Managing nextgeneration IT infrastructure
The days of building to order are over The time is ripe for an industrial revolution
James M Kaplan Markus Löffler and Roger P Roberts
The McKinsey Quarterly Web exclusive February 2005
In recent years companies have worked hard to reduce the cost of the IT infrastructure—the data centers networks databases and software tools that support businesses These efforts to consolidate standardize and streamline assets technologies and processes have delivered major savings Yet even the most effective costcutting program eventually hits a wall the complexity of the infrastructure itself
The root cause of this complexity is the buildtoorder mindset traditional in most IT organizations The typical infrastructure may seem to be high tech but actually resembles an oldfashioned automobile handmade by an expert craftsperson and customized to the specifications of an individual customer Today an application developer typically specifies the exact server configuration for each application and the infrastructure group fulfills that request The result thousands of application silos each with its own customconfigured hardware and a jumble of often incompatible assets that greatly limit a company＇s flexibility and time to market Since each server may be configured to meet an application＇s peak demand which is rarely attained vast amounts of expensive capacity sit unused across the infrastructure at any given time Moreover applications are tightly linked to individual servers and storage devices so the excess capacity can＇t be shared
Now however technological advances—combined with new skills and management practices—allow companies to shed this buildtoorder approach A decade into the challenging transition to distributed computing infrastructure groups are managing clientserver and Webcentered architectures with growing authority Companies are adopting standardized application platforms and development languages And today＇s highperformance processors storage units and networks ensure that infrastructure elements rarely need handtuning to meet the requirements of applications
In response to these changes some leading companies are beginning to adopt an entirely new model of infrastructure management—more offtheshelf than buildtoorder Instead of specifying the hardware and the configuration needed for a business application （I need this particular maker model and configuration for my networkattached storage box ） developers specify a service requirement （I need storage with highspeed scalability ） rather than building systems to order infrastructure groups create portfolios of productized reusable services Streamlined automated processes and technologies create a factory that delivers these products in optimal fashion （Exhibit 1） As product orders roll in a factory manager monitors the infrastructure for capacityplanning and sourcing purposes
With this model filling an IT requirement is rather like shopping by catalog A developer who needs a storage product for instance chooses from a portfolio of options each described by service level （such as speed capacity or availability） and priced according to the infrastructure assets consumed （say 7 a month for a gigabyte of managed storage） The system＇s transparency helps business users understand how demand drives the consumption and cost of resources
Companies that make the transition gain big business benefits By reducing complexity eliminating redundant activity and boosting the utilization of assets they can make their infrastructure 20 to 30 percent more productive—on top of the benefit from previous efficiency efforts—thereby providing far greater output and flexibility Even larger savings can be achieved by using lowcost commodity assets when possible Developers no longer must specify an application＇s technical underpinnings and can therefore focus on work that delivers greater business value the new model improves times to market for new applications
Nevertheless making this transition calls for major organizational changes Application developers must become adept at forecasting and managing demand so that in turn infrastructure groups can manage capacity more tightly Infrastructure groups must develop new capabilities in product management and pricing as well as introduce new technologies such as grid computing and virtualization1 As for CIOs they must put in place a new model of governance to manage the new infrastructure organization
The road forward
Deutsche Telekom knows firsthand the challenges involved over 18 months hoping to balance IT supply and demand it implemented this new infrastructuremanagement model at two divisions （see sidebar Nextgeneration infrastructure at Deutsche Telekom） In the old days the company＇s IT infrastructure like most was a landscape of application silos Today accurate forecasts of user demand are critical so newly minted product managers must take a horizontal view across applications to assess the total needs of the business and create the right products They must then work closely with infrastructure teams to align supply—infrastructure assets such as hardware software and storage—with demand
In the past employees of the infrastructure function were order takers Now they can be more entrepreneurial choosing the mix of hardware software and technology that optimizes the infrastructure To keep costs low they can phase in grids of lowend servers cheaper storage disks and other commodity resources Factory managers now focus on automating and industrializing production Although Deutsche Telekom＇s two divisions didn＇t radically change their organizational or reporting structures IT governance now seeks to ensure that product and service levels are consistent across business units in order to minimize costs and to improve the infrastructure＇s overall performance
What we＇ve seen at Deutsche Telekom and other companies suggests that creating a nextgeneration infrastructure involves action on three fronts segmenting user demand developing productlike services across business units and creating shared factories to streamline the delivery of IT
