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The Trouble With

Enterprise Software

F A L L 2 0 0 7 V O L . 4 9 N O . 1

R E P R I N T N U M B E R 4 9 1 0 1

Cynthia Rettig

Please note that gray areas reflect artwork that has been

intentionally removed. The substantive content of the ar-

ticle appears as originally published.



CONTRAR IA

Technology has al-

w a y s b e e n a b o u t

hope. Since the begin-

ning of the industrial

revolution, businesses

have embraced new

technologies enthusi-

astically, and their

optimism has been

rewarded with im-

proved processes ,lower costs and re-

duced workforces. As the pace of technological

innovation has intensified over the past two de-

cades, businesses have come to expect that the next

new thing will inevitably bring them larger market

opportunities and bigger profits. Software, a tech-

nology so invisible and obscure to most of us that it

appears to work like magic, especially lends itself to

this kind of open-ended hope.

Software promises evolutions, revolutions and

even transformations in how companies do busi-

ness. The triumphant vision many buy into is that

enterprise software in large organizations is fully

integrated and intelligently controls infinitely com-

plex business processes while remaining flexible

enough to adapt to changing business needs. This

vision of software lies at the core of what Thomas

Friedman in “The World Is Flat” calls “the Wal-

Mart Symphony in multiple movements — with

no finale. It just plays over and over 24/7/365.”1

Whole systems march in lock step, providing syn-

chronized, fully coordinated supply chains,

production lines and services, just like a world-class orchestra. From online web orders through

fulfillment, delivery, billing and customer service

— the entire enterprise, organized end to end —

that has been the promise. The age of smart

machines would seem to be upon us.

Or is it? While a few companies like Wal-Mart

Stores Inc. have achieved something close to that

ideal, the way most large organizations actually

process information belies that glorious vision and

reveals a looking-glass world, where everything is

in fact the opposite of what one might expect.

Back-office systems — including both software ap-

plications and the data they process — are a

variegated patchwork of systems, containing 50 or

more databases and hundreds of separate software

programs installed over decades and intercon-

nected by idiosyncratic, Byzantine and poorly

documented customized processes. To manage this

growing complexity, IT departments have grown

substantially: As a percentage of total investment,IT rose from 2.6% to 3.5% between 1970 and 1980.2

By 1990 IT consumed 9%, and by 1999 a whopping

22% of total investment went to IT. Growth in IT

spending has fallen off, but it is nonetheless sur-

prising to hear that today’s IT departments spend

70% to 80% of their budgets just trying to keep ex-

isting systems running.

According to a multiyear study of over 400 com-

panies by MIT researchers Jeanne Ross, Peter Weill

and David Robertson,3 IT departments tend not to

be innovative leaders within organizations, but

rather conservative forces, viewed by business ex-

ecutives as cost sinks and liabilities. In many

companies, it takes the IT department one to two

years to implement a new strategic initiative —

hardly the agility companies are striving for. The

research shows the typical IT structure is so dense

and extensive that it’s often a miracle that it works

at all. The researchers observe: “Legacy systems

cobbled together to respond to each new business

initiative create rigidity and excessive costs. Every

change becomes a risky, expensive venture.”

The Proliferation of ComplexityHow did this happen? James Cordata, who has

written extensively about the information econ-

omy, points out that as work became more complex

and specialized over the 20th century, the use of

data — numbers and facts — as fodder for more

and more analysis and fact-based decision making

intensified. And digital technology “was perfect for

this kind of world.”4 Of course, digital technology

The Trouble With Enterprise Software

Has enterprise

software become

too complex to

be effective?

CYNTHIA RETTIG

FALL 2007 MIT SLOAN MANAGEMENT REVIEW 21

This article, originally

published on the

MIT Sloan Management

Review Web site,

stirred up a good deal

of discussion in the

blogosphere, a sampling

of which is included in

the following pages.



