"The Four IT Business Management Domains"

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C H A P T E R 2 Why Does IT Behave the Way It Does? Bill Flemming

MAKING SENSE OF IT BUSINESS MANAGEMENT

With all the money spent on IT system management, with all the

products purchased to improve IT performance, and with all the con-

sulting dollars spent, why has the average IT organization progressed

only to the point where IT management proudly boasts of proactive

engagements in preventing system failures?

How Did IT Get to This Point?

In the 2007 edition of this book, SAS Institute quoted Gartner statistics

that surveyed the degree to which different industries developed in

Gartner ’ s IT Infrastructure and Operations Maturity Model. Gartner

data from 2005 showed that only nine percent of IT operations had

reached the “ Service ” level of maturity. Nine percent! Further, 51

percent wanted to be at the Service level by 2006. What were the

corresponding numbers for results released in 2008? Eight percent had

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42 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

made it to Service and twelve percent hoped to be there by 2012. 1

Granted, the Gartner IT Maturity Model changed to a more sophisti-

cated version, but with a sustained industry - wide lack of progress

toward achieving IT infrastructure and operations “ maturity, ” either

the paradigm is wrong, or IT leadership and their C - Suite peers haven ’ t

yet put all of the pieces in place to achieve the goal. This chapter

examines the key elements of IT maturity, what the industry provides

in terms of products and thought leadership, remaining gaps, and how

the best practice CIO can address these issues.

The best place to start is a neglected but essential leading indicator:

higher education for IT professionals. This fi rst became obvious after

speaking about IT opportunities with a newly minted Computer

Science graduate student. As we spoke about system and IT business

management jobs, it became clear to me that this new grad from a

high - priced school had no idea what I was talking about. This lack of

integrated IT system and business management curricula isn ’ t just

restricted to young graduates. Some of the answers to our neglected

business management education lie in how IT professionals are edu-

cated and trained.

Colleges and universities educate and train engineers within

Computer Science curriculums. Engineering expertise is required to

keep the lights on and the systems functioning, but the comprehen-

sive, strategic management of information technology is not an engi-

neering exercise, particularly the challenging business alignment

portion. Strategic IT management is a business exercise that requires

a more comprehensively educated breed of manager. When hiring IT

professionals out of college, most businesses hire Computer Science

majors, MBAs, or Computer Engineers. Those IT engineers eventually

progress into management. The curriculum for an undergraduate

Computer Science major at Carnegie Mellon appears in Exhibit 2.1 .

Where are the courses in Capacity Management? Service Level

Management? Costing? Business Alignment? Computer Science and

Computer Engineering programs train technologists but not business

managers; MBA programs produce business managers but not IT tech-

nologists. If higher education is not producing IT business managers,

then the answers have to come from elsewhere. To get to the answers

a historical perspective is necessary.

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44 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

When Mainframes Ruled

When I fi rst entered the industry in the mid - 1980s, stable, effi cient

mainframes were the predominant business computer. They were

housed in raised - fl oor, environmentally controlled, glass - walled

rooms typically called the Glass House. While machines were large,

the business computing world was small by today ’ s standards. The

programming languages — COBOL, FORTRAN, and PL/1 — were pro-

cedural and well - suited for the business applications of the era.

For the most part, business applications were devoted to payroll,

receivables, payables, general ledger, transaction management, batch

reporting, and database management. Business applications crunched

numbers quickly and accurately. The business connection was obvious.

Businesses without the applications did the number management by

hand — a pencil - and - paper bound method that was slow, expensive,

and prone to error.

While the Glass House was centrally controlled, monolithic, and

infl exible, it was stable, reliable, and almost always available. End

users at the time complained about the control and infl exibility of IT,

but that infl exibility and control safeguarded system management.

IBM ’ s Multiple Virtual Storage (MVS) operating system and Systems

Network Architecture (SNA) network environment defi ned and con-

trolled access. User transactions were entered into 3270 terminals

written for Customer Interface Control System (CICS). Users

claimed they were hard to use, and training costs were high. Virtual

Telecommunications Access Method (VTAM) controlled peripheral

access. Everyone adhered to the standards set by this MVS/SNA world.

The quickest route to vendor disgrace was to offer a product incom-

patible with Glass House standards, and when product incompatibility

brought down a production system, the vendor seldom got a second

chance. Stability and reliability were paramount values for mainframe

performance.

Before long, MVS could not supply all the necessary system man-

agement tools. 2 While MVS focused on control, other system manage-

ment vendors such as Computer Associates and Legent marketed

products for job scheduling, tape backup, report production and dis-

tribution, network management, storage management, console man-

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 45

agement, and capacity management/chargeback systems. During this

era, most businesses managed for high transaction volume during

business hours and tight batch windows in the evenings. System

managers were concerned with hardware tuning and ensuring the

availability of online environments. They were well paid and no one

in the business understood them, but MVS was the operating system

that ran the world. It was a perfect system management world, but

not a perfect end - user world.

The hermetically sealed Glass House that no one on the outside

understood was not spending time reacting to outages. MVA and SNA

were built to provide an environment that set standards, and those

standards ensured high availability. Network managers knew what

the access traffi c was going to be and where it was coming from.

Unlike today, networks were not open to the outside world. Capacity

Management concentrated on CPU utilization and storage needs in a

controlled fashion. The Glass House was charged with providing stable

environments for transactions, accounting systems, and reports. In a

sense, they were completely aligned with higher business priorities.

But all good things must come to an end. The personal computer and

UNIX made their debuts, rapidly reordering IT system management

priorities.

Desktop and Distributed Technology Explode

In the early 1990s, several technologies incubating since the 1970s

had matured and gained rapid acceptance, but each of these innova-

tive technologies depended on the other co - evolving technologies to

achieve that acceptance. For example, the Internet depended on other

enabling platforms, and the enabling technology that led the charge

and changed all the rules was the personal computer (PC) when it

debuted in the 1980s.

The PC broke rules and standards formulated for the Glass House

on a number of levels. 3 IBM made business decisions about the PC

that had the unintended consequence of changing the mainframe

system management world forever. When IBM decided to enter the

PC business they adopted a nonstandard IBM approach. To save time

getting a product to market, IBM outsourced the product components,

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46 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

including the operating system DOS to Microsoft and the CPU to Intel.

Uncharacteristically, IBM also decided to only license DOS and the

CPU chips, allowing Microsoft and Intel to sell the technology to com-

petitors in any manner they chose. Based on the business model and

early marketing, IBM probably never intended or foresaw that the

personal computer would become a personal Business computer. Early

PC marketing showed a family gathered around a DOS green screen

PC with a child at the keyboard as everyone beamed at the camera. 4

The PC was positioned as fl exible and easy to use in the home, classroom,

and offi ce. The PC was slow to gain traction until Microsoft and Intel

began to sell to other companies.

Without the restraining infl uence of the mainframe world and an

attractive platform to exploit, the time frame of 1992 to 1995 unleashed

the greatest era of technology innovation the computer industry had

ever witnessed. Windows 3.1, Offi ce, LANS Web browsers, the Internet

“ superhighway, ” ISPs, and client server computing all hit the market.

When Microsoft introduced Windows 3.1 and Intel developed more

powerful chips, PC sales gained rapid traction. That traction gener-

ated the demand for easy - to - use IT applications such as Windows.

In short - order Silicon Valley, and the industry addressed that

demand, albeit in a manner that created huge problems for IT system

management.

In April of 1992, Microsoft released Windows 3.1. It was an instant

success with three million copies sold in two months. 5 Windows 3.1

wasn ’ t just a desktop release. It went far beyond personal productivity.

Windows 3.11 for workgroups was an expansion of 3.1, which added

many network capabilities for network connectivity, peer - to - peer

support, and client/server applications. The Windows NT release soon

dominated the LAN server market.

Shortly after Windows 3.1, Offi ce 92 hit the market, which estab-

lished the PC as a platform for professionals in most businesses.

By extension, Microsoft had set new standards for Graphical User

Interface use and business application interface standards. By com-

parison, those 3270 green screen applications began to look very tired

and cumbersome.

As the PCs arrived on more and more business desktops, Bell Labs

introduced another technology that took hold in the marketplace and

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 47

became a key distributing component enabler, 6 a new operating envi-

ronment that made it easier for developers to create software, particu-

larly with non - procedural applications. UNIX was born, and it was

open sourced — a new environment for small, powerful, cheaper

machines that could be easily networked. No system management,

baked in, none available.

A further technology with roots in the 1970s emerged as a key

distributed computing enabler. Ethernet won international approval

by the International Organization for Standards as the standard for

LANS in 1989. 7 This acceptance made Ethernet the leader in LAN

technology and spurred LAN growth in business offi ces connecting

WINTEL machines to client/server applications and email.

The move away from mainframes toward the world of graphical

desktops and client server applications hit critical mass. The ability to

develop multitier applications, such as clients using Windows, data-

base servers, and business processing across LANs on cheaper, faster

UNIX servers exploded. Applications moved off the mainframe and

sometimes out of the IT organization altogether. Distributed comput-

ing succeeded in breaking the Glass House monopoly of a carefully

crafted environment that kept computing stable and available.

In 1993, Marc Andreessen introduced Mosaic, an Internet browser

developed at the University of Illinois, and everyone with a computer

had access to the World Wide Web. 8 Mr. Andreessen left to found

Netscape where he found stiff competition from Microsoft and Internet

Explorer. Along with browsers, search engines entered the market-

place in 1994 with WEBCRAWLER, Lycos, and a pair of 1995 births,

YAHOO and Altavista. The twin technologies, browsers and search

engines helped fuel the Internet explosion and later ecommerce. The

growth in the Internet alone was more than enough for system man-

agers to handle. Exhibit 2.2 shows the growth in Internet host sites

from October 1991 to July 2006, where 439,286,364 sites existed.

The result for IT system management was a huge vacuum, and

vendors scrambled to fi ll the void. Applications and the infrastructure

that housed them were scattered everywhere outside the Glass House.

Stability, availability, and response time became IT organization head-

aches, and fi refi ghting was the new normal. Gaining visibility into the

“ health ” of the distributed environment was not yet possible. Until

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48 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

1991, Legent, a leading system management vendor only offered

products for the mainframe, when the company acquired Spectrum

for its XCOM 6.2 product to connect disparate systems through

to mainframes to share data. From there, Legent and Computer

Associates, another leading systems management vendor, spent mil-

lions and millions of dollars on R & D to bring the disciplines of the

Glass House out on to the wide open spaces of the new Wild West of

distributed computing. “ Simply put, we ’ re accelerating CA ’ s move into

client/server, ” said Charles Wang, Computer Associate ’ s CEO of the

acquisition. 9

The lack of stability in the distributed world was aggravated by

another problem. Software vendors rushed products to market with

both infrastructure incompatibility problems and a general lack of

testing. Both situations lead to further system instability because

immature products created outages that sometimes brought distrib-

uted production systems down. Without adequate tools to manage

those kinds of problems, IT lapsed from the stability and predictability

of the Glass House to the chaotic problems still evident in some enter-

prises today.

