that rationalizes platforms
                 and products will help set the stage for the creation of the data
                 center of the future, one that can give corporate customers
                 what they want: efficient and flexible computing capacity.




Booz & Company                                                                      1
Key Findings

•  ven as demand for data services is
  E
  on the rise, the data center is under
  tremendous pressure to cut costs,
  reduce energy usage, and develop
  new delivery models.

•  hose pressures, and the threat of
  T
  rising costs, will force every data
  center operator to reassess how it
  does business if it wishes to remain
  competitive.

•  e believe there are six areas in
  W
  which companies can work to im-
  prove their data center operations:

    • mprove asset utilization through
      I
      virtualization                       Rethinking                                Deutsche Bank, and DHL—are
                                                                                     making major investments in state-
    •  onsolidate the data center foot-
      C                                    the                                       of-the-art data centers in hopes of
      print                                Data Center                               making their data center operations
                                                                                     more efficient and less costly. Such
    •  anage consumption to reduce
      M                                                                              efforts can lower total capital and
      usage and energy costs                                                         operating expenses by as much as
    •  estructure data center manage-
      R                                                                              40 percent. If corporations desire
      ment and operating model                                                       to maximize the value of their data
                                           At a time when every large-scale orga-    center assets and reach the next level
    •  reate a global data services
      C                                    nization is looking to cut expenses and   in performance, cost efficiency, and
      sourcing strategy                    streamline operations, the data center    quality control, they must begin now
                                           has come under increasing pressure to     to rethink the core structures of their
    •  odularize services offerings and
      M
                                           make its operations leaner. And the       data center production model.
      rationalize payment schemes
                                           time is ripe: Traditional data centers
                                           are facing the upper limits of their      Creating the data center of the future
                                           data capacity even as they continue to    will require a reassessment of the
                                           underutilize computing assets, while      current model in six specific areas:
                                           their massive appetite for electrical     technology platforms, data center
                                           power continues to raise concerns         topology, consumption management,
                                           about their impact on the environment.    end-to-end process efficiency, global
                                                                                     sourcing models, and commercial
                                           Any number of information-intensive       models. The risk of not doing so?
                                           companies—including the likes             Falling behind in the very competitive
                                           of Google, Microsoft, Facebook,           race for IT efficiency.




2                                                                                                            Booz  Company
Pressures        Four factors are driving the need
                 to rethink the data center. First,
                                                            typical data center is saddled with
                                                            a large and unwieldy inventory of
on the           despite ever more powerful comput-         operating systems, database software,
Data Center      ing technologies, such as multi-core,
                 64-bit chip architectures, the installed
                                                            and middleware. That in turn adds
                                                            hugely to the complexity of systems
                 base of servers has been growing           administration and maintenance—not
                 12 percent a year, from 14 million         to mention adding to cost. And server
                 in 2000 to 35 million in 2008. Yet         utilization is often low, with too many
                 that growth isn’t keeping up with the      CPUs idle or nearly so. Poor utiliza-
                 demands placed on data centers for         tion is a central cause of inflated data
                 computing power and the amount of          center capacity requirements, unnec-
                 data they can handle. Almost 30 per-       essarily high investments in hardware,
                 cent of respondents to a 2008 survey       and big energy bills.
                 of data center managers said their
                 centers will have reached their capac-     Moreover, companies face grow-
                 ity limits in three years or sooner.       ing concerns about the enormous
                                                            amounts of energy their data centers
                 At the same time, too many data            use and the resulting high levels of
                 centers are just not managed very          CO2 emissions they cause; indeed, a
                 well. Thanks to long histories of          number of European countries are
                 legacy systems and software, a lack        looking to regulate emissions even
                 of discipline regarding standards, and     more strictly than they do now.
                 ineffective life-cycle management, the     European data centers currently




                 European data centers currently
                 consume more energy than
                 the entire country of Denmark;
                 by 2019 they are expected to
                 use more than the Netherlands.




Booz  Company                                                                                     3
consume more energy than the entire                        tion. The auctioning of emission                 Exhibit 1), even as both external and
country of Denmark; by 2019 they                           certificates to utilities, slated to begin       internal customers apply downward
are expected to use more than                              in 2012, will further increase the cost          pressure on the price of data center
the Netherlands. A European Code                           of electricity.                                  services. Much of that increase is
of Conduct is already in place;                                                                             due to the rising cost of energy and
companies subscribing to the code                          There is only one future for compa-              higher labor costs, including wage
must make a voluntary commitment                           nies whose data centers continue to              inflation, an aging, more highly paid
to reduce power consumption by                             be traditionally operated: a world               workforce, and a coming shortage
applying best practices such as                            of rapidly rising costs. Under cur-              in the skills needed to operate data
energy audits, specific action plans                       rent practices and assuming constant             centers, all of which will result in
for reducing emissions, and continu-                       capacity, data center costs will rise 17         stagnating productivity. Although
ous monitoring of energy consump-                          percent over the next four years (see            continuing improvements in hardware




Exhibit 1
Over Time, Manpower and Energy Cost Inflation Will Eat Up Traditional Operators’ Margins


                          Enterprise Computing Cost Outlook
                Indexed Cost, Assuming Zero Volume Growth  Stable Delivery Model

                                                                                       117
                                                  110                 112
                              105                                                                       • Wage inflation
        100                                                                                             • Aging workforce
                                                                                                        • Skill shortages
                                                                                        50              • Stagnating productivity
                                                   45                  47
                               43
        41
                                                                                                        • Improving hardware performance
                                                                                                        • Stable price/performance ratio

                  5%
                                                   36                  36               36              • Rising power density
                               35
        35                                                                                              • Energy prices and emissions trading
                                                                                                        • Capacity shortages
                               10                  11                  11               12
         7
                                                                                                        • ncreasing construction
                                                                                                          I
        17                     17                  18                  18               19                and facility services costs

       2008                  2009                 2010                2011             2012


                                                                                                             Data Center Margin
                                                     -5%
                                                                                                             Manpower Cost
                                                                                                             Hardware/Software Cost
                 “Business as usual”
                 will turn a 5% profit into a                          -8%                                   Energy Cost
                 11% loss within 4 years                                                                     Facility Cost


                                                                                         -11%



Source: Booz  Company Econometric Data Center Planning Model




4                                                                                                                                          Booz  Company
performance will mean that the ratio                             Only by reinventing how they run
of price to performance will remain                              their centers—rethinking everything
steady, rising energy costs will eat up                          from technology platforms and data
those gains, as will higher costs of                             center topology to consumption
construction, operations, and facility                           management, global sourcing models,
services. The inevitable result: Driven                          end-to-end process efficiency, and
by bottom-line cost pressures alone,                             commercial models—can providers
providers of data center services will                           of data center services hope to thrive
see their already thin margins erode                             despite the pressures they face (see
further, turning average profits of                              Exhibit 2). How should data center
5 percent of revenues in 2008 into                               operators work to transform their
losses of 11 percent by 2012.                                    businesses in each of these six areas?