22 MIT SLOAN MANAGEMENT REVIEW FALL 2007

not only supported that complexity but also played

a large part in actually creating it, weaving a con-

tinuous web of unending data. “More computers

are better than fewer” remains a key belief of Amer-

ican business, Cordata says. “There are no limits to

how much is good.” Management became accus-

tomed to the idea that buying more computers andmore software would continue to cut costs and im-

prove operations.

But there are limits, some of which are inherent

in the nature of software itself. Software is code,

lines and lines of code that run sequentially. Build-

ing software programs entails accumulating more

and more code. Much of the seemingly boundless

complexity of enterprise software is founded on

conditional branching (if-then statements) and a

hierarchy of interacting objects, all of which ma-

nipulate information in a logical succession ofsmall steps. Each step contains explicit instruc-

tions. To build software, programmers routinely

break down processes into discrete steps, effectively

systematizing and standardizing how work is done.

An entire sequence of such instructions works

more like a calculator than a “thinking machine.”

Thus the so-called intelligence of digital technol-

ogy arises not through magic, nor, in more

contemporary terms, through some emergent or

self-organizing principle, as some would believe.

The result is not greater than the sum of the parts.

Rather, it’s more akin to Adam Smith’s division of

labor and Frederick Taylor’s scientific manage-

ment, a process dependent on relentless analysis

and rationalization of the work to be done.

General software programming used in enter-

prise systems may contain intricate branching and

handle a huge number of conditions, all of which

allow it to control a certain amount of complexity.It does not, however, tolerate ambiguity, inconsis-

tencies or illogical conclusions. To be sure, there

are fuzzy logic programs, dynamic simulations,

genetic algorithms and neural nets with subtler

powers, but a vast amount of software working in

today’s large organizations is not of these more ad-

vanced types. In fact, enterprise software systems

are more likely to succeed at relatively straightfor-

ward tasks such as procurement and order

processing. As the problems get more complex, so

does the software that solves them. It is estimatedthat for every 25% increase in complexity in the

tasks to be automated, the complexity of the soft-

ware solution itself rises by 100%.5

Business users and management inevitably want

changes in their automated processes as their needs

and markets evolve. And they expect to be able to

customize their software to fit their own needs.

“Software is infinitely malleable,” says computer

historian Martin Campbell-Kelly.6 This is in theory

true; however, as enterprise software becomes in-

creasingly comprehensive and complex, the costs

and risks involved in changing it increase as well.

No single person within an organization could

possibly know how a change in one part of the soft-

ware will affect its functioning elsewhere.

Software’s supposed flexibility and unending

ability to manage complexity contributed to the

discrepancies between the great expectations and

mediocre reality that plagued the first round of

implementations of enterprise resource planning

systems. In the middle to late 1990s, U.S. corpora-

tions rushed to purchase and install such systems.

These systems — Germany-based SAP Aktienge-sellschaft’s is the most common — promised to

eliminate the complexity of multiple operating sys-

tems and applications by replacing them with a

single set of interconnected modules to run the fi-

nancial, manufacturing, human resources and

other major functions of a typical multinational

corporation. Theoretically, a single monolithic sys-

tem would seamlessly connect various distinct and

geographically separate locations through private

CONTRAR IA

From the Wall Street Journal Business Technology Bloghttp://blogs.wsj.com/biztech

Technology is supposed to simplify business. This has been true fromthe Industrial Revolution to the Internet age. But did the large softwareapplications that were supposed to streamline large companies insteadirrevocably slow them down?

There’s a compelling argument to be made that they have. The aver-age company spends $15 million on Enterprise Resource Planningsoftware, the monolithic systems of record from vendors like SAP andOracle, and many large companies have spent tens and even hundredsof times that, according to [Ms. Rettig’s article].

