Cutting IT Costs by Applying Lean Principles CAST

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White Paper

Cutting IT Costs by Applying
Lean Principles
Software Measurement
for Lean Application Management

IT organizations are experimenting with Lean techniques to reduce
application costs and delivery times with mixed results. To achieve
these objectives, IT must eliminate the largest source of waste in
application development and maintenance—defects and the
enormous rework they cause. This paper shows how focusing on
the Jidoka pillar of the Toyota Production System, which is the
use of automation to detect and eliminate defects early, attacks
and reduces defects and rework. By applying the waste-reducing
principles of Jidoka to development, maintenance, and the design
of applications, IT can both cut costs and shorten time-to-service.

Dr. Bill Curtis
Senior Vice President and Chief Scientist, CAST
Director, Consortium for IT Software Quality

Cutting IT Costs by Applying Lean Principles
Page 2

Dr. Bill Curtis, SVP and Chief Scientist at CAST, explains how the Lean
Executive Summary
practices pioneered in the Toyota Production System apply to the develop-
ment and maintenance of application software, leading to decreased
total cost of ownership and improved business responsiveness and
operational dependability.

The Problem
• IT organizations have been applying Lean practices to development
and maintenance of application software, yet the powerful benefits
have yet to be fully realized because they have not focused on the
early detection and elimination of defects.
• Defects in source code and the rework they cause are the largest
sources of waste in application development – accounting for 30%
to 50% of development effort.
• As much as two thirds of all application maintenance effort can be
classified as waste due to rework caused by defects and time
spent trying to understand what is going on in poorly constructed
applications.
• Over time, applications become less responsive and obese with
code that is no longer needed, wasting machine resources.
• The fast pace and short release cycles of Agile truncates the time
available for identifying and remediating structural problems in the
source code of an application.

The Solution
• By focusing on Jidoka, the pillar of Lean involving the automated
early detection and elimination of defects, defects can be identified
when they are injected into the source code and fixed quickly, rather
than later in the life cycle when their repair is often 10 times more
time-consuming and expensive.
• Eliminating the causes of defects and continually training developers
for defect-free work can dramatically improve productivity and shorten
time-to-release.
• In application maintenance, it is vital to address the changeability of
code before its release to reduce the time needed to understand the
application for subsequent releases, and sustain the quality of the
application over its lifetime.
• Over an application’s operational life, you must continuously tune
the performance of the code and manage application size,
especially when deploying it in a cloud environment.

Page 3

Executive Summary (continued) Key Takeaways
• Through adherence to the Jidoka component of Lean, the
combination of Lean Application Development, Lean Application
Maintenance, and Lean Application Assets provides the foundation
for Lean Application Management.
• Software analysis and measurement is key to supporting Lean
Application Management. The automated analysis and
measurement of structural quality of applications is critical to the
overall cost of ownership, business responsiveness, and
operational dependability required to run a Lean Enterprise.
1. Lean processes work at their most efficient when performed on
Lean products. The best way to reduce waste is to design it out of
the application from the beginning by driving design decisions
based on prioritized quality goals.

Page 4

I. How Lean Applies to Software Applications
Contents
For the past several years, IT organizations have been exploring the
I. How Lean Applies to Software application of Lean practices pioneered in the Toyota Production System1,2
Applications for automobile assembly to the development and maintenance of appli-
II. Lean Application Development cation software. Its focus on empowered teams and process streamlining3,4
III. Lean Application Maintenance has popularized Lean in the Agile Methods community. However, some
IV. Lean Application Assets of the most powerful benefits of Lean have yet to be fully realized in
V. Lean Application Management application development since the Agile community has focused more on
VI. References the just-in-time aspects of Lean rather than on Jidoka, the automated
early detection and elimination of defects.

Jidoka is one of the two pillars of the Toyota Production System that
provides the foundation for Lean practices (Figure 1). Jidoka uses
automation to detect defects early in the production process, as well as
their causes so they can be identified and eliminated. The fifth principle
of what has become known as the Toyota Way is to “build a culture of
stopping to fix problems and get quality right the first time.”5 This principle
had a profound effect on the productivity of automobile manufacturing, and
has the potential to transform the economics of application development
as well.