One of the fi rst products that addressed the problem of distributed

visibility to enter the system management marketplace and gain trac-

tion was brought by a UNIX hardware vendor, Hewlett Packard (HP).

HP used agents to monitor the health and availability of a device. The

simplest implementation was to send an agent alert to a console when

the device was unavailable. As the product and monitoring industry

Exhibit 2.2: Growth of the Web

Source: Robert H. Zakon, “ Hobbes ’ Internet Timeline v8.2, ” January 1, 2010, www .zakon.org/robert/internet/timeline/ .

Year Sites 617,00010/91

10/93 2,056,000 10/94 3,864,000

1/96 9,472,000 1/97 16,146,000 1/98 29,670,000 7/06 439,286,364

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 49

grew, the agents read and collected a variety of metrics from system

logs. Agent technology reporting alerts back to a central console

become the standard for distributed operations management. The

system management disciplines of backup, report management, job

control, and capacity management grew more slowly because the IT

organization had to fi rst solve the acute pain of system instability — still

a problem today.

Y 2 K and the Growth of the Enterprise Applications

As the 1990s ended, two new, self - feeding phenomena entered the

fray. Programs written (either hardware or business applications) with

only two digits representing the year fi eld would potentially be ren-

dered inoperative on January 1, 2000. Software would not be able to

tell whether the year was 1900 or 2000, and some predicted cata-

strophic consequences if the programs and hardware weren ’ t retrofi t-

ted or replaced with new Y2K compliant products.

Faced with enormous retrofi tting costs with little upside in terms

of additional functionality, many companies elected to buy new

enterprise applications and new hardware. The new enterprise

applications pushed IT organizations deeper into the management of

business processes because the enterprise applications leveraged the

new distributive technology rather than running on mainframes.

Related business processes included e - commerce, enterprise resource

planning, supply chain management, and customer relationship man-

agement with applications were very different from traditional

accounting - oriented mainframe applications.

The physical implementation of the enterprise applications also

brought a technology complexity that most IT organizations lacked

the system management experience acumen to handle. Many of the

“ clients ” were browser - based utilizing Intranet and Internet net-

works. 10 The applications crossed enterprise IT boundaries in the sense

that business processes could be open to other businesses and consum-

ers. Servers part of more complex architecture were placed into pools

to provide specialized functions rather than simply working as a part

of multi - tier application architecture. Data was far more complex, and

there was more of it every day.

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50 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Applications of innovative technologies promoted new uses,

more complexity, more demands for service, and wider distribution

as employees worked both inside the enterprise and at home.

Enterprises now primarily promote ongoing growth and innovation,

fi nding more and more intensive uses for IT - enabled technology,

along with the requisite demands for less cost and more business

alignment. And system management? Best practice CIOs work to lead

their IT organizations out of fi re - fi ghting mode toward practices that

increasingly enable enterprise strategies as educated, informed busi-

ness partners. Enterprise IT organizations face competitive system

management outsourcing pressures from managed service providers.

Wherever system management responsibilities reside, the best practice

CIO must remain current with new system management processes

and tools entering the arena. The system management industry still

lacks a coherent view of what is needed to address the demands placed

on the CIO and IT organization. The following sections build just such

a perspective for systems management.

The System Management Challenge

After the spine - tingling technology transformation of the 1990s and

the enterprise - wide adoption of ever more complex applications, it is

fair to say that the business demand for new IT enablement continues

to intensify. It is also fair to say that system management as a profes-

sion still lags behind the technology transformation of the 1990s and

business demands for application of the technology. It is interesting

to note that the elements of technology transformation in the early

1990s took place approximately twenty years from their inception in

the 1970s. While the PC would have undoubtedly been a successful

product independently, other products such as UNIX, Ethernet,

Internet, browsers, Client/Server, and even proprietary software

applications would not have succeeded as spectacularly as they did

without concurrent platform development.

From the perspective of a twenty - year cycle for system manage-

ment starting from 1992, 2012 should mark the start of a system

management golden era. The industry has many perspectives to con-

sider and many products ready to mature, exploit, and integrate with

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 51

other products to initiate a new era of system management. Viewed

as an industry, IT system management is composed of the industry

analyst community, major system management/hardware vendors,

niche players, and thought leaders from IT itself.

The Industry Analysts

The industry analyst component is the vanguard of twenty - fi rst

century system management. While many fi rms work in this market

space, SAS settled on two thought leadership representatives that

have very different approaches and only join ideas at the business

alignment juncture. McKinsey concentrates on managing IT as a busi-

ness and promoting IT practices as strategic business enablers. Gartner

emphasizes IT maturity models and approaches IT business manage-

ment considerations from system management toward business align-

ment. McKinsey is steering non - IT business managers toward IT

business alignment and Gartner is steering IT engineers through the

engineering maturity processes to achieve IT business alignment.

During the Glass House era, business applications were primarily

devoted to accounting and online fi nancial transactions. The business

value was more obvious, and the technology was far narrower in

application compared to the enterprise applications in play today.

With the broader, enterprise - wide applications, the need for strategic

intent is now even more acute. McKinsey therefore emphasizes the

articulation of strategic themes. In the article, “ Innovations in IT

Management, ” McKinsey states that IT generates value on two com-

plementary levels: (1) core assets of hardware, software, and pro-

cesses, and (2) value in use. 11 “ Value in use ” refers to business

applications that are optimized to yield maximum investment value.

Optimizing investment value here means that the enterprise

establishes a value on the IT organization and its resources through a

series of metrics that determine the economic value of the IT invest-

ment to the business. While metrics are not hard and fast, important

measures determine the cost - to - revenue ratio, strategic value, and

competitive edge. McKinsey also advocates measuring operational value

by putting key performance indicators (KPIs) on the operational level

of the business, such as “ on - time delivery. ”

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52 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

In a second article, “ Managing IT in a Downturn: Beyond Cost

Cutting, ” McKinsey emphasizes delivering increased value to the busi-

ness as opposed to merely cutting cost. 12 As the IT organization and

its resources increase in value and integrate more deeply into business

processes, it becomes harder to cut costs and easier to increase value.

After IT has engaged in efforts to streamline application portfolios,

reduce infrastructure costs, and outsourcing, what remains is to create

greater business impact through better management of sales and

pricing, sourcing and production, support processes, and performance

management (PM).

McKinsey continues their strategic focus via metrics in a third

article, “ Assessing Innovation Metrics. ” 13 While most enterprises value

innovation, most don ’ t measure it. Those enterprises that actually

measure innovation generally depend on eight metrics to make their

assessment. Innovation metrics provide strategic direction for innova-

tion activities, guide allocation resources, and improve innovation

performance. Interestingly, McKinsey noted that few enterprises

tracked the relationship between innovation and shareholder value.

Companies track revenue growth, customer satisfaction, and percent-

age of sales, but less than one - third track the relationship between

innovation spending and shareholder value. Only the best companies

pursue and measure innovations as a portfolio, and track the entire

innovation process as inputs.

The Gartner Maturity Models approach to IT system management

thought leadership begins from the polar opposite of McKinsey.

Gartner maturity models aim directly at where system management

has consistently felt the most pain from the early 1990s through to

today: the inability to keep IT infrastructure up and running. Because

of infrastructure redundancy and other safeguards, entire production

systems seldom go dark. Rather than fi ght system - wide outages, the

IT organization fi ghts a continuous stream of small outages. Fighting

small or large outages is expensive, time consuming, and a drain on

services. Gartner reports that fi fty - one percent of IT budgets are spent

on system management and support of product applications. 14

The Gartner IT Infrastructure and Operations (I & O) Maturity Model

is a matrix with people, processes, technology, and business manage-

ment on the left axis, with the maturity steps called Survival, Awareness,

Committed, Proactive, Service Aligned, and Business Partnership across

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 53

the top of the matrix. Survival , of course, is absence of any formal

strategy or functions, an extremely chaotic, immature environment.

Awareness indicates a level of insight that system management improve-

ments are both possible and necessary. The IT organization is aware of

needs, has some basic tools in place, but faces a big job for system man-

agement maturity. Committed requires an investment in both tools and

processes. Real progress is made with the Proactive stage, where the IT

organization implements processes, standards, domain management,

and project management. The Service Aligned IT organization begins to

implement customer and business services and management, which is

essential to attaining a business partnership. IT organizations at the

Business Partnership stage of maturity focus on business processes, busi-

ness optimization, and business contribution metrics. Business

Partnership practices overlap with the McKinsey perspective practices.

The Business Partnership stage cannot be attained without an infra-

structure foundation that is as well managed, stable, and available as

the mainframes were in the Glass House.

How mature has the IT industry become? Exhibit 2.3 shows the

results. I & O maturity levels will differ across industries, enterprise size,

and business strategies, but the exhibit is an estimate of I & O maturity

at each level with a prediction of progress by year - end 2012. 15 Gartner

states that sustainable maturity develops over years, but CIOs and

their IT organizations face rapid return on investment (ROI) expecta-

tions of four to six months. The answers to another Gartner survey

that polled CIOs in 2006 for the reasons behind their lack of progress

are still as revealing and relevant:

� Lack of senior management support

� Lack of practical implementation guidelines

� Lack of time to develop a thoughtful approach

� Lack of hierarchical reporting structure

� Lack of effective organizational communication 16

Exhibit 2.3: IT I & O Maturity

Timeline Survival Awareness Committed Proactive Service Aligned

Business Partnership

12/2007 <2 45 30 15 8 <1 12/2012 <2 30 35 21 12 <2

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54 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

System Management Vendors

System management vendors have always been on the fault line

between industry advances that are a step or two ahead of enterprise

adoption and the fi ght to keep infrastructure up and running.

The system management tool market is large and lucrative because

the need for these products and services is obvious, the pain is

acute, and the large ROI is easy to justify. The vendors aim their

products and services at the heart of the most critical distributed

computing model problems: lack of infrastructure stability and opera-

tional fi refi ghting. With homogeneous environments that were widely

distributed and extraordinarily complex, monitoring and managing

within that model was a massive challenge. As the industry matured

beyond fi refi ghting and chaos, vendors expanded their respective

legacy products and acquired technology to round out their offer-

ings. 17 Their subsequent offerings followed the Gartner maturity

models building from infrastructure management toward business

alignment and management, as opposed to the McKinsey perspective

that linked IT practices with enterprise strategic intent.

If the history of business computing since 1992 tells us anything,

the lesson would be that the problem to be solved is bigger than

any single vendor or any single sector in the industry. The large

system management vendors bring strong solutions in certain areas

while other portions of the solutions seem to be isolated (Portfolio

Management), an afterthought (Capacity Management), or nonexis-

tent (Financial Management). The next plateau for the system man-

agement vendors coincides with the next rung on the Gartner scale,

Service Management, and is marketed to a segment of IT that is

complex and labor intensive.

Vendors have their own particular slant on service management.