Exhibit 2
CIOs Must Rethink the Core Structures of Their Production Model to Remain Competitive


                                                                  Structural Optimization Levers


                           Commercial Models                                                                               Technology Platforms
           • Capacity-on-demand is the wave                             6                            1                     •  y increasing utilization, server
                                                                                                                             B
                of the future, requiring service                                                                             and storage virtualization
                            modularization and                                                                               has the greatest potential for
              transparent payment schemes.                                                                                   lowering data center costs.
                          • Potential gains: N/A                                                                           • Potential gains: 15%–20%

              Global Sourcing Models                                          Next Level …                                         Data Center Topology
       • Optimizing the global delivery                                       • Cost Efficiency                                    •  ootprint consolidation and
                                                                                                                                     F
           strategy involves balancing                   5                                                         2                 a proper tier structure can save
                                                                              • Performance
               commodity applications                                         • Quality Control                                      money, but a balance must be
              with more complex tasks                                                                                                struck between scale and complexity.
            • Potential gains: 10%–15%                                                                                             • Potential gains: 15%–30%

                      E2E Process Efficiency                                                                               Consumption Management
         • Restructuring both the data center                                                                              •  etter utilization of data center assets
                                                                                                                             B
           management organization and the                             4                             3                       and reduced energy consumption
  operating model can lead to better capacity                                                                                offer significant benefits in cost and
     planning and lower administrative costs.                                                                                reduced complexity.
                    • Potential gains: 5%–15%                                                                              • Potential gains: 5%–25%



Note: All figures should be read as “total cash-out reduction potential”; they include both capital and operational expense reductions.
Source: Booz  Company analysis




Booz  Company                                                                                                                                                              5
The Virtual                                                        Of all the steps that can be taken
                                                                   to reduce costs, using data center
                                                                                                                                       amounts of operational and capital
                                                                                                                                       expenditures that could be better used
Data Center                                                        assets more efficiently has perhaps                                 elsewhere. After a detailed analysis
                                                                   the greatest potential for generating                               of its data center costs, one large
                                                                   significant savings. Underutilization                               European corporation found that a
                                                                   of both computing and facility assets                               large-scale virtualization program had
                                                                   remains a large problem in data cen-                                the potential to lower its overall data
                                                                   ters: Servers typically run at less than                            center costs by 29 percent.
                                                                   10 percent of capacity, and it is not
                                                                   uncommon for more than 50 percent                                   The economics of virtualization
                                                                   of data center floor space to sit under-                            are powerful (see Exhibit 3). The
                                                                   utilized as well. The result: significant                           technology has the potential to lower



Exhibit 3
Virtualization Technology Has Tremendous Potential to Drive Cost Reduction throughout the Data Center


                            Virtualization Cost Impact                                                          Virtualization Economics
                           Average Cost per Windows Instance

    Illustrative                                                                                                                                           Net Effect/Instance1
                              €12,600                                                                   Virtualization Economics
                                             -29%
                                                                                                                                                              Low         High

                                                                                    Each full-time employee can manage 60 or more
                                                                                    virtual servers, compared with the current 20 to 30                    	 -30%	         -45%
                               5,500                                                dedicated servers.
             Manpower                                €8,950
                                                                                    Virtualization can more than double the current
                                                                                    dedicated hardware utilization rates of less than 10%,                 	 -15%	         -35%
                                                                                    although cost per CPU will be higher.
                                                      3,200
                                                                                    Operating systems, databases, and middleware can be run
                                                                                    virtually, although overall expenses may increase, thanks to           	 +15%	         -10%
              Hardware         3,800                                                added costs for virtualization management software.
                                                      2,900                         Each dedicated server currently uses 300 to 500 watts
                                                                                    of electricity, compared with an average of just 100 watts             	 +45%	         -70%
                                                                                    per virtual server.
               Software        1,900
                                                      2,100                         Each dedicated server currently needs, on average,
            Energy              800                                                 one to two rack units; that can be reduced to less than                	 -25%	         -50%
                                                       300
Data Center Facility            600                    450                          one rack unit per virtual server.
                            Instance on          Instance on
                          dedicated server       virtual server


1
 Size of effect depends on ratio of dedicated servers to newly virtualized servers, type of virtualization platform, degree of standardization, power density, and tier level of data center.
Source: Booz  Company analysis




6                                                                                                                                                                           Booz  Company
total costs of ownership by as much          tion—primarily high-volume platforms        includes, on the hardware front, an
as 40 percent. Consider hardware.            such as Windows and standard Unix           inventory of assets—the number
Dedicated servers frequently have            or Linux—lies somewhere between 20          of harmonized vendor clusters and
utilization rates of less than 10            and 60 percent of assets, depending on      machines with fewer than four
percent, whereas servers run virtually       the production model and computing          CPUs—and an analysis of utilization
can often more than double those             footprint. Trying to virtualize more        levels. As to software, the inventory
rates. And even though virtual servers       than that will usually involve the virtu-   should include harmonized operating
typically cost more per CPU, the             alization of more exotic platforms with     systems, database software and
overall benefit can be hardware cost         lower server counts, such as legacy         middleware clusters, and standard,
savings of between 15 and 35 percent.        Unix systems, and the effort simply         multi-platform certified applications
                                             won’t bring the returns expected.           such as Web and e-mail and standard
Despite the very real benefits of virtu-                                                 ERP and CRM. Finally, it’s important
alization, it rarely makes sense to try to   Achieving the maximum return                to ascertain whether any applications
virtualize everything. Indeed, the “sweet    requires a careful review of the            have technical restrictions, such as
spot” for generating the maximum             preconditions in the data center            maintenance liabilities, that might
return on investments in virtualiza-         for successful virtualization. That         restrict the use of virtualization.




Dedicated servers frequently have
utilization rates of less than 10 percent,
whereas servers run virtually can
often more than double those rates.




Booz  Company                                                                                                               7
Mapping the                                                                                Large multinational corporations use
                                                                                            different strategies for siting their data
                                                                                                                                                   ated by excess complexity have
                                                                                                                                                   not begun to make themselves felt
 Data Center                                                                                centers. Some may find themselves                      (see Exhibit 4).
                                                                                            running dozens of data centers around
                                                                                            the world. Hewlett-Packard, for                        Another way to put the problem is
                                                                                            instance, maintains about 60 centers                   in terms of utilization. Obviously,
                                                                                            worldwide. Others, such as ING,                        data centers are expensive. Looked
                                                                                            maintain just one primary hub. Data                    at in terms of cost as a function of
                                                                                            center topology, however, creates a                    utilization rate, however, unit costs
                                                                                            dilemma: Scale or resilience? A topol-                 come down rapidly. But the benefits
                                                                                            ogy that includes a small number of                    go only so far. After about 90 percent
                                                                                            large-scale centers offers the benefit                 utilization, data centers run a real
                                                                                            of scale, but the lack of diversification              risk of losing operational flexibility.
                                                                                            can pose a security risk, and individ-                 Generally speaking, the utilization
                                                                                            ual centers risk being simply too com-                 goal should be about 80 percent,
                                                                                            plex to operate efficiently. A plan that               which leaves adequate headroom for
                                                                                            includes many smaller centers runs the                 peak demand. Service providers will
                                                                                            opposite risk: Security concerns and                   want to leave somewhat more room
                                                                                            complexity are eased, but the individ-                 depending on their mid-term deal
                                                                                            ual centers may not be large enough                    pipeline, which may add sudden large
                                                                                            to reap the maximum benefits of scale.                 demands on their data centers. By the
                                                                                            Where is the happy medium?                             same token, in coping with capacity
                                                                                                                                                   bottlenecks, before expanding capac-
                                                                                            To operate at peak efficiency, data                    ity in a lower-tier center and reducing
                                                                                            centers should be about 10,000                         its utilization rate, consider the pos-
                                                                                            square meters. At that size, each                      sibility of using higher-tier capacity
                                                                                            center’s annual operating expenses are                 with better utilization and overall
                                                                                            minimized, but the added costs cre-                    lower unit costs.