Some of this resonates. Certainly, companies that have tried to cus-tomize these systems to reflect their own customized processes havespent a lot of time and money to do so. And ERP systems do introduce acertain amount of rigidity. On the flip side, having a system of record is abenefit in and of itself that shouldn’t be discounted. — Ben Worthen

SLOANREVIEW.MIT.EDU

http://sloanreview.mit.edu/





networks. Companies understood that they could

customize these systems as needed to suit their

unique business processes.

That was the hope. But these massive programs,

with millions of lines of code, thousands of instal-

lation options and countless interrelated pieces,

introduced new levels of complexity, often with-out eliminating the older systems (known as

“legacy” systems) they were designed to replace. In

addition, concurrent technological and business

changes made closed ERP systems organized

around products less than a perfect solution: Just

as companies were undertaking multiyear ERP

implementations, the Internet was evolving into a

major new force, changing the way companies

transacted business with their customers, suppli-

ers and partners. At the same time, businesses were

realizing that organizing their information aroundcustomers and services — and using newly avail-

able customer relationship management systems

— was critical to their success.

The concept of a single monolithic system failed

for many companies. Different divisions or facili-

ties often made independent purchases, and other

systems were inherited through mergers and ac-

quisitions. Thus, many companies ended up having

several instances of the same ERP systems or a vari-

ety of different ERP systems altogether, further

complicating their IT landscape. In the end, ERP

systems became just another subset of the legacy

systems they were supposed to replace.

The Costs of ImplementationERP systems were expensive, too, costing com-

panies more than they had ever paid for software

when costs had been based on per-workstation

usage. But that price tag was dwarfed by the in-

stallation charges, because companies had to

hire brigades of outside consultants, often for a

number of years, to actually get the software up

and running. While the average installation cost$15 million, large organizations ended up spend-

ing hundreds of millions of dollars. Even such

large expenditures did not guarantee success,

however. In fact, 75% of ERP implementations

were considered failures.7

Try as they might to measure the productivity

gains of ERP implementations or IT in general, re-

searchers have yet to arrive at any coherent or

consistent conclusions. One problem is that there

is little statistical evidence, especially about

whether the benefits of ERP implementations out-

weigh the costs and risks. Researchers even have

suggested that ERP implementations are so diffi-

cult that those companies that actually complete

them with relative success gain a competitive ad-

vantage in the marketplace.8 It seems that ERPs,

which had looked like the true path to revolution-

ary business process reengineering, introduced so

many complex, difficult technical and business is-

sues that just making it to the finish line with one’s

shirt on was considered a win.

All that complexity and all those options createdanother conundrum. As Nicholas Carr famously

pointed out in his book, “Does IT Matter? Informa-

tion Technology and the Corrosion of Competitive

Advantage,”9 simply implementing the plain-vanilla

business processes that your competitors have does

not provide any competitive advantage. On the

other hand, as many companies learned the hard

way, customizing the already complex ERP software

created yet more complexity and even larger risks.

From Rough Type: Nicholas Carr’s Blogwww.roughtype.com

Over the last two decades, companies have plowed many billions of dol-lars into enterprise resource planning (ERP) systems and the hardwarerequired to run them. But what, in the long run, will be the legacy ofERP? Will it be viewed as it has been promoted by its marketers: as amilestone in business automation that allowed companies to integratetheir previously fragmented information systems and simplify their dataflows? Or will it be viewed as a stopgap that largely backfired by tanglingcompanies in even more systems complexity and even higher IT costs?

In “The Trouble with Enterprise Software,” Cynthia Rettig deftly laysout the case for the latter view. Enterprise systems, argues Rettig, notonly failed to deliver on their grand promise, but often simply aggravatedthe problems they were supposed to solve. Different divisions or facilitiesoften made independent purchases, and other systems were inheritedthrough mergers and acquisitions. In the end, ERP systems became justanother subset of the legacy systems they were supposed to replace.