Figure 1. The Toyota Production System

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Jidoka can be implemented in an application portfolio through the practices
Highlights of Lean Application Management, which focuses on applying Lean methods
in three areas: Application Development, Application Maintenance, and
An IT organization can establish Application Assets. In the context of development and maintenance of
Lean Application Management by
business applications, Jidoka involves the use of technologies such as
automating software measurement
static analysis to identify defects when they are added to the source
that supports key Lean practices.
code, so they can be fixed before being passed on to a later life cycle
phase where their repair is much more expensive. The sections that
follow describe how an IT organization can establish Lean Application
Management by automating software measurement that supports key
Lean practices in each of these three areas.

II. Lean Application Development
The largest opportunity for improving quality and productivity during
application development is by eliminating its largest sources of waste—
defects and the rework they cause. In many organizations, 30% to 50%
of development effort is devoted to rework7, 8. These staggering numbers
are exacerbated by the fact that defects become 10 times more expensive
to fix for each major phase of the software life cycle they slip past. Under
these circumstances, productivity is largely determined by quality.

Before the Toyota Production System, 25% of the effort in traditional mass
production automobile manufacturing was devoted to fixing defects in
fully assembled automobiles at the end of the production line1. Defects
that would have been inexpensive to fix during assembly became expensive
because large portions of the car had to be disassembled to make the
needed repairs. Lean practices in the Toyota Production System virtually
eliminated rework areas at the end of production lines, contributing
heavily to Lean’s dramatic improvements in productivity, quality, and
time-to-market over traditional mass production.1

The level of rework in software applications is actually worse than that
observed in traditional automobile assembly (Figure 2). As in mass
production automobile manufacturing, rework in application development
piles up at the end of the development cycle, causing delays and often
throwing the project into chaotic thrashing to get the application sufficiently
stable for release. This rework is manifest in the continuing cycle of
testing, recoding defective components, and then retesting them to find
even more defects.

Page 6

Figure 2. Comparison of rework in traditional automobile assembly and software development

Why doesn’t testing eliminate the rework problem? Modern testing
practices are generally effective in detecting functional defects—deviations
from what the customer wanted. However, testing is not as effective in
detecting the non-functional defects that represent structural flaws in
the construction of the application.9,10,11 These structural defects are
difficult to detect through testing and are frequently the most expensive
to fix because they involve interactions between multiple tiers of the
application, which are often written in different languages and hosted on
different platforms. Structural defects are at the root of most devastating
operational problems such as outages, security breaches, data corruption,
and performance degradation.9,10 Static analysis of the structural quality
of business applications augments other quality assurance techniques
such as testing and design inspections to eliminate such defects.

Page 7

There are three main keys to eliminating rework (Figure 3) in Lean
Application Development.

Figure 3. How structural analysis contributes to Lean Application Development

1. Detect and remediate defects early: Every component added to the
source code should be analyzed at build time when it is integrated
with the evolving application to see its impact on the system as a
whole. Detection and repair at this point can be an order of magnitude
cheaper than if these structural flaws slip into the final stages of testing,
when they are deeply embedded in the application and a larger portion
of the code has to be torn down, fixed, and rebuilt. If structural defects
escape into operations where multiple versions of the software are in
use, the cost of correcting them can expand by an additional order
of magnitude.

Early detection of defects is especially critical when using Agile. Agile
methods are popular development techniques, but their fast pace
and short release cycles truncate the time available for identifying
and remediating the structural problems remaining in the source
code. Although Agile teams typically rebuild their application daily to
integrate newly developed components, their short schedules do
not allow time for evaluating structural quality at the application level
unless the analysis is automated. Agile teams benefit from detecting

Page 8

structural defects early so the most severe ones can be remediated
Highlights before release if a schedule buffer provides time for addressing
them. Addressing structural problems prior to release helps prevent
Organizations that rigorously apply waste in maintenance.
Lean techniques have been able
to reduce rework by 80% to 90%.
2. Eliminate the causes of defects: When structural quality diagnostics
are coupled with a powerful root cause analysis method such as
Orthogonal Defect Classification12, application teams can identify
the process sources of structural defects so that their root causes
can be eliminated. Typically an organization will not investigate the
causes of every defect, but instead focus on those that recur most
frequently or have the potential for devastating impact. While early
detection minimizes rework, root cause-based process improvement
virtually eliminates it.

3. Train developers continually for defect-free work: Techniques such
as Pareto charts of structural quality violations identify the most
frequent types of structural defects being injected into applications.
The results can be fed into training activities to help developers avoid
these recurring structural defects in the future, further eliminating
sources of rework. Some projects have a formal launch process for each
phase of development, giving the opportunity to review current issues
and the types of errors to be avoided during the next phase. Developing
workflow and a knowledge center to classify and guide developers
in understanding and remediating structural defects can raise the
bar on the performance of an application development organization.