     Exhibit 4
     When Consolidating Data Centers, It Is Vital to Find the Right Balance between Scale and Complexity


                                                                                           Data Center Cost by Size

                                                  16,000
Annual Operational Expense (€ per Square Meter)




                                                                                                 Efficient Data
                                                                                                                                                         Case A
                                                                                                  Center Size
                                                  14,000
                                                                                                                                                         Case B
                                                                                                                                                         Case C
                                                  12,000
                                                                                                                                                         Case D
                                                  10,000                                                                                                 Case E

                                                   8,000

                                                   6,000

                                                   4,000

                                                   2,000

                                                      0
                                                           0              5,000                      10,000                    15,000                     20,000



                                                               	 Scale Effects Dominate	                          Complexity Costs Erode Scale Effects

                                                                                   Computing Floor Space (in Square Meters)


     Source: Booz  Company analysis




      8                                                                                                                                                                   Booz  Company
Managing         On the other side of the utilization
                 coin is the issue of consumption man-
                                                            changes in resource utilization in order
                                                            to understand why they occur. These
Consumption      agement, involving the consumption         steps can reduce consumption of assets
                 of both computing assets and energy.       by up to 15 percent.
                 Significant savings can be found in the
                 effort to reduce the use of assets and     A further 15 to 20 percent reduction
                 to optimize the kinds and number of        in the use of resources can be achieved
                 assets being used. The key here is to      by identifying, and balancing, differ-
                 implement an efficient capacity plan-      ences in utilization by region, season,
                 ning process. On the consumption           time of day, and line of business.
                 side, begin by identifying the resources   Work with application owners and
                 required for each software application.    application development teams to
                 Then retire or move any resources          identify the factors driving utilization
                 that do not get accessed frequently.       and to develop measures for reducing
                 Together with the application develop-     consumption, including the renegotia-
                 ment team, work to limit increases in      tion of service-level agreements, the
                 consumption that may occur when            restructuring of job networks, and the
                 new application releases are rolled out.   redesign of applications to run at peak
                 Set up a program to closely monitor        efficiency. Again, devise a program




                 A further 15 to 20 percent reduction
                 in the use of resources can also be
                 achieved by identifying, and balancing,
                 differences in utilization by region,
                 season, time of day, and line of business.



Booz  Company                                                                                     9
to monitor utilization and how the                            the CPUs consume the most energy.                             number of AC-DC/DC-AC conversion
  measures you have taken are affecting                         Ideas for reducing the amount of                              cycles and by converting to high-
  resource utilization rates.                                   power consumed by CPUs include                                efficiency power distribution systems.
                                                                virtualization and the use of more                            Cooling costs can be lowered by the
  Data center operators can take a                              efficient multi-core processors and                           use of district cooling, heat pumps to
  variety of steps to save money on                             processors with dynamic scaling.                              reduce fan loading, desiccant cooling
  the energy side (see Exhibit 5). Of                           Gains can also be made in the area of                         driven from waste heat, variable
  the various data center components,                           power distribution by reducing the                            speed fans, and direct liquid cooling.




   Exhibit 5
   Data Center Operators Can Deploy a Number of Effective Measures to Optimize Energy Consumption


                                                         Typical Data Center Energy Usage by Component (%)


                   100
                                                    •  igh-efficiency systems (e.g., multi-core
                                                      H                                                                                  Processor load
                    90                                processors, virtualization, processors with                                        Power system load
                                                      dynamic frequency scaling, silicon storage, etc.
                                                                                                                                         Cooling system load
                    80   41%         41%
                                                                                                                                         Potential improvement measures
                    70                                                        •  educed AC-DC/DC-AC conversion cycles
                                                                                R
% Power Consumed




                                                                              • High-efficiency power distribution
                    60
                                                                                                                                       • District cooling
                    50                              20%                                                                                • Heat pumps to reduce fan loading
                                                                                                                                         
                                                                                                                                       • Desiccant cooling driven from waste heat
                                                                                                                                         
                    40   37%                                                                                                           • Variable speed fans
                                                                    12%                                                                • Direct liquid cooling
                    30
                                                                                     8%
                    20
                                                                                                     7%
                    10   23%                                                                                       6%
                                                                                                                                                 2%
                                                                                                                                  4%                            1%
                     0
                         Total      CPUs          Power            Chillers    Uninterruptible    Voltage       Server Fans    Computer        Power           Water
                                                Supply Units                   Power Supply      Regulators                    Room Fans     Distribution      Pumps

                                                                                       Component


   Source: Data Center Energy Briefing, U.S. Department of Energy; Intel Corporation; Booz  Company analysis




  10                                                                                                                                                         Booz  Company
The Efficient                                              The typical data center faces a further
                                                           challenge: the lack of truly efficient
                                                                                                              Many of the causes of inefficiency can
                                                                                                              be attributed to organizational prob-
Data Center                                                organizational structures and pro-                 lems such as understaffed demand
                                                           cesses. The causes of inefficiency                 and capacity planning functions and
                                                           are many: Too many data centers                    the lack of an integrated operating
                                                           find themselves focusing on day-to-                model. After a careful analysis of its
                                                           day troubleshooting rather than on                 employees’ activities, one company
                                                           strong system architecture and design.             running a midrange hosting operation
                                                           Furthermore, data centers often move               discovered that employees were spend-
                                                           into production mode prematurely,                  ing far too little time on planning and
                                                           before they have completed proper                  building out their systems, and far too
                                                           testing and deployment procedures.                 much time on daily operations and
                                                           The result is a low degree of stan-                ad-hoc troubleshooting. The result:
                                                           dardization in commodity operations                Day-to-day operations struggled with
                                                           activities and no clearly modularized              a poorly integrated operating model—
                                                           service and product portfolios, which              and efforts to standardize infrastruc-
                                                           makes both sales and product manage-               ture and increase utilization were
                                                           ment needlessly complex. Incoherent                doomed from the start.
                                                           process routines and lack of fully
                                                           transparent end-to-end service man-                The consequences of a poorly orga-
                                                           agement often lead to the delivery of              nized operating model can be dire
                                                           service levels over and above what has             (see Exhibit 6). In the model on the
                                                           been agreed to (and is being paid for)             left, the various functions of the data
                                                           by the customer—24/7 support, for                  center, from hosting to storage to con-
                                                           instance, becomes the default setting.             nectivity, are effectively siloed, with




Exhibit 6
A Cross-Platform Planning and Management Capability Can Improve Efficiency


            Typical Data Center Operating Model                                       Integrated Data Center Operating Model



                     Customer-Facing Functions                                                     Customer-Facing Functions




                                                                                               Capacity Planning  Administration
   Admin.                               Admin.                                                                                                        Reduce Costs
                      Admin.                               Admin.
                                                                                                                                                         Risks

  Service                                                                                             Service Management
  Manage-            Service            Service           Service
   ment              Manage-            Manage-           Manage-
                      ment               ment              ment



   Service                                                                      Service            Service            Service             Service
                     Service            Service           Service               Delivery           Delivery           Delivery            Delivery
   Delivery
                     Delivery           Delivery          Delivery




    Host            Midrange            Storage         Connectivity              Host             Midrange           Storage          Connectivity


•  urrent data center management is fragmented into many layers,
  C                                                                           • By integrating service management and thinking in terms of
                                                                                
  with too many handoffs of core processes, such as problem resolution          “services,” not “servers,” data centers can achieve better capacity
  and operations and change management, between functions.                      planning and management and lower administration costs.


Source: Booz  Company client example




Booz  Company                                                                                                                                                  11
each function running its own admin-       with the goal of automating routine,        features can help with compliance
istration and service management and       labor-intensive tasks such as trouble       and risk management tasks, and some
delivery. The resulting fragmentation      ticketing, fault management, and            suites offer the ability to manage
creates the need for an excessive          performance management. And the             workflow aligned with standard ITIL
number of handoffs when problems           number of automation tools is growing       processes. The maturity of such suites
occur, and any effort of the various       fast, as are the different configurations   remains a concern, however. Many of
functions to work together to change       of these automation systems, and the        them still lack real depth and interop-
operating procedures becomes very          move to virtualization will only add to     erability, and they do not typically
difficult. Instead, planning, admin-       that complexity. As long as each plat-      cover critical areas such as storage area
istration, and service management          form possesses its own management           networks and other network functions.
should be integrated across all the        silo, moreover, each silo will look to      The market includes a number of niche
functions, as in the model on the right,   automate its own platform operations.       players in such areas as server provi-
allowing for better capacity planning                                                  sioning, migration to virtual machines,
and lower administration costs.            Vendors are offering a variety of           patch management, and storage
                                           automation suites that can aid in the       allocation. The result: Automation
Can the automation of data centers         process of automation. Such tools           efforts still require a patchwork of
help improve efficiency? That, of          already include configuration manage-       tools—BMC Patrol combined with
course, is the hope of every operator of   ment functions such as automatic asset      MS System Center, for instance, or
data centers, especially as both process   discovery and resource transparency         VMware vCenter Server and EMC
and management complexity increases.       and are beginning to offer dependency       ControlCenter. Buyer, beware.
The desire to raise the efficiency of      mapping and advanced configuration
IT processes themselves is strong,         item reporting. New audit and control




One company running a midrange
hosting operation discovered that employees
were spending far too little time on
planning and building out their systems,
and far too much time on daily
operations and ad-hoc troubleshooting.