Segmenting user demand
Large IT organizations support thousands of applications hundreds of physical sites and tens of thousands of end users All three of these elements are critical drivers of infrastructure demand applications require servers and storage sites need network connectivity and users want access to desktops laptops PDAs and so forth To standardize these segments an IT organization must first develop a deep understanding of the shape of current demand for infrastructure services and how that demand will most likely evolve Then it needs to categorize demand into segments （such as uptime throughput and scalability） that are meaningful to business users
When grouped in this way most applications fall into a relatively small number of clusters A pharmaceutical manufacturer for instance found that most of a business unit＇s existing and planned applications fell into one of five categories including sales force applications that need aroundtheclock support and offline availability and enterprise applications that must scale up to thousands of users and handle batch transactions efficiently
In contrast a typical wholesale bank＇s application portfolio has more segments with a wider range of needs Some applications—such as derivatives pricing and riskmanagement tools—must execute computationintensive analyses in minutes rather than hours Fundstransfer applications allow for little or no downtime programtrading applications must execute transactions in milliseconds or risk compromising trading strategies
Although simple by comparison the needs of physical sites and user groups can be categorized in a similar way One marketingservices company that evaluated its network architecture for example segmented its sites into offices with more than 100 seats those with 25 to 100 and remote branches with fewer than 25 A cable systems operator divided its users into senior executives with conciergesupport needs professional employees callcenter agents and field technicians
Most companies find that defining the specific infrastructure needs of applications sites and users is the key challenge of segmenting demand Major issues include the time and frequency of need the number of users the amount of downtime that is acceptable and the importance of speed scalability and mobility
Standardizing products
Once the infrastructure group has assessed current and future demand it can develop a set of productlike reusable services for three segments management and storage products for applications access products such as desktops and laptops for end users and networkaccess products for various sites For each of these three product lines the group must then make a series of decisions at both the portfolio and the product level
At the portfolio level it has to make decisions about the scope depth and breadth of product offerings with an eye toward optimizing resources and minimizing costs Exceptions must be detailed up front The group may decide for example against offering products to support applications with stringent requirements such as verylowlatency processing these applications may be better built by hand and from the ground up Other applications such as legacy ones may be better left outside the new model if they＇re running well and can＇t easily be ported to new hardware The group should also decide how to introduce new technologies and to migrate existing applications that are easier to move
At the product level the group must define the features service levels and price of each product For each application support product to give one example it will be necessary to specify a programming language an acceptable level of downtime and a price for infrastructure usage That price in turn depends on how the group decides to charge for computing storage processor and network usage The group has to consider whether its pricing model should offer discounts for accurate demand forecasts or drive users to specific products through strategic pricing
Looking forward companies may find that welldefined products and product portfolios are the single most important determinant of the infrastructure function＇s success Developers and users may rebel if a portfolio offers too few choices for instance but a portfolio with too many won＇t reap the benefits of scale and reuse Good initial research into user needs is critical as it is for any consumer products company
The supply side Creating shared factories
The traditional buildtoorder model limits the infrastructure function＇s ability to optimize service delivery Delivery has three components operational processes for deploying running and supporting applications and technologies software tools for automating these operational processes and facilities for housing people and assets
At most companies variations in architecture and technology make it impossible to use repeatable processes applied across systems This problem hinders efficiency and automation and restricts the amount of work that can be performed remotely in lowcost locations thus limiting the scope for additional cost savings
In the nextgeneration infrastructure model however application developers specify a service need but have no input into the underlying technologies or processes chosen to meet it The application may for instance require highspeed networked storage but the developer neither knows nor cares which vendor provides the storage media This concept isn＇t new—consumers who have call waiting on their home telephone lines don＇t know whether the local carrier has a Lucent Technology or Nortel Networks switch at its closest central office
Because the infrastructure function can now choose which software technologies hardware and processes to use it can rethink and redesign its delivery model for optimal efficiency Using standardized and documented processes it can start developing an integrated set of software tools to automate its operations Next by leveraging its processes and automation tools it can develop an integrated location strategy that minimizes the need for data centers so that more functions can operate remotely in lowcost—even offshore—locations