Whether marketed as Service - Oriented Architecture (SOA) or Business

Service Management (BSM), the heart of the offering is a service

catalog of IT offerings. Simply put, offerings are assembled to create a

business application. The underpinning of the application is a contract

that specifi es the parameters of the offering, usually in terms of

availability/response time/throughput (A/R/T). Such contracts may

have chargeback provisions to be paid to IT and penalties paid to the

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 55

end user if IT fails to meet service levels. Vendors are expanding prod-

ucts to provide varying amounts of automated provisioning with a set

of common goals: minimize service costs, minimize developing and

building service/business processes, reuse services, and of course, keep

IT customers happy.

Niche Vendors

Niche vendors tend to be smaller startup companies plugging holes in

the system management market that the megasystem management

vendors address poorly, if at all. Service management is the core

offering of most niche vendors, along with the customer ’ s ability to

transparently calculate the cost of service. Most of these offerings also

have a dashboard of the service and fi nancial results, and many of the

niche vendors align with Information Technology Infrastructure

Library (ITIL) consultancies.

A review of the products offered in this space reveals overlap with

the larger vendor service management products. Service catalogs and

service - level management are standard. Niche vendors differentiate

their services most markedly in terms of the costing/chargeback

engines. Cost of service and transparency are usually key components

of fi nancial management, but not for SAS. Nor is reporting results in

a dashboard PM. If costing is limited to service while ignoring capacity

management and other important IT costs, the niche is a bit too

narrow. The tool is rendered to the tactical, rather than strategic, level.

IT Management

This discussion now turns to the very individuals responsible for IT

system management and who perform the work day in and day out.

Giving advice is much easier than implementing advice. SAS gathers

IT management perspectives from conferences, publications, and one -

on - one interactions. Everyone in IT management seems to agree on

one idea: The Business is First. Always. Most IT managers want

“ actionable ” metrics. Others avidly look for ROI Management. The

front runners are taking a strong, disciplined approach to cost cutting

and fi nancial management.

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56 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

In 2007, Intel presented “ The Road to Enterprise SOA ” at America ’ s

SAP Users Group (ASUG), which discusses how the enterprise fol-

lowed a maturity formula to attain SOA. 18 The project was driven by

a SAP upgrade and a need for master data management. This situation

is emblematic of current system management: grappling with the

complexity of the enterprise applications and gaining a solid system

management foundation. Intel ’ s desired state was service portfolio

planning, which would lead to cost savings in service re - use. The steps

on the path were infrastructure consolidation, virtualization, instru-

mentation, service taxonomy, and value dials — a great start, but a very

engineering - centric approach that would dovetail in the future with

business services planning driven by service portfolios, and enable

Intel to roll out applications faster and cheaper. The process began in

2001, and by 2007 was paying substantial dividends.

At the P100 conference in Orlando, Florida in January 2009, two

major themes were cost - cutting and fi nancial management. A panel

of CIOs participated in a discussion devoted solely to cost - cutting.

Their attitudes refl ected a bit of McKinsey and a bit of Gartner.

Panelists cited big savings of up to 33 percent in managed services and

hoped to gain the same with virtualization. They stressed strengthen-

ing their infrastructure. Cutting costs was only part of their manage-

ment emphasis. Demonstrating business benefi ts and using metrics

were equally important, and participants expressed a desire to do a

better job. Participants generally wanted to look and plan further into

the future, some as far as four years. Industry analyst perspectives on

the benefi ts of both maturity and business alignment were well

represented.

Madge Meyers of State Street Bank presented a vision that

clearly stood out. She also re - articulated the idea that an optimized

infrastructure reduces costs. (In the spirit of disclosure, State Street

Bank is a SAS customer.) In the domain of fi nancial discipline, State

Street is a clear front - runner. Under the rubric of governance,

State Street established a model of end - to - end business cases and ROI

management. This model produces self - funding enhancements, cost

transparency, and charge back by usage.

In the broader context of SAS client and sales engagements, calls,

and conversations, the typical IT organization is still ratcheting their

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 57

way up to a level of proactive management, where they manage daily

threshold infrastructure exceptions that could affect availability or

service and implement an effective long - term capacity management

forecasting system. The inability to forecast capacity across the enter-

prise is crippling to many IT organizations. This kind of effort is most

always managed by engineers, and the proactive/capacity projects are

rarely visible outside of the originating group, much less tied to busi-

ness strategy.

Four IT Business Management Domains

Distributed computing sent shock waves through IT and system man-

agement from which IT has yet to fully recover. Industry analysts,

system management vendors, niche vendors, and IT management all

have perspectives on partial solutions, but none of the stakeholders

espouses a complete model or the means to integrate all the perspec-

tives. The essential management pieces are obviously missing and

must come from new management approaches. This section explores

the four IT business domains of capacity optimization, service level

management, fi nancial management, and business alignment as they

apply to the current IT industry environment. SAS established these

four domains based on ITIL version 3, our own thought leadership,

and industry analyst feedback to form a hybrid model with invigorated

focus and emphasis. The enhancement of these four domains will help

lead to the transformation of IT system and business management into

a stable, available, and business - aligned model. This section discusses

the four domains in terms of the current state and emerging oppor-

tunities to expand the management of each IT business domain, to

fulfi ll its promise and enable the other domains to fulfi ll their strategic

promise.

Capacity Optimization

Current State : When discussing capacity management, people often misunderstand the term capacity . As an essential IT management

domain, capacity in this context means maintaining enough infra-

structure to meet business computing requirements where infrastruc-

ture means network bandwidth, connections, server capacity, data

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58 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

storage space, even power and cooling. Capacity management does

not refer to human resources, offi ce space, desks, or parking places.

From the SAS perspective, capacity optimization is a desired state for

capacity management in terms of demand management and avail-

ability management. IT organizations have long been hampered in this

area by their inability to create an enterprise view of servers, net-

works, and end - to - end enterprise business applications performance

and metrics. A direct result of the rapid acceptance of distributed

computing in the early 1990s, a heterogeneous, extremely complex

infrastructure is now spread out across the globe, and managed and

monitored by heterogeneous systems tools. Large companies generate

vast amounts of performance and utilization metrics data, which they

are unable to consolidate into a single enterprise view. Without enter-

prise views, it is nearly impossible to forecast capacity and business

needs or to synchronize capacity with service views. The end result is

that capacity management is usually done poorly — machine - by -

machine or location - by - location — or not done at all.

A broader problem emerges when capacity management is per-

formed server - by - server, location - by - location, or through educated

guesswork. Inadequate capacity management acts to prevent business

alignment by improperly sizing applications, burdening service man-

agement, and destroying fi nancial projections. Capacity managers

either buy too much infrastructure or undersize capacity, only to

make a panic buy later . Most often, capacity managers either overbuy pooled infrastructure or buy oversized infrastructure to host a single

application. Capacity managers work under the premise that oversized

infrastructure will deliver the necessary performance and stability

while preventing service disruptions during production times. Buying

infrastructure sized for cost effi ciency can lead to disruptions if manag-

ers can ’ t assimilate the views needed to manage for performance.

Opportunities : Beyond the inherent promise to provide ade- quate infrastructure to run the business, capacity management pres-

ents business management opportunities in terms of both cost

management and alignment to the other three business domains.

Armed with end - to - end views of servers, capacity managers can

provide a quick and large ROI by eliminating excess server capacity

through server consolidation. Server consolidation requires both a

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 59

current utilization baseline and a time series forecast of utilization

extending out a year.

Consolidation is a solid maturity approach utilized by forward-

thinking businesses. In addition, many IT organizations look to virtu-

alization as a cost reduction initiative, and are correct in looking to

virtualization for cost gains. Best practice capacity managers properly

size virtualization allocations to maximize the cost management

opportunity (i.e., not too big nor too small) by studying the allocation

utilization rates and forecasting their growth. Not involving capacity

managers in virtualization projects is a missed opportunity. After

determining the optimal capacity, managing to that level wrings out

the costs of idle capacity and also eliminates panic infrastructure buys.

Buying in panic mode never results in a smooth, cost - effi cient imple-

mentation, and enterprises often come dangerously close to impacting

service levels. A recurring theme in this section is the interconnected-

ness of the processes across these four management domains. Capacity

management should not be performed in the isolation of an engineer-

ing silo. To achieve greater levels of IT maturity, capacity managers

must cross - pollinate and be cross - pollinated by performance measure-

ment information fl owing into and out of the four other IT business

management domains.

For example, capacity managers need fi nancial information beyond

budget allocations for capacity buys. Determining the cost of capacity

not only promotes more effective capacity management but also

provides foundation costs for service management and service

management contracts. The cost of capacity includes the cost of uti-

lized capacity, reserve capacity, and unused capacity. Attacking unused

capacity without distressing service levels is a combined capacity,

service, and fi nancial management exercise. Capacity managers must

also determine capacity in nontraditional ways. Predicting the exhaust

rates of standardized services and the growth of business services

create other ripe opportunities.

Service Management

Current State : From thirty - fi ve thousand feet above the landscape where fi ne details are obscured, the various approaches to service

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60 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

management appear more alike than different. The differences some-

times appear to be more of a marketing exercise. From that altitude,

service managers appear to build catalogs of IT services (Premium Web

Service, Bronze Network Access, etc.) and assemble those components

into business service contracts that specify service parameters in terms

of availability, response time, throughput, and service hours. System

management and niche vendors sell this approach, which appears to

also follow the engineering focus of Gartner IT Infrastructure and

Operational Maturity Model. Only a small minority of IT organizations

has achieved this level of maturity. Best practice service managers

remain vigilant for several issues while implementing this large and

very necessary IT business management domain.

Service managers ignorant of the true cost of service are driving

in a thunderstorm without windshield wipers. It ’ s hard to see, and

the risk of collision is unacceptably high. For example, service manag-

ers run into cost mismanagement issues when they enter into service

contracts with business users who cost more than specifi ed by the

contract. Some niche vendors already address a portion of this issue,

but service managers generally fail to make the connection between

IT operational budgets and the planning process for new and ongoing

services, as well as the connection between capacity management and

service level management.

Opportunities : The capacity management section discussed the value of forecasting for optimizing infrastructure over time. Forecasting

provides equal value for service management. Service reporting

and fi nancial measures are inherently reactive. Forecasting service

level performance, future capacity needs, and cost of service growth

augment service management practices. In addition to forecasting, a

management structure that contains value measures is another essen-

tial opportunity for more mature service management. Reporting cost

and service results are inadequate without knowledge of the degree

to which the IT organization succeeded in terms of key enterprise

strategic objectives and the metrics that track them. Meeting business

goals and objectives are the ultimate measure of IT value. Forecasting

performance is engineering; applying intelligence to enabling and

meeting business strategy is a new level of business maturity for IT

management.