12                                                                                                             Booz  Company
Global                                            As corporations look to rationalize
                                                  and save money on their overall data
                                                                                                ers—continues to grow quickly. A
                                                                                                well-planned and well-executed global
Delivery                                          center footprints, the opportunity to         delivery model for data center services
                                                  offshore and nearshore a variety of           can generate considerable savings,
                                                  data center services—and to farm out          depending on which services are sent
                                                  some services to third-party provid-          offshore, where they are sent, and
                                                                                                to whom. Offshoring or nearshoring
                                                                                                suitable “commodity” activities such
                                                                                                as application management, database
                                                                                                management, monitoring, and engi-
Exhibit 7                                                                                       neering will bring the greatest cost
The Market for Offshore and Nearshore Services Continues to Gain Momentum,                      decreases—thanks primarily to lower
Offering Significant Cost Reduction Opportunities
                                                                                                salary and benefits costs, significant
                                                                                                process improvements, and lower
                             Offshore/Nearshore IT Production: Examples                         overall management costs.
                                        Total Cost Structure Shifts

                 Application management                        Midrange server operations       Moving application management
                          -22%                                           -10%
                                                                                                efforts to a combined onshore/
                                                                                                nearshore model probably offers the
                                                  Manpower      37%
 Manpower        69%
                                                                                    29%         greatest benefit—cost reductions of
                                       56%                                                      up to 22 percent—primarily because
  Hardware                                         Hardware     28%                 31%
   Software      0%
                                       1%                                                       of the large reduction in labor costs.
                                       27%          Software    11%                 12%
Connectivity
                 21%
                                       3%        Data Center    14%                 16%
                                                                                                Manpower typically makes up fully
                  0%
     Other       10%                   13%             Other    10%                 11%         69 percent of the cost of onshore
               Onshore       Onshore/Nearshore                 Onshore          RIM Nearshore
                                                                                                application management; moving to a
                                 combined
                                                                                                combined model, however, can reduce
                  Mainframe operations                             Storage operations
                          -6%                                             -6%
                                                                                                labor costs to just 48 percent of the
                                                                                                total. Cost savings can also be found
                                                  Manpower      16%                 13%
 Manpower        30%                   28%                                                      in other remote management models,
  Hardware       19%                   19%         Hardware     43%                 44%         including mainframes, infrastructure,
                                                                                                and storage (see Exhibit 7).
   Software      28%                   29%         Software     14%                 14%
Data Center      11%                   12%       Data Center    15%                 15%
      Other      12%                   12%            Other     13%                 13%
               Onshore           RIM Nearshore                 Onshore          RIM Nearshore


RIM=Remote Infrastructure Management
Source: Booz  Company analysis




Booz  Company                                                                                                                      13
Companies have taken a variety of         as eastern Europe gain expertise in       A third company, a large European
routes in their efforts to reap the       running large-scale data centers.         industrial manufacturer, outsourced
cost and flexibility benefits of global   Looking to create a shared onshore/       all of its data center operations,
sourcing. India has long been a prime     offshore infrastructure delivery          including remote management
region for such activities. One large     model, one German corporation             of more than 5,000 servers, to a
data center operator, for example,        recently set up a nearshore subsidiary    provider in India. In addition to data
turned to an Indian outsourcer for        to provide its more commoditized          services, the scope of the project
services that included 350 servers, 46    second- and third-line services on a      included incident management,
separate databases, 3,200 network         24/7 basis, in addition to its onshore    monitoring, and change execution,
elements, and 10 firewalls. In            data center, where the tasks requiring    all provided on a 24/7 basis. The
addition, the provider offered virus      a more highly skilled workforce           project began with just 50 full-time
management, as well as backup and         took place. Again, the benefits came      employees, but within three years that
storage management. The benefits          primarily in the form of lower labor      number was approaching 150. Again,
obtained included service levels          costs. Wages were about 40 percent        the advantage in labor costs provided
of 99.95 percent, 24 hours a day,         lower than those in Germany, and          the greatest savings: Wages in India
and higher productivity, as well as       the average age of the nearshore          averaged less than half of those in
significant wage differentials.           employees was likewise lower. The         the European headquarters. And
                                          client also found a strong talent pool    the project also allowed the client
Such benefits can be found closer         surrounding its new facility, with        to enforce a high level of process
to home as well, as regions such          adequate English and IT skills, thanks    standardization and automation.
                                          to the presence of nearby universities.




Manpower typically makes up fully
69 percent of the cost of onshore application
management; moving to a combined
onshore/nearshore model, however, can reduce
labor costs to just 48 percent of the total.




14                                                                                                        Booz  Company
Managing         Data center operators looking to
                 offer their services to others on a
                                                           and the revenues obtained from them.
                                                           Without that connection, they cannot
the Third-       commercial basis frequently face the      clearly link capacity planning and
Party            same problem: Too often they don’t
                 have the ability to conduct effective
                                                           revenue projections, and they cannot
                                                           determine clear targets for their costs
Data Center      end-to-end capacity management            of production, given what the market
                 and cost steering, or the means to        expects. Solving this problem requires
                 provide transparency for costs and        simple, transparent connections
                 services. Typically, their catalog        between services and modular
                 of services is too diversified, with      production building blocks and the
                 every customer enjoying its own set       capacity to understand the market
                 of specific, personally configured        and link it to target cost planning.
                 services. The result is an overly
                 complex set of offerings that is          A further consequence of the typical
                 difficult to benchmark or rationally      collection of diversified services
                 and transparently charge for. Making      maintained by most commercial
                 the transition to a demand-driven         data centers is a lack of transparency
                 model will require significant changes    regarding the total cost of the
                 in how data centers operate. They         data center’s operations and poor
                 must move to a standardized set of        governance in managing those
                 limited platform products that can        costs. The mechanisms by which
                 be strictly managed and maintained,       costs are allocated become overly
                 easily compared with the offerings of     complex, thanks in part to poor
                 competitors, and straightforward to       organizational alignment. Here again,
                 cost out.                                 the solution lies in introducing a cost-
                                                           reporting mechanism that is simple,
                 In the area where service and             transparent, and based on total cost
                 production issues merge, the problem      of ownership, and in realigning
                 is similar. Many data centers struggle    the organization into “production
                 to maintain a clear, logical connection   towers” that can help organize the
                 between how services are produced         process of cost reporting.




Booz  Company                                                                                   15
The capacity-on-demand model                               customer’s needs, and based more on
is clearly the future of data center                       computing capacity and performance
operations (see Exhibit 8). Customers                      than on specific hardware and
no longer want to pay for capacity                         software configurations. That
they aren’t always using, and they                         means developing efficient new
don’t much care anymore about the                          ways to deploy capacity and shut
specifics of the hardware and software                     it down when not needed, to better
being employed. In order to stay                           balance total capacity usage, and
competitive, providers must move                           to standardize both hardware and
quickly to offer data center services                      software platforms so they can scale
that are scalable depending on the                         up capacity quickly.