Building a new organization
What changes must CIOs make to capitalize on these new opportunities The nextgeneration infrastructure has major implications for the roles responsibilities and governance of the infrastructure organization
The most critical new roles are those of the product manager who defines products and product portfolios and of the factory architect who designs the shared processes to deploy operate and support them （Exhibit 2） Product managers must focus on service offerings and be accountable for reaching productivity targets Their other key responsibilities include building relationships with business users and application developers understanding and segmenting demand defining product portfolios and persuading developers and business users to accept their decisions
Factory architects are in equal parts technology strategists and industrial engineers codifying the architectures processes and tools that support the product portfolio Their other key responsibilities include confirming that product commitments can be met choosing technologies defining processes developing processautomation plans and selecting tools Although this was an established role at Deutsche Telekom factory architects are now more focused on automating and industrializing production
Organizational structures must change as well Specialized silos with administrators focused on specific technology platforms—mainframes midrange computing distributed servers storage and voice and data networks—should give way to multidisciplinary teams that manage the performance of the infrastructure and the delivery of services
CIOs must also put in place novel governance mechanisms to deal with capacity planning the launch of new services and investmentfinancing issues Although Deutsche Telekom opted to keep its existing governance structure many companies create an enterpriselevel infrastructure council to ensure the consistency of products and service levels across business units Such consistency is critical for keeping costs low and optimizing performance
To make sure the new infrastructure is running efficiently and to sustain performance improvements IT leaders should focus on five key areas
1Demand forecasting and capacity planning A key goal of the new infrastructure model is to match supply and demand more closely thereby minimizing the waste of resources To achieve this objective the IT group must work closely with business units in order to forecast demand and thus improve capacity planning Forecasts are more accurate when companies follow Deutsche Telekom＇s example and aggregate demand across products instead of applications
2Funding and budgeting Product demand drives budgets Since the new model uses real demand forecasts budgeting is easier Moreover with pricing transparency comes knowledge Business units will now know what their IT choices are going to cost the infrastructure group will understand the budget implications of user requests and be able to create a more accurate capital plan
3Productportfolio management Companies can expect to spend six months developing newproduct portfolios The infrastructure team should reexamine them two or three times during the first year to ensure that they are appropriate given projected workloads and emerging enduser needs Thereafter a yearly review usually suffices Teams should monitor all phases of the product life cycle from planning and sourcing new products to retiring old services and redeploying resources
4Release management To ensure that new technologies or upgrades are integrated effectively and that change causes less upheaval and lost productivity leading companies carefully manage the release of both infrastructure products and applications in parallel Moreover to plan ahead application developers need to know about any impending change in the infrastructure catalog
5Supply and vendor management IT leaders must ensure that computing resources are available to meet the contracted service levels of product portfolios Infrastructure managers should revisit their sourcing strategy annually seeking opportunities to lower costs and improve productivity
Even with the restructuring and the new roles and processes in place changing the buildtoorder mindset and culture may remain the biggest challenge of all Deutsche Telekom adjusted its incentives hired new people developed training workshops and appointed change agents to spread the word and build enthusiasm These organizational and cultural changes are central to realizing the potential of the nextgeneration infrastructure model Investing the time and attention needed to get the right results is just as critical as refreshing the technical architecture
Reference
Nextgeneration infrastructure at Deutsche Telekom
Otto Zeppenfeld＇s cheerful demeanor may be surprising given his job As head of IT operations for TCom Deutsche Telekom＇s fixednetwork division he＇s responsible for ensuring that all applications run smoothly even during times of peak demand
TCom which outsources almost all of its IT operations to its sister company TSystems provides voice and data services to about 40 million consumers and very small businesses It generates higher revenues than any other division of Deutsche Telekom The company＇s IT infrastructure is massive 13 petabytes of storage capacity 25000 MIPS of computing power approximately 3000 servers and 100000 workstations and hundreds of applications
Many of TCom＇s IT infrastructure assets like those of most companies once sat idle waiting for peak loads To address the problem TCom and TSystems began implementing the key elements of a nextgeneration infrastructure model productlike services transparent pricing strict demand forecasting and capacity management
Managing supply and demand across applications