So what’s the solution? Rettig doesn’t offer one, beyond suggest-ing that top executives do more to educate themselves about theproblem and to work more closely with their CIOs. That may be goodadvice, but it hardly addresses the underlying technical challenge. ButRettig nevertheless has provided a valuable service with her article.While some will argue that her indictment is at times overstated, she

makes a compelling case that the traditional approach to corporatecomputing has become a dead end. We need to set a new course. — Nicholas Carr

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Without intimate knowledge of how the integrated

pieces of these modular software packages actually

worked, customizing could lead to in-house bugs

and glitches that were hard to foresee and expensive

to fix. Perhaps even worse, customization made

changing the software later — or upgrading to a

newer version — far more difficult, and in somecases prohibitively expensive. Christopher Koch,

executive editor of CIO Magazine, tells the story of

one head of a corporate SAP installation group who

bragged that he had his installation time down to a

mere three months for various facilities around the

world: “It didn’t matter that he was honing his skills

on a 10-year-old version of the software because the

costs of upgrading are so huge — tens, even hun-

dreds of millions of dollars, or as much as it cost to

install the stuff in the first place — that he keeps in-

stalling old versions of the software so that it will

line up with the old software they already have.”10

Unexpected bugs present another type of dif-

ficulty that increases with complexity. Robert

Pool, technology journalist and author of “Beyond

Engineering,” explains it this way: “It’s possible to

go through a program line by line and make sure

that each individual instruction makes sense but it

is not possible to guarantee that the program as a

whole has no flaws.”11 The average professional

coder makes 100 to 150 errors for every 1,000 lines

of code, according to a Carnegie Mellon studyconducted by Watts Humphrey.12 That means for

every million lines of code there would be 100,000

mistakes. Software developers do extensive testing

on the paths users seem likely to take and correct

many of these errors. Nevertheless, they cannot

test or even anticipate every possible usage path, so

released software inevitably contains unknown

defects. “Civilization depends on software. So al-

though much software code is poorly written, you

can’t just stop the world to fix it,” says Bjarne

Stroustrup, the Danish-born computer scientistwho designed the popular C++ programming

language. On the other hand, Stroustrup does

concede that “muddling along is expensive, dan-

gerous, and depressing.”13

The Vagaries of DataThe data that software processes and generates is

another constant and growing problem. Estimates

of errors are astoundingly high. Single systems can

have error rates of 50% or more from myriad

sources — everything from mistyped data to stale

information to data placed in the wrong fields

within the database structure. But the really nasty,

intractable data problems erupt when companies

integrate multiple data sources, as was necessary

for ERP implementations, so that they could have

all their product, inventory and production records

stored in one place. Because of differing formats,

conventions, abbreviations and so on, such inte-

grations can result in a 100 or more records that

actually point to a single product or customer. In

the case of enterprise system implementations,

data problems alone precipitate many of the fail-ures perceived by business users and much of the

added expense as well. Overwhelmed by the sheer

difficulty and complexity of the new software itself,

companies literally “forgot about the data,” as exec-

utive vice president John Nicoli of Harte-Hanks

Trillium Software in Billerica, Massachusetts, de-

scribes it, until the tail end of the project, thereby

necessitating enormous reworking to properly

clean up and integrate the data.14 And with corpo-

From Andrew McAfee’s Bloghttp://blog.hbs.edu/faculty/amcafee

It is certainly true that enterprise systems have failed in many companies,and it’s also true that, as [Ms. Rettig] points out, many others have notbeen able to shut off legacy systems to the extent they expected after ERPwent live. But it is simply not the case that researchers have been unableto draw any coherent conclusions about these technologies.

Rettig’s argument falls into a long line of pessimistic writing about thevalue of corporate IT. Much of this writing takes the implicit, and at timesexplicit, view that the executives who make technology decisions are

dupes, perennially falling for a “triumphant vision” of software. The onlyway I can see for the IT pessimists to be right is if the delusion about IT’sbenefits is both persistent and virtually universal. And I don’t buy that.