                                                                                                  In Summary



                                                                                                  These six areas in which data center
                                                                                                  operations can be enhanced offer
                                                                                                  data centers the potential for major
                                                                                                  improvements in their performance,
Exhibit 8                                                                                         and significant benefits in the form
The Continued Move toward Capacity-on-Demand Models Will Force                                    of reduced operating costs. Both
Data Centers to Rationalize Platforms and Services Offerings                                      corporate data centers and centers
                                                                                                  providing computing services to
                    Data Center Service Model Trends                                              others should consider some or all of
                                                                                                  the improvements suggested if they
                                                                                                  wish to maintain their competitive
                                                                                                  position. The data center is rapidly
                      Classical
                     Outsourcing                                                                  moving toward a new model in which
                                                                                                  what matters is delivering as much
                                                                                                  computing capacity as customers
Spend                                   Managed
                                        Services
                                                                                                  need, when they need it. Will you be
                                                                                                  ready to give it to them?


                                                          Computing
                                                            Utility


      0
           2005	                                                      2020



          Servers        Toward variable commercial delivery        Services


  • Platform specific                                          • Platform independent
  •  ased on individual system
    B                                                          •  ased on computing capacity
                                                                 B
    configurations customized                                    and performance
    for each customer                                          •  calable depending on needs
                                                                 S


Source: Booz  Company analysis




16                                                                                                                      Booz  Company
About the Authors

Stefan Stroh is a partner with       Dr. Florian Gröne is
Booz  Company in Frankfurt.         a senior associate with
He leads the global transporta-      Booz  Company in Berlin.
tion technology practice and         He supports telecommunica-
works for leading players in the     tions companies and ICT
international railway, logistics,    Service Providers in develop-
aviation, travel, high tech, and     ing their market positioning
consumer products sectors.           strategies and improving IT
                                     operations efficiency. He also
Dr. Germar Schröder is a             works on CRM strategy and
principal with Booz  Company        architecture across industries.
in Frankfurt. He focuses on
IT strategy, large-scale transfor-
mation programs, and finance
IT, primarily for the telecom-
munications industry. He also
supports IT service providers
in business model develop-
ment, strategy, and operational
efficiency.




Booz  Company                                                         17
The most recent list of     Worldwide        Bangkok        Madrid        Dubai           South America
our office addresses and    Offices          Brisbane       Milan         Riyadh          Buenos Aires
telephone numbers can                        Canberra       Moscow                        Rio de Janeiro
be found on our website,    Asia             Jakarta        Munich        North America   Santiago
www.booz.com                Beijing          Kuala Lumpur   Oslo          Atlanta         São Paulo
                            Hong Kong        Melbourne      Paris         Chicago
                            Mumbai           Sydney         Rome          Cleveland
                            Seoul                           Stockholm     Dallas
                            Shanghai         Europe         Stuttgart     Detroit
                            Taipei           Amsterdam      Vienna        Florham Park
                            Tokyo            Berlin         Warsaw        Houston
                                             Copenhagen     Zurich        Los Angeles
                            Australia,       Dublin                       McLean
                            New Zealand     Düsseldorf     Middle East   Mexico City
                            Southeast Asia   Frankfurt      Abu Dhabi     New York City
                            Adelaide         Helsinki       Beirut        Parsippany
                            Auckland         London         Cairo         San Francisco




Booz  Company is a leading global management
consulting firm, helping the world’s top businesses,
governments, and organizations.

Our founder, Edwin Booz, defined the profession
when he established the first management consulting
firm in 1914.

Today, with more than 3,300 people in 58 offices
around the world, we bring foresight and knowledge,
deep functional expertise, and a practical approach
to building capabilities and delivering real impact.
We work closely with our clients to create and deliver
essential advantage.

For our management magazine strategy+business,
visit www.strategy-business.com.

Visit www.booz.com to learn more about
Booz  Company.




Printed in Germany
©2009 Booz  Company Inc.

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Keeping the Data Center Competitive