For each infrastructure product category—storage hosting and so forth—TCom appointed a product manager to assess demand across all applications in that category and to work with TSystems on defining the right products and service levels and negotiating prices TCom＇s process for forecasting demand aggregates it across all categories and then forwards that information to TSystems for use in capacity planning and management
TSystems supplies TCom＇s products and manages the underlying hardware software and networks Like TCom it takes a bird＇seye view looking across applications at total storage and computing needs The two units now work in tandem to balance supply and demand—a radical departure from the traditional applicationsilo mentality
The success of this model depends on two key factors TCom must learn to predict how much computing power it will need and when TSystems must learn how to use excess capacity in other areas TSystems must take on a lot more responsibility notes Michael Auerbach the TSystems manager for all TCom IT operations At the end of the day it＇s our job to leverage the idle capacity elsewhere
Paying only for usage
Since the new model requires TSystems—rather than TCom—to pick up the tab for unused capacity TSystems is under pressure to think and operate in new ways Formerly when Zeppenfeld needed a new business application for TCom TSystems＇ Auerbach supplied the appropriate hardware software and services and then tallied up the cost It was usually the subject of intense debate because the value of complex computer systems is hard to determine and so is the cost of the associated installation operations and maintenance
Now Zeppenfeld pays only for the computing resources he uses every month the hardware software and storage needed to power TCom＇s applications are Auerbach＇s problem This model however gives TSystems the freedom to make decisions that optimize the infrastructure as a whole rather than specific applications Wherever possible TSystems uses cheaper commodity resources such as grids of lowend servers storage disks and Intel processors instead of Unix systems In essence it now acts more as an entrepreneur than as an order taker
Transparency of costs is a major benefit of this model TCom merely reads off the bytes it consumed and pays a predetermined price that factors in TSystems＇ engineering support TCom＇s invoice includes a handful of service categories （such as storage backup computing the operation of applications and the help desk） and quantifies usage in detail Each service unit has a fixed price so TCom knows exactly what it will pay for a gigabyte of storage an hour of telephone support or a backup copy of a database Moreover these services can be benchmarked individually so TCom has the ability to check that prices are reasonable Zeppenfeld and Auerbach agree that transparency helps create an atmosphere of trust
Gaining greater flexibility
TCom also gains flexibility its contract lets it increase or decrease its computing capacity if it gives three months＇ notice Drastic acrosstheboard changes in usage are unlikely for most companies but this added flexibility in individual areas is still a welcome benefit Marketing for instance has fluctuating needs Take an email campaign generating several million responses Previously a sixmonth lead time was needed to purchase new hardware and software The new model forces marketing to produce more accurate forecasts but cuts the lead time in half Now TCom lets TSystems know about the marketing group＇s plans and requirements three months before such a campaign the earlier it alerts TSystems the lower the added capacity costs The department managers who with their teams plan in advance and make the most accurate forecasts can increase their savings These incentives are designed to improve the forecasting of TCom and the capacity planning of TSystems
Making it happen
A nextgeneration infrastructure model poses practical challenges The concept of IT bills based on actual consumption for instance is still very much in the development phase Moreover some companies get stuck migrating legacy applications to the new systems Depreciation schedules may mean that purchase and leasing agreements for old ones still have a long time to run At most large companies IT has hundreds of individual contracts expiring at different times so it is hard to make a clean break
TCom and TSystems found that an allornothing approach was unnecessary Making better use of existing resources and phasing in new technology allowed them to use savings generated by the new model to offset the cost of migrating applications The two units also started small focusing solely on storage services for a few key applications Only later did they expand the model to computing services for mainframe applications Today 80 percent of the relevant IT infrastructure has been converted
TCom and TSystems are very satisfied with the early results of the new infrastructure model which has delivered major cost savings improved the use of assets provided for greater flexibility and made the system far less complex to manage
About the Authors
James Kaplan is an associate principal in McKinsey＇s global IT practice and specializes in IT infrastructure He is based in New York Markus Löffler is an associate principal in McKinsey＇s global IT practice and specializes in IT infrastructure and architecture He is based in Stuttgart Roger Roberts leads McKinsey＇s IT architecture practice in North America and specializes in the hightech and industrial sectors He is based in Silicon Valley
The authors wish to thank Andrew Appel for his contributions to this article
This article was first published in the Winter 2004 issue of McKinsey on IT
Notes
1 Grid computing breaks down an application＇s processing requirements into pieces for distribution among a number of servers Server virtualization is a technology that allows a single centralprocessing unit to run a number of different operating systems—Windows NT Windows XP and Linux for instance—at the same time