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M A K I N G S E N S E O F I T B U S I N E S S M A N A G E M E N T ◂ 61

Financial Management

Current State : We don ’ t need to discuss IT fi nancial management from thirty - fi ve thousand feet. So neglected is the subject that I doubt

it would even be visible from that altitude. Most CIOs and their IT

organizations need to get down on their hands and knees at weed

level to see the primary problems. Most IT organizations manage their

budgets in spreadsheets. Spreadsheets are easy for individuals to use,

inexpensive, and most everyone already has one. But as widely dis-

tributed spreadsheets quickly lose their effectiveness, they become

very expensive. Diffi cult to consolidate into department views and

then into an enterprise view, widely distributed spreadsheets result in

inaccuracies, and a large percentage of expense planning is lost. The

wide use of spreadsheets for IT budgeting can be traced to adoption

of corporate budget systems that are not tailored for IT organizations

and resource management. In addition, IT also budgets in another

management area where the spreadsheet inaccuracy is even higher:

planning and managing the portfolio of new and existing business

service projects. Large corporations have hundreds and hundreds of

such projects trapped in spreadsheets that they ruefully call “ the

swamp. ” With the utmost diffi culty and many complete failures,

fi nancial managers attempt to reconcile the hundreds of spreadsheets

into an accurate, consolidated view, and then reconcile the consoli-

dated portfolio view to the operational budgets.

Trapped within this swamp are the answers to essential IT man-

agement questions with enterprise - wide strategic implications: On

whom are we spending, and what are we spending it on? Was the

spending justifi ed? Optimized? How are we prioritizing IT support,

service, and spend? How do we plan future IT resources and ser-

vices? How do we minimize unused IT resources? How does this

information inform overall decision making for IT, business units,

and the bottom line?

Opportunity : The opportunity is to create an IT fi nancial man- agement system for a service - oriented IT organization. IT fi nancial

managers may continue to use a spreadsheet for individual opera-

tional and portfolio project planning, but they put all the data in one

foundation to preserve its integrity. Financial managers then combine

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62 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

fi nancial data with capacity and service data, which provide fi nancial

intelligence to the other IT business management domains in a usable

format for optimizing their own strategic management decisions.

Capacity managers need to know the cost of capacity, including

unused capacity, and cost of the support processes necessary to manage

the infrastructure. Service managers need to know the cost of service,

unused service, and who consumed the service, including relevant

support processes for both the standard service catalog components

and each business service.

Business Alignment

Current State : True business alignment, or in Gartner terms, busi- ness partnership, is still an illusion as borne out by Gartner statistics.

They report that less than one percent of IT organizations achieve their

Business Alignment stage of maturity — a very small number in any

survey sample that includes best practices. Two factors account for the

lack of business alignment in the IT industry. First, vendors do not

supply IT organizations with the support they need for developing

portfolio management and system management tools that span metrics

collected by various enterprise and IT monitoring and management

systems. IT vendors focus on building maturity from the infrastructure

management up — a purely engineering focus. What tools exist for

fi nancial and business management are neither integrated nor applied

by IT managers seeking to solve their business challenges. Second,

despite IT analysts pointing the industry toward aligning visions and

techniques, the most important alignment achievement must include

participation by the business intelligence community for new IT strate-

gies with supporting applications.

Opportunities : Because true examples of business alignment are rare and few people in the industry have actually seen a single

example, the opportunity for business alignment is far greater than

most CIOs realize. This IT business management domain opportunity

means that as a key strategic enabler for most enterprises, CIOs would

manage the IT organization like a business with a business. CIOs and

their IT organizations will a create value axis for every IT product

and service from the performance metrics in each of the four IT busi-

ness management domains. Business objectives that IT products and

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 63

services must enable will be traced back to overall business strategy

through these metrics. Enabling these strategic business objectives will

carry a negotiated price tag to build and support after implementation.

That negotiated price tag must fi t within the ROI calculation of each

business objective. CIOs will determine support costs through business

user volume and service estimates, which IT will translate into service

and capacity levels. Once built and implemented, the applications and

their related IT services will be measured, forecasted, and optimized

from business objectives, service results, costs, and business strategy.

The IT transparency illustrated here requires a different set of tools

and processes that have yet to be broadly discussed in the IT market.

While the rest of the enterprise is either already using or receptive to

strategic performance management (SPM), many IT organizations

have yet to reach this stage of business maturity. The utilization metrics

increases in value when associated with strategy, initiatives, goals, and

objectives that are mapped to other IT management domains.

PUTTING THE PIECES TOGETHER

While IT has made strides toward monitoring and managing infra-

structure on the machine level, management is often done with mul-

tiple tools in multiple locations. In order to enable the four IT

management domains with the required infrastructure metrics, best

practice CIOs work to consolidate the metrics trapped in isolated tools

and design new IT infrastructure metrics data management tools to

access, integrate, aggregate, analyze, and manage large quantities of

IT resource performance data from hardware, operating system soft-

ware, networks, Web servers, databases, and applications. 19

Step One: IT Infrastructure Metrics Data Management

IT resource performance metrics are generated by the logging mecha-

nisms inherent to IT resources or are created by the Enterprise Systems

Management tools used in managing IT infrastructures. Everything

needed to analyze IT resource performance data from multiple sources

for capacity planning and forecasting, consumption metrics for fi nan-

cial management, service - level performance measures, seasonality

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64 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

analysis, and enterprise IT performance summaries should be included

in the initiative.

As demonstrated in Exhibit 2.4 , SAS collects resource data, nor-

malizes across platforms, and publishes the data for use by multiple

users across the IT management domains. Of course, data management

must scale to enterprise demands. When faced with multiple - system

management tools, locations, or perhaps no tools at all, inherent to the

SAS IT Resource Management server is the ability to natively extract

information from many industry standard operating systems and

systems management tools. Native support is the predefi ned ability to

translate source data into a SAS representation for storage in the per-

formance database. Data is retrieved from its native data source and

brought into the IT resource data warehouse, where IT metrics are

represented exactly as they are extracted. In the detailed level of the

performance database, it is likely that IT data metrics are available for

analysis and reporting on a per - polling cycle or per - event basis, as

would be necessary for daily proactive management of a stable system.

As detailed level data is retained, it is reduced — statistically summa-

rized into aggregation levels that require incrementally less storage,

enabling longer term storage as would be required for capacity

management time series analysis. Any part of this data warehouse

defi nition can be modifi ed, added to, or deleted from at any time.

The staging transformation invoked by SAS IT Resource Manage-

ment adapters extracts the raw IT resource performance data, per-

forms any calculations and conversions that are required by that

adapter, and loads (stages) the resulting data into tables in the IT data

mart. Staging jobs can be run interactively or scheduled to run in

batch mode, depending on the enterprise requirements. An aggrega-

tion transformation specifi es how data is to be transformed and stored

so that it can provide analysis and report - ready IT resource perfor-

mance data.

For example, an aggregation transformation provides specifi ca-

tions for fi ltering data, calculating statistics, performing rolling accu-

mulations, and ranking and grouping (classifying) the data according

to user specifi cations. For any given adapter, SAS IT Resource

Management generates transformations that create information maps

referencing the data needed to create and view reports.

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E x h

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66 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Simple summary aggregation tables and the information maps

for those tables are the primary inputs for creating IT resource per-

formance and capacity planning reports such as CPU utilization,

threshold analysis, and peak period analysis. SAS offers a collection

of easy - to - use query and reporting interfaces for different types of

users and recipients (e.g., capacity planners, IT infrastructure ana-

lysts, IT operations managers, senior IT management for business

alignment, fi nancial managers, and service - level management).

Whatever the IT management domain, data must be accessible to a

wide variety of reporting tools and visualization techniques as repre-

sented in Exhibit 2.5 .

In summary, IT data management must aggregate data into enter-

prise and domain management views, regardless of the source of the

data. Data must be accessible to other tools as necessary as well as

reporting and visualization tools. IT data management is the founda-

tion that the capacity, service, fi nancial, and business alignment man-

agement domains are built upon.

Exhibit 2.5: Data Reporting Tool Accessibility

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 67

Step Two: Capacity Management for Risk, Expense, and Quality

Lack of senior management support, practical implementation guide-

lines, time to develop a thoughtful approach, hierarchical reporting

structure, and effective organizational communication — of these fi ve

major barriers to IT maturity, the lack of time to develop a thoughtful

approach and the lack of effective organizational communication are

more symptoms than root causes. If CIOs and their IT organizations

found the time to develop a coherent articulation of enterprise -

relevant IT business thought expressed in terms of business measures

and ways IT resources enabled those business measures, IT/business

communications would mature quickly.

As a business within a business, mature CIOs expect enterprise

business users to provide the IT organization with business plans based

on specifi c technology request and commensurate measures that dem-

onstrate the ways that the technology resources provide and enable

their strategic objectives. Best practice CIOs expect those business

plans to address the four IT business management domains to facilitate

the development of appropriate metrics and ongoing communications

about performance results and related IT service forecasts. In short,

thoughtfully developed business plans that promote strategic com-

munications must include business measurable goals and objectives

for the alignment domain, volume estimates for the capacity domain,

service requirements for the service management domain, and the

price the technology user is willing to pay for capital investments and

ongoing services expenses for the fi nancial management domain.

Adequate capacity enables technology business plans and service

levels. Well - managed capacity promotes fi nancial management.

Capacity management has other benefi ts as well. Here is what Martha

Hays and Margaret Churchill have to say:

Critical IT systems are managed by monitoring day - to - day activities to ensure they are performing within stated utilization and performance thresholds. Responding to system alarms causes the operations team to react to the problem and implement an immediate change. These changes may cause unforeseen consequences on other parts of the environment, resulting in a ripple or cascade effect across the enterprise.

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68 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

A capacity management process will instill a discipline of preparing for the future and planning for appropriate changes well before the system alarms go off. This allows the IT organization to predict when thresholds will be reached and prescribe the right changes. By doing so, better decisions can be made about server consolidation, hardware procurement, and service level management. 20

The discipline of capacity management reduces risk and expense in a

far - reaching manner. SAS places capacity as the fi rst IT mana gement

domain to emphasize that mature capacity management (1) addresses

instability problems endemic since the advent of distributed comput-

ing; and (2) pulls IT much closer to the service management, fi nancial

management, and business alignment domains. Hayes and Churchill

expand the implications for the CIO and IT organization, where the

fi gures they reference appear in Exhibit 2.6 :

Forecasts provide advance notice that an outage or other type of problem is likely to occur. Once the predictions have been made, what is the best way to prevent the problem from actually occurring? Modeling delivers this capability through what - if scenarios that identify the impact of planned or unplanned changes to the system in areas such as workload levels, workload patterns, server confi gurations, network infrastructure, and storage arrays.

Exhibit 2.6: Hayes and Churchill on Capacity Management

Source: Martha Hays and Margaret Churchill, “ Paper 6151 Forecasting + Modeling: A Partnership to Predict and Prevent Capacity Bottlenecks, ” Computer Measurement Group Presentation, 2006, Volume 1, (Computer Measurement Group), www.daschmelzer.com/cmg2006/PDFs/033.pdf .

Forecasting and Modeling

Application Sizing

Production

of Capacity Plan

Iterative Activities

Demand Management Timeouts

due to undercapacity

1400

1200

1000

800

600

400

200

New Web site rolled out. Expected increase in Web site traffic is significant.

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 69

IT fi refi ghting is expensive, time - consuming, and distracts the organization from spending time on innovative solutions that add value back to the business. However, IT fi re prevention is seldom practiced. The combination of forecasting and modeling, as part of a capacity manage- ment process, provides the insight needed into future IT events, and effectively prevents the IT fi res.