  • 1. Perspective Stefan Stroh Dr. Germar Schröder Dr. Florian Gröne Keeping the Data Center Competitive Six Levers for Boosting Performance, Reducing Costs, and Preparing for an On-Demand World
  • 2. Contact Information Beirut Frankfurt London New York Ramez Shehadi Stefan Stroh Louise Fletcher Jeff Tucker Partner Partner Partner Partner +961-1-336433 +49-69-97167-423 +44-20-7393-3530 +1-212-551-6653 ramez.shehadi@booz.com stefan.stroh@booz.com louise.fletcher@booz.com jeff.tucker@booz.com Berlin Dr. Germar Schröder Milan Sydney Dr. Florian Gröne Principal Enrico Strada Chris Manning Senior Associate +49-69-97167-426 Partner Partner +49-30-88705-844 germar.schroeder@booz.com +39-02-72-50-93-00 +61-2-9321-1924 florian.groene@booz.com enrico.strada@booz.com chris.manning@booz.com Hong Kong   Chicago Edward Tse Mumbai Tokyo Mike Cooke Senior Partner Suvojoy Sengupta Shigeo Kizaki Partner +852-3650-6100 Partner Partner +1-312-578-4639 edward.tse@booz.com +91-22-2287-2001 +81-3-3436-8647 mike.cooke@booz.com suvojoy.sengupta@booz.com shigeo.kizaki@booz.com Christopher Schmitz and Christian Beekes also contributed to this Perspective. Booz & Company
  • 3. EXECUTIVE Cost and capacity pressures on the corporate data center are mounting. Increasing computing power demands, poor asset SUMMARY utilization, excess complexity, and growing concerns about energy usage and costs are forcing companies to reassess how they manage their data centers. Whether they operate their data centers for internal customers or as third-party providers of data center services to others, companies that don’t make the effort to rethink their data center strategy face a future of rising costs and declining performance relative to their competitors. Companies that do make the effort can expect to cut the cost of operating their data centers by as much as 40 percent. Managers of data centers should look at six areas in which their operations can be improved. The greatest potential sav- ings lie in improved utilization of data center assets, through server and storage virtualization and by making better use of the data center facility itself—including a careful analysis of the total worldwide footprint of data center facilities as well as how operations are organized. Understanding how and when data center resources are consumed can further improve asset utilization and save energy. Restructuring the data cen- ter’s operating model can increase efficiency, as can devising a global sourcing strategy for data center services. Finally, moving to a demand-driven model that rationalizes platforms and products will help set the stage for the creation of the data center of the future, one that can give corporate customers what they want: efficient and flexible computing capacity. Booz & Company 1
  • 4. Key Findings • ven as demand for data services is E on the rise, the data center is under tremendous pressure to cut costs, reduce energy usage, and develop new delivery models. • hose pressures, and the threat of T rising costs, will force every data center operator to reassess how it does business if it wishes to remain competitive. • e believe there are six areas in W which companies can work to im- prove their data center operations: • mprove asset utilization through I virtualization Rethinking Deutsche Bank, and DHL—are making major investments in state- • onsolidate the data center foot- C the of-the-art data centers in hopes of print Data Center making their data center operations more efficient and less costly. Such • anage consumption to reduce M efforts can lower total capital and usage and energy costs operating expenses by as much as • estructure data center manage- R 40 percent. If corporations desire ment and operating model to maximize the value of their data At a time when every large-scale orga- center assets and reach the next level • reate a global data services C nization is looking to cut expenses and in performance, cost efficiency, and sourcing strategy streamline operations, the data center quality control, they must begin now has come under increasing pressure to to rethink the core structures of their • odularize services offerings and M make its operations leaner. And the data center production model. rationalize payment schemes time is ripe: Traditional data centers are facing the upper limits of their Creating the data center of the future data capacity even as they continue to will require a reassessment of the underutilize computing assets, while current model in six specific areas: their massive appetite for electrical technology platforms, data center power continues to raise concerns topology, consumption management, about their impact on the environment. end-to-end process efficiency, global sourcing models, and commercial Any number of information-intensive models. The risk of not doing so? companies—including the likes Falling behind in the very competitive of Google, Microsoft, Facebook, race for IT efficiency. 2 Booz Company
  • 5. Pressures Four factors are driving the need to rethink the data center. First, typical data center is saddled with a large and unwieldy inventory of on the despite ever more powerful comput- operating systems, database software, Data Center ing technologies, such as multi-core, 64-bit chip architectures, the installed and middleware. That in turn adds hugely to the complexity of systems base of servers has been growing administration and maintenance—not 12 percent a year, from 14 million to mention adding to cost. And server in 2000 to 35 million in 2008. Yet utilization is often low, with too many that growth isn’t keeping up with the CPUs idle or nearly so. Poor utiliza- demands placed on data centers for tion is a central cause of inflated data computing power and the amount of center capacity requirements, unnec- data they can handle. Almost 30 per- essarily high investments in hardware, cent of respondents to a 2008 survey and big energy bills. of data center managers said their centers will have reached their capac- Moreover, companies face grow- ity limits in three years or sooner. ing concerns about the enormous amounts of energy their data centers At the same time, too many data use and the resulting high levels of centers are just not managed very CO2 emissions they cause; indeed, a well. Thanks to long histories of number of European countries are legacy systems and software, a lack looking to regulate emissions even of discipline regarding standards, and more strictly than they do now. ineffective life-cycle management, the European data centers currently European data centers currently consume more energy than the entire country of Denmark; by 2019 they are expected to use more than the Netherlands. Booz Company 3
  • 6. consume more energy than the entire tion. The auctioning of emission Exhibit 1), even as both external and country of Denmark; by 2019 they certificates to utilities, slated to begin internal customers apply downward are expected to use more than in 2012, will further increase the cost pressure on the price of data center the Netherlands. A European Code of electricity. services. Much of that increase is of Conduct is already in place; due to the rising cost of energy and companies subscribing to the code There is only one future for compa- higher labor costs, including wage must make a voluntary commitment nies whose data centers continue to inflation, an aging, more highly paid to reduce power consumption by be traditionally operated: a world workforce, and a coming shortage applying best practices such as of rapidly rising costs. Under cur- in the skills needed to operate data energy audits, specific action plans rent practices and assuming constant centers, all of which will result in for reducing emissions, and continu- capacity, data center costs will rise 17 stagnating productivity. Although ous monitoring of energy consump- percent over the next four years (see continuing improvements in hardware Exhibit 1 Over Time, Manpower and Energy Cost Inflation Will Eat Up Traditional Operators’ Margins Enterprise Computing Cost Outlook Indexed Cost, Assuming Zero Volume Growth Stable Delivery Model 117 110 112 105 • Wage inflation 100 • Aging workforce • Skill shortages 50 • Stagnating productivity 45 47 43 41 • Improving hardware performance • Stable price/performance ratio 5% 36 36 36 • Rising power density 35 35 • Energy prices and emissions trading • Capacity shortages 10 11 11 12 7 • ncreasing construction I 17 17 18 18 19 and facility services costs 2008 2009 2010 2011 2012 Data Center Margin -5% Manpower Cost Hardware/Software Cost “Business as usual” will turn a 5% profit into a -8% Energy Cost 11% loss within 4 years Facility Cost -11% Source: Booz Company Econometric Data Center Planning Model 4 Booz Company
  • 7. performance will mean that the ratio Only by reinventing how they run of price to performance will remain their centers—rethinking everything steady, rising energy costs will eat up from technology platforms and data those gains, as will higher costs of center topology to consumption construction, operations, and facility management, global sourcing models, services. The inevitable result: Driven end-to-end process efficiency, and by bottom-line cost pressures alone, commercial models—can providers providers of data center services will of data center services hope to thrive see their already thin margins erode despite the pressures they face (see further, turning average profits of Exhibit 2). How should data center 5 percent of revenues in 2008 into operators work to transform their losses of 11 percent by 2012. businesses in each of these six areas? Exhibit 2 CIOs Must Rethink the Core Structures of Their Production Model to Remain Competitive Structural Optimization Levers Commercial Models Technology Platforms • Capacity-on-demand is the wave 6 1 • y increasing utilization, server B of the future, requiring service and storage virtualization modularization and has the greatest potential for transparent payment schemes. lowering data center costs. • Potential gains: N/A • Potential gains: 15%–20% Global Sourcing Models Next Level … Data Center Topology • Optimizing the global delivery • Cost Efficiency • ootprint consolidation and F strategy involves balancing 5 2 a proper tier structure can save • Performance commodity applications • Quality Control money, but a balance must be with more complex tasks struck between scale and complexity. • Potential gains: 10%–15% • Potential gains: 15%–30% E2E Process Efficiency Consumption Management • Restructuring both the data center • etter utilization of data center assets B management organization and the 4 3 and reduced energy consumption operating model can lead to better capacity offer significant benefits in cost and planning and lower administrative costs. reduced complexity. • Potential gains: 5%–15% • Potential gains: 5%–25% Note: All figures should be read as “total cash-out reduction potential”; they include both capital and operational expense reductions. Source: Booz Company analysis Booz Company 5