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The days of building to order are over The time is ripe for an industrial revolution
James M Kaplan Markus Löffler and Roger P Roberts
The McKinsey Quarterly Web exclusive February 2005
In recent years companies have worked hard to reduce the cost of the IT infrastructure—the data centers networks databases and software tools that support businesses These efforts to consolidate standardize and streamline assets technologies and processes have delivered major savings Yet even the most effective costcutting program eventually hits a wall the complexity of the infrastructure itself
The root cause of this complexity is the buildtoorder mindset traditional in most IT organizations The typical infrastructure may seem to be high tech but actually resembles an oldfashioned automobile handmade by an expert craftsperson and customized to the specifications of an individual customer Today an application developer typically specifies the exact server configuration for each application and the infrastructure group fulfills that request The result thousands of application silos each with its own customconfigured hardware and a jumble of often incompatible assets that greatly limit a company＇s flexibility and time to market Since each server may be configured to meet an application＇s peak demand which is rarely attained vast amounts of expensive capacity sit unused across the infrastructure at any given time Moreover applications are tightly linked to individual servers and storage devices so the excess capacity can＇t be shared
Now however technological advances—combined with new skills and management practices—allow companies to shed this buildtoorder approach A decade into the challenging transition to distributed computing infrastructure groups are managing clientserver and Webcentered architectures with growing authority Companies are adopting standardized application platforms and development languages And today＇s highperformance processors storage units and networks ensure that infrastructure elements rarely need handtuning to meet the requirements of applications
In response to these changes some leading companies are beginning to adopt an entirely new model of infrastructure management—more offtheshelf than buildtoorder Instead of specifying the hardware and the configuration needed for a business application （I need this particular maker model and configuration for my networkattached storage box ） developers specify a service requirement （I need storage with highspeed scalability ） rather than building systems to order infrastructure groups create portfolios of productized reusable services Streamlined automated processes and technologies create a factory that delivers these products in optimal fashion （Exhibit 1） As product orders roll in a factory manager monitors the infrastructure for capacityplanning and sourcing purposes
With this model filling an IT requirement is rather like shopping by catalog A developer who needs a storage product for instance chooses from a portfolio of options each described by service level （such as speed capacity or availability） and priced according to the infrastructure assets consumed （say 7 a month for a gigabyte of managed storage） The system＇s transparency helps business users understand how demand drives the consumption and cost of resources
Companies that make the transition gain big business benefits By reducing complexity eliminating redundant activity and boosting the utilization of assets they can make their infrastructure 20 to 30 percent more productive—on top of the benefit from previous efficiency efforts—thereby providing far greater output and flexibility Even larger savings can be achieved by using lowcost commodity assets when possible Developers no longer must specify an application＇s technical underpinnings and can therefore focus on work that delivers greater business value the new model improves times to market for new applications
Nevertheless making this transition calls for major organizational changes Application developers must become adept at forecasting and managing demand so that in turn infrastructure groups can manage capacity more tightly Infrastructure groups must develop new capabilities in product management and pricing as well as introduce new technologies such as grid computing and virtualization1 As for CIOs they must put in place a new model of governance to manage the new infrastructure organization
The road forward
Deutsche Telekom knows firsthand the challenges involved over 18 months hoping to balance IT supply and demand it implemented this new infrastructuremanagement model at two divisions （see sidebar Nextgeneration infrastructure at Deutsche Telekom） In the old days the company＇s IT infrastructure like most was a landscape of application silos Today accurate forecasts of user demand are critical so newly minted product managers must take a horizontal view across applications to assess the total needs of the business and create the right products They must then work closely with infrastructure teams to align supply—infrastructure assets such as hardware software and storage—with demand
In the past employees of the infrastructure function were order takers Now they can be more entrepreneurial choosing the mix of hardware software and technology that optimizes the infrastructure To keep costs low they can phase in grids of lowend servers cheaper storage disks and other commodity resources Factory managers now focus on automating and industrializing production Although Deutsche Telekom＇s two divisions didn＇t radically change their organizational or reporting structures IT governance now seeks to ensure that product and service levels are consistent across business units in order to minimize costs and to improve the infrastructure＇s overall performance
What we＇ve seen at Deutsche Telekom and other companies suggests that creating a nextgeneration infrastructure involves action on three fronts segmenting user demand developing productlike services across business units and creating shared factories to streamline the delivery of IT