Indeed. One begins to wonder how much of the IT organization ’ s

budget has been spent fi refi ghting in the last seventeen years. And

The combination of these two methods also extends capacity management from a silo or server - centric view, to a broader end - to - end view. This allows predictions to be made about utilization, response time, workload growth, workload changes and infrastructure modifi cations.

For example, today ’ s systems may be running within acceptable thresholds, and a linear trend shows that there is enough capacity on the servers to sustain a 5 percent fi xed workload growth over the next three months. However, this trend does not account for a spike in demand that is expected for the upcoming holiday season. By using a time - series forecast, we can predict that the servers will bottleneck at the beginning of the peak shopping season. A model is built from the fore- casted data and is used to evaluate several confi guration changes that could support the increased workload. This analysis allows us to plan for the changes needed to the system to support the seasonal demand. With ample time before the peak season starts, we have the time to properly procure and plan for the changes, avoiding emergency procedures and expensive procurement. We have maintained user service and utilization levels — and have prevented an IT fi re.

How does IT move from fi refi ghting to a thoughtfully determined,

well managed capacity that provides for service levels and fi nancial

management?

Capacity management evolves once an organization has implemented a PM system that focuses on monitoring

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70 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

current systems and reacting to alarms that result from exceeding utilization thresholds or service levels.

Since there must be an actual historical basis for the predictions, the data captured from performance monitors is required for the capacity planning process. Even if systems monitoring and event management are taking place, the resulting data must be stored for analysis and reporting purposes.

A great deal of capacity management information can be uncovered from basic analysis of the system and event data. These include the following:

� Which systems are experiencing outages or exceed- ing utilization thresholds?

� Is there a pattern based on time, day, month, etc.?

� Are the events consistent with changes in workload?

� Is there correlation between multiple events?

� When an issue occurs, what is the impact on the other systems?

For further analysis, data can be captured from the system monitors and stored in a centralized performance data repository. Since information from heterogeneous systems may have been collected at different time inter- vals and in different time zones, an extraction, transfor- mation, and load (ETL) is used to “ homogenize ” the data. Once done, reports can be created that provide detailed historical analysis. These reports are useful to show a correlation of past events and past system responses to those events.

Once the data is captured, forecasting and modeling can be done. ITIL, however, does not differentiate between the two, as depicted in Figure 1 . In practice, the two methods are different even though they use some of the same terminology.

Capacity builds on IT performance metrics. After performing a basic

analysis of the infrastructure and establishing baselines, the role of

forecasting becomes increasingly important. The CIO and IT organiza-

tion perform forecasting on the baseline to predict normal business

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 71

growth and from business plans that pass along volume predictions to

capacity and fi nancial managers.

A common report generated from historical data is a linear trend. This is the quickest and simplest report and is supported by spreadsheet software. Trend lines are based on an average of three or more historical data points extended to some future point. Trend lines are appropriate when future system behavior is expected to be at the same rate as the historical data with no seasonality.

In cases of seasonality or expected workload changes, trends will provide erroneous results. This is depicted in Figure 2 . The forecast would indicate that there is suffi - cient capacity to support the system. However, when a new Web site comes online, the Web server is unable to handle the traffi c. As a result, the trend provided an incorrect result since it was not able to predict the impact of this workload change.

Business decisions based on this trend will result in a false confi dence that the system will continue to operate properly. As a result, basic linear trending is not recom- mended for making predictions of complex systems. For systems that experience pattern changes due to seasonal- ity or planned business promotions, robust forecasting like time series with seasonality, trend, and event correla- tion is recommended.

Another problem with the linear trend is that it can ’ t be used for systems that are close to experiencing a bottle- neck. These systems will start queuing and/or consuming additional system overhead. This will cause the utiliza- tions to skew, which will not be identifi ed through a linear trend. Notice how a prediction of seasonal behavior from the chart above would have resulted in underesti- mating the capacity needed.

Time Series Forecasting analyzes time series variables and forecasts future values by extrapolating trends and patterns in the past values of the series or by extrapolat- ing the effect of other variables on the series. With the use of sophisticated statistical software, a forecasting model can be developed and customized to best predict your time series. In the IT environment, these time series

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72 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

are easily obtained from your performance measurement data which has been stored and summarized in a capacity database (CDB). By choosing the proper time intervals (day, week or month) and variables as input, your historical data can lead you to a justifi able forecast of capacity requirements. Forecasting is accomplished through the following:

� Storing and summarizing the data

� Analyzing the data to determine seasonality and other

patterns

� Selecting an appropriate forecasting method

� Generating a forecast, which includes expected business

projections and events.

In addition to data management, analysis and forecasting tools are

essential to capacity managers. Forecasting the complex enterprise

applications is a set of intricate tasks, not the least of which is picking

the proper statistical to fi t the forecast problem. One approach is to hire

statistical talent. Another is to use statistical software that analyzes the

data and the problem and selects the best statistical approaches for you.

After integrating statistical management approaches, capacity manag-

ers expand their roles by sending capacity data to fi nancial managers

and receive costing information in return. The next step is service man-

agement, because service managers would be ill prepared without

capacity service level forecasts.

Step Three: Standard Services as a Foundation to Business Services

Stepping into service management requires the leveraging of the pre-

viously built IT data management foundation. Since service contracts

are the underpinning of the services that the IT organization provides

to enterprise business users via their business plans, cost of service is

crucial to contract negotiation. Determining how much each business

is able to pay for the IT business service is one building block in deter-

mining the value IT provides to business users.

Building an array of standard services based on the technology

silos that all the Computer Science majors manage is a natural starting

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 73

point. Network engineers manage networks as a service. The IT orga-

nization independently manages Web servers as a standard service.

Standard services are those IT components that enable the business

plans submitted by the business users. Standard services can be turned

into “ branded ” services by attaching differing levels of value to each

service, such as premium, gold, and bronze service levels, with price

and performance gradations for each level. In terms of IT manage-

ment, each standard service requires an internal contract that specifi es

the level of service, the cost we wish to manage to, and a capacity

plan. Monitoring the results is essential.

With a stable set of standard services, service managers match

business plan requirements in terms of availability, response times,

and throughput to the catalog of services and determine the price

when the business plan passes through capacity to ensure that

the volume estimates in the plan can be supported. Agreement

on services and costs constitute the elements of a service contract.

Planning each contract is an exercise in capacity, service, and fi nancial

management.

Financial Management: A New Era

Financial management specifi c to the IT organization has received less

thought and support than either capacity or service management.

Very few IT organizations have found effective solutions for fi nancial

management challenges. Most IT organizations fi nd that even the

budgeting applications are ill suited for IT management. Tools for

planning the capital and expense of business user new project portfo-

lios are nonexistent. The result: IT manages budgets and projects in a

swamp of spreadsheets. There are several reasons for the dependency

on spreadsheets, but primary among them is the General Ledger (GL).

The GL has other important purposes in the custodial role of fi nance

that center on external reporting and internal controls. It has its

own highly controlled environment with many rules governed by

external reporting and tax requirements. Since the GL is optimized

for external and tax reporting purposes, it is a poor tool for internal

analysis and reporting, especially for the service - focused business of

IT management.

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74 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Assuming that the best practice CIO manages the IT organization

as an internal company separate from those business units consuming

IT services, the resulting perspective clearly emphasizes the four IT

management domains as the basis of the IT Value Axis: If IT services

are being purchased, what does the customer expect from IT? What

would IT as a supplier provide? The customer would expect:

� Consistent service delivery as specifi ed in contract

� Consistent quality

� Competitive pricing

As an external supplier, IT would provide:

� Adequate capacity to assure consistent service delivery as

required by contract

� Robust processes to provide consistent service

� Invoices with prices and supporting documentation of services

provided

In such a business relationship, the price that the customer is

willing to pay is based on perceived business value and a benchmark

of prices and services offered by other IT suppliers. Customers are

willing to pay for what their business services consume but not for

waste or excess capacity. Excesses are not allowed to infl ate the price.

If the price is too high, the customer fi nds other alternatives. It is criti-

cal to note that the cost to provide the service does not establish the

price for a profi t - oriented IT provider. Independently, market condi-

tions set prices, as it does for the rest of the business. The profi t motive

drives the supplier ’ s desire and willingness to provide the service.

Profi t equals revenue minus cost. For a high enough price, an IT

service provider purchases whatever capacity it needs to make a profi t.

When prices are too low, IT service providers redeploy resources to a

more profi table market and potentially stop offering the service. If

profi tability is low, IT service providers are highly motivated to improve

the effi ciency of their operations. If profi tability is too low, the service

provider leaves the business.

IT fi nancial management must address the costing of services,

processes, and business services while bridging that data into a project

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 75

portfolio planning environment that anticipates project capital costs

(essentially new capacity and development costs), projects the ongoing

expense of the capitalized costs, and delivers a projected fi nancial

impact on existing capacity for capacity managers. Key ingredients of

the model depicted in Exhibit 2.7 are:

� Standard fi nancial and statistical forecast models used for

planning

� Fixed and variable qualifi cations available in both cost and plan

model

� Planned capital expenditures and commitments used to manage

depreciation

� Interactive scenarios used for simulations

� IT planning process that can be integrated with enterprise plan-

ning as a separate loop

� Department ownership of the loop

� Comparisons of operational and fi nancial results available for

monitoring and management

As depicted in Exhibit 2.7 , the planning process allows planners

to retain the front end use of Excel but without the consolidation

Exhibit 2.7: IT Financial Management Process

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76 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Exhibit 2.8: Project Consolidation for Directors and Capacity Managers

headaches associated with free - fl oating spreadsheets. Planning data is

housed within the SAS foundation but displayed in Excel. Project

managers plan individual projects by assembling the anticipated stan-

dard service components. Within the spreadsheet are the costs for the

services, the existing capacity, the unit costs, entry for the new

volumes, and the impact on capacity. Conditional highlighting dis-

plays when capacity is impacted. Projects are consolidated for project

directors and capacity managers as shown in Exhibit 2.8 .

Central to the fi nancial management system is the conversion of

operational budgeting into the costing of services, processes, and capac-

ity. The tool used for this conversion is Activity - Based Management

(ABM). An IT ABM analysis starts by identifying the resources deployed

in the IT organizations. Typically, these are recorded in the GL for each

IT department — usually the only relationship between ABM and the

GL. The SAS ABM model begins with GL costs by department and by

account as its fi rst view, retaining the original GL view to provide a

fi rm common starting point and for correlation with external fi nancial

reporting. However, it then also provides a parallel view of resources

that better refl ects operational requirements and realities.

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 77

Regrettably, the level of GL data detail is both greater and lesser

than the optimum set required for ABM. Where there is too much

detail, such as accounts required for tax reporting, these details can

be aggregated. Where there is too little detail, such as for asset depre-

ciation, a well - designed ABM model uses its capabilities to split these

costs to a more appropriate and useful level to support decision

making. The reorganization is accomplished in the transition between

the GL view and the new operations view.