“ERP doesn’t help” is a testable hypothesis, and some colleaguesof mine have tested it. NYU’s Sinan Aral, Georgia Tech’s D.J. Wu, andmy friend and coauthor Erik Brynjolfsson at MIT recently published awonderful paper, “Which Came First, IT or Productivity? Virtuous Cycleof Investment and Use in Enterprise Systems” (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=942291). [This paper] contains a vital in-sight: If IT were not delivering value, rational decision makers would notkeep investing in it .

I agree that it’s important not to naively accept anyone’s triumphantvision of corporate IT. But it’s also important not to make claims in theother direction that are too sweeping. Perhaps most fundamentally, it’scritical at some point to stop floating hypotheses about IT’s impact (orlack thereof), and to start testing them. — Andrew McAfee

SLOANREVIEW.MIT.EDU






rate data stores doubling every three years, such

data issues are only compounding.

Is enterprise software just too complex to de-

liver on its promises? After all, enterprise systems

were supposed to streamline and simplify busi-

ness processes. Instead, they have brought h igh

risks, uncertainty and a deeply worrying level ofcomplexity. Rather than agility, they have pro-

duced rigidity and unexpected barriers to change,

a veritable glut of information containing myriad

hidden errors, and a cloud of questions regarding

their overall benefits. Leaders in computer science

are clearly worried. “Complexity is death,” says

Chuck Thacker, one of 16 technical fellows at Mi-

crosoft Corp. “We are hanging on with our

fingertips right now.”15

Business executives, however, simply want to

continue to believe that technology will lowercosts, improve processes and reduce the size of the

workforce. They don’t want to understand IT is-

sues. In part, this is because technology requires

special skills and intellectual talents that are quite

distinct from those needed to understand and

manage business organizations, markets and

strategy. But it is also because executives do not

like to hear about the downside of technology.

Observes Jim Shepherd, senior vice president of

Boston-based AMR Research Inc., “Senior man-

agers often don’t particularly want to be told that

there’s a high risk and that there’s a great deal of

expenditure involved in minimizing it.”16 Yet the

only sure thing about new technologies and the

changes they introduce is their uncertainty. In

summarizing decades of research into technologi-

cal change, MIT Sloan School of Management’s

Wanda Orlikowski and the National Science

Foundation’s Suzanne Iacono conclude that

changes involving technology are both “pro-

foundly complex and uncertain.”17

For their part, CIOs and their managers rate

aligning IT with business strategy as their No. 1 pri-ority. They struggle year after year to prove the value

of IT to the business side of the organization. Yet the

cost overruns, delays and outright failures of enter-

prise systems have if anything widened the digital

divide between IT and the executive suite.

The Next New ThingThe proposed fix for these problems — the next

new thing — is service-oriented architecture. Ba-

sically, SOA proposes to overcome the problems

involved with updating and changing legacy sys-

tems by building modular cross-system business

processes. These processes would connect the rel-

evant pieces of functionality from various IT

systems, thereby making it easier to change pro-

cesses to adapt to new business goals. But technical

realists point out that many difficult technical

problems must be solved before SOA can become

the backbone for a new strategic architecture, in-

cluding robust protocols for accessing the

applications, high-quality integrated data storesand a sound methodology for managing the over-

all process. Researchers Ross, Weill and Robertson

admit that most companies are in the early stages

of a four-part transformation to SOA that may

take many years — even decades — to realize.18

The estimates of how long this will take reflect a

growing acknowledgment of just how deep and

radical are the organizational changes these tech-

nological innovations mandate. It is a process of

From the ZDNet.com Bloghttp://blogs.zdnet.com

There’s really nothing new in [Ms. Rettig’s] analysis. But Rettig goes astep further and says there’s no hope for the future. In fact, while shedoesn’t offer any remedies for her gloomy prognosis, she does quashone — service-oriented architecture (SOA).