Segmenting user demand
Large IT organizations support thousands of applications hundreds of physical sites and tens of thousands of end users All three of these elements are critical drivers of infrastructure demand applications require servers and storage sites need network connectivity and users want access to desktops laptops PDAs and so forth To standardize these segments an IT organization must first develop a deep understanding of the shape of current demand for infrastructure services and how that demand will most likely evolve Then it needs to categorize demand into segments （such as uptime throughput and scalability） that are meaningful to business users
When grouped in this way most applications fall into a relatively small number of clusters A pharmaceutical manufacturer for instance found that most of a business unit＇s existing and planned applications fell into one of five categories including sales force applications that need aroundtheclock support and offline availability and enterprise applications that must scale up to thousands of users and handle batch transactions efficiently
In contrast a typical wholesale bank＇s application portfolio has more segments with a wider range of needs Some applications—such as derivatives pricing and riskmanagement tools—must execute computationintensive analyses in minutes rather than hours Fundstransfer applications allow for little or no downtime programtrading applications must execute transactions in milliseconds or risk compromising trading strategies
Although simple by comparison the needs of physical sites and user groups can be categorized in a similar way One marketingservices company that evaluated its network architecture for example segmented its sites into offices with more than 100 seats those with 25 to 100 and remote branches with fewer than 25 A cable systems operator divided its users into senior executives with conciergesupport needs professional employees callcenter agents and field technicians
Most companies find that defining the specific infrastructure needs of applications sites and users is the key challenge of segmenting demand Major issues include the time and frequency of need the number of users the amount of downtime that is acceptable and the importance of speed scalability and mobility
Standardizing products
Once the infrastructure group has assessed current and future demand it can develop a set of productlike reusable services for three segments management and storage products for applications access products such as desktops and laptops for end users and networkaccess products for various sites For each of these three product lines the group must then make a series of decisions at both the portfolio and the product level
At the portfolio level it has to make decisions about the scope depth and breadth of product offerings with an eye toward optimizing resources and minimizing costs Exceptions must be detailed up front The group may decide for example against offering products to support applications with stringent requirements such as verylowlatency processing these applications may be better built by hand and from the ground up Other applications such as legacy ones may be better left outside the new model if they＇re running well and can＇t easily be ported to new hardware The group should also decide how to introduce new technologies and to migrate existing applications that are easier to move
At the product level the group must define the features service levels and price of each product For each application support product to give one example it will be necessary to specify a programming language an acceptable level of downtime and a price for infrastructure usage That price in turn depends on how the group decides to charge for computing storage processor and network usage The group has to consider whether its pricing model should offer discounts for accurate demand forecasts or drive users to specific products through strategic pricing
Looking forward companies may find that welldefined products and product portfolios are the single most important determinant of the infrastructure function＇s success Developers and users may rebel if a portfolio offers too few choices for instance but a portfolio with too many won＇t reap the benefits of scale and reuse Good initial research into user needs is critical as it is for any consumer products company
The supply side Creating shared factories
The traditional buildtoorder model limits the infrastructure function＇s ability to optimize service delivery Delivery has three components operational processes for deploying running and supporting applications and technologies software tools for automating these operational processes and facilities for housing people and assets
At most companies variations in architecture and technology make it impossible to use repeatable processes applied across systems This problem hinders efficiency and automation and restricts the amount of work that can be performed remotely in lowcost locations thus limiting the scope for additional cost savings
In the nextgeneration infrastructure model however application developers specify a service need but have no input into the underlying technologies or processes chosen to meet it The application may for instance require highspeed networked storage but the developer neither knows nor cares which vendor provides the storage media This concept isn＇t new—consumers who have call waiting on their home telephone lines don＇t know whether the local carrier has a Lucent Technology or Nortel Networks switch at its closest central office
Because the infrastructure function can now choose which software technologies hardware and processes to use it can rethink and redesign its delivery model for optimal efficiency Using standardized and documented processes it can start developing an integrated set of software tools to automate its operations Next by leveraging its processes and automation tools it can develop an integrated location strategy that minimizes the need for data centers so that more functions can operate remotely in lowcost—even offshore—locations