This operationally focused view reorganizes resources and their

costs to align them with operational resources — it captures resources

in terms of teams of people, types of equipment, and other more

operationally natural categories. This operational view is designed for

use and easy understanding by operating personnel. At the same time,

all costs are easily traced and reconciled to traditional fi nancial views,

which aggregate into a robust and comprehensive resource view that

is also verifi able. This provides IT managers with a view of what the

resources that they deploy actually cost in terms that they easily under-

stand and use for decision making purposes. This view is also the

foundation for subsequent views of activities and services. The overall

model cost fl ow and management views are shown in Exhibit 2.9 .

Exhibit 2.9: IT Cost Flow Model

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78 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

IT components are tracked separately because they constitute a

signifi cant cost and play an essential part of IT business services. For

these components, the cost recorded in the GL is usually aggregated

to a level not useful to operations management. For this reason, com-

ponent information is obtained from asset registers or other sources

to identify the current costs of components at a suffi ciently granular

level to support service level agreements and capacity forecasting

models.

After establishing an operational view of resources, the next step

is to assign these costs to the work that these people do. This model

uses existing ITIL process defi nitions as activity defi nitions. Using

the ITIL process defi nitions provides a sound, common basis for

measuring predictable, repeatable IT processes. ITIL processes are a

necessary component in the IT maturity process. Without them, it

would be diffi cult to attain a proactive, service - oriented, value - driven

IT organization. Resources are traced department by department to

the ITIL processes representing the work performed by people from

each department. At this level of detail within the departments, this

work is considered in terms of activities. Later, using reporting tools,

costs are easily reported at the organization - wide ITIL process level.

After these costs have been assigned, the costs of ITIL processes

become available. Since the ITIL costs are tied to the operations

resource and fi nancial resource views, people can observe more

powerful relationship costs with breakdowns by department and by

types of resources either by the operational view or the fi nancial

view of cost.

The next step in ABM deployment enables tracing costs to the

products and services provided by the IT organization. Following the

business plans, service level agreements contain the value defi nition

for business applications as well as service level requirements. In addi-

tion to documented SLAs, there may be more general standard services

offered as a cost savings or legacy services not yet formally documented

with customers. Even without formal documentation, IT should ascer-

tain cost and service performance for internal management purposes.

ABM methodology requires a cause and effect tracing of costs.

Consumption metrics often provide the best basis for this assignment.

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 79

Standard services may also be traced to specifi c services, where they

are used as components of a broader business service offering.

At this point, cost analysis of services becomes available for service

cost trend and service unit cost trend. With the relationships to ITIL

processes, components, and people resources already established,

these services can be analyzed by ITIL process and/or the resources

consumed. Conversely, resources can be analyzed in terms of the

services that ultimately consume them.

In the fi nal step of ABM deployment, services are assigned to

customers based on usage consumption metrics. Cost metrics are now

available by customer. As these are added to the relationships already

calculated in the model, a rich analysis base becomes available to help

users and providers understand the operations and relationships to

operating results. Since the symphonies that IT plays are business

applications covered by SLAs, the results can be used for both value

reporting to customers and also for internal IT optimization. In

summary:

� Activity - Based Modeling is used do defi ne, manage, and change

the cost model and scenarios.

� The cost model contains operational and project data to derive

costs, notably time per position to produce project costs.

� Costs assignment rules are defi ned on operational drivers.

� The cost model is populated, integrating fi nancial data from

fi nancial systems and operational data from operational systems.

� Web reporting and business reporting are also used.

A sample of an online analytical processing (OLAP) cube extrac-

ted from ABM and posted to a dashboard appears in Exhibit 2.10 .

The subject is the costs associated with a branded standard service —

Premium Web Servers. The cost transparency shows three main cost

categories: the business services (projects) consuming the service,

overhead reserve costs, and excess capacity costs. The next level of

cost categories breaks down the individual hardware components

of the service and the ITIL processes consumed by the branded, stan-

dard service. The data is essential for fi nancial management.

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80 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Step Four: Strategic Performance Management

PM isn ’ t necessarily the last step in achieving IT management maturity

and business alignment. PM can and should be applied throughout

the maturity process. Let ’ s review the key issues. CIOs identifi ed the

lack of organizational communication and the lack of time for thought-

ful planning as barriers to IT maturity. Educational institutions gener-

ally prepare either IT engineers or business managers but not IT

business managers. The distributed computing technology adopted in

the early 1990s that neglected to include system management as a

part of the business model put IT in a twenty - year cycle of attempts

to overcome that neglect. Enterprise applications are complex, expen-

sive, deeply embedded into business processes, and therefore demand

a new business/IT relationship that is still evolving. And lastly, no one,

not the system management vendors, industry analysts, niche vendors,

or IT management, has a complete answer to the best practices at

this stage of IT maturity. We do know that CIOs and their IT organiza-

tions have not comprehensively focused on the IT business manage-

ment domains or applied business analytics to those IT management

domains. In other words, CIOs are still learning to use business tools

with IT tools for a complete picture.

Exhibit 2.10: ABM - Extracted OLAP Cube Posted to Dashboard

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 81

PM has three discrete measure areas to communicate throughout

the IT organization and to enterprise business partners: (1) business

strategy, goals, and objectives; (2) IT internal engineering and man-

agement strategy, goals, and objectives; and (3) the cross - section of

the business and IT strategy, goals, and objectives (see Exhibit 2.11 ).

Suffi ce to say that PM requires a foundation as do the other IT man-

agement domains. PM is not a matter of placing metrics in a spread-

sheet. PM provides the deliberate linkage between the management

centers of business enablement ROI, business objectives, IT service

contracts, capacity management, forecasting, and IT service cost trans-

parency. Gary Cokins writes that many application failures are tied to

the lack of a strategic view and the lack of a forward view. Let ’ s tie

the pieces together with examples.

PM metrics drill down from broadly stated metrics to lower levels

of detail following the path of organizational intent through to group

performance. Metrics should contain, at a minimum, a target to manage

toward the actual achievement and a performance calculation that

expresses how close the actual achievement came to the target. In

Exhibit 2.12 , PM is managing the performance achievement for three

essential IT domains that link IT to the business: business objective

measurements, IT service level performance, and the cost of the service.

Exhibit 2.11: Strategic Integration

Service Level

Management Service

Management

Strategic

Alignment

Charge

Management

Cost

Management

Financial

BusinessCosts

T e c h n o lo

g y

S e rv

ic e

S tr

a te

g y

O rg

a n iz

a ti o n

Resource

Management

Investment

Management

Planning Process

Investments Scenarios

Cost Modeling Process

Unitary Costs of Services

Capacity Management Process

and Resource Optimization

Cost Modeling Process

Unitary Costs of Services

Strategic Objectives

Action Plans

Scorecard

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82 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

For an executive view, this dashboard is probably suffi cient. For

other levels of the business it is not. Tracking the business perfor-

mance requires three levels displayed in four examples of detail. The

second level measures business objectives that justifi ed the investment

in Marketing Automation. While there is more business detail in sub-

sequent drill - downs, the dashboard icons link directly to the original

business case objectives for the Marketing Automation investment

decision (see Exhibit 2.13 ).

The drill - down on the cost performance provides more insight

by delivering an OLAP cube summary of the cost of providing the

Exhibit 2.12: Executive Dashboard PM View

Exhibit 2.13: Marketing Automation Drill - Down

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 83

service of a business process in the Marketing Automation. Financial

transparency detailing the costs of providing the service is attained

by presenting standard service consumption by infrastructure compo-

nent and the IT system management processes that were expended

in supporting the infrastructure components in the service (see

Exhibit 2.14 ).

Measuring business objectives, service contracts, and the cost of

service is a major step forward for IT maturity. It is, however, only

part of the maturity picture. IT internal engineering and management

must be brought into the PM picture. Let ’ s start with the business of

capacity management. Capacity has several management objectives

that look for cost savings and service improvement. Capacity manag-

ers must manage to keep excess capacity as low as possible through

consolidation and virtualization and forecast as accurately as possible

(see Exhibit 2.15 ).

Exhibit 2.14: Standard Service Consumption

Exhibit 2.15: Capacity Management Objectives

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84 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Excess capacity is a cost that IT must absorb, and the IT organiza-

tion must manage excess as close to zero as possible. In Exhibit 2.16 ,

the fi nancial OLAP cube depicts the excess capacity costs by device

and the IT system management services engaged in managing the

excess capacity. Excess capacity isn ’ t simply idle components, but

components that are utilized to some degree but underutilized beyond

the overhead capacity built in for headroom.

Service management must manage the twin centers of standard

service and business services to a level of cost and service performance

determined as a part of the IT organization ’ s business management

and planning. Standard services are managed to internal IT service

contracts and are measured as a part of good IT business management.

If the standard service is not performing to specifi cations, then the

business services won ’ t perform to contract specifi cations either (see

Exhibit 2.17 ). Excess capacity can also be managed in the business -

facing side of IT: in the standard services that comprise the business

services. IT “ sells ” the standard services. Excess capacity here is similar

to excess inventory. In this OLAP example, this service has far too

much excess capacity (see Exhibit 2.18 ).

Exhibit 2.16: Excess Capacity Visualization with the Financial OLAP Cube

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P U T T I N G T H E P I E C E S T O G E T H E R ◂ 85

Exhibit 2.17: Shared Services Performance Dashboard

Exhibit 2.18: Excess Capacity

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86 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Has the application of traditional PM supplied all the information

and tools necessary to make intelligent decisions? Do we have all the

tools to judge which of our management domains impacts success or

failure the greatest? Have we the tools to test the impact of proposed

changes to our initiatives and forecast the results? In other words, can

we apply advanced analytics to PM and move PM planning and inter-

pretation from educated guesswork to confi dence interval based

analytics?

We can. SAS calls it Intelligent Scorecarding .

CHANGING THE WAY IT BEHAVES

The CIO and IT organization spend signifi cant time, effort, and money

designing and implementing strong, proactive programs to build effec-

tive capacity, service, fi nancial, and alignment practices. You con-

vinced your business users to provide business objectives along with

their requests for IT investments. From those business objectives IT

has created service, cost, and capacity contracts and spawned a broader

set of internal management objectives. Now IT and its business part-

ners are measuring alignment metrics up and down the value axis. In

spite of all the planning, the measurement results indicate you are a

little short of expectations. The programs didn ’ t produce the results

everyone had bet their bonuses on.

What do you do now? IT has been steered in a new direction,

and while results are adequate, improvements must be made. Do you

stay the course, adjust the course, or is a new, improved course

needed?

If it were possible . . . to know which assumptions and initiatives

were correct and which were wrong . . . to know which measures had

the greatest impact on success, which assumptions failed, and to what

degree . . . to know how much better we might understand the ways

that IT was doing the right things, measuring the right things, and

selecting measures refl ect the correct strategy in the proper portions

. . . to know when changes needed to be made (as they inevitably do)

. . . could we then predict the impact of those changes before the

changes are made?

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C H A N G I N G T H E W A Y I T B E H A V E S ◂ 87

This chapter is not just about SPM. It is about SPM and Intelligent

Scorecarding for IT, which gives IT an additional tool, honed specifi -

cally for IT, to help steer IT management and initiatives in the direc-

tion that provides the most value for the business. Poorly conceived

and ill - applied SPM undermines the achievement of optimized results,

or even worse, becomes the wrong tool addressing the wrong problem.