Combinations of these three Lean techniques enabled by software
analysis and measurement technology can reduce, and in many cases
eliminate, the structural defects that cause the most severe rework in
application development. Organizations that apply these techniques
rigorously have been able to reduce rework by 80% to 90%13, dramatically
improving productivity and shortening time-to-release.

III. Lean Application Maintenance
The two primary sources of waste in application maintenance are rework
due to defects or badly constructed software and the staggering time
maintenance staff spend trying to understand what is going on in poorly
constructed applications. Correcting defects frequently accounts for as
much as one third of all postrelease work, and time spent understanding
the code has been shown to account for as much as half of all the effort
expended by maintenance staff14,15 (Figure 4). When the overlap between
these two activities is removed, as much as two thirds of all maintenance

Page 9

effort can be classified as waste. Since these sources of waste result
from poor application design and coding, they must be addressed as a
critical focus of Lean Application Maintenance.

Figure 4. How maintenance staff spend their time15

By identifying structural defects that have a high probability of causing
operational problems and result in maintenance rework, software analysis
and measurement provides strong support for Lean Application Main-
tenance. In addition, by addressing the changeability of the code before a
release, the time spent understanding the application can be dramatically
reduced in maintaining subsequent releases. Similarly, by sustaining
the quality of the application over its lifetime, IT can avoid degraded
applications and costly redevelopments.

There are three main keys to eliminating waste (Figure 5) in Lean
Application Maintenance.

1. Improve application changeability: The maintenance team can identify
the most serious structural flaws degrading the changeability of an
application using diagnostics from structural analysis of the application,
such as high coupling among components especially across application
layers. Prioritizing and remediating the most severe changeability
problems will reduce the time that maintenance staff spends trying
to trace control and data flows through the code. Improving the
changeability of an application not only slashes the time wasted on
understanding unnecessarily complex code, but also shortens imple-
mentation and verification cycles. As a result, the amount of functionality
delivered in a single release can be as much as doubled.

In addition, as the ease of changing an application improves, fewer new
defects will be injected into the code during maintenance by eliminating

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the misunderstanding of interactions among application layers. Lessons
learned in improving changeability can be used in training developers
how to produce more changeable architectures and code.

Figure 5. How structural analysis contributes to Lean Application Development

2. Reduce defect-fixing releases: IT organizations must too frequently
plan releases devoted primarily to fixing defects in the application. The
defects that take the longest to fix in maintenance are frequently
structural, since such flaws are harder to detect through traditional
testing. Implementing software analysis and measurement as a
component of the development process helps dramatically reduce
the number of structural defects that slip into operational software. By
detecting and eliminating these defects before release, it is possible
to reduce defect fixing in maintenance to near zero in a mature
development environment13. The percentage of maintenance effort
devoted to implementing new business functions is dramatically
increased as the releases of an application devoted to defect fixing
are eliminated.

3. Sustain lifetime quality: To track and sustain the quality of an appli-
cation throughout its lifetime, software analysis and measurement
should be implemented as a standard component of the maintenance
process. The structural quality of many applications degrades
continually over a succession of maintenance releases, to the point that
management has to weigh the tradeoff between the increasing time

Page 11

and expense of adding functionality versus the cost of redeveloping
Highlights the application. The quality of an application can be sustained across
its lifetime by measuring the status of various quality attributes
Technical debt is the cost of fixing during maintenance and remediating the quality problems created
structural problems that are not by maintenance actions, eliminating the need for extremely costly
fixed before release, but can cause redevelopments.
problems in the future.
All three of these aspects of Lean Application Maintenance involve
reducing the technical debt that builds up in applications. Technical debt
can be defined as the cost of fixing the structural problems in source
code that are not fixed before release, but will have to be corrected so
they don’t cause operational problems or degrade the maintainability of
the application. Technical debt has been conservatively measured to
cost $2.82 per line of code, although the actual cost based on more
realistic assumptions about time to repair defects is easily twice as
high.16 Applications appear to differ in their technical debt based on the
language in which they were implemented (Figure 6). Structural analysis
and measurement provides executives with a way to measure the
opportunity for cost reductions from applying the practices of Lean
Application Maintenance.