Building a new organization
What changes must CIOs make to capitalize on these new opportunities The nextgeneration infrastructure has major implications for the roles responsibilities and governance of the infrastructure organization
The most critical new roles are those of the product manager who defines products and product portfolios and of the factory architect who designs the shared processes to deploy operate and support them （Exhibit 2） Product managers must focus on service offerings and be accountable for reaching productivity targets Their other key responsibilities include building relationships with business users and application developers understanding and segmenting demand defining product portfolios and persuading developers and business users to accept their decisions
Factory architects are in equal parts technology strategists and industrial engineers codifying the architectures processes and tools that support the product portfolio Their other key responsibilities include confirming that product commitments can be met choosing technologies defining processes developing processautomation plans and selecting tools Although this was an established role at Deutsche Telekom factory architects are now more focused on automating and industrializing production
Organizational structures must change as well Specialized silos with administrators focused on specific technology platforms—mainframes midrange computing distributed servers storage and voice and data networks—should give way to multidisciplinary teams that manage the performance of the infrastructure and the delivery of services
CIOs must also put in place novel governance mechanisms to deal with capacity planning the launch of new services and investmentfinancing issues Although Deutsche Telekom opted to keep its existing governance structure many companies create an enterpriselevel infrastructure council to ensure the consistency of products and service levels across business units Such consistency is critical for keeping costs low and optimizing performance
To make sure the new infrastructure is running efficiently and to sustain performance improvements IT leaders should focus on five key areas
1Demand forecasting and capacity planning A key goal of the new infrastructure model is to match supply and demand more closely thereby minimizing the waste of resources To achieve this objective the IT group must work closely with business units in order to forecast demand and thus improve capacity planning Forecasts are more accurate when companies follow Deutsche Telekom＇s example and aggregate demand across products instead of applications
2Funding and budgeting Product demand drives budgets Since the new model uses real demand forecasts budgeting is easier Moreover with pricing transparency comes knowledge Business units will now know what their IT choices are going to cost the infrastructure group will understand the budget implications of user requests and be able to create a more accurate capital plan
3Productportfolio management Companies can expect to spend six months developing newproduct portfolios The infrastructure team should reexamine them two or three times during the first year to ensure that they are appropriate given projected workloads and emerging enduser needs Thereafter a yearly review usually suffices Teams should monitor all phases of the product life cycle from planning and sourcing new products to retiring old services and redeploying resources
4Release management To ensure that new technologies or upgrades are integrated effectively and that change causes less upheaval and lost productivity leading companies carefully manage the release of both infrastructure products and applications in parallel Moreover to plan ahead application developers need to know about any impending change in the infrastructure catalog
5Supply and vendor management IT leaders must ensure that computing resources are available to meet the contracted service levels of product portfolios Infrastructure managers should revisit their sourcing strategy annually seeking opportunities to lower costs and improve productivity
Even with the restructuring and the new roles and processes in place changing the buildtoorder mindset and culture may remain the biggest challenge of all Deutsche Telekom adjusted its incentives hired new people developed training workshops and appointed change agents to spread the word and build enthusiasm These organizational and cultural changes are central to realizing the potential of the nextgeneration infrastructure model Investing the time and attention needed to get the right results is just as critical as refreshing the technical architecture
Reference
Nextgeneration infrastructure at Deutsche Telekom
Otto Zeppenfeld＇s cheerful demeanor may be surprising given his job As head of IT operations for TCom Deutsche Telekom＇s fixednetwork division he＇s responsible for ensuring that all applications run smoothly even during times of peak demand
TCom which outsources almost all of its IT operations to its sister company TSystems provides voice and data services to about 40 million consumers and very small businesses It generates higher revenues than any other division of Deutsche Telekom The company＇s IT infrastructure is massive 13 petabytes of storage capacity 25000 MIPS of computing power approximately 3000 servers and 100000 workstations and hundreds of applications
Many of TCom＇s IT infrastructure assets like those of most companies once sat idle waiting for peak loads To address the problem TCom and TSystems began implementing the key elements of a nextgeneration infrastructure model productlike services transparent pricing strict demand forecasting and capacity management
Managing supply and demand across applications