Deliberate and judiciously applied SPM is absolutely necessary for

effective and effi cient strategy execution.

IT strategy that addresses system management issues while knit-

ting an effective business relationship with IT customers has proven

to be an elusive goal since the end of mainframe dominance in the

early 1990s. To understand the ways that SPM and Intelligent

Scorecarding applications address this strategic IT management goal,

we have to rummage through several subject areas and cross - pollinate

germane material throughout four main themes:

1. IT and SPM

2. Management domains in the PM context

3. Analytical performance management

4. IT analytical PM

Addressing the Challenges of IT and Strategic Performance Management

SPM for IT is more than just generating and reporting a mishmash of

stovepipe metrics. Reporting historical performance while ignoring

correlation or forecasting is not a better way forward. SPM is not

magic. It is part art, part science. SPM has its own lessons learned from

how businesses applied it to handle business problems. SPM and ana-

lytical performance management (APM) do not have much of a history

in IT management applications, so we have to extrapolate and garner

insight from its use in other areas of the business. The art of SPM

eventually leads us to the realization that the IT organization ’ s busi-

ness users are trying to solve very similar business issues as IT manag-

ers. The users just have a little more problem - solving experience in

this area.

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88 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

In its simplest form, SPM without Intelligent Scorecarding provides

the linkages to ROI, objectives, and IT enablement, which contains a

simple view of the business/IT value axis. The value axis is broad

enough and layered enough to not only contain the business/IT value

axis but also refl ect an internal IT management model that covers the

four essential IT management domains of business alignment, capacity

management, service management, and fi nancial management dis-

cussed earlier in this chapter. The value axis is important because most

application failures lack strategic perspective — such application failures

look to correct current issues and fail to address future conditions.

While the IT organization ’ s business partners must justify the acquisi-

tion and purpose of strategic business applications, IT is not excused

from understanding and contributing toward that strategic perspective,

which is the crux of business/IT value axis alignment.

Accordingly, the CIO ’ s contribution to the value axis starts when

IT fi rst begins to process new business application goals and objectives.

The best practice CIO uses the following steps to translate the applica-

tion into empirical values that can be implemented and measured:

� Business application goals and objectives

� Determining the price to be paid for IT enablement and ongoing

service

� System projections of volume, data storage, and other criteria

� Service level requirements

� Impact on capacity: infrastructure, capital, and expense

� Measurement system

Sounds easy enough, unless your IT organization hasn ’ t matured

into a service provider or learned to manage IT like a business. In that

case, the steps on the value axis won ’ t be attainable in the short term.

IT organizations all too often manage by engineering expertise that

translates into technology stovepipes. Managing by engineering and

technology stacks is an effective and effi cient approach given that we

educate and train engineers by discipline rather than educating and

employing generalists. What is not provided, especially as engineers

are promoted to management, is an enterprise management view of

IT organization responsibilities — a management view of IT not taught

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C H A N G I N G T H E W A Y I T B E H A V E S ◂ 89

in most management programs. Earlier sections articulated the per-

spectives researched by two key members of the analyst community,

McKinsey and Associates from a business perspective, and Gartner

taking an engineering approach. While these two perspectives start

from different ends of the maturity process, both promote the conclu-

sion that IT should be run like a business. The following discussion

fi lls in the space between these two perspectives.

SPM provides more than just linkages between ROI, objectives,

and IT enablement. The benefi t is far, far greater, and the job demands

more than mere linkages. Engineering disciplines in IT are typically

awash in internal key performance indicators (KPIs) generated by

monitoring and management tools that don ’ t necessarily address the

obstacle that stymies most IT organizations from maturating into

business - oriented enterprise service providers: fi refi ghting infrastruc-

ture failures. Neglected, or missing altogether, are the business -

oriented KPIs from service management, fi nancial management, and

business/application strategy.

Although many CIOs and their IT organizations have very little

applied experience with SPM, the business side of the house generally

has similar communication and management holes. SPM synchronizes

business and IT improvements to create value. Since misapplication

or under - application of SPM can lead to undesired outcomes, Gary

Cokins lists three questions that enterprise and IT leadership should

use SPM for focusing value creation and synchrony:

1. What products or service lines should we offer or not?

2. What markets and types of customers should we serve or not?

3. How are we going to win and keep winning?

When business is good, choices are easier; when business is bad,

choices are harder. Many executives have found themselves on new

ground that makes decision making more challenging than in the past.

Enterprises have discovered that many of the products they have in

the marketplace are basically commodities that offer little difference

in terms of quality or functionality. Consumers choosing between cell

phone A or cell phone B or fl at screen 1 or fl at screen 2 have little to

lose (or gain) between brand choices or where to make the purchase.

One transaction seems as good as the other.

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90 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

Compounding the commoditization of products and services,

enterprise and IT executives fi nd themselves managing organizations

that are complex and constantly changing. Their strategies often fail

due to the lack of communication. Interest consequently spiked in

SPM because businesses faced eight major chronic problems that

needed resolution:

1. Failure to execute strategy

2. Unfulfi lled return on ROI promises from transactional systems

3. Escalation in accountability (consequences) for results

4. Need for quick trade - off decision analysis

5. Mistrust of the managerial accounting systems

6. Poor customer value management

7. Dysfunctional supply chain management

8. Broken budgeting process

How were these issues addressed through SPM? The most typical

activity was the reporting of standard information at standard fre-

quencies. A simple, widely used example is reporting sales by geo-

graphic region each quarter. 21 Executives see how many fl at screens

1 and 2 were sold, when and where, on a quarterly and regional basis.

Adding just a bit more sophistication, managers and executives can

drill down into the data and see trends, patterns, or anomalies that

need attention. They see that fl at screen 1 ’ s numbers were trending

up in the Chicago area in August, but most likely they wouldn ’ t make

a connection with the Cubs stretch run for the pennant, know why

fl at screen 1 was chosen over fl at screen 2, or know which fl at screen

was the most profi table model of the two. Additional sophistication

adds executive alerts for responsible managers when parameters

approach established preset performance levels. The Cubs were elimi-

nated (again), sales nose - dived, and the alert was sent.

Since the IT organization ’ s maturity has been surveyed, measured,

and critiqued, it is fair to ask about the maturity of SPM application

in businesses. More Davenport statistics: 22

� Integrated SPM across the entire organization: 37%

� SPM throughout the enterprise, but not integrated: 32%

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C H A N G I N G T H E W A Y I T B E H A V E S ◂ 91

� SPM in some areas: 24%

� Nothing: 7%

It seems that almost all enterprises use PM and reporting to some

extent. Most reporting, however, is not built on the foundation of a

balanced scorecard or strategy maps. In other words, enterprise strat-

egy is generally not embedded in the reporting system. Without the

underlying relationships of major enterprise strategy initiatives, delib-

erate to the extent that investments measurably impact enterprise

objectives, the result is often a loose knit system of KPIs, for ill or

good, displayed on an executive dashboard that does not demand the

attention of the decision maker.

A comparison of the eight major chronic problems that drove

enterprise executives toward SPM and the problems faced by CIOs

and their IT organizations today reveals striking similarities. A deep

and persistent topic for the CIO over the last fi fteen years has been

the failure of IT to execute strategy on two principal levels: system

management and customer value management. A key part of IT ’ s

customer value management breakdown is centered on the “ unful-

fi lled return on ROI promises from transactional systems. ” Even as

unfulfi lled ROI shows up as a major driving force on the business side

of the ledger, enterprise executives point the fi nger at IT costs rather

than service delivery and optimizing IT system value by those very

same systems. The keys to costing too much? (1) Mistrust of the

managerial accounting systems; (2) a broken budgeting process; and

(3) dysfunctional supply chain management in the form of discon-

nected engineering silos.

Few CIOs question that their IT organizations face daunting cost

and PM challenges. System management problems that affect business

performance and drain cash continue to plague enterprise IT. As any

fi refi ghter will tell you, it is cheaper and far more convenient to

prevent fi res than to put them out and repair the damage. When any

organization fi nds itself refl exively reacting to one unforeseen event

after another, the employees fi nd it very diffi cult to muster the energy

and resources to move strategic imperatives forward. The toll exacted

in the case of such an IT organization is a group of people, no matter

how talented or well - led, who are unable to overcome the system

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92 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

management challenges wrought by the rapid technology changes of

the 1990s and Y2K - spawned enterprise applications that have bur-

rowed so deeply into enterprise business processes (and yes, those

same applications that failed to produce a ROI).

As the CIO and the IT organization seek to solve system manage-

ment and business alignment issues, APM is the approach that can

provide the tools to form, test, and forecast strategy that aligns enter-

prise strategy with IT enablers. Earlier sections identifi ed four key IT

management domains, which are also the building blocks of IT man-

agement maturity and the basis for SPM Intelligent Scorecarding.

Best practice CIOs recognize the importance of business manage-

ment opportunities and how those opportunities should be strategi-

cally managed and measured, both to enable business end users to

gain ROI for their IT investments, but also to enable strategic internal

IT resource management. Intelligent SPM doesn ’ t necessarily use

capacity management as a starting point, but capacity management is

the starting point for IT management maturity. Intelligent Scorecarding

addresses the challenge faced by best practice CIOs to balance the

right capacity at the right cost, to provide strategically enabling IT

services, and to measure the impact on enterprise business objectives.

Best practice CIOs and their IT organizations develop capacity

management from an engineering silo into partnership with other

IT enterprise business management domains and cement system

management maturity with strategic enterprise business priorities.

For example, after determining the optimal capacity level, actively

managing the capacity to that level wrings out the excess capacity

costs of idle capacity and also eliminates panic infrastructure buys.

Determining the cost of capacity not only effectively manages capac-

ity but also provides foundation costs for service management and

service management contracts. The cost of capacity includes the cost

of utilized capacity, reserve capacity, and unused capacity. Capacity

managers must also determine capacity beyond the traditional

manner. Predicting the exhaust rates of standardized services and the

growth of business services remains a ripe opportunity for the best

practice CIO.

Coupled with cost, service management is the most visible and

measurable portion of the IT organization. All IT resource users have

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C H A N G I N G T H E W A Y I T B E H A V E S ◂ 93

to be able to articulate what the IT organization should provide,

how much is it going to cost, and why it is needed. Thus far in the

marketplace, service reporting and fi nancial measures have been reac-

tive in nature, as has been most IT - related enterprise PM reporting.

Forecasting service - level performance, future capacity needs, and cost

of service growth moves service management from looking in the

rearview mirror to using a GPS. Best practice CIOs may not avoid

all the problems, but they can manage them. Forecasting provides

value for service management. Best practice CIOs use one other

opportunity for service management: the IT - related strategy manage-

ment structure must contain enterprise business value measures.

Reporting cost and service results are inadequate without knowing

progress toward enterprise business strategy objectives. Meeting busi-

ness goals and objectives are the ultimate measure of the ways that

IT enables enterprise strategic value. Applying intelligence to enabling

and meeting business strategy is a new breed of IT management.