  • 8. The Virtual Of all the steps that can be taken to reduce costs, using data center amounts of operational and capital expenditures that could be better used Data Center assets more efficiently has perhaps elsewhere. After a detailed analysis the greatest potential for generating of its data center costs, one large significant savings. Underutilization European corporation found that a of both computing and facility assets large-scale virtualization program had remains a large problem in data cen- the potential to lower its overall data ters: Servers typically run at less than center costs by 29 percent. 10 percent of capacity, and it is not uncommon for more than 50 percent The economics of virtualization of data center floor space to sit under- are powerful (see Exhibit 3). The utilized as well. The result: significant technology has the potential to lower Exhibit 3 Virtualization Technology Has Tremendous Potential to Drive Cost Reduction throughout the Data Center Virtualization Cost Impact Virtualization Economics Average Cost per Windows Instance Illustrative Net Effect/Instance1 €12,600 Virtualization Economics -29% Low High Each full-time employee can manage 60 or more virtual servers, compared with the current 20 to 30 -30% -45% 5,500 dedicated servers. Manpower €8,950 Virtualization can more than double the current dedicated hardware utilization rates of less than 10%, -15% -35% although cost per CPU will be higher. 3,200 Operating systems, databases, and middleware can be run virtually, although overall expenses may increase, thanks to +15% -10% Hardware 3,800 added costs for virtualization management software. 2,900 Each dedicated server currently uses 300 to 500 watts of electricity, compared with an average of just 100 watts +45% -70% per virtual server. Software 1,900 2,100 Each dedicated server currently needs, on average, Energy 800 one to two rack units; that can be reduced to less than -25% -50% 300 Data Center Facility 600 450 one rack unit per virtual server. Instance on Instance on dedicated server virtual server 1 Size of effect depends on ratio of dedicated servers to newly virtualized servers, type of virtualization platform, degree of standardization, power density, and tier level of data center. Source: Booz Company analysis 6 Booz Company
  • 9. total costs of ownership by as much tion—primarily high-volume platforms includes, on the hardware front, an as 40 percent. Consider hardware. such as Windows and standard Unix inventory of assets—the number Dedicated servers frequently have or Linux—lies somewhere between 20 of harmonized vendor clusters and utilization rates of less than 10 and 60 percent of assets, depending on machines with fewer than four percent, whereas servers run virtually the production model and computing CPUs—and an analysis of utilization can often more than double those footprint. Trying to virtualize more levels. As to software, the inventory rates. And even though virtual servers than that will usually involve the virtu- should include harmonized operating typically cost more per CPU, the alization of more exotic platforms with systems, database software and overall benefit can be hardware cost lower server counts, such as legacy middleware clusters, and standard, savings of between 15 and 35 percent. Unix systems, and the effort simply multi-platform certified applications won’t bring the returns expected. such as Web and e-mail and standard Despite the very real benefits of virtu- ERP and CRM. Finally, it’s important alization, it rarely makes sense to try to Achieving the maximum return to ascertain whether any applications virtualize everything. Indeed, the “sweet requires a careful review of the have technical restrictions, such as spot” for generating the maximum preconditions in the data center maintenance liabilities, that might return on investments in virtualiza- for successful virtualization. That restrict the use of virtualization. Dedicated servers frequently have utilization rates of less than 10 percent, whereas servers run virtually can often more than double those rates. Booz Company 7
  • 10. Mapping the Large multinational corporations use different strategies for siting their data ated by excess complexity have not begun to make themselves felt Data Center centers. Some may find themselves (see Exhibit 4). running dozens of data centers around the world. Hewlett-Packard, for Another way to put the problem is instance, maintains about 60 centers in terms of utilization. Obviously, worldwide. Others, such as ING, data centers are expensive. Looked maintain just one primary hub. Data at in terms of cost as a function of center topology, however, creates a utilization rate, however, unit costs dilemma: Scale or resilience? A topol- come down rapidly. But the benefits ogy that includes a small number of go only so far. After about 90 percent large-scale centers offers the benefit utilization, data centers run a real of scale, but the lack of diversification risk of losing operational flexibility. can pose a security risk, and individ- Generally speaking, the utilization ual centers risk being simply too com- goal should be about 80 percent, plex to operate efficiently. A plan that which leaves adequate headroom for includes many smaller centers runs the peak demand. Service providers will opposite risk: Security concerns and want to leave somewhat more room complexity are eased, but the individ- depending on their mid-term deal ual centers may not be large enough pipeline, which may add sudden large to reap the maximum benefits of scale. demands on their data centers. By the Where is the happy medium? same token, in coping with capacity bottlenecks, before expanding capac- To operate at peak efficiency, data ity in a lower-tier center and reducing centers should be about 10,000 its utilization rate, consider the pos- square meters. At that size, each sibility of using higher-tier capacity center’s annual operating expenses are with better utilization and overall minimized, but the added costs cre- lower unit costs. Exhibit 4 When Consolidating Data Centers, It Is Vital to Find the Right Balance between Scale and Complexity Data Center Cost by Size 16,000 Annual Operational Expense (€ per Square Meter) Efficient Data Case A Center Size 14,000 Case B Case C 12,000 Case D 10,000 Case E 8,000 6,000 4,000 2,000 0 0 5,000 10,000 15,000 20,000 Scale Effects Dominate Complexity Costs Erode Scale Effects Computing Floor Space (in Square Meters) Source: Booz Company analysis 8 Booz Company
  • 11. Managing On the other side of the utilization coin is the issue of consumption man- changes in resource utilization in order to understand why they occur. These Consumption agement, involving the consumption steps can reduce consumption of assets of both computing assets and energy. by up to 15 percent. Significant savings can be found in the effort to reduce the use of assets and A further 15 to 20 percent reduction to optimize the kinds and number of in the use of resources can be achieved assets being used. The key here is to by identifying, and balancing, differ- implement an efficient capacity plan- ences in utilization by region, season, ning process. On the consumption time of day, and line of business. side, begin by identifying the resources Work with application owners and required for each software application. application development teams to Then retire or move any resources identify the factors driving utilization that do not get accessed frequently. and to develop measures for reducing Together with the application develop- consumption, including the renegotia- ment team, work to limit increases in tion of service-level agreements, the consumption that may occur when restructuring of job networks, and the new application releases are rolled out. redesign of applications to run at peak Set up a program to closely monitor efficiency. Again, devise a program A further 15 to 20 percent reduction in the use of resources can also be achieved by identifying, and balancing, differences in utilization by region, season, time of day, and line of business. Booz Company 9
  • 12. to monitor utilization and how the the CPUs consume the most energy. number of AC-DC/DC-AC conversion measures you have taken are affecting Ideas for reducing the amount of cycles and by converting to high- resource utilization rates. power consumed by CPUs include efficiency power distribution systems. virtualization and the use of more Cooling costs can be lowered by the Data center operators can take a efficient multi-core processors and use of district cooling, heat pumps to variety of steps to save money on processors with dynamic scaling. reduce fan loading, desiccant cooling the energy side (see Exhibit 5). Of Gains can also be made in the area of driven from waste heat, variable the various data center components, power distribution by reducing the speed fans, and direct liquid cooling. Exhibit 5 Data Center Operators Can Deploy a Number of Effective Measures to Optimize Energy Consumption Typical Data Center Energy Usage by Component (%) 100 • igh-efficiency systems (e.g., multi-core H Processor load 90 processors, virtualization, processors with Power system load dynamic frequency scaling, silicon storage, etc. Cooling system load 80 41% 41% Potential improvement measures 70 • educed AC-DC/DC-AC conversion cycles R % Power Consumed • High-efficiency power distribution 60 • District cooling 50 20% • Heat pumps to reduce fan loading • Desiccant cooling driven from waste heat 40 37% • Variable speed fans 12% • Direct liquid cooling 30 8% 20 7% 10 23% 6% 2% 4% 1% 0 Total CPUs Power Chillers Uninterruptible Voltage Server Fans Computer Power Water Supply Units Power Supply Regulators Room Fans Distribution Pumps Component Source: Data Center Energy Briefing, U.S. Department of Energy; Intel Corporation; Booz Company analysis 10 Booz Company
  • 13. The Efficient The typical data center faces a further challenge: the lack of truly efficient Many of the causes of inefficiency can be attributed to organizational prob- Data Center organizational structures and pro- lems such as understaffed demand cesses. The causes of inefficiency and capacity planning functions and are many: Too many data centers the lack of an integrated operating find themselves focusing on day-to- model. After a careful analysis of its day troubleshooting rather than on employees’ activities, one company strong system architecture and design. running a midrange hosting operation Furthermore, data centers often move discovered that employees were spend- into production mode prematurely, ing far too little time on planning and before they have completed proper building out their systems, and far too testing and deployment procedures. much time on daily operations and The result is a low degree of stan- ad-hoc troubleshooting. The result: dardization in commodity operations Day-to-day operations struggled with activities and no clearly modularized a poorly integrated operating model— service and product portfolios, which and efforts to standardize infrastruc- makes both sales and product manage- ture and increase utilization were ment needlessly complex. Incoherent doomed from the start. process routines and lack of fully transparent end-to-end service man- The consequences of a poorly orga- agement often lead to the delivery of nized operating model can be dire service levels over and above what has (see Exhibit 6). In the model on the been agreed to (and is being paid for) left, the various functions of the data by the customer—24/7 support, for center, from hosting to storage to con- instance, becomes the default setting. nectivity, are effectively siloed, with Exhibit 6 A Cross-Platform Planning and Management Capability Can Improve Efficiency Typical Data Center Operating Model Integrated Data Center Operating Model Customer-Facing Functions Customer-Facing Functions Capacity Planning Administration Admin. Admin. Reduce Costs Admin. Admin. Risks Service Service Management Manage- Service Service Service ment Manage- Manage- Manage- ment ment ment Service Service Service Service Service Service Service Service Delivery Delivery Delivery Delivery Delivery Delivery Delivery Delivery Host Midrange Storage Connectivity Host Midrange Storage Connectivity • urrent data center management is fragmented into many layers, C • By integrating service management and thinking in terms of with too many handoffs of core processes, such as problem resolution “services,” not “servers,” data centers can achieve better capacity and operations and change management, between functions. planning and management and lower administration costs. Source: Booz Company client example Booz Company 11