For each infrastructure product category—storage hosting and so forth—TCom appointed a product manager to assess demand across all applications in that category and to work with TSystems on defining the right products and service levels and negotiating prices TCom＇s process for forecasting demand aggregates it across all categories and then forwards that information to TSystems for use in capacity planning and management
TSystems supplies TCom＇s products and manages the underlying hardware software and networks Like TCom it takes a bird＇seye view looking across applications at total storage and computing needs The two units now work in tandem to balance supply and demand—a radical departure from the traditional applicationsilo mentality
The success of this model depends on two key factors TCom must learn to predict how much computing power it will need and when TSystems must learn how to use excess capacity in other areas TSystems must take on a lot more responsibility notes Michael Auerbach the TSystems manager for all TCom IT operations At the end of the day it＇s our job to leverage the idle capacity elsewhere
Paying only for usage
Since the new model requires TSystems—rather than TCom—to pick up the tab for unused capacity TSystems is under pressure to think and operate in new ways Formerly when Zeppenfeld needed a new business application for TCom TSystems＇ Auerbach supplied the appropriate hardware software and services and then tallied up the cost It was usually the subject of intense debate because the value of complex computer systems is hard to determine and so is the cost of the associated installation operations and maintenance
Now Zeppenfeld pays only for the computing resources he uses every month the hardware software and storage needed to power TCom＇s applications are Auerbach＇s problem This model however gives TSystems the freedom to make decisions that optimize the infrastructure as a whole rather than specific applications Wherever possible TSystems uses cheaper commodity resources such as grids of lowend servers storage disks and Intel processors instead of Unix systems In essence it now acts more as an entrepreneur than as an order taker
Transparency of costs is a major benefit of this model TCom merely reads off the bytes it consumed and pays a predetermined price that factors in TSystems＇ engineering support TCom＇s invoice includes a handful of service categories （such as storage backup computing the operation of applications and the help desk） and quantifies usage in detail Each service unit has a fixed price so TCom knows exactly what it will pay for a gigabyte of storage an hour of telephone support or a backup copy of a database Moreover these services can be benchmarked individually so TCom has the ability to check that prices are reasonable Zeppenfeld and Auerbach agree that transparency helps create an atmosphere of trust
Gaining greater flexibility
TCom also gains flexibility its contract lets it increase or decrease its computing capacity if it gives three months＇ notice Drastic acrosstheboard changes in usage are unlikely for most companies but this added flexibility in individual areas is still a welcome benefit Marketing for instance has fluctuating needs Take an email campaign generating several million responses Previously a sixmonth lead time was needed to purchase new hardware and software The new model forces marketing to produce more accurate forecasts but cuts the lead time in half Now TCom lets TSystems know about the marketing group＇s plans and requirements three months before such a campaign the earlier it alerts TSystems the lower the added capacity costs The department managers who with their teams plan in advance and make the most accurate forecasts can increase their savings These incentives are designed to improve the forecasting of TCom and the capacity planning of TSystems
Making it happen
A nextgeneration infrastructure model poses practical challenges The concept of IT bills based on actual consumption for instance is still very much in the development phase Moreover some companies get stuck migrating legacy applications to the new systems Depreciation schedules may mean that purchase and leasing agreements for old ones still have a long time to run At most large companies IT has hundreds of individual contracts expiring at different times so it is hard to make a clean break
TCom and TSystems found that an allornothing approach was unnecessary Making better use of existing resources and phasing in new technology allowed them to use savings generated by the new model to offset the cost of migrating applications The two units also started small focusing solely on storage services for a few key applications Only later did they expand the model to computing services for mainframe applications Today 80 percent of the relevant IT infrastructure has been converted
TCom and TSystems are very satisfied with the early results of the new infrastructure model which has delivered major cost savings improved the use of assets provided for greater flexibility and made the system far less complex to manage
About the Authors
James Kaplan is an associate principal in McKinsey＇s global IT practice and specializes in IT infrastructure He is based in New York Markus Löffler is an associate principal in McKinsey＇s global IT practice and specializes in IT infrastructure and architecture He is based in Stuttgart Roger Roberts leads McKinsey＇s IT architecture practice in North America and specializes in the hightech and industrial sectors He is based in Silicon Valley
The authors wish to thank Andrew Appel for his contributions to this article
This article was first published in the Winter 2004 issue of McKinsey on IT
Notes
1 Grid computing breaks down an application＇s processing requirements into pieces for distribution among a number of servers Server virtualization is a technology that allows a single centralprocessing unit to run a number of different operating systems—Windows NT Windows XP and Linux for instance—at the same time
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