Figure 6. Technical Debt measured in applications by language16

Page 12

IV. Lean Application Assets
Highlights
Lean processes work at their most efficient when performed on Lean
The best way to reduce waste is to products. The best way to reduce waste is to design it out of the appli-
design it out of the application from cation from the beginning by driving design decisions based on prioritized
the beginning by driving design quality goals. However, even when designed well, applications age and
based on prioritized quality goals. can become less responsive and obese with code that is no longer needed,
wasting machine resources. This excess is especially acute in a cloud
environment where the application owner is being charged for both
space and processing time.

There are three keys to creating Lean Applications that eliminate waste
(Figure 7).

Figure 7. How waste is reduced by creating Lean Application Assets

1. Design for prioritized quality characteristics: The principles of Lean
Product Development and Design for Six Sigma both encourage
applications that are designed with quality priorities in mind. Quality
characteristics such as Robustness, Changeability, Security, and
Performance Efficiency should be prioritized for each application at the
beginning of its development. Architectural and coding decisions
should maximize the most important quality characteristics. These
quality characteristics can be measured and analyzed during both
development and maintenance to ensure the quality of the source

Page 13

code is consistent with its quality priorities. Architectural and coding
Highlights lessons from an IT organization’s application experience related to
these characteristics should be captured for consideration when
An application’s code base should making future design and coding decisions, since the most effective
be evaluated at each release to
way to eliminate waste is to design it out of the application from the
detect code that is no longer
beginning.
needed.

2. Tune the performance of application code: Poorly designed and
coded applications can waste expensive machine resources by
requiring more processing than necessary. Structural analysis should
be applied to detect poor coding and architectural practices that can
dramatically affect processing requirements and time. Structural
problems such as expensive calls inside loops, failure to properly
index queries, and embedding functions inside ‘WHERE’ clauses
can dramatically increase processing loads, requiring the acquisition
of additional machine resources and slowing response times. In one
example, a major multinational financial services company that started
proactively measuring and remediating performance problems in their
applications saw processing expenses reduced by roughly $10,000
each month for a single application. Performance issues are especially
acute in cloud environments where such problems can result in
unexpectedly large bills.

3. Manage application size: The size of an application should be
continually monitored to ensure its growth is under control and fits
within parameters appropriate for its environment. Automated measure-
ment of code size can be done in both function points and lines of
code to indicate the amount of code added, changed, or deleted.
When these measures indicate that code growth exceeds allowable
thresholds, corrective actions should be triggered. Further, the code
base should be evaluated at each release to detect code that is no
longer needed. Dead code throughout the application can then be
scheduled for removal in an upcoming release. Removing dead code
ensures that application growth and the machine resources needed
to support it are consistent with the business requirements of the
application. In addition to tracking application growth, these size
measures will be important for evaluating maintenance productivity,
as will be explained in the next section.

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V. Lean Application Management
Highlights
Establishing a Lean IT organization requires rapid and continual feedback
Automated analysis and measure- on the quality of the applications being placed in operation. The combination
ment of structural quality is critical of Lean Application Development, Lean Application Maintenance, and
to run a Lean Enterprise. Lean Application Assets provides the foundation for Lean Application
Management (Figure 8), a critical step in turning an IT organization into
a Lean Enterprise. By aggressively pursuing the Jidoka component of
Lean, the analysis and measurement of applications provides a critical
ingredient required to reduce many sources of waste associated with
application development and maintenance.

Figure 8. Lean Application Management

The ability to continually monitor application productivity is another critical
component of Lean Application Management. Productivity data provides
insight into the effectiveness of Lean practices at the application, portfolio,
and delivery center level. It is important to choose a consistent measure
for the numerator of productivity measures – that is, for the size of both
the application and the actual work accomplished during each release.
When these size measures are fully automated, they can be evaluated
consistently across all applications and used for comparisons across
an application portfolio or between different delivery centers.

Page 15

Consequently, the benefits of Lean practices and other improvement
activities can also be assessed at the application, portfolio, or delivery
center levels. These analyses provide the insight needed by application
executives to target troubled applications or delivery centers, and allocate
the resources required to optimize their cost structure and service to
the business.

Software analysis and measurement can be easily integrated into a
disciplined software life cycle process. In an undisciplined environment,
diagnostics can be used to motivate disciplined work by holding developers
accountable for the quality of the applications they produce. In either
environment, automated analysis and measurement of structural quality
of applications is critical to the overall cost of ownership, business
responsiveness, and operational dependability required to run a Lean
Enterprise.