  • 14. each function running its own admin- with the goal of automating routine, features can help with compliance istration and service management and labor-intensive tasks such as trouble and risk management tasks, and some delivery. The resulting fragmentation ticketing, fault management, and suites offer the ability to manage creates the need for an excessive performance management. And the workflow aligned with standard ITIL number of handoffs when problems number of automation tools is growing processes. The maturity of such suites occur, and any effort of the various fast, as are the different configurations remains a concern, however. Many of functions to work together to change of these automation systems, and the them still lack real depth and interop- operating procedures becomes very move to virtualization will only add to erability, and they do not typically difficult. Instead, planning, admin- that complexity. As long as each plat- cover critical areas such as storage area istration, and service management form possesses its own management networks and other network functions. should be integrated across all the silo, moreover, each silo will look to The market includes a number of niche functions, as in the model on the right, automate its own platform operations. players in such areas as server provi- allowing for better capacity planning sioning, migration to virtual machines, and lower administration costs. Vendors are offering a variety of patch management, and storage automation suites that can aid in the allocation. The result: Automation Can the automation of data centers process of automation. Such tools efforts still require a patchwork of help improve efficiency? That, of already include configuration manage- tools—BMC Patrol combined with course, is the hope of every operator of ment functions such as automatic asset MS System Center, for instance, or data centers, especially as both process discovery and resource transparency VMware vCenter Server and EMC and management complexity increases. and are beginning to offer dependency ControlCenter. Buyer, beware. The desire to raise the efficiency of mapping and advanced configuration IT processes themselves is strong, item reporting. New audit and control One company running a midrange hosting operation discovered that employees were spending far too little time on planning and building out their systems, and far too much time on daily operations and ad-hoc troubleshooting. 12 Booz Company
  • 15. Global As corporations look to rationalize and save money on their overall data ers—continues to grow quickly. A well-planned and well-executed global Delivery center footprints, the opportunity to delivery model for data center services offshore and nearshore a variety of can generate considerable savings, data center services—and to farm out depending on which services are sent some services to third-party provid- offshore, where they are sent, and to whom. Offshoring or nearshoring suitable “commodity” activities such as application management, database management, monitoring, and engi- Exhibit 7 neering will bring the greatest cost The Market for Offshore and Nearshore Services Continues to Gain Momentum, decreases—thanks primarily to lower Offering Significant Cost Reduction Opportunities salary and benefits costs, significant process improvements, and lower Offshore/Nearshore IT Production: Examples overall management costs. Total Cost Structure Shifts Application management Midrange server operations Moving application management -22% -10% efforts to a combined onshore/ nearshore model probably offers the Manpower 37% Manpower 69% 29% greatest benefit—cost reductions of 56% up to 22 percent—primarily because Hardware Hardware 28% 31% Software 0% 1% of the large reduction in labor costs. 27% Software 11% 12% Connectivity 21% 3% Data Center 14% 16% Manpower typically makes up fully 0% Other 10% 13% Other 10% 11% 69 percent of the cost of onshore Onshore Onshore/Nearshore Onshore RIM Nearshore application management; moving to a combined combined model, however, can reduce Mainframe operations Storage operations -6% -6% labor costs to just 48 percent of the total. Cost savings can also be found Manpower 16% 13% Manpower 30% 28% in other remote management models, Hardware 19% 19% Hardware 43% 44% including mainframes, infrastructure, and storage (see Exhibit 7). Software 28% 29% Software 14% 14% Data Center 11% 12% Data Center 15% 15% Other 12% 12% Other 13% 13% Onshore RIM Nearshore Onshore RIM Nearshore RIM=Remote Infrastructure Management Source: Booz Company analysis Booz Company 13
  • 16. Companies have taken a variety of as eastern Europe gain expertise in A third company, a large European routes in their efforts to reap the running large-scale data centers. industrial manufacturer, outsourced cost and flexibility benefits of global Looking to create a shared onshore/ all of its data center operations, sourcing. India has long been a prime offshore infrastructure delivery including remote management region for such activities. One large model, one German corporation of more than 5,000 servers, to a data center operator, for example, recently set up a nearshore subsidiary provider in India. In addition to data turned to an Indian outsourcer for to provide its more commoditized services, the scope of the project services that included 350 servers, 46 second- and third-line services on a included incident management, separate databases, 3,200 network 24/7 basis, in addition to its onshore monitoring, and change execution, elements, and 10 firewalls. In data center, where the tasks requiring all provided on a 24/7 basis. The addition, the provider offered virus a more highly skilled workforce project began with just 50 full-time management, as well as backup and took place. Again, the benefits came employees, but within three years that storage management. The benefits primarily in the form of lower labor number was approaching 150. Again, obtained included service levels costs. Wages were about 40 percent the advantage in labor costs provided of 99.95 percent, 24 hours a day, lower than those in Germany, and the greatest savings: Wages in India and higher productivity, as well as the average age of the nearshore averaged less than half of those in significant wage differentials. employees was likewise lower. The the European headquarters. And client also found a strong talent pool the project also allowed the client Such benefits can be found closer surrounding its new facility, with to enforce a high level of process to home as well, as regions such adequate English and IT skills, thanks standardization and automation. to the presence of nearby universities. Manpower typically makes up fully 69 percent of the cost of onshore application management; moving to a combined onshore/nearshore model, however, can reduce labor costs to just 48 percent of the total. 14 Booz Company
  • 17. Managing Data center operators looking to offer their services to others on a and the revenues obtained from them. Without that connection, they cannot the Third- commercial basis frequently face the clearly link capacity planning and Party same problem: Too often they don’t have the ability to conduct effective revenue projections, and they cannot determine clear targets for their costs Data Center end-to-end capacity management of production, given what the market and cost steering, or the means to expects. Solving this problem requires provide transparency for costs and simple, transparent connections services. Typically, their catalog between services and modular of services is too diversified, with production building blocks and the every customer enjoying its own set capacity to understand the market of specific, personally configured and link it to target cost planning. services. The result is an overly complex set of offerings that is A further consequence of the typical difficult to benchmark or rationally collection of diversified services and transparently charge for. Making maintained by most commercial the transition to a demand-driven data centers is a lack of transparency model will require significant changes regarding the total cost of the in how data centers operate. They data center’s operations and poor must move to a standardized set of governance in managing those limited platform products that can costs. The mechanisms by which be strictly managed and maintained, costs are allocated become overly easily compared with the offerings of complex, thanks in part to poor competitors, and straightforward to organizational alignment. Here again, cost out. the solution lies in introducing a cost- reporting mechanism that is simple, In the area where service and transparent, and based on total cost production issues merge, the problem of ownership, and in realigning is similar. Many data centers struggle the organization into “production to maintain a clear, logical connection towers” that can help organize the between how services are produced process of cost reporting. Booz Company 15
  • 18. The capacity-on-demand model customer’s needs, and based more on is clearly the future of data center computing capacity and performance operations (see Exhibit 8). Customers than on specific hardware and no longer want to pay for capacity software configurations. That they aren’t always using, and they means developing efficient new don’t much care anymore about the ways to deploy capacity and shut specifics of the hardware and software it down when not needed, to better being employed. In order to stay balance total capacity usage, and competitive, providers must move to standardize both hardware and quickly to offer data center services software platforms so they can scale that are scalable depending on the up capacity quickly. In Summary These six areas in which data center operations can be enhanced offer data centers the potential for major improvements in their performance, Exhibit 8 and significant benefits in the form The Continued Move toward Capacity-on-Demand Models Will Force of reduced operating costs. Both Data Centers to Rationalize Platforms and Services Offerings corporate data centers and centers providing computing services to Data Center Service Model Trends others should consider some or all of the improvements suggested if they wish to maintain their competitive position. The data center is rapidly Classical Outsourcing moving toward a new model in which what matters is delivering as much computing capacity as customers Spend Managed Services need, when they need it. Will you be ready to give it to them? Computing Utility 0 2005 2020 Servers Toward variable commercial delivery Services • Platform specific • Platform independent • ased on individual system B • ased on computing capacity B configurations customized and performance for each customer • calable depending on needs S Source: Booz Company analysis 16 Booz Company
  • 19. About the Authors Stefan Stroh is a partner with Dr. Florian Gröne is Booz  Company in Frankfurt. a senior associate with He leads the global transporta- Booz Company in Berlin. tion technology practice and He supports telecommunica- works for leading players in the tions companies and ICT international railway, logistics, Service Providers in develop- aviation, travel, high tech, and ing their market positioning consumer products sectors. strategies and improving IT   operations efficiency. He also Dr. Germar Schröder is a works on CRM strategy and principal with Booz Company architecture across industries. in Frankfurt. He focuses on IT strategy, large-scale transfor- mation programs, and finance IT, primarily for the telecom- munications industry. He also supports IT service providers in business model develop- ment, strategy, and operational efficiency. Booz Company 17
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