Rettig doesn’t offer any encouraging words about SOA as an ERPworkaround. SOA may take years to come to full fruition, not in enoughtime to help beleaguered companies, she says. And SOA may simply betoo slow to keep up the dynamic business environments of today. Not tomention technical challenges. Rettig says that SOA increases complex-

ity, as it becomes “additional layers of code superimposed on theexisting layers,” and she doesn’t buy the Lego-block concept that un-derpins much of the thinking about SOA.

Let’s put it this way: aside from SOA, what is the alternative? No oneis willing, or can afford to, to stay with the rigid, stovepiped systems intheir current form. One solution is just throw the entire mess out, andbuy a huge, well-integrated, modular application. But no one has thetime or budgets. The only workable approach, then, is gradual integra-tion between systems, and gradual, greater agility — if not through SOA,then how? SOA, pure and simple, is the first step to software industrial-ization — creating massive, adaptable systems in an automated andmodular fashion through greater economies of scale. ERP was a step inthis direction, since it modularized, and brought many vital pieces ofthe business together into a single standardized system. SOA takes it tothe next level, beyond the domain offered by a single vendor. That’s thecore value proposition of SOA. — Joe McKendrick

SLOANREVIEW.MIT.EDU






CONTRAR IA

adoption and adaptation that by definition cannot

occur overnight. Nor, conclude the researchers,

can companies skip a step. Given that only 6% of

companies have made it into the later stages, this

model would suggest that companies are in for a

long haul if they are to escape the tangle of techno-

logical complexity inherent in large organizations

today, and it will be a journey fraught with cultural

as well as technical problems.

The timeline itself for this kind of transforma-

tion may just be too long to be realistically

sustainable and successful. The dynamic business

environments of today, where whole industries and

markets can undergo radical changes in a matter of

a few years and the horizon for corporate strategies

has shrunk from 10 years to three to five, makes it

questionable whether companies actually can

maintain a focused strategy long enough to align

their core business processes with IT.

Technical problems raise additional questionsabout the feasibility of such an undertaking. The

hallmark of service-oriented architecture — one

reasonably might argue its entire raison d’être — is

the fundamental modularity of its software business

processes. A self-contained business process adopts

parts of the functionality from multiple enterprise

applications to automatically complete a set of tasks.

For example, a single business process might begin

with an order from a customer on the Internet in a

web services system and send it to manufacturing in

an ERP system. The same business process would set

up delivery in a logistics system and then send all the

relevant information to billing in an accounting sys-

tem as well as a customer relationship management

system. Companies would build (or purchase) busi-

ness modules for their core processes. They wouldthen be able to change these processes easily, snap-

ping out and in functional pieces of code from

enterprise systems in Lego-like fashion.

The Lego dream has been a persistent favorite

among a generation or more of programmers who

grew up with those construction toys. Unfortu-

nately, however, software does not work as Legos do.

For one thing, a unit of software code is not similar

to other software code in terms of scale or function-

ality, as Legos are.19 On the contrary, code is widely

various and heterogeneous. It contains differentnumbers and types of connections to other code,

more like fractals, as Victoria University of Welling-

ton researchers James Noble and Robert Biddle

describe it, than Legos, with their uniform connec-

tions. Software engineering expert Robert Glass sees

another problem with the Legos idea: The notion of

reusable software works on a small scale. Program-

mers have successfully built and reused subroutines

of standard functions. But as software grows more

complex, reusability becomes a difficult or impos-

sible task. “It is simply a problem too hard to be

solved, a problem rooted in software’s diversity.”20

“Complexity is a deadly software killer,” says

Yale University computer scientist David Gelern-

ter, and he argues that managing complexity is

more of an art than a science, and a difficult one at

that, especially given the monumental real-world

systems today’s software attempts to automate.21

And to the extent that these service-oriented ar-

chitectures use subsets of code from within ERP

and other enterprise systems, they do not escape

the mire of complexity built over the past 15 years

or so. Rather, they carry it along with them, incor-porating code from existing applications into a

fancy new remix. SOAs become additional layers

of code superimposed on the existing layers. That

means it is possible that a process will fail at some

point due to some fault in the layers below, and in

order to understand and fix that problem, software

engineers will need to deal with the layers of enter-

prise applications below the modular business

processes.