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VI. Lean Application Management
1. J.P. Womack, D.T. Jones, & D. Roos (1990). The Machine That
Changed the World. New York: Free Press.
2. J. Womack & D.T. Jones (1996). Lean Thinking. New York: Simon
& Schuster.
3. M. Poppendieck & T. Poppendieck (2003). Lean Software
Development: An Agile Toolkit. Boston: Addison Wesley.
4. M. Poppendieck & T. Poppendieck (2007). Implementing Lean
Software Development. Boston: Addison Wesley.
5. J.K. Liker (2004). The Toyota Way. New York: McGraw-Hill.
6. J.M. Morgan & J.K. Liker (2006). The Toyota Product Development
System. New York: Taylor & Francis.
7. R. Dion (1993). Process improvement and the corporate balance
sheet. IEEE Software, 10 (4), 28-35.
8. B. Boehm (1987). Increasing software productivity. IEEE
Computer, 20 (9), 43-57.
9. D. Spinellis (2006). Code Quality. Boston: Addison Wesley.
10. M.T. Nygard (2007). Release It. Raleigh, NC: The Pragmatic
Bookshelf.
11. D. Jackson (2009). A direct path to dependable software.
Communications of the ACM, 52 (4), 78-88.
12. R. Chillarege, et al. (1992). Orthogonal Defect Classification:
Concept for In-Process Measurement. IEEE Transaction on
Software Engineering, 18 (11), 943-956.
13. M.C. Paulk, C.W. Weber, B. Curtis, & M.B. Chrissis (1995). The
Capability Maturity Model. Boston: Addison Wesley.
14. D.C. Littman, J. Pinto, S. Letovsky, & E. Soloway (1987). Mental
models and software maintenance. Journal of Systems and
Software, 7 (4), 341-355.
15. M. Ben-Menachem & G.S. Marliss (2005). IT assets - control by
importance and exception: Supporting the "paradigm of change".
IEEE Software, 22 (4), 94-102.
16. J. Sappidi, B. Curtis, & J. Subramanyam (2010). CAST Worldwide
Application Software Quality Study2010. New York: CAST
Research Labs.

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About the Author
Bill Curtis is an industry luminary who is responsible for influencing CAST’s
scientific and strategic direction, as well as helping CAST educate the IT
market to the importance of managing and measuring the quality of its
software. He is best known for leading the development of the Capability
Maturity Model (CMM) which has become the global standard for evaluating
the capability of software development organizations.

Prior to joining CAST, Dr. Curtis was a Co-Founder of TeraQuest, the
global leader in CMM-based services, which was acquired by Borland.
Prior to TeraQuest, he directed the Software Process Program at the
Dr. Bill Curtis Software Engineering Institute (SEI) at Carnegie Mellon University. Prior
Senior Vice President and Chief Scientist to the SEI he directed research on intelligent user interface technology
and the software design process at MCC, the fifth generation computer
research consortium in Austin, Texas. Before MCC he developed a
software productivity and quality measurement system for ITT, managed
research on software practices and metrics at GE Space Division, and
taught statistics at the University of Washington.

Dr. Curtis holds a Ph.D. from Texas Christian University, an M.A. from the
University of Texas, and a B.A. from Eckerd College. He was recently
elected a Fellow of the Institute of Electrical and Electronics Engineers for
his contributions to software process improvement and measurement. In
his free time Dr. Curtis enjoys traveling, writing, photography, helping
with his daughter’s homework, and University of Texas football.

About CAST
CAST is a pioneer and world leader in Software Analysis and Measurement,
with unique technology resulting from more than $90 million in R&D
investment. CAST provides IT and business executives with precise
analytics and automated software measurement to transform application
development into a management discipline. More than 650 companies
across all industry sectors and geographies rely on CAST to prevent
business disruption while reducing hard IT costs. CAST is an integral part
of software delivery and maintenance at the world’s leading IT service
providers such as IBM and Capgemini.

Founded in 1990, CAST is listed in NYSE-Euronext (Euronext: CAS) and
services IT intensive enterprises worldwide with a network of offices in
North America, Europe, and India.

www.castsoftware.com

North America Europe
373 Park Avenue South 3, rue Marcel Allegot
www.castsoftware.com New York, NY 10016 92190 Meudon - France
Phone: +1 212-871-3330 Phone: +33 1 46 90 21 00

© CAST All Rights Reserved

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