When capacity management has additional tools that include the

cost of capacity (including unused capacity), the cost of the support

processes, and the strategy metrics to manage toward enterprise stra-

tegic objectives, capacity emerges from the cocoon of an engineering

silo as an IT strategic enabler. When service management consider-

ations include the cost of service, unused service, who consumes the

service, relevant support processes for both the standard service catalog

components and each business service, along with strategy metrics,

the fi nancial domain becomes the pinnacle of the new IT management

model of business alignment.

Because many CIOs and IT organizations have little experience in

applying either SPM or Intelligent Scorecarding to business alignment,

best practice examples are rare. Most examples of business alignment

center on portfolio management, which has been disconnected from

true fi nancial management and SPM as just another silo. The oppor-

tunity presented by business alignment is far greater than typically

imagined. As one of the key strategic enablers of most enterprises, IT

would be managed like a business while performing as a part of the

greater enterprise. IT products in the form of applications that enable

business processes enjoy the same benefi ts as other enterprise - wide

management tools. Enterprise leadership creates a value axis from the

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94 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

performance metrics from each of the IT management domains. Each

IT organization responsibility must have business objectives that trace

back to overall enterprise business strategy, enabled by the CIO. This

enablement must have a pre - established price tag before implementa-

tion of any new IT products, projects, or services. That price tag must

fi t within the ROI calculation of the enterprise business objectives,

where the support costs are determined by the volume and service

estimates articulated by the IT resource users, which the CIO and the

IT organization translates into service and capacity levels. Once built

and implemented, IT applications and related services can be mea-

sured, forecasted, and optimized from business objectives, service

results, costs, and business strategy.

Intelligent Scorecarding and Analytical Performance Management

Thomas Davenport articulated four key points that he considered the

Holy Grail of APM:

1. In an ideal world, consider or control for all possible variables

that might have a substantial effect on fi nancial performance

(customer relationships, employee attitudes and behaviors,

level of innovations, value of brand equity, and the others) for

one overall equation that described the relative contributions.

2. No longer would organizations report metrics simply because

they are familiar or because a standard balanced scorecard

format suggests them.

3. Business strategies (those in a strategy map) would be

testable.

4. Firms would also be able to predict the impact of increases or

decreases in non - fi nancial performance. 23

Davenport suggests that enterprises statistically test relationships

in business strategies through PM reporting: where that reporting

would be more creative, relevant, and valuable than the sales stats

for fl at screen TVs and other conventional performance reporting.

Businesses would know what worked and what failed, and modify

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C H A N G I N G T H E W A Y I T B E H A V E S ◂ 95

their strategies accordingly. Davenport suggests applying statistical

analyses to variables in PM, with demonstrates dramatic results.

Carrying his work further, SAS shows how to perform the analysis.

Let ’ s examine some Davenport examples. Each example tested

two variables, one fi nancial and one nonfi nancial:

� Hilton: Five percent improvement in customer retention results

in a 1.1 percent increase in annual revenues at a typical

property.

� Harrah ’ s: For each 1 percent growth in its share of customer

gaming budgets, its share price increases by $1.10.

� Best Buy: Discovers that for every tenth of a point on a fi ve -

point scale increase in employee engagement at a particular

store, operating income rises $100,000.

� Victoria ’ s Secret: Finds that raising its average conversion rate

by 1 percent brings more than $35 million in sales and $15

million in operating profi t.

In a couple of more sophisticated examples where two variable

analyses were performed with controls to focus the results:

� Toronto Dominion Bank: Controlled for customer service -

fi nancial performance of its branches, the bank fi nds that cus-

tomer service equals 19 percent of the variation in branch

profi tability and further fi nds that service improvement only

affects profi tability in the middle of service rankings; incentives

are aimed at the middle.

� Store24: Creates a balanced scorecard and a strategy map for a

program titled “ ban boredom ” on the assumption that enter-

tained customers buy more; the program does not work; it

lowers profi tability even when controlled for demographics and

income levels, but the program works where employee skill

levels are high.

As discussed in Chapter 1 , enterprises regard the relationship

between customer satisfaction and loyalty, employee satisfaction, and

product capability as key indicators in driving fi nancial success. Most

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96 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

businesses measure them to some degree. Other nonfi nancial vari-

ables are less common. For example, a tech services company found

that the average time it takes to close a case is a strong predictor of

gross margins. An oil refi ner found uptime closely correlated to profi ts.

Intelligent Scorecarding takes the best of APM and embeds itself

in the strategy map of a scorecard. Most businesses have avoided the

rigor of a balanced scorecard or the complexity of the strategy map

that evolves from a balanced scorecard. Balanced scorecards impose a

structure that might be too confi ning for IT. The fi rst edition of CIO

Best Practices discussed an IT balanced scorecard. Seeking a way to

guide the implementation of IT maturity, SAS subsequently labored

on that scorecard, complete with a strategy map, for another year or

more. While strategy maps have value, SAS has found that the

approach does have its fl aws. A strategy map is a map, nothing more.

If one is planning a car trip and uses an atlas to map the route, travel-

ers can rest assured that the map is accurate but cannot be assured

that the chosen route is the best route. These maps are not designed

to identify traffi c patterns, bottlenecks, construction zones, or factor

in weather forecasts. Neither are strategy maps. No history to look

back on. No forecasting to rely on. No indication which part of the

plan is more important than any other.

Intelligent Scorecarding removes the tediousness of designing a

scorecard, balanced or otherwise. CIOs and their C - Suite peers can

design visually, drawing relationships as the path forward is more

clearly articulated. As executives design strategic IT measurements,

the tool applies statistical techniques to measure results and predict

the impact of changes. By building the statistical measures and fore-

casts of the relationships into the strategy map, Intelligent Scorecarding

overcomes a major shortcoming of strategy mapping, which gives

equal weight to all relationships, whether fi nancial or nonfi nancial.

In addition, Intelligent Scorecarding removes uncertainty associated

with making changes in strategy by forecasting the impact of proposed

changes with confi dence intervals.

Designing Intelligent Scorecards can be done either by working

from the top down or by building from the bottom up. Working from

the top down is the easier and surer method. In honing this

tool for IT, SAS works from the top, beginning with the four IT

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N O T E S ◂ 97

management domains of capacity, service, fi nancial, and business

alignment. Each domain is a “ perspective ” in the strategy map. As in

any strategy map, thought must be given to the relationships between

the management domains. The trick is to settle on the order of infl u-

ence between domains.

NOTES

1. Donna Scott , Jay E. Pultz , Ed Holub , Thomas J. Bittman , and Paul McGuckin , “ Introducing the Gartner IT Infrastructure and Operations Maturity Model , ” Gartner ID Number: G00147962, October 2007 , confl u- ence.arizona.edu/ … /introducing_the_gartner_it_iInfrastructure + and_ Operations_1479621.pdf .

2. Paul McCann and David Migliore , “ What is MVS? ” November 3, 2005 , http://searchdatacenter.techtarget.com/sDefi nition/0,,sid80_gci212618 ,00.html .

3. Tom Hormby , “ What a Legacy: The Origin of the IBM PC , ” August 11, 2006 , http://lowendmac.com/orchard/06/ibm - pc - 5150 - origin.html .

4. IBM , “ IBM Personal Computer , ” Brochure 1982 .

5. Google search for “ Microsoft Windows 3.1 Sales History, ” www.google.com/ search?hl = en & tbo = p & tbs = tl%3A1 & q = microsoft + windows + 3.1 + sales + history & aq = f & aql = & aqi = & oq = .

6. Michael Hauben and Rhonda Hauben , “ On the Early History and Impact of Unix Tools to Build the Tools for a New Millennium , ” Netizens: On the History and Impact of Usenet and the Internet ( Wiley - IEEE Computer Society Press , 1997 ), www.columbia.edu/ ∼ rh120/ch001j.c11 .

7. Brevard User ’ s Group , “ History of the Ethernet , ” LAN Networking Networks Packet Xerox, http://bugclub.org/beginners/history/Ethernet History.html .

8. Marcus Kazmierczak , “ History of the Internet , ” September, 24, 1997 , http://mkaz.com/ebeab/history/ .

9. “ Legent Corporation — Company History , ” www.fundinguniverse.com/ company - histories/Legent - Corporation - Company - History.html .

10. Steven Chan , blogs.oracle.com/images/Architecture%20Diagram%20 R12.png .

11. Michael Bloch and Andres Hoyos - Gomez , “ How CIOs Should Think about Business Value , ” McKinsey Quarterly , March 2009 , www.mckinsey quarterly.com/How_CIOs_should_think_about_business_value_2307 .

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98 ▸ W H Y D O E S I T B E H A V E T H E W A Y I T D O E S ?

12. James M. Kaplan , Roger P. Roberts and Johnson Sikes , “ Managing IT in a Downturn: Beyond Cost Cutting , ” McKinsey Quarterly , September 2008 , www.mckinseyquarterly.com/Managing_IT_in_a_downturn_Beyond _cost_cutting_2196 .

13. Vanessa Chan , Chris Musso and Venkatesh Shankar , “ Assessing Inno- vation Metrics: McKinsey Global Survey Results , ” McKinsey Quarterly , November 2008 , www.mckinseyquarterly.com/McKinsey_Global_Survey _Results_Assessing_innovation_metrics_2243?pagenum = 5 .

14. Michael Smith and Kurt Potter , “ IT Spending and Staffi ng Report, 2009 , ” Gartner ID Number: G00164940, January 27, 2009 , www.gartner .com/DisplayDocument?doc_cd = 164940 .

15. See note 1.

16. Gartner, Incorporated, April 4, 2006/ID G00138514.

17. Jean - Pierre Garbani and Peter O ’ Neill , “ The Megavendors in IT Management Software , ” Forrester Research Incorporated, May 21, 2008 , www.forrester.com/rb/Research/megavendors_in_it_management_ software/q/id/43904/t/2 .

18. Gregg Wyant , Russ Heinsen , “ Intel and the Road to Enterprise SOA , ” 2007 ASUG Annual Conference, Session 1601, presented by Intel Corporation.

19. Joseph Hatcher , “ Overview of SAS ITRM Resource Management 3.1.1 , ” Introduction to SAS ® IT Resource Management 3.1.1 , ( Cary, NC : SAS Institute Inc. , 2007 ), support.sas.com/documentation/onlinedoc/itsv/intro311.pdf .

20. Martha Hays and Margaret Churchill , “ Paper 6151 Forecasting + Modeling: A Partnership to Predict and Prevent Capacity Bottlenecks , ” Computer Measurement Group Presentation, 2006 , Volume 1, (Computer Measure- ment Group), http://direct.bl.uk/bld/PlaceOrder.do?UIN = 203791356 & ETOC = RN & from = searchengine. All subsequent Hays/Churchill quota- tions and exhibits come from this presentation.

21. Thomas H. Davenport , “ The Rise of Analytical Performance Management , ” SAS Institute White Paper, www.sas.com/resources/whitepaper/wp_5596 .pdf .

22. Ibid .

23. Ibid .

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