From the Deal Architect Blogwww.dealarchitect.typepad.com

The good news is [Ms. Rettig’s] article will get executive attention. Notthat they do not know. I recently met an executive at a client about tostart an ERP implementation. He sounded like a man headed to the gal-lows. Nervous, not excited about the project. (That afternoon, I feltreally embarrassed for our industry that after 100K+ ERP projects, we stillcannot make it a no-brainer.)

But it is way past talking about messes. Companies are in various stagesof ERP hangover management, not always looking at software as a service(SaaS), as those vendors would have you believe — it’s not that easy to ripand replace a backbone ERP solution — but software as a customized ser-vice (SaCS). [Those companies are in] aggressive re-negotiation of ERPmaintenance contracts or moving to third party maintenance.

The only ones who do not seem to realize the party is over are thevendors, who are using service-oriented architecture (SOA), complianceand more low payback justifiers to extend the run.

— Vinnie Mirchandani

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Culturally, this long-term plan calls for closer and

closer communication and collaboration between

the IT and business sides of the organization. While

much to be desired, this has proved difficult in the

past, and with increasing complexity in software sys-

tems, it is unlikely to improve by itself in the future.

Differing backgrounds and perspectives, goals, evenvocabularies — all hamper efforts to improve com-

munication across this internal digital divide. Biases

intrude: A recent study by Forrester Research Inc. of

Cambridge, Massachusetts, found that only 28% of

CEOs thought their CIOs were proactive or creative

in terms of business process improvement.22 For-

rester’s advice to CIOs is to get more deeply involved

in the business issues and educate executives on what

IT is and what it actually does.

Sound advice, no doubt, but it may be time for

business executives themselves to become moreproactive. Executives could educate themselves

more about technology. They could send promis-

ing younger executives to executive programs

designed to teach business people how to better

understand, communicate with and capitalize on

their IT. And business schools, too, could do better

at teaching the interdependence of business and IT.

At present, however, corporations see in software’s

seductive invisibility and seemingly open-ended

flexibility a ne ver-ending frontier of promise,

where hope triumphs over reality and the search

for the next new thing trumps addressing difficult

existing problems. And hope, unfortunately, has

never been a very effective strategy.

Cynthia Rettig was director of knowledge management

for B2B consulting company Canopy International of

Newton, Massachusetts. She has consulted to software

companies for over 20 years. Comment on this article or

contact the author through [email protected].

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10. C. Koch, “The Monopoly That Matters More Than

Microsoft,” Nov. 13, 2006, http://advice.cio.com.

11. R. Pool, “Beyond Engineering: How Society Shapes

Technology” (New York: Oxford University Press, 1997),

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12. C. Mann, “Why Software Is So Bad,” Technology

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14. Author’s interview with John Nicoli, executive vice

president, Harte-Hanks Trillium Software; Aug. 8, 2005.

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Meta,” Technology Review (January-February 2007): 45.

16. M. Wheatley, “ERP Training Stinks,” CIO Magazine,

June 1, 2000, 86-96.

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There: An Enacted View of the ‘Digital Economy,’” in

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Research,” ed. E. Brynjolfsson and B. Kahin (Cam-

bridge: MIT Press, 2000), 355.

18. Ross, “Enterprise Architecture As Strategy.”

19. S. Rosenberg, “Dreaming in Code: Two Dozen Pro-

grammers, Three Years, 4,732 Bugs, and One Quest for

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2007), 94-95.

20. Glass, “Facts and Fallacies of Software Engineering.”

21. D. Gelernter, “Mirror Worlds: Or the Day Software

Puts the Universe in a Shoebox … How It Will Happen

and What It Will Mean” (New York: Oxford University

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Magazine, April 1, 2007, 20.

Reprint 49